A DISTRIBUTED UNIT AND A RADIO UNIT IN A RADIO ACCESS NETWORK

TECHNICAL FIELD

The disclosure relates generally to communications and, more particularly but not exclusively, to dynamic low layer virtual network function distribution between a distributed unit and a radio unit in a radio access network .

BACKGROUND

An open radio access network Alliance (O-RAN) aims for interoperability and standardization of RAN elements including a unified interconnection standard for network functions from different vendors . In the O-RAN, a distributed unit (DU) and a remote radio unit (RU) are connected via an open fronthaul con- nection .

To split low layer functions (e . g . , layer 1 (L1 ) func- tions ) between the DU and the RU across the open fronthaul , a 7- 2 split has currently been adopted, in which fast Fourier trans- form (FFT) and beamforming are handled by the RU . Channel esti- mation, equalization and decoding are handled by the DU .

However, at least in some situations other options to split the low layer functions may be desirable . Furthermore , at least in some situations it may be desirable to be able to dynamically reconfigure a currently deployed split of the low layer functions .

SUMMARY

The scope of protection sought for various example em- bodiments of the invention is set out by the independent claims . The example embodiments and features , if any, described in this specification that do not fall under the scope of the independent claims are to be interpreted as examples useful for understanding various example embodiments of the invention .

An example embodiment of a radio access network controller in a radio access network comprising a distributed unit , at least one radio unit and at least one fronthaul con- nection between the distributed unit and the at least one radio unit , comprises at least one processor, and at least one memory including computer program code . The at least one memory and the computer program code are configured to, with the at least one processor, cause the radio access network controller at least to perform obtaining data flow optimization information related to the at least one fronthaul connection . The at least one memory and the computer program code are further configured to, with the at least one processor, cause the radio access network controller at least to perform determining a distribution of low layer virtual network functions between the distributed unit and the at least one radio unit based on the obtained data flow optimization information . The at least one memory and the computer program code are further configured to, with the at least one proces sor, cause the radio access network controller at least to perform transmitting control signaling to at least one of the distributed unit or the at least one radio unit . The control signaling comprises instructions to deploy the determined distribution of the low layer virtual network functions .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the data flow optimization information comprises information about at least one of : traffic load of the at least one radio unit , energy saving requirements in the radio access network, available bandwidth of the at least one fronthaul connection, available processing capacity in the at least one radio unit , available processing capacity in the distributed unit , user grouping, quality of service , maximum bandwidth of the at least one fron- thaul connection, maximum processing capacity in the at least one radio unit , or maximum processing capacity in the distributed unit .

At least in some embodiments , dynamic data flow optimization information ( including information about the traf- fic load of the at least one radio unit , the energy saving requirements in the radio access network, the available bandwidth of the at least one fronthaul connection, the available processing capacity in the at least one radio unit , the user grouping, the quality of service , and/or the available pro- cessing capacity in the distributed unit , ) may be collected from the distributed unit , the at least one radio unit , and/or the at least one fronthaul connection (e . g . , at runtime ) and sent to the radio access network controller .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the low layer virtual network functions comprise at least one of : a fast Fou- rier transform, FFT, related virtual network function, a beam- forming related virtual network function, a channel estimation related virtual network function, an equalization related virtual network function, or a decoding related virtual network function .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the determining of the distribution of the low layer virtual network functions comprises applying a machine learning model to predict an optimal distribution of the low layer virtual network functions based on the obtained data flow optimization information .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the control signaling further comprises timing information indicating when to activate the determined distribution of the low layer virtual network functions .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the radio access network controller comprises a non-real time radio access network controller or a near-real time radio access network controller .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the at least one memory and the computer program code are further configured to, with the at least one processor, cause the radio access network controller to recurringly perform at least one of the obtaining of the data flow optimization information, the determining of the distribution of the low layer virtual network functions , or the transmitting of the control signaling . In an example embodiment , alternatively or in addition to the above-described example embodiments , the radio access network comprises an open radio access network .

An example embodiment of a radio access network controller in a radio access network comprising a distributed unit , at least one radio unit and at least one fronthaul con- nection between the distributed unit and the at least one radio unit , comprises means for performing obtaining data flow optimization information related to the at least one fronthaul connection . The means are further configured to perform determining a distribution of low layer virtual network functions between the distributed unit and the at least one radio unit based on the obtained data flow optimization information . The means are further configured to perform transmitting control signaling to at least one of the distributed unit or the at least one radio unit . The control signaling comprises instructions to deploy the determined distribution of the low layer virtual network functions .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the data flow optimization information comprises information about at least one of : traffic load of the at least one radio unit , energy saving requirements in the radio access network, available bandwidth of the at least one fronthaul connection, available processing capacity in the at least one radio unit , available processing capacity in the distributed unit , user grouping, quality of service , maximum bandwidth of the at least one fron- thaul connection, maximum processing capacity in the at least one radio unit , or maximum processing capacity in the distributed unit .

At least in some embodiments , dynamic data flow optimization information ( including information about the traf- fic load of the at least one radio unit , the energy saving requirements in the radio access network, the available bandwidth of the at least one fronthaul connection, the available processing capacity in the at least one radio unit , the user grouping, the quality of service , and/or the available pro- cessing capacity in the distributed unit , ) may be collected from the distributed unit , the at least one radio unit , and/or the at least one fronthaul connection (e . g . , at runtime ) and sent to the radio access network controller .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the low layer virtual network functions comprise at least one of : a fast Fou- rier transform, FFT, related virtual network function, a beam- forming related virtual network function, a channel estimation related virtual network function, an equalization related virtual network function, or a decoding related virtual network function .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the determining of the distribution of the low layer virtual network functions comprises applying a machine learning model to predict an optimal distribution of the low layer virtual network functions based on the obtained data flow optimization information .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the control signaling further comprises timing information indicating when to activate the determined distribution of the low layer virtual network functions .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the radio access network controller comprises a non-real time radio access network controller or a near-real time radio access network controller .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the means are fur- ther configured to recurringly perform at least one of the ob- taining of the data flow optimization information, the deter- mining of the distribution of the low layer virtual network functions , or the transmitting of the control signaling .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the radio access network comprises an open radio access network .

An example embodiment of a method comprises obtaining, by a radio access network controller, data flow optimization information related to at least one fronthaul connection in a radio access network . The radio access network comprises a distributed unit , at least one radio unit and the at least one fronthaul connection between the distributed unit and the at least one radio unit . The method further comprises determining, by the radio access network controller, a distribution of low layer virtual network functions between the distributed unit and the at least one radio unit based on the obtained data flow optimization information . The method further comprises transmitting, by the radio access network controller, control signaling to at least one of the distributed unit or the at least one radio unit . The control signaling comprises instructions to deploy the determined distribution of the low layer virtual network functions .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the data flow optimization information comprises information about at least one of : traffic load of the at least one radio unit , energy saving requirements in the radio access network, available bandwidth of the at least one fronthaul connection, available processing capacity in the at least one radio unit , available processing capacity in the distributed unit , user grouping, quality of service , maximum bandwidth of the at least one fron- thaul connection, maximum processing capacity in the at least one radio unit , or maximum processing capacity in the distributed unit .

At least in some embodiments , dynamic data flow optimization information ( including information about the traf- fic load of the at least one radio unit , the energy saving requirements in the radio access network, the available bandwidth of the at least one fronthaul connection, the available processing capacity in the at least one radio unit , the user grouping, the quality of service , and/or the available pro- cessing capacity in the distributed unit , ) may be collected from the distributed unit , the at least one radio unit , and/or the at least one fronthaul connection (e . g . , at runtime ) and sent to the radio access network controller . In an example embodiment , alternatively or in addition to the above-described example embodiments , the low layer virtual network functions comprise at least one of : a fast Fou- rier transform, FFT, related virtual network function, a beam- forming related virtual network function, a channel estimation related virtual network function, an equalization related virtual network function, or a decoding related virtual network function .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the determining of the distribution of the low layer virtual network functions comprises applying a machine learning model to predict an optimal distribution of the low layer virtual network functions based on the obtained data flow optimization information .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the control signaling further comprises timing information indicating when to activate the determined distribution of the low layer virtual network functions .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the radio access network controller comprises a non-real time radio access network controller or a near-real time radio access network controller .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the method further comprises recurringly performing at least one of the obtaining of the data flow optimization information, the determining of the distribution of the low layer virtual network functions , or the transmitting of the control signaling .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the radio access network comprises an open radio access network .

An example embodiment of a computer program comprises instructions for causing a radio access network controller to perform at least the following : obtaining data flow optimization information related to at least one fronthaul connection in a radio access network, the radio access network comprising a distributed unit , at least one radio unit and the at least one fronthaul connection between the distributed unit and the at least one radio unit ; determining a distribution of low layer virtual network functions between the distributed unit and the at least one radio unit based on the obtained data flow optimization information; and transmitting control signaling to at least one of the distributed unit or the at least one radio unit , the control signaling comprising instructions to deploy the determined distribution of the low layer virtual network functions .

An example embodiment of a distributed unit connected to at least one radio unit via at least one fronthaul connection in a radio access network, comprises at least one processor, and at least one memory including computer program code . The at least one memory and the computer program code are configured to, with the at least one processor, cause the distributed unit at least to perform receiving control signaling from a radio access network controller in the radio access network . The control signaling comprises instructions to deploy a determined distribution of low layer virtual network functions between the distributed unit and the at least one radio unit . The at least one memory and the computer program code are further configured to, with the at least one processor, cause the distributed unit at least to perform, in response to the received control signaling, deploying the determined distribution by at least one of activating or deactivating at least one of the low layer virtual network functions in accordance with the instructions comprised in the received control signaling .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the at least one memory and the computer program code are further configured to, with the at least one processor, cause the distributed unit at least to perform collecting data flow optimization information, and transmitting the collected data flow optimization information to the radio access network controller .

An example embodiment of a distributed unit connected to at least one radio unit via at least one fronthaul connection in a radio access network comprises means for performing receiving control signaling from a radio access network controller in the radio access network . The control signaling comprises instructions to deploy a determined distribution of low layer virtual network functions between the distributed unit and the at least one radio unit . The means are further configured to perform, in response to the received control signaling, deploying the determined distribution by at least one of activating or deactivating at least one of the low layer virtual network functions in accordance with the instructions comprised in the received control signaling .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the means are further configured to perform collecting data flow optimization information, and transmitting the collected data flow optimization information to the radio access network controller .

An example embodiment of a method comprises receiving, at a distributed unit connected to at least one radio unit via at least one fronthaul connection in a radio access network, control signaling from a radio access network controller in the radio access network . The control signaling comprises instructions to deploy a determined distribution of low layer virtual network functions between the distributed unit and the at least one radio unit . The method further comprises , in response to the received control signaling, deploying, by the distributed unit , the determined distribution by at least one of activating or deactivating at least one of the low layer virtual network functions in accordance with the instructions comprised in the received control signaling .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the method further comprises collecting data flow optimization information, and transmitting the collected data flow optimization information to the radio access network controller .

An example embodiment of a computer program comprises instructions for causing a distributed unit connected to at least one radio unit via at least one fronthaul connection in a radio access network to perform at least the following : receiving control signaling from a radio access network controller in the radio access network, the control signaling comprising instructions to deploy a determined distribution of low layer virtual network functions between the distributed unit and the at least one radio unit ; and in response to the received control signaling, deploying the determined distribution by at least one of activating or deactivating at least one of the low layer virtual network functions in accordance with the instructions comprised in the received control signaling .

An example embodiment of a radio unit connected to a distributed unit via a fronthaul connection in a radio access network, comprises at least one processor, and at least one memory including computer program code . The at least one memory and the computer program code are configured to, with the at least one processor, cause the radio unit at least to perform receiving control signaling from a radio access network controller in the radio access network . The control signaling comprises instructions to deploy a determined distribution of low layer virtual network functions between the radio unit and the distributed unit . The at least one memory and the computer program code are further configured to, with the at least one processor, cause the radio unit at least to perform, in response to the received control signaling, deploying the determined distribution by at least one of activating or deactivating at least one of the low layer virtual network functions in accordance with the instructions comprised in the received control signaling .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the at least one memory and the computer program code are further configured to, with the at least one processor, cause the radio unit at least to perform collecting data flow optimization information, and transmitting the collected data flow optimization information to the radio access network controller .

An example embodiment of a radio unit connected to a distributed unit via a fronthaul connection in a radio access network comprises means for performing receiving control signaling from a radio access network controller in the radio access network . The control signaling comprises instructions to deploy a determined distribution of low layer virtual network functions between the radio unit and the distributed unit . The means are further configured to perform, in response to the received control signaling, deploying the determined distribution by at least one of activating or deactivating at least one of the low layer virtual network functions in accordance with the instructions comprised in the received control signaling .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the means are further configured to perform collecting data flow optimization information, and transmitting the collected data flow optimization information to the radio access network controller .

An example embodiment of a method comprises receiving, at a radio unit connected to a distributed unit via a fronthaul connection in a radio access network, control signaling from a radio access network controller in the radio access network . The control signaling comprises instructions to deploy a determined distribution of low layer virtual network functions between the radio unit and the distributed unit . The method further com- prises , in response to the received control signaling, deploying, by the radio unit , the determined distribution by at least one of activating or deactivating at least one of the low layer virtual network functions in accordance with the instructions comprised in the received control signaling .

In an example embodiment , alternatively or in addition to the above-described example embodiments , the method further comprises collecting data flow optimization information, and transmitting the collected data flow optimization information to the radio access network controller .

An example embodiment of a computer program comprises instructions for causing a radio unit connected to a distributed unit via a fronthaul connection in a radio access network to perform at least the following : receiving control signaling from a radio access network controller in the radio access network, the control signaling comprising instructions to deploy a determined distribution of low layer virtual network functions between the radio unit and the distributed unit ; and in response to the received control signaling, deploying the determined distribution by at least one of activating or deactivating at least one of the low layer virtual network functions in accordance with the instructions comprised in the received control signaling .

DESCRIPTION OF THE DRAWINGS

The accompanying drawings , which are included to pro- vide a further understanding of the embodiments and constitute a part of this specification, illustrate embodiments and to- gether with the description help to explain the principles of the embodiments . In the drawings :

FIG . 1 shows an example embodiment of the subject matter described herein illustrating an example radio access network, where various embodiments of the present disclosure may be im- plemented;

FIG . 2A shows an example embodiment of the subject mat- ter described herein illustrating a radio access network controller;

FIG . 2B shows an example embodiment of the subject mat- ter described herein illustrating a distributed unit ;

FIG . 2C shows an example embodiment of the subject mat- ter described herein illustrating a radio unit ;

FIG . 3A shows an example embodiment of the subject mat- ter described herein illustrating a dynamic 7-3 split to 7-2 split transition to exploit resource pooling at a distributed unit ;

FIG . 3B shows an example embodiment of the subject mat- ter described herein illustrating redistributing low layer func- tions to offload a portion of the processing from a 7-3 split radio unit to a distributed unit ;

FIG . 3C shows an example embodiment of the subject mat- ter described herein illustrating redistributing low layer func- tions to support 7-3 split processing in a radio unit for coor- dinated multi-points traffic; FIG . 3D shows an example embodiment of the subject mat- ter described herein illustrating redistributing low layer func- tions to support ultra reliable low latency communication traf- fic;

FIG . 4 shows an example embodiment of the subject matter described herein illustrating a machine learning model applied by the radio access network controller;

FIG . 5A shows an example embodiment of the subject mat- ter described herein illustrating a dynamic low layer split through a non-real time radio access network controller;

FIG . 5B shows an example embodiment of the subject mat- ter described herein illustrating a dynamic low layer split using a near-real time radio access network controller;

FIG . 6 shows an example embodiment of the subject matter described herein illustrating a method;

FIG . 7 shows an example embodiment of the subject matter described herein illustrating another method;

FIG . 8 shows an example embodiment of the subject matter described herein illustrating yet another method .

Like reference numerals are used to designate like parts in the accompanying drawings .

DETAILED DESCRIPTION

Reference will now be made in detail to embodiments , examples of which are illustrated in the accompanying drawings . The detailed description provided below in connection with the appended drawings is intended as a description of the present examples and is not intended to represent the only forms in which the present example may be constructed or utilized . The descrip- tion sets forth the functions of the example and the sequence of steps for constructing and operating the example . However, the same or equivalent functions and sequences may be accomplished by different examples .

At least some of the disclosed embodiments may be im- plemented in an open radio access network (O-RAN) architecture .

The O-RAN aims for interoperability and standardization of RAN elements including a unified interconnection standard for network functions from different vendors . The O-RAN architecture provides a foundation for build- ing a virtualized RAN on open hardware with an embedded artifi- cial intelligence (Al ) -powered radio control .

Function blocks of the O-RAN may comprise , e . g . , an orchestration / network management system layer with a non-real time RAN intelligent controller (non-RT RIC) , a near-real time RAN intelligent controller (nRT RIC) application layer, multi - radio access technology (RAT) central unit (CU) protocol stack functions , a distributed unit (DU) , and a remote radio unit (RU) function blocks connected through an open fronthaul connection .

Fronthaul is a term that refers to a fiber-based con- nection between the RU and the DU in the RAN . Open fronthaul is an interface between O-DU and O-RU, allowing to connect any vendor DU to any vendor RU via a standard interface .

In the O-RAN architecture , the non-real time RIC may operate on a time scale of >> 1 second, and handle high level / orchestration functions , and provide Al-enabled policies to ma- chine learning (ML) -based models over an Al interface to the near-real time RIC . The near-real time RIC may operate on a time scale of < 1 second, and execute these policies and models to change the operational behavior (e . g . , radio resource management (RRM) / self-organizing networks ( SON) ) of the network, for ex- ample .

To split low layer functions (e . g . , layer 1 (LI ) func- tions ) between the DU and the RU across the open fronthaul , a 7- 2 split has currently been adopted, in which fast Fourier trans- form (FFT) and beamforming may be handled by the RU . Channel estimation, equalization and decoding may be handled by the DU . In the case of a layer 1 function split , the LI functions that reside at the RU may be referred to as Lllow functions , whereas the LI functions that reside at the DU care may be referred to as Llhigh functions .

Another variant of the low layer split is a 7-3 split . The 7-3 split is being proposed as a next generation open fron- thaul split . In the 7-3 split , the FFT, beamforming, channel estimation and equalization may be handled by the RU, and the decoding may be handled by the DU . Benefits of the 7-2 split may include : a relatively simple RU which may require lower energy consumption and a smaller form factor, and a centralized Llhigh function ( i . e . , channel estimation and equalization) in the DU providing base- band pooling capabilities .

Benefits of the 7-3 split may include : by performing channel estimation and equalization to spatial streams inside the RU, the fronthaul bandwidth scales with the number of data streams ( i . e . , layers ) which is in general much smaller than in the 7-2 split ; and the equalizer in the RU may potentially pro- cess more spatial streams (as it is no longer constrained by the fronthaul bandwidth) and it may achieve a better performance . This particularly applies to massive multiple-output (MIMO) sce- narios .

In the following, various example embodiments will be discussed . At least some of these example embodiments may allow dynamic redistribution of low layer functions across a fronthaul ( such as an open fronthaul ) . Thereby, the example embodiments are not restricted to the 7-2 and 7-3 splits . An objective is to optimize the operation of the DU and RU in order to meet a desired receiver performance with the least amount of power con- sumption .

At least some of the disclosed embodiments may allow a hybrid low layer split in the fronthaul ( such as an open fron- thaul ) , wherein low layer functions may be redistributed dynam- ically in more than one way across the DU and the RU . A radio access network controller 200 may adjust the distribution on a near real-time basis in response to traffic conditions and energy saving needs against physical capacity constraints in the RU and the fronthaul , for example . Additionally, at least some of the embodiments may provide control signaling between the radio ac- cess network controller 200 , the distributed unit (DU) 210 and the radio unit (RU) 220 .

Fig . 1 illustrates an example radio access network 100 , where various embodiments of the present disclosure may be im- plemented . The radio access network 100 comprises the radio ac- cess network controller 200 , the distributed unit 210 , and the radio unit 220 . As shown in Fig . 1 , the layer 1 (LI ) function is split between the DU 210 and the RU 220 across the fronthaul (open fronthaul in the example of Fig . 1 ) connection 110 , wherein the portion of LI functions that reside in the DU 210 is referred to as Llhigh and the portion of LI functions that reside in the RU 220 is referred to as Lllow . In a virtualized architecture , the Llhigh and Lllow may be constructed as containers 210A, 220A which run their respective virtual network functions . The con- tainers 210A, 220A may also include configuration and orches- tration functions that manage the virtual network functions , such as Llhigh and fronthaul configuration block 210A1 and Lllow and fronthaul configuration block 220A1 .

Furthermore , the DU 210 may comprise layer 2 (L2 ) func- tions 210B, such as data link layer and scheduling functions . The RU 220 may further comprise radio frequency functions 220B .

Different LI function splits may result in different distributions of virtual network functions in the DU 210 and the RU 220 . For a 7-2 split , Lllow functions may include FFT and beamforming in the RU 220 ( shown as Lllow_7-2 220A2 ) , whereas Llhigh functions may include channel estimation, equalization and decoding ( shown as Llhigh_7-2 210A2 ) . For a 7-3 split , Lllow functions may include FFT, beamforming, channel estimation and equalization in the RU 220 ( shown as Lllow_7-3 220A3 ) , whereas Llhigh functions may include decoding ( shown as LlHigh_7-3 210A3 ) .

At least some of the disclosed embodiments may allow more than one type of LI function split to be active across the (open) fronthaul connection 110 . As shown in Fig . 1 , both the 7- 2 split and the 7-3 split may be supported across the (open) fronthaul connection 110 . The radio access network controller 200 may determine an optimal ratio between the 7-2 split flows and the 7-3 split flows in a near-real time basis according to, e . g . , user traffic conditions , power reservation needs , availa- ble fronthaul bandwidth, and a maximum processing capacity in the RU 220 .

As also shown in Fig . 1 , over the fronthaul connection 110 , besides the control flow 111 that the radio access network controller 200 may use to communicate with the RU 220 , there may be more than one type of active data flows 112 , 113 belonging to different low layer splits simultaneously . The different fron- thaul data flows 112 , 113 may carry their respective identifiers in order to be differentiated and handled correctly by their respective network functions in the DU 210 and/or the RU 220 .

In other words , since the fronthaul 110 may simultane- ously transmit traffic of different functional splits , a tag or the like may be needed to identify the different data flows over the fronthaul 110 . Such a tag field may be added, e . g . , to the corresponding header information that describes the payload .

The radio access network 100 may further comprise a control interface 120 ( such as an E2 control interface ) via which the radio access network controller 200 may send control messages / signaling to the DU 210 and which control messages / signaling may be routed through the fronthaul control flow 111 to the RU 220 .

Fig . 2A is a block diagram of the radio access network controller 200 in the radio access network 100 comprising the distributed unit 210 , at least one radio unit 220 and at least one fronthaul connection 110 between the distributed unit 210 and the at least one radio unit 220 , in accordance with an example embodiment . For example , the radio access network 100 may comprise an open radio access network . In this case , the at least one fronthaul connection 110 may comprise an open fronthaul connection . For example , the radio access network controller 200 may comprise a non-real time radio access network controller or a near-real time radio access network controller .

The radio access network controller 200 comprises at least one processor 202 and at least one memory 204 including computer program code . The radio access network controller 200 may also include other elements not shown in Fig . 2A.

Although the radio access network controller 200 is depicted to include only one processor 202 , the radio access network controller 200 may include more processors . In an em- bodiment , the memory 204 is capable of storing instructions , such as an operating system and/or various applications . Fur- thermore , the memory 204 may include a storage that may be used to store , e . g . , at least some of the information and data used in the disclosed embodiments .

Furthermore , the processor 202 is capable of executing the stored instructions . In an embodiment , the processor 202 may be embodied as a multi-core processor, a single core processor, or a combination of one or more multi-core processors and one or more single core processors . For example , the processor 202 may be embodied as one or more of various processing devices , such as a coprocessor, a microprocessor , a controller, a digital sig- nal processor (DSP ) , a processing circuitry with or without an accompanying DSP , or various other processing devices including integrated circuits such as , for example , an application spe- cific integrated circuit (ASIC) , a field programmable gate array (FPGA) , a microcontroller unit (MCU) , a hardware accelerator, a special-purpose computer chip, or the like . In an embodiment , the processor 202 may be configured to execute hard-coded func- tionality . In an embodiment , the processor 202 is embodied as an executor of software instructions , wherein the instructions may specifically configure the processor 202 to perform the algo- rithms and/or operations described herein when the instructions are executed .

The memory 204 may be embodied as one or more volatile memory devices , one or more non-volatile memory devices , and/or a combination of one or more volatile memory devices and non- volatile memory devices . For example , the memory 204 may be embodied as semiconductor memories ( such as mask ROM, PROM (pro- grammable ROM) , EPROM (erasable PROM) , flash ROM, RAM ( random access memory) , etc . ) .

The at least one memory 204 and the computer program code are configured to, with the at least one processor 202 , cause the radio access network controller 200 at least to perform obtaining data flow optimization information related to the at least one fronthaul connection 110 . For example , the data flow optimization information may comprise information about traffic load of the at least one radio unit 220 , 220 ₁₁ , 22012, 220 ₂₁ , 220 ₃₁ , 22 O32 , 220 ₄₁ , energy saving requirements in the radio access network 100 , available bandwidth of the at least one fronthaul connection 110 , 110 ₁₁ , 11012, 110 ₂₁ , 110 ₃₁ , 110 ₃₂ , 110 ₄₁ , available processing capacity in the at least one radio unit 220, 220 ₁₁ , 220 ₁₂ , 220 ₂₁ , 220 ₃₁ , 220 ₃₂ , 220 ₄₁ , available processing capacity in the distributed unit 210, 210 ₁₁ , 210 ₂₁ , 210 ₃₁ , 210 ₄₁ , user group- ing, quality of service, maximum bandwidth of the at least one fronthaul connection 110, 110 ₁₁ , 110 ₁₂ , 110 ₂₁ , 110 ₃₁ , 110 ₃₂ , 110 ₄₁ , maximum processing capacity in the at least one radio unit 220, 220 ₁₁ , 220 ₁₂ , 220 ₂₁ , 220 ₃₁ , 220 ₃₂ , 220 ₄₁ , and/or maximum processing capacity in the distributed unit 210, 210 ₁₁ , 210 ₂₁ , 210 ₃₁ , 210 ₁₁ .

In other words, the data flow optimization information comprising information about the traffic load of the at least one radio unit 220, 220 ₁₁ , 220 ₁₂ , 220 ₂₁ , 220 ₃₁ , 220 ₃₂ , 220 ₄₁ , the energy saving requirements in the radio access network 100, the available bandwidth of the at least one fronthaul connection 110, 110 ₁₁ , 110 ₁₂ , 110 ₂₁ , 110 ₃₁ , 110 ₃₂ , 110 ₄₁ , the available pro- cessing capacity in the at least one radio unit 220, 220 ₁₁ , 220 ₁₂ , 220 ₂₁ , 220 ₃₁ , 220 ₃₂ , 220 ₁₁ , the user grouping, the quality of ser- vice, and/or the available processing capacity in the distrib- uted unit 210, 210 ₁₁ , 210 ₂₁ , 210 ₃₁ , 210 ₁₁ is dynamic data flow optimization information, whereas the data flow optimization information comprising information about the maximum bandwidth of the at least one fronthaul connection 110, 110 ₁₁ , 110 ₁₂ , 110 ₂₁ , 110 ₃₁ , 110 ₃₂ , 110 ₄₁ , the maximum processing capacity in the at least one radio unit 220, 220 ₁₁ , 220 ₁₂ , 220 ₂₁ , 220 ₃₁ , 220 ₃₂ , 220 ₁₁ , and/or the maximum processing capacity in the distributed unit 210, 210 ₁₁ , 210 ₂₁ , 210 ₃₁ , 210 ₄₁ is static data flow optimization information .

At least in some embodiments, the dynamic data flow optimization information may be collected from the distributed unit 210, 210 ₁₁ , 210 ₂₁ , 210 ₃₁ , 210 ₁₁ , the at least one radio unit 220, 220 ₁₁ , 220 ₁₂ , 220 ₂₁ , 220 ₃₁ , 220 ₃₂ , 220 ₁₁ , and/or the at least one fronthaul connection 110, 110 ₁₁ , 110 ₁₂ , 110 ₂₁ , 110 ₃₁ , 110 ₃₂ , 110 ₄₁ (e.g., at runtime) and sent to the radio access network controller 200. In these embodiments, the obtaining of the data flow optimization information may comprise the radio access network controller 200 receiving the dynamic data flow optimization information from the distributed unit 210, 210 ₁₁ , 210 ₂₁ , 210 ₃₁ , 210 ₁₁ , the at least one radio unit 220, 220 ₁₁ , 220 ₁₂ , 220 ₂₁ , 220 ₃₁ , 220 ₃₂ , 220 ₄₁ , and/or the at least one fronthaul connection 110, 110 ₁₁ , 110 ₁₂ , 110 ₂₁ , 110 ₃₁ , 110 ₃₂ , 110 ₄₁ .

For example, the radio access network controller 200 may obtain knowledge about physical constraints, such as maximum fronthaul bandwidth and/or peak RU 220 processing capacity through capability signaling during system initialization. Fur- thermore, the radio access network controller 200 may collect a set of parameters during operation that are measured by the RU 220, the DU 210 and/or the fronthaul connection 110. These pa- rameters may include, e.g., traffic conditions (such as sector loading, user spatial density, user quality of service (QoS) parameters) , current RU 220 processing capacity, current fron- thaul connection 110 bandwidth in use, etc.

In other words, the capability signalling may be used by the network elements (e.g., the DU 210, RU 220, FH 110) to report their capabilities to the radio access network controller 200, e.g., during system initialization. The information in the capacity signalling may reflect the maximum physical processing capacity of the RU 220 in the Lllow container, whether the RU 220 is capable of supporting certain low layer split options (e.g., option 7-3 split, or option 6 split, etc.) , the maximum fronthaul bandwidth, the supported compression mode to the data flow, etc.

At least in some embodiments, the DU 210 may report, e.g., the current user traffic conditions and user groupings, the RU 220 may report, e.g., the current LILow container pro- cessing loading and current power consumption, and the fronthaul 110 interface may report, e.g., the current fronthaul bandwidth usage .

The at least one memory 204 and the computer program code are further configured to, with the at least one processor 202, cause the radio access network controller 200 at least to perform determining a distribution of low layer virtual network functions between the distributed unit 210 and the at least one radio unit 220 based on the obtained data flow optimization information. For example, the low layer virtual network functions may comprise a fast Fourier transform, FFT, related virtual network function, a beamforming related virtual network function, a channel estimation related virtual network function, an equalization related virtual network function, and/or a decoding related virtual network function . For example , the low layer may comprise layer 1 (L1 ) .

For example , the radio access network controller 200 may determine an optimal ratio of 7-2 split and 7-3 split flows in the fronthaul connection 110 to achieve an optimal operating condition under the physical constraints .

For example , this may be achieved by aiming to dimension the DU 210 and the RU 220 jointly to operate in a best possible combination of low layer splits to meet a network optimization goal , e . g . , best performance with least energy consumption in response to ever changing traffic conditions .

At least in some embodiments , the determining of the distribution of the low layer virtual network functions may comprise applying a machine learning (ML) model 400 to predict an optimal distribution of the low layer virtual network functions based on the obtained data flow optimization information .

In other words , intelligence may be built into AI/ML algorithms of the radio access network controller 200 to predict optimal low layer split ( s ) in order to optimize the network to meet the needs for the highest performance with the least energy consumption . Such a prediction model may be realized using AI/ML . For example , it may be implemented as a deep neural network (DNN) . A DNN may have, e . g . , an input layer 401 , an output layer 403 , and two or more hidden layers 402 . Diagram 400 of Fig . 4 illustrates an example DNN with its inputs 401 and outputs 403 listed in accordance with the present disclosure .

As shown in Fig . 4 , an example DNN may have , e . g . , the following inputs 401 , which may include measurements collected from the DU 210 , the RU 220 , and the fronthaul connection 110 :

- current processing load in the Lllow container in RU1 and RU2 ,

- current fronthaul connection bandwidth usage ,

- current power consumption at the RU,

- user grouping information by spatial correlation, and

- user grouping information by QoS . At the output layer 403 , the DNN may have , e . g . , the following outputs :

- low layer split decision for RU1 , and

- low layer split decision for RU2 .

The AI/ML algorithm may also have knowledge about the physical constraints , e . g . , the maximum fronthaul connection bandwidth and the maximum low layer processing capacity . These constraints may, e . g . , impact the weights assigned to each path in the hidden layers 402 and subsequently the outputs 403 .

The AI/ML algorithm may also have built-in hysteresis to avoid frequent transition between different low layer splits . At least in some embodiments , this may be a part of training of the DNN model to learn a threshold of safe transition, taking into account the time needed to prepare the transition and the need to protect the integrity of the existing data traffic during the transition .

The at least one memory 204 and the computer program code are further configured to, with the at least one processor 202 , cause the radio access network controller 200 at least to perform transmitting control signaling to the distributed unit 210 and/or the at least one radio unit 220 . The control signaling comprises instructions to deploy the determined distribution of the low layer virtual network functions .

At least in some embodiments , the at least one memory 204 and the computer program code may be further configured to, with the at least one processor 202 , cause the radio access network controller 200 to recurringly perform at least one of the obtaining of the data flow optimization information, the determining of the distribution of the low layer virtual network functions , or the transmitting of the control signaling . This recurring performing may be executed, e . g . , in response to changes in the dynamic data flow optimization information .

For example , the radio access network controller 200 may send control signaling / messages through the E2 control interface 120 to the configuration module 210A1 in the Llhigh container 210A in the DU 210 , wherein the configuration module 210A1 may rescale the virtual network functions for Llhigh_7-2 210A2 and Llhigh 7-3 210A3 . The configuration module 210A1 may also rescale the fronthaul connection 110 handling functions to match with the new ratio of 7-2 and 7-3 flows over the fronthaul connection 110 .

Furthermore , the radio access network controller 200 may send control signaling / messages via the E2 control inter- face 120 to the DU 210 to be routed through the fronthaul control flow 111 to the configuration module 220A1 in the Lllow container 220A in the RU 220 , wherein the configuration module 220A1 may rescale the virtual network functions for Lllow_7-2 220A2 and Lllow_7-3 220A3 . The configuration module 220A1 may also rescale the fronthaul connection 110 handling functions to match with the new ratio of 7-2 and 7-3 flows over the fronthaul connection 110 .

At least in some embodiments , the control signaling may further comprise timing information indicating when to activate the determined distribution of the low layer virtual network functions .

For example , the control signaling / messages for the DU 210 and RU 220 may comprise timing information such that the activation time of the new ratio can be synchronized between the DU 210 and RU 220 to enable seamless transition without inter- ruption to existing services .

As described above , at least in some embodiments the radio access network controller 200 may send control signaling / messages to the DU 210 and RU 220 to enable changing the fronthaul connection 110 split dynamically . This control message may comprise , e . g . , at least some of the following parameters :

- a source node identification ( ID ) (e . g . , an identi- fication of the DU 210 ,

- a target node ID (e . g . , an identification of the RU 220 and the corresponding Lllow container) ,

- a new low layer split assignment (e . g . , a percentage of the processing capability dedicated to a low layer split type one on the target node , and a percentage of the processing ca- pability dedicated to a low layer split type two on the target node ) . This may use relative percentage values as well , e . g . , increase the existing network function capacity by a certain percentage , - a time to trigger (e.g., frame number / subframe offset) . This may specify the point in time when the new low layer split (s) can take place.

At least in some embodiments, the disclosure may be mapped directly to the open RAN architecture.

One option is to map the radio access network controller 200 to a non-RT RIC 132. An example flow chart of the low layer reconfiguration through the non-real time RIC 132 is shown in diagram 500A of Fig. 5A. More specifically, the non-RT RIC 132 may create and train ML models based on inputs received at op- erations 501-502 from an 01 interface, such as processing load at the RUs, fronthaul bandwidth measurements, RU power measure- ments, RU traffic composition by correlation (e.g., COMP vs. non-COMP, clustered users vs. isolated users) , and/or RU traffic composition by QoS (e.g., eMBB vs. URLLC) .

The 01 interface is an operations, administration and management (0AM) 131 interface from service management and or- chestration (SMO) 130 to the RAN and also from the SMO 130 to the near-real time radio access network controller 140. The SMO 130 may incorporate the non-real time radio access network controller 132 function, but the 01 interface does not terminate on the non-real time radio access network controller 132. The Al interface is a policy -based interface from the non-real time radio access network controller 132 to the near-real time radio access network controller 140.

As shown in Figs. 5A and 5B, the O-RAN 100 may further comprise an O-RAN central unit-control plane node 151 (e.g., hosting radio resource control (RRC) and a control plane part of packet data convergence protocol (PDCP) ) and an O-RAN central unit-user plane node 152 (e.g., hosting a user plane part of the PDCP protocol and service data adaptation protocol (SDAP) ) .

The output of the ML model may comprise the threshold at which any given O-RU 220 changes the ratio of the low layer split .

The O-DU 210 and O-RU 220 may change the low layer split at operations 505-510 (as described above in more detail) ac- cording to the thresholds provided by the non-real time RIC 132 at operation 504 based on a transition decision made at operation 503 .

Another option is to map the radio access network con- troller 200 to a near-real time RIC 140 . An example flow chart of the low layer split reconfiguration using the near-real time RIC 140 is shown in diagram 500B of Fig . 5B .

A near-RT RIC 140 may provide faster ( less than 1 sec- ond) control . The near-RT RIC 140 may accept declaratives -based policy guidance from the non-real time RIC 132 through an Al interface at operations 551-552 . The policy may be converted into a utility metric used in development of the AI/ML model , operation 553 . The AI/ML model may be updated dynamically based on E2 inputs ( such as processing load at the RUs , fronthaul bandwidth measurements , RU power measurements , RU traffic com- position by correlation (e . g . , COMP vs . non-COMP , clustered us- ers vs . isolated users ) , and/or RU traffic composition by QoS (e . g . , eMBB vs . URLLC) ) received at operations 554-555 from the DU 210 . RU 220 and fronthaul 110 information may be aggregated by the DU 210 via the fronthaul 110 . The AI/ML model may deter- mine (transition decision made at operation 556 ) for each RU 220 at which point each RU 220 changes the configuration of the low layer splits at operations 558-563 (as described above in more detail ) based on the transition decision received at operation 557 .

Furthermore , the above-described signaling messages may be mapped to corresponding O-RAN interfaces .

At least in some embodiments , at least some of the above-described low layer split changes may be made on a near real-time scale .

As discussed above , at least some of the disclosed em- bodiments may allow dynamic transition or co-existence of more than one type of low layer split across the (open) fronthaul connection 110 . It is be understood that the low layer split is not limited to the 7-2 and 7-3 splits , nor it is limited to splits within layer 1 . Any other types of fronthaul connection 110 split may be implemented without departing from the spirit and scope of the subject matter described herein, such as a split option 6 in which the entire LI function is in the RU 220 . In the following, some example embodiments are de- scribed with reference to Figs . 3A-3D .

In the embodiment shown in diagram 300A of Fig . 3A, a 7-3 split may be transitioned to a 7-2 split to reduce power consumption .

As shown in Fig . 3A, the DU 210 ₁₁ is connected to both RU1 220ii and RU2 22012 . Initially, DU 210 ₁₁ , RU1 220 ₁₁ and RU2 22012 operate in a 7-3 split , i . e . , the two RUs 220 ₁₁ , 220 ₁₂ perform channel estimation, equalization, beamforming and FFT functions in the Lllow container 220A, whereas the DU 210 ₁₁ per- forms decoding function in the Llhigh container 210A.

At least in the embodiment shown in diagram 300A of Fig . 3A, the 7-3 split may be seamless transitioned to a 7-2 split according to the directions of the radio access network controller 200 . The radio access network controller 200 may de- termine that the combined traffic loading from the two RUs 220 ₁₁ , 22012 may fall below a certain threshold and there is sufficient fronthaul bandwidth to carry all the needed spatial streams to the DU 210ii without loss of receiver performance . More specif- ically, the Lllow containers 220A may deactivate the channel estimation and equalization functions in the RUs 220 ₁₁ , 220 ₁₂ and the Llhigh container 210A may activate the channel estimation and equalization functions in the DU 210 ₁₁ , which effectively transforms the 7-3 split to a 7-2 split .

By exploiting the resource pooling, this transition may reduce the total energy consumption of the network without sac- rificing the performance .

In the embodiment shown in diagram 300B of Fig . 3B, a 7-2 split can be used to offload a portion of processing capacity from a 7-3 split in an overloaded situation .

As shown in Fig . 3B, the DU 210 ₂₁ is connected to an RU1 220 ₂₁ . Initially, the DU 210 ₂₁ and RU 220 ₂₁ operate in a 7-3 split , wherein the channel estimation and equalization is handled by the RU 220 ₂₁ . As the cell gets overloaded due to the amount of user traffic or due to the user density requiring more spatial streams , the Lllow container 220A in the RU 220 ₂₁ may be ap- proaching its nominal maximum capacity . At least in the embodiment shown in diagram 300B of Fig . 3B, a portion of the Lllow network functions for the 7-3 split may be transitioned to a 7-2 split to take advantage of the additional processing capacity at the DU 210 ₂₁ to satisfy the increased traffic load . The radio access network controller 200 may determine an optimal ratio between the 7-2 split flow and the 7-3 split flow with the physical constraints in the maximum fronthaul bandwidth and the Lllow container 220A processing ca- pacity taken into consideration . More specifically, the radio access network controller 200 may separate the users in two groups , i . e . , ( 1 ) the group 301 of users that are highly corre- lated to each other (e . g . , in close proximity) , where a higher number of spatial streams (potentially higher than the fronthaul connection 110 ₂₁ bandwidth) may be required to separate them apart and to achieve good receiver performance ; and ( 2 ) the group 302 of users that are relatively isolated, or are reduced capa- bility (RedCap) devices , where a fewer number of spatial streams are sufficient to meet the receiver performance target . At least in the embodiment shown in diagram 300B of Fig . 3B, the isolated / reduced capability users 302 may be offloaded to the DU 210 ₂₁ by activating the channel estimation and equalization functions in the DU 210 ₂₁ and dedicating the vacated capacity in the RU 220 ₂ 2 ₁ to boost channel estimation and equalization processing capacity for the highly correlated users 301 . As a result , there may be two types of data flows ( i . e . , a 7-2 split flow and a 7- 3 split flow) over the fronthaul connection 110 ₂₁ , as shown in Fig . 3B .

The offloading allows optimal distribution of pro- cessing capacity across the DU 210 ₂₁ and the RU 220 ₂₁ , to allow handling both highly correlated group 301 of users and isolated / reduced capability group 302 of users .

In the embodiment shown in diagram 300C of Fig . 3C, a 7-2 split may be used to offload processing capacity from a 7-3 split in order to support inter-RU coordinated processing (e . g . , uplink (UL) coordinated multi-points (CoMP ) traffic) .

As shown in Fig . 3C, the DU 210 ₃₁ is connected to the RU1 220 ₃₁ and RU2 220 ₃₂ through their respective fronthaul con- nections 110 ₃₁ , 110 ₃₂ . Initially the RU1 220 ₃₁ operates in a 7-3 split with the DU 210 ₃₁ , wherein the channel estimation and equalization functions are performed in the Lllow container 220A in the RU1 220 ₃₁ . During network operation, some users may be located in the overlapped coverage area between RU1 220 ₃₁ and RU2 22032 , wherein it is beneficial to combine the spatial streams from both the RU1 220 ₃₁ and RU2 220 ₃₂ and perform channel esti- mation and equalization jointly through UL CoMP . The UL CoMP operation adds additional processing requirements and may not be fully dimensioned into the current 7-3 RU processing capacity .

At least in the embodiment shown in diagram 300C of Fig . 3C, users 304 who may benefit from the UL CoMP may still be processed in the 7-3 split , wherein the spatial streams may be joint-processed in the serving RU ( shown in Fig . 3C as data path 323 and data path 322 ) , whereas some other users 303 may be offloaded to the DU 210 ₃₁ to be processed through the 7-2 split ( shown in Fig . 3C as the data path 321 ) . Here , RU1 220 ₃₁ is the serving RU that aggregates the post-FFT and beamforming data from the RU1 220 ₃₁ and RU2 220 ₃₂ of the CoMP users 304 , and performs joint channel estimation and equalization in the RU1 220 ₃₁ . The radio access network controller 200 may determine the ratio of the 7-2 and 7-3 split flows over the fronthaul connec- tions 110 ₃₁ , 110 ₃₂ by evaluating the processing needs of the CoMP users 304 for channel estimation and equalization functions in the Lllow container 220A in the RU1 220 ₃₁ , and the processing needs of non-CoMP users 303 in the Llhigh container 210A in the DU 210 ₃₁ with the physical constraints of the fronthaul connec- tions 110 ₃₁ , 110 ₃₂ bandwidth and the 7-3 RU maximum processing capacity taken into consideration .

The DU 210 ₃₁ offloading in this case may benefit the inter-site (RU1 220 ₃₁ and RU2 220 ₃₂ are not collocated) or intra- site (RU1 220 ₃ 3 ₁ and RU2 220 ₃₂ are collocated and point to differ- ent directions ) joint-reception without sacrificing receiver performance of the other users .

In the embodiment shown in diagram 300D of Fig . 3D , redistribution of network functions across the fronthaul con- nection 110 ₄₁ may serve to improve latency for latency sensitive traffic, such as ultra-reliable low latency communication

(URLLC) traffic . As shown in Fig . 3D , the DU 210 ₄₁ is connected to the RU 220 ₄₁ through the fronthaul connection 110 ₄₁ . Enhanced mobile broadband (eMBB) traffic 305 (traf fic that is not latency sen- sitive ) may operate in a 7-3 split , whereas for URLLC traffic 306 , the Lllow container 220A in the RU 220 ₄₁ may activate option 6 220A6 , wherein the entire layer 1 function (FFT, beamforming, channel estimation, equalization, and decoding) resides in the RU 220 ₄₁ . This approach may allow a hybrid automatic repeat re- quest (HARQ) loop to be handled in the RU 220 ₄₁ , which allows faster retransmission ( i . e . , avoids the latency incurred by the fronthaul connection 110 ₄₁ ) for URLLC traffic .

Fig . 6 illustrates an example flow chart of a method 600 , in accordance with an example embodiment .

At operation 601 , the radio access network controller 200 obtains data flow optimization information related to the at least one fronthaul connection 110 in the radio access network 100 . As discussed above in more detail , the radio access network 100 comprises the distributed unit 210 , the at least one radio unit 220 and the at least one fronthaul connection 110 between the distributed unit 210 and the at least one radio unit 220 .

At operation 602 , the radio access network controller 200 determines a distribution of low layer virtual network functions between the distributed unit 210 and the at least one radio unit 220 based on the obtained data flow optimization information .

At operation 603 , the radio access network controller 200 transmits control signaling to the distributed unit 210 and/or the at least one radio unit 220 . The control signaling comprises instructions to deploy the determined distribution of the low layer virtual network functions .

As discussed above, the radio access network controller 200 may recurringly perform at least one of the obtaining 601 of the data flow optimization information, the determining 602 of the distribution of the low layer virtual network functions , or the transmitting 603 of the control signaling, as shown in Fig . 6. This recurring performing may be executed, e . g . , in response to changes 604 in the dynamic data flow optimization information . The method 600 may be performed by the radio access network controller 200 of Fig . 2A . The operations 601-604 can, for example , be performed by the at least one processor 202 and the at least one memory 204 . Further features of the method 600 directly result from the functionalities and parameters of the radio access network controller 200 , and thus are not repeated here . The method 600 can be performed by computer program ( s ) .

Fig . 2B is a block diagram of the distributed unit 210 connected to the at least one radio unit 220 via the at least one fronthaul connection 110 in the radio access network 100 , in accordance with an example embodiment . For example , the radio access network 100 may comprise an open radio access network . In this case , the at least one fronthaul connection 110 may comprise an open fronthaul connection .

The distributed unit 210 comprises at least one pro- cessor 212 and at least one memory 214 including computer program code . The distributed unit 210 may also include other elements not shown in Fig . 2B .

Although the distributed unit 210 is depicted to in- clude only one processor 212 , the distributed unit 210 may in- clude more proces sors . In an embodiment , the memory 214 is ca- pable of storing instructions , such as an operating system and/or various applications . Furthermore , the memory 214 may include a storage that may be used to store , e . g . , at least some of the information and data used in the disclosed embodiments .

Furthermore , the processor 212 is capable of executing the stored instructions . In an embodiment , the processor 212 may be embodied as a multi-core processor, a single core processor, or a combination of one or more multi-core processors and one or more single core processors . For example , the processor 212 may be embodied as one or more of various processing devices , such as a coprocessor, a microprocessor , a controller, a digital sig- nal processor (DSP ) , a processing circuitry with or without an accompanying DSP , or various other processing devices including integrated circuits such as , for example , an application spe- cific integrated circuit (ASIC) , a field programmable gate array (FPGA) , a microcontroller unit (MCU) , a hardware accelerator, a special-purpose computer chip, or the like . In an embodiment , the processor 212 may be configured to execute hard-coded func- tionality . In an embodiment , the processor 212 is embodied as an executor of software instructions , wherein the instructions may specifically configure the processor 212 to perform the algo- rithms and/or operations described herein when the instructions are executed .

The memory 214 may be embodied as one or more volatile memory devices , one or more non-volatile memory devices , and/or a combination of one or more volatile memory devices and non- volatile memory devices . For example , the memory 214 may be embodied as semiconductor memories ( such as mask ROM, PROM (pro- grammable ROM) , EPROM (erasable PROM) , flash ROM, RAM ( random access memory) , etc . ) .

The at least one memory 214 and the computer program code are configured to, with the at least one processor 212 , cause the distributed unit 210 at least to perform receiving the control signaling from the radio access network controller 200 in the radio access network 100 . The control signaling comprises the instructions to deploy the determined distribution of the low layer virtual network functions between the distributed unit 210 and the at least one radio unit 220 , as discussed above in more detail .

The at least one memory 214 and the computer program code are further configured to, with the at least one processor 212 , cause the distributed unit 210 at least to perform, in response to the received control signaling, deploying the determined distribution by activating and/or deactivating at least one of the low layer virtual network functions in accordance with the instructions comprised in the received control signaling .

At least in some embodiments , the at least one memory 214 and the computer program code may be further configured to, with the at least one processor 212 , cause the distributed unit 210 , 210ii , 2 IO21 , 2 I O31 , 2 IO41 at least to perform collecting data flow optimization information e . g . , dynamic data flow optimization information, as discussed above in more detail ) , and transmitting the collected data flow optimization information to the radio access network controller 200 . Further features of the distributed unit 210 directly result from the functionalities and parameters of the radio access network controller 200 and thus are not repeated here .

Fig . 7 illustrates an example flow chart of a method 700 , in accordance with an example embodiment .

At optional operation 701 , the distributed unit 210 connected to the at least one radio unit 220 via the at least one fronthaul connection 110 in the radio access network 100 may collect data flow optimization information (e . g . , dynamic data flow optimization information) .

At optional operation 702 , the distributed unit 210 may transmit the collected data flow optimization information to the radio access network controller 200 .

At operation 703 , the distributed unit 210 receives the control signaling from the radio access network controller 200 in the radio access network 100 . The control signaling comprises the instructions to deploy the determined distribution of the low layer virtual network functions between the distributed unit 210 and the at least one radio unit 220 .

At operation 704 , the distributed unit 210 deploys , in response to the received control signaling, the determined distribution by activating and/or deactivating at least one of the low layer virtual network functions in accordance with the instructions comprised in the received control signaling .

The method 700 may be performed by the distributed unit 210 of Fig . 2B . The operations 701-704 can, for example , be performed by the at least one processor 212 and the at least one memory 214 . Further features of the method 700 directly result from the functionalities and parameters of the distributed unit 210 , and thus are not repeated here . The method 700 can be performed by computer program ( s ) .

Fig . 2C is a block diagram of the radio unit 220 connected to the distributed unit 210 via the fronthaul connec- tion 110 in the radio access network 100 , in accordance with an example embodiment . For example , the radio access network 100 may comprise an open radio access network . In this case , the at least one fronthaul connection 110 may comprise an open fronthaul connection . The radio unit 220 comprises at least one processor 222 and at least one memory 224 including computer program code . The radio unit 220 may also include other elements not shown in Fig . 2C .

Although the radio unit 220 is depicted to include only one processor 222 , the radio unit 220 may include more proces- sors . In an embodiment , the memory 224 is capable of storing instructions , such as an operating system and/or various appli- cations . Furthermore , the memory 224 may include a storage that may be used to store , e . g . , at least some of the information and data used in the disclosed embodiments .

Furthermore , the processor 222 is capable of executing the stored instructions . In an embodiment , the processor 222 may be embodied as a multi-core processor, a single core processor, or a combination of one or more multi-core processors and one or more single core processors . For example , the processor 222 may be embodied as one or more of various processing devices , such as a coprocessor, a microprocessor , a controller, a digital sig- nal processor (DSP ) , a processing circuitry with or without an accompanying DSP , or various other processing devices including integrated circuits such as , for example , an application spe- cific integrated circuit (ASIC) , a field programmable gate array (FPGA) , a microcontroller unit (MCU) , a hardware accelerator, a special-purpose computer chip, or the like . In an embodiment , the processor 222 may be configured to execute hard-coded func- tionality . In an embodiment , the processor 222 is embodied as an executor of software instructions , wherein the instructions may specifically configure the processor 222 to perform the algo- rithms and/or operations described herein when the instructions are executed .

The memory 224 may be embodied as one or more volatile memory devices , one or more non-volatile memory devices , and/or a combination of one or more volatile memory devices and non- volatile memory devices . For example , the memory 224 may be embodied as semiconductor memories ( such as mask ROM, PROM (pro- grammable ROM) , EPROM (erasable PROM) , flash ROM, RAM ( random access memory) , etc . ) . The at least one memory 224 and the computer program code are configured to, with the at least one processor 222 , cause the radio unit 220 at least to perform receiving the control signaling from the radio access network controller 200 in the radio access network 100 . The control signaling comprises the instructions to deploy the determined distribution of the low layer virtual network functions between the radio unit 220 and the distributed unit 210 , as discussed above in more detail .

The at least one memory 224 and the computer program code are further configured to, with the at least one processor 222 , cause the radio unit 220 at least to perform, in response to the received control signaling, deploying the determined distribution by activating and/or deactivating at least one of the low layer virtual network functions in accordance with the instructions comprised in the received control signaling .

At least in some embodiments , the at least one memory 224 and the computer program code may be further configured to, with the at least one processor 222 , cause the radio unit 220 , 220 ₁₁ ,, 220 ₁₂ , 220 ₂₁ , 220 ₃₁ , 220 ₃₂ , 220 ₄₁ at least to perform collecting data flow optimization information (e . g . , dynamic data flow optimization information, as discussed above in more detail ) , and transmitting the collected data flow optimization information to the radio access network controller 200 .

Further features of the radio unit 220 directly result from the functionalities and parameters of the radio access network controller 200 and the distributed unit 210 , and thus are not repeated here .

Fig . 8 illustrates an example flow chart of a method 800 , in accordance with an example embodiment .

At optional operation 801 , the radio unit 220 connected to the distributed unit 210 via the fronthaul connection 110 in the radio access network 100 may collect data flow optimization information (e . g . , dynamic data flow optimization information) .

At optional operation 802 , the radio unit 220 may transmit the collected data flow optimization information to the radio access network controller 200 .

At operation 803 , the radio unit 220 receives the control signaling from the radio access network controller 200 in the radio access network 100 . The control signaling comprises the instructions to deploy the determined distribution of the low layer virtual network functions between the radio unit 220 and the distributed unit 210 .

At operation 804 , the radio unit 220 deploys , in response to the received control signaling, the determined distribution by activating and/or deactivating at least one of the low layer virtual network functions in accordance with the instructions comprised in the received control signaling .

The method 800 may be performed by the radio unit 220 of Fig . 2C . The operations 801-804 can, for example , be performed by the at least one processor 222 and the at least one memory 224 . Further features of the method 800 directly result from the functionalities and parameters of the radio unit 220 , and thus are not repeated here . The method 800 can be performed by com- puter program ( s ) .

At least some of the embodiments described herein may allow dynamic redistribution of virtual functions between the radio unit 220 and the distributed unit 210 according to traffic loads and energy conservation needs . One split option may be transitioned to another split option seamlessly during active operation .

Furthermore , two or more functional split options may co-exist over the fronthaul 110 to better utilize the processing resources in the RU 220 and the DU 210 to maximize the perfor- mance and at the same time leverage the pooling capability in the DU 210 .

At least some of the embodiments described herein may allow the radio access network controller 200 to manage the low layer functional split between the DU 210 and the RU 220 , which may be mapped to a non-real time RIC and a near-real time RIC, and an El interface may be mapped to the DU 210 and RU 220 in an open architecture , such as O-RAN .

At least some of the embodiments described herein may allow an AI/ML based model mapped to an O-RAN intelligent man- agement layer, which may monitor the user traffic loading and performance requirements (e . g . , whether it is necessary for a user or a group of users to be processed in the RU 220 ) and determine the best strategy for the low layer split under the physical constraints of the computing capability in the radio unit 220 and the fronthaul 110 bandwidth, etc .

At least some of the embodiments described herein may allow control signaling to handle the redistribution of virtual functions across the fronthaul 110 . At least some of the embod- iments described herein may allow data signaling to identify the different types of data flows due to different splits over the fronthaul connection 110 . These messages may be mapped to the open fronthaul 110 and/or other open interfaces in O-RAN .

At least some of the embodiments described herein may allow better utilization of the network capacity . At least some of the embodiments described herein may allow dynamic redistri- bution of network functions between the DU 210 and the RU 220 to better utilize the processing capacity in the RU 220 ( for users that require high number of beams ) and the DU 210 (offload the isolated users to the DU 210 ) to maximize performance .

At least some of the embodiments described herein may allow energy saving and carbon footprint reduction . If the system is lightly loaded (also the fronthaul 110 may be under-utilized due to fewer physical resource blocks (PRBs ) or smaller bandwidth parts (BWPs ) being used) , moving the fronthaul 110 split from 7- 3 to 7-2 may leverage the resource pooling at the DU 210 (turn off the channel estimation / equalization functions from all RUs ) and reduce energy consumption .

At least some of the embodiments described herein are not restricted to 7-2 vs 7-3 split . At least some of the embod- iments described herein are applicable to other kinds of low layer splits between the RU 220 and the DU 210 .

The radio access network controller 200 may comprise means for performing at least one method described herein . In an example , the means may comprise the at least one processor 202 , and the at least one memory 204 including program code configured to, when executed by the at least one processor 202 , cause the radio access network controller 200 to perform the method .

The distributed unit 210 may comprise means for per- forming at least one method described herein . In an example , the means may comprise the at least one processor 212 , and the at least one memory 214 including program code configured to, when executed by the at least one processor 212 , cause the distributed unit 210 to perform the method .

The radio unit 220 may comprise means for performing at least one method described herein . In an example , the means may comprise the at least one processor 222 , and the at least one memory 224 including program code configured to, when executed by the at least one processor 222 , cause the radio unit 220 to perform the method .

The functionality described herein can be performed, at least in part , by one or more computer program product components such as software components . According to an embodiment , the network node device 200 may comprise a processor or processor circuitry, such as for example a microcontroller, configured by the program code when executed to execute the embodiments of the operations and functionality described . Alternatively, or in ad- dition, the functionality described herein can be performed, at least in part , by one or more hardware logic components . For example , and without limitation, illustrative types of hardware logic components that can be used include Field-programmable Gate Arrays (FPGAs ) , Program-specific Integrated Circuits (ASICs ) , Program-specific Standard Products (ASSPs ) , System-on- a-chip systems ( SOCs ) , Complex Programmable Logic Devices (CPLDs ) , and Graphics Processing Units (GPUs ) .

Any range or device value given herein may be extended or altered without losing the effect sought . Also, any embodiment may be combined with another embodiment unless explicitly dis- allowed .

Although the subj ect matter has been described in lan- guage specific to structural features and/or acts , it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above . Rather, the specific features and acts de- scribed above are disclosed as examples of implementing the claims and other equivalent features and acts are intended to be within the scope of the claims .

It will be understood that the benefits and advantages described above may relate to one embodiment or may relate to several embodiments . The embodiments are not limited to those that solve any or all of the stated problems or those that have any or all of the stated benefits and advantages . It will further be understood that reference to ' an ' item may refer to one or more of those items .

The steps of the methods described herein may be car- ried out in any suitable order, or simultaneously where appro- priate . Additionally, individual blocks may be deleted from any of the methods without departing from the spirit and scope of the subject matter described herein . Aspects of any of the em- bodiments described above may be combined with aspects of any of the other embodiments described to form further embodiments without losing the effect sought .

The term ' comprising ' is used herein to mean including the method, blocks or elements identified, but that such blocks or elements do not comprise an exclusive list and a method or apparatus may contain additional blocks or elements .

It will be understood that the above description is given by way of example only and that various modifications may be made by those skilled in the art . The above specification, examples and data provide a complete description of the structure and use of exemplary embodiments . Although various embodiments have been described above with a certain degree of particularity, or with reference to one or more individual embodiments , those skilled in the art could make numerous alterations to the dis- closed embodiments without departing from the spirit or scope of this specification .