Technical Field

The present invention relates to dynamic Block Error Rate (BLER) target selection for spectrum coexistence. In particular, the present invention relates to a radio network node, a method performed by the radio network node, and a communication system comprising a user terminal and the radio network node to dynamically adapt the BLER target according to a current radio channel condition.

Background

As with 5G (the fifth-generation mobile communication standard) and future mobile communication standards, the focus has been expanding beyond the classical mobile broadband applications. Particularly, the industry is moving towards adopting new wireless communications standards capable of handling high number of user equipment (UE), user terminals, or terminal devices which may be connected to sensors, robots, controllers, mobile platforms, etc. There is a need for efficient wireless communication not only for machine-type communication but also for the interaction and collaboration between humans and machines. 5G aims at enabling new manufacturing concepts to be implemented in the Industry 4.0 context. From the research point of view, many new topics and questions arise, for instance, how two or more networks in close vicinity on adjacent or co-channel spectrum would coexist and satisfy the expected Quality of Service (QoS) targets for the Industry 4.0 applications.

Recent studies on empirical analysis of coexisting networks highlight potential issues of outdoor interference to an indoor network. In such coexisting scenarios, a locally deployed network for indoor industrial applications, i.e. an indoor network, may operate on the same spectrum as other neighbouring networks, i.e. outdoor networks.

One of the conclusions from the empirical analysis is that a UE from the outdoor network, like a Public Network (PN), getting close to the indoor network, like a Non-Public Network (NPN), may significantly degrade the indoor downlink and uplink performance. Such performance degradation may depend upon a number of factors such as the proximity of interfering transmitter, like a transmitting node of the PN, to the receiver, like a receiving node of the NPN, and antenna directionality aspects, the power levels of the transmitting node and that of the interfering entity, signal quality level at the receiving node due to propagation characteristics, etc.

The issue of interference is particularly concerning for industrial use-cases with mission critical traffic demands. The indoor network performance in the presence of interference with unsynchronized Time Division Duplex (TDD) patterns has been analysed. The term unsynchronized TDD pattern refers to a scenario where the indoor and outdoor networks use different TDD patterns, i.e. the TDD pattern used for the indoor network is not the same as for the outdoor interfering network. However, the two networks may still have a common time reference, and their respective TDD patterns may be slot-aligned.

Such an analysis of the indoor network performance in the presence of interference with unsynchronized TDD patterns is of relevance since many industrial, production and automation applications require a more balanced uplink (UL)/downlink (DL) TDD pattern, i.e. a rather similar UL/DL split in the TDD pattern, in contrast of the primarily DL oriented TDD patterns used in classical mobile broadband applications. The interference for such unsynchronized TDD patterns is different compared to scenarios with synchronized TDD patterns since indoor UL slots, i.e. UL slots of the indoor network, may collide not only with the outdoor UL slots, i.e. UL slots of the outdoor network, but with the DL transmissions as well (similarly for indoor DL slots) adding cross-link interference to the study. Cross-link interference means that DL-to-UL and UL-to-DL interference occurs, while near-far interference means that DL-to-DL and UL-to-UL occurs.

There are not only two sources of interference, i.e. near-far interference and cross-link interference, but such interference is different to every slot. This is shown in Figure 1 which illustrates an example of interference sources on uplink slots of an indoor network. Figure 1 illustrates the slots of an indoor network and slots of an outdoor network. Interferences are illustrated with arrows. For instance, as shown in Figure 1, on every TDD pattern period the interferences on the indoor UL opportunities or indoor UL slots, i.e. the UL slots of the indoor network, come from different outdoor slots, see the outdoor DL slots, the outdoor UL slots, and the outdoor special slots. The special slots can flexibly be configured to DL and UL symbols. In Figure 1, the special slots are treated as DL symbols and are mainly considered to carry DL transmitted data. The dashed arrows illustrate cross-link interference and the solid arrow illustrates near-far interference, wherein DL-to-UL interference is named cross-link interference and UL-to-UL is named near-far interference. This is of relevant importance, because the indoor UL performance depends on the location of the UEs and radio network nodes (like a base station, gNB, or the like), transmission bitrate, interference sources (only UL, only DL, or both) and interference levels. Therefore, each indoor UL slot opportunity may suffer different interference levels. This in turn is very relevant for a Link Adaptation (LA) algorithm, wherein the Signal to Interference plus Noise Ratio (SINR) of the indoor network is quite unique for each of the slots of the TDD pattern and not only across the duration of the indoor TDD pattern. Theoretically, it is the least common multiple between the indoor and outdoor TDD patterns that define the interference constellation for all the slots, i.e. the 20 slots as illustrated as an example in Figure 1. Moreover, for an unsynchronized TDD pattern scenario, the interference levels may vary and distort the SINR. Hence, the assignment of the modulation and coding scheme (MCS) and resource blocks (RB) by the LA might not be very accurate. The inaccuracy of the estimated SINR by the LA may lead to either too optimistic or too pessimistic resource allocation which may significantly impact the indoor network performance and radio resource utilization. For example, for too pessimistic resource allocation, precious radio resources may be wasted.

Thus, interference levels may vary based on locations of the UEs, transmission bitrates, UL or DL transmission direction, interference levels, received UL/DL interference, the TDD patterns and the like. In addition, spatial aspects for transmissions may also be considered, like beamforming, partial blockage, shadowing, etc. While there may already be solutions to address some of these problems by, for example, selecting a different BLER target manually per UE or by choosing manually different BLER targets for UL and DL, an automatic method is missing which is able to adapt to variations depending upon the specific encountered conditions as mentioned above in a dynamic manner.

Summary

It may be an object of the invention to optimize the resource assignment of a link adaptation algorithm. According to a first aspect, a method performed by a radio network node comprises the steps of receiving an initial radio channel condition from a user terminal, setting a Block Error Rate (BLER) target based on the initial radio channel condition as an initial BLER target, and adapting the BLER target according to a current radio channel condition as part of an outer loop link adaptation at a per time interval level.

According to a second aspect, a radio network node may comprise a processor and a memory, the memory including instructions that when executed by the processor cause the processor to perform operations. The operations may comprise to receive an initial radio channel condition from a user terminal, set a BLER target based on the initial radio channel condition as an initial BLER target, and adapt the BLER target according to a current radio channel condition as part of an outer loop link adaptation at a per time interval level.

According to a third aspect, a radio network node may be adapted to receive an initial radio channel condition from a user terminal, set a BLER target based on the initial radio channel condition as an initial BLER target, and adapt the BLER target according to a current radio channel condition as part of an outer loop link adaptation at a per time interval level.

According to a fourth aspect, a method may be performed in a communication system. The communication system may comprise a user terminal and a radio network node. The method may comprise transmitting, by the user terminal, an initial radio channel condition to the radio network node, receiving, by the radio network node, the initial radio channel condition from the user terminal and setting, by the radio network node, a BLER target based on the initial radio channel condition as an initial BLER target. The method may further comprise transmitting, by the user terminal, a current radio channel condition to the radio network node, and adapting, by the radio network node, the BLER target according to the current radio channel condition as part of an outer loop link adaptation at a per time interval level.

According to a fifth aspect, a communication system may comprise a user terminal and the radio network node according to the third aspect. The user terminal may comprise a first processor and a first memory, and the first memory may include instructions that when executed by the first processor cause the first processor to perform operations. The operations may comprise transmitting an initial radio channel condition to the radio network node, and transmitting a current radio channel condition to the radio network node.

According to a sixth aspect, a communication system may comprise a user terminal and the radio network node according to the third aspect. The user terminal may be adapted to transmit an initial radio channel condition to the radio network node, and transmit a current radio channel condition to the radio network node.

According to a seventh aspect, a computer program may comprise program code to be executed by a processor of a radio network node. Execution of the program code may cause the radio network node to perform operations. The operations may comprise receiving an initial radio channel condition from a user terminal, setting a BLER target based on the initial radio channel condition as an initial BLER target, and adapting the BLER target according to a current radio channel condition as part of an outer loop link adaptation at a per time interval level.

According to an eighth aspect, a computer program product may comprise a non-transitory storage medium including program code to be executed by a processor of a radio network node. Execution of the program code may cause the radio network node to perform operations. The operations may comprise receiving an initial radio channel condition from a user terminal, setting a BLER target based on the initial radio channel condition as an initial BLER target, and adapting the BLER target according to a current radio channel condition as part of an outer loop link adaptation at a per time interval level.

According to a nineth aspect, a computer program may comprise program code to be executed by a processor of a user terminal and a processor of a radio network node. The user terminal and the radio network node may be included in a communication system. Execution of the program code may cause the user terminal and the radio network node to perform operations. The operations may comprise transmitting, by the user terminal, an initial radio channel condition to the radio network node, and receiving, by the radio network node, the initial radio channel condition from the user terminal. The operations may further comprise setting, by the radio network node, a BLER target based on the initial radio channel condition as an initial BLER target, transmitting, by the user terminal, a current radio channel condition to the radio network node, and adapting, by the radio network node, the BLER target according to the current radio channel condition as part of an outer loop link adaptation at a per time interval level.

According to a tenth aspect, a computer program product may comprise a non-transitory storage medium including program code to be executed by a processor of a user terminal and a processor of a radio network node. The user terminal and the radio network node may be included in a communication system. Execution of the program code may cause the user terminal and the radio network node to perform operations. The operations may comprise transmitting, by the user terminal, an initial radio channel condition to the radio network node, and receiving, by the radio network node, the initial radio channel condition from the user terminal. The operations may further comprise setting, by the radio network node, a BLER target based on the initial radio channel condition as an initial BLER target, transmitting, by the user terminal, a current radio channel condition to the radio network node, and adapting, by the radio network node, the BLER target according to the current radio channel condition as part of an outer loop link adaptation at a per time interval level.

Brief Description of Drawings

The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this application, illustrate certain non-limiting embodiments of inventive concepts. In the drawings:

Figure 1 illustrates an example of interference sources on uplink slots of an indoor network.

Figure 2 illustrates the location of various user terminals in a factory shopfloor.

Figure 3 illustrates a method performed by a radio network node for dynamically adapting a Block Error Rate target according to an embodiment of the invention.

Figure 4 illustrates an example for UE Assistance Information transmission used in an embodiment of the invention.

Figure 5 illustrates an exemplary table assigning Block Error Rate targets to different UE Assistance Information Values for a given user terminal used in an embodiment of the invention. Figure 6 illustrates an embodiment for dynamic Block Error Rate target assignment according to UE Assistance Information according to an embodiment of the invention.

Figure 7 illustrates a diagram of a link adaptation algorithm for dynamic BLER target assignment according to an embodiment of the invention.

Figure 8 illustrates examples for performing a dynamic Outer Loop Link Adaptation algorithm at various granularity levels according to embodiments of the invention.

Figure 9 illustrates an example of the functionality of dynamic BLER target assignment per four TDD slots according to an embodiment of the invention.

Figure 10 illustrates example candidates on dOLLA periods for three different Time Division Duplex patterns used in an embodiment of the invention.

Figure 11 illustrates an exemplary radio network node according to an embodiment of the invention.

Figure 12 illustrates an exemplary user terminal according to an embodiment of the invention.

Figure 13 illustrates an embodiment of the invention relating a method performed by a communication system comprising a radio network node and at least one user terminal.

Detailed Description

Concepts of embodiments of the invention will now be described more fully hereinafter with reference to the accompanying drawings, in which examples of embodiments of inventive concepts are shown. Inventive concepts may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of present inventive concepts to those skilled in the art. It should also be noted that these embodiments are not mutually exclusive. Components from one embodiment may be tacitly assumed to be present/used in another embodiment.

The following description presents various embodiments of the disclosed subject matter. These embodiments are presented as teaching examples and are not to be construed as limiting the scope of the disclosed subject matter. For example, certain details of the described embodiments may be modified, omitted, or expanded upon without departing from the scope of the described subject matter.

The following explanation of potential problems with some approaches is a present realization as part of the present disclosure and is not to be construed as previously known by others.

Below, solutions are described which address the interference issue arising from a coexisting network as explained above using a dynamic predictive BLER target assignment at a per time interval level for an outer loop link adaption. This mechanism may be particularly useful in the case when the network nodes may use TDD for communication. The time interval may be defined with respect to the underlying frame structure (e.g. a TDD pattern). The time interval could be a unit of an underlying frame structure, e.g. a slot or multiple slots, or a time interval corresponding to a radio channel condition feedback periodicity (e.g. a Channel State Information (CSI) periodicity or Sounding Reference Signal (SRS) periodicity) or a multiple of the radio channel condition feedback periodicity (e.g. a multiple of the CSI periodicity or a multiple of the SRS periodicity). Thus, a resource assignment of a link adaptation algorithm is optimized through this new dynamic outer loop link adaptation that updates used BLER target over time. An underlying goal is to create optimal resource allocation for a wide range of applications in the presence of spectral interference, variations of radio channel conditions, capacity requirements, dynamic traffic QoS demands, etc. One example for applications is 5G New Radio (NR) industrial applications requiring a highly reliable bounded low latency communication. Hence, it is very important to ensure that the expected QoS targets are met even in the presence of spectral interference. The solutions described below dynamically select and adapt appropriate BLER targets considering current radio channel conditions and traffic demands in a network. For example, the BLER targets may be dynamically adapted per TDD slot (e.g. every TDD slot) or per multiple TDD slots (e.g. every multiple of TDD slots) or per feedback granularity (e.g. every feedback periodicity) or per multiple feedback granularity (e.g. every multiple of the feedback periodicity) as described in more detail below.

As mentioned above, optimal resource allocation may be required in 5G NR industrial applications. Figure 2 illustrates an exemplary scenario for such a 5G NR industrial application. In Figure 2, several user terminals or user equipment UE1, UE2, UE3, UE4, and UE5 which may be connected to robots, sensors, controllers, mobile platforms, industrial machines, or the like, are located, for example, in a factory shopfloor. UE1, UE2, UE3, UE4, and UE5 are just examples and more or less user terminals may be located in the factory shopfloor or at any other location. An indoor network may cover the factory shopfloor.

The radio channel conditions and interferences may vary for each UE based on its location. As an example, UE1 in Figure 2 may be deployed deep inside the factory shopfloor premises, wherein its deployment may be fixed/static, for instance on a machine. Thus, UE1 may have very good radio channel conditions and very low exposure to interference.

On the other hand, UE2 and UE3 may be deployed at edge locations of the factory shopfloor leading to worse radio channel conditions compared to the radio channel conditions of UE1. Furthermore, UE2 and UE3 may be exposed to spectral interference from other networks, for example from an outdoor network.

Furthermore, UE4 and UE5 may be non-static and may move around the factory shopfloor (see dashed arrows). Thus, their exposure to interference may be very high when they need to move in and out of the factory shopfloor.

The example of Figure 2 illustrates that a method for dynamic BLER target selection or dynamic BLER target adaptation at a finer granularity is required to satisfy the application QoS targets even in the presence of interference from coexisting networks. Furthermore, it is necessary to enable efficient Physical Resource Block (PRB) allocation, specifically protecting cell-edge user terminals and UEs. This allows meeting the QoS targets of mission critical traffic (requiring low latency and high reliability), which otherwise suffer from interference issues. Furthermore, a method is required which flexibly targets UE groups and traffic types for granular and adaptive BLER target selection and efficiently utilizes resources. Such a method performed by a radio network node and fulfilling these requirements is now described with regard to Figure 3.

Figure 3 illustrates a method performed by a radio network node for dynamically adapting or selecting a BLER target. The radio network node may be a base station, a gNodeB, gNB, or any other radio network node according to 3GPP standards. The radio network node may be able to transmit and receive signals to and from user terminals or UEs. The user terminals or UEs may be UE1, UE2, UE3, UE4, and UE5 illustrated in

Figure 2.

At step S301, the radio network node may receive an initial radio channel condition, i.e. information on an initial radio channel condition, from a user terminal. The initial radio channel condition may indicate the link condition between the user terminal and the radio network node. For example, the initial radio channel condition indicates a position of the user terminal, expected mobility of the user terminal, expected radio quality conditions, a level of exposure to interference with respect to the user terminal, and/or traffic profiles. The traffic profiles may include requirements on throughput, latency, data traffic volume, priority class, etc.

According to an embodiment, the initial radio channel condition may be indicated by Sounding Reference Signals (SRS) for uplink link adaptation, Channel State Information (CSI) for downlink link adaptation, or User Equipment (UE) Assistance Information. The network node may receive the SRS or CSI from the user terminal to set the initial BLER target, wherein the SRS or CSI indicates the initial radio channel condition. It is also possible that the network node receives the UE Assistance Information, wherein the UE Assistance Information indicates the initial radio channel condition.

According to an embodiment, the user terminal may transmit the UE Assistance Information in a Radio Resource Control (RRC) message to the radio network node. In other words, the radio network node may receive the UE Assistance Information in the RRC message from the user terminal. 3GPP defined Information Element within the UE Assistance Information may be used in the RRC messaging. For example, 3GPP specifications describe RRC messages that can be used to ensure reliable bounded low latency communication between the user terminal and the radio network node (see, for example, 3GPP TS 38.331 V17.0.0 (2022-03), section 5.7.4). However, please note that even if the UE Assistance Information is mentioned to help the radio network node to assign dynamic BLER targets and range selection at a granular level, any other information including any (prior) pre-configured or independently acquired information at the base station from the user terminal, application context and/or inference at the radio network node may be used to dynamically assign BLER targets and adapt the BLER targets at a granular level.

Figure 4 illustrates an example for UE Assistance Information transmission. As shown in Figure 4, based on RRC Reconfiguration Information 430 transmitted between a UE 410 and a radio network node 420, the UE 410 may transmit UE Assistance Information 440 to the radio network node 420. The purpose of such a procedure may be for the UE 410 to inform the radio network node 420 of its delay budget report carrying desired increment/decrement in a connected mode discontinuous reception (DRX) cycle length; its overheated assistance information; its In-Device Coexistence (IDC) assistance information; its preference of DRX parameters for power saving; its preference on a maximum aggregated bandwidth for power saving; its preference on a maximum number of secondary component carriers for power saving; its preference on a maximum number of Multiple-Input-Multiple- Output (MIMO) layers for power saving; its preference on a minimum scheduling offset for cross-slot scheduling for power saving; its preference on a RRC state; configured grant assistance information for NR sidelink communication; and/or its preference in being provisioned with reference time information .

Using, for example, the SRS, CSI, or the already standardized UE Assistance Information within the RRC messaging, when establishing a new connection, the user terminal is able to report initial radio channel conditions, for example information regarding its position, expected mobility, expected radio quality conditions, the level of exposure to interference, throughput requirements, traffic profiles, etc.

In addition, the initial radio channel condition may indicate Radio Resource Management (RRM) cell measurements. The RRM cell measurements, like Reference Signal Received Power (RSRP), Reference Signal Strength Indicator (RSSI), Reference Signal Received Quality (RSRQ), SINR, and the like, may also be reported regularly to the radio network node. Thus, the initial radio channel condition may include RSRP, RSSI, RSRQ, SINR, and the like. Based on the aforementioned information, the radio network node can establish more robust links for user terminals that are more susceptible to interference and can set a more robust baseline for them. For instance, Figure 2 illustrates that as the user terminals are distributed at different locations in a factory shopfloor, some user terminals may be more prone to interference than others.

Based on the initial radio channel condition, the radio network node may set a BLER target as an initial BLER target, see step S302. The initial BLER target may be a BLER target range and may be coarsely set. For example, the initial BLER target is set to a coarse BLER target range.

As shown in empirical studies and baseband trace analysis, lower BLER targets may reduce the number of retransmissions and may clearly help in lowering communication latency. However, when selecting lower BLER targets, additional capacity (i.e., lower spectral efficiency) may be required as more physical resources are required per transmission. Thus, the initial BLER target may be assigned for a given user terminal according to, for example, the exposure level to potential interference at the user terminal, deployment position (for example, in a shopfloor), traffic QoS requirements, and the observed and predicted channel quality aspects in order to achieve reliable communication within the desirable latency bounds. As explained above as an example, UE1 in Figure 2 is deployed deep inside the factory shopfloor premises and its deployment is fixed/static, for instance, on a machine. UE1 has hence very good radio conditions and very low exposure to interference. This may be notified to the radio network node by means of the initial radio channel condition, like the SRS, CSI, and the UE Assistance Information as part of the RRC signalling. Since UE2 and UE3 are deployed at the edge locations of the factory shopfloor in Figure 2, their radio channel conditions are not as good as that of UE1, and are exposed to spectral interference from other networks, the initial BLER target may be lower for UE2 and UE3 compared to UE1. Moreover, for those mobile user terminals like UE4 and UE5, the exposure to interference may be very high if they need to move in and out of the factory shopfloor. With such information, the radio network node may set a lower BLER target for UE4 and UE5 compared to UE1, UE2, and UE3.

Thus, the radio network node is able to set or assign a specific BLER target as an initial BLER target for each user terminal, wherein the specific BLER targets for each user terminal depends on information reported by each user terminal. The initial BLER target may indicate a coarse BLER target range.

According to an embodiment, the initial BLER target may be set by using a table. The table may assign the initial radio channel condition to a specific BLER target. Figure 5 illustrates an exemplary table assigning BLER targets to different UE Assistance Values for a given user terminal. As shown in Figure 5, the BLER targets may be BLER target ranges, wherein the ranges of BLER targets may consist of nine different values as listed in the table of Figure 5. However, this is not limiting and the ranges of the BLER targets may consist of more or less values. Furthermore, the table is not limiting and any other mapping technique which assigns the initial radio channel condition to a specific BLER target can be used.

The radio network node may assign the BLER targets, here BLER target ranges, per user terminal according to a matrix that divides the user terminals based on, for example, their latency requirements, expected radio channel conditions, the level of exposure to interference, the traffic requirements, etc. For example, the first eight values in the table shown in Figure 5 may be assigned to user terminals with traffic having time-critical requirements where room for a retransmission is low, while the nineth value in the table may be assigned to user terminal with traffic having nontime-critical requirements. The minimum BLER target value within the assigned range should be the lowest possible BLER target value that sets the most robust transmission possible. The upper BLER target value within the assigned range, i.e. the upper bound of the BLER target range, should define the maximum value allowed for retransmission.

For instance, if the exposure of interference of a certain user terminal is low, a UE Assistance Information value of 0 may be indicated by the user terminal and a higher BLER target may be defined. For example, for the UE Assistance Information value of 0, the initial BLER target may be set to a BLER target range of 0.1% to 10%, see the table in Figure 5. Here, the BLER target range is quite wide and thus the initial BLER target is coarsely set.

According to another example, if the level of exposure to interference regarding the user terminal is high and, thus, the number of retransmissions should be limited, a more robust transmission may be selected from the beginning. Here, a UE Assistance Information value of 5 may be indicated by the user terminal and a lower upper bound BLER target value may be defined. For example, for the UE Assistance Information value of 5, the initial BLER target may be set to a BLER target range of 0.1% to 7%, see the table in Figure 5. Again, the BLER target range is quite wide and thus the initial BLER target is coarsely set.

Moreover, for user terminals without time-critical requirements and more capacity demanding, the minimum value of the BLER target range may be higher, i.e. increased, in order to allow more data to be transmitted even if this would mean that more retransmissions are required. In such a case, the UE Assistance Information may indicate a value of 8, wherein the radio network node may set a BLER target range of 5% to 10% as initial BLER target, see the table in Figure 5. Again, the BLER target range is quite wide and thus the initial BLER target is coarsely set.

Please note that the table in Figure 5 is just an example and each of the BLER target ranges and the UE Assistance Information values may be different.

Referring back to Figure 3, when the BLER target, for example a BLER target range, has been coarsely set based on initial radio channel conditions, the BLER target may be dynamically assigned, adapted, or updated according to a current radio channel condition as part of an outer loop link adaptation (OLLA) at a granular level, see step S303 in Figure 3. The granular level may be a per time interval level. Thus, the BLER target may be dynamically assigned, adapted, or updated according to a current radio channel condition as part of an OLLA at a per time interval level. Thus, the radio network node may dynamically or in real-time update the BLER target at finer granularity. The current radio channel condition may be determined based on SRS or CSI received from the user terminal after the initial radio channel condition has been reported. For example, SRS for uplink link adaptation or CSI for downlink link adaptation is used for reporting the current radio channel condition, wherein the SRS or CSI is transmitted from the user terminal to the network node. Thus, the BLER target adaptation may be done automatically on a level of fixed time intervals. Here the time interval length for which the BLER target is calculated remains the same throughout the OLLA. The time interval level may be a slot level, a level of multiple of slots, a CSI periodicity level, a level of multiple of the CSI periodicity, an SRS periodicity level or a level of multiple of the SRS periodicity .

For example, in order to ensure that the BLER target is adapted at a granular level, hence at a per time interval level, the BLER target may be adapted per (multiple of) TDD slot or per (multiple of) radio channel condition (s) granularity. The radio channel condition granularity may indicate the periodicity of reporting the radio channel condition, i.e. how often the radio channel condition is, for example, reported by the user terminal, i.e. is transmitted from the user terminal to the radio network node. In other words, the periodicity of reporting the radio channel condition could be the periodicity of the radio channel condition feedback. If, for example, CSI is used for indicating the radio channel condition, the BLER target may be adapted per CSI granularity. If, for example, SRS is used for indicating the radio channel condition, the BLER target may be adapted per SRS granularity.

The BLER target adaption or assignment for consecutive time intervals (slot - or multiple slots, radio channel feedback interval - or multiple radio channel feedback intervals) may be different and independent. In other words, different dOLLA instances of a link adaption algorithm can be running for each of the consecutive time intervals. The time period of each dOLLA instance, i.e. the time interval for the dOLLA and the BLER target per one instance is adapted or updated, may be defined in the following by the term "dOLLA period" (see in Figure 10). In the update of the dOLLA and the BLER target of one dOLLA instance for one of the consecutive time intervals happening after a time dOLLA time interval, the respective values of the dOLLA and the BLER target for the particular time interval of the consecutive time intervals from the previous time instance may be used. For example, if the time interval of a dOLLA (hence the dOLLA period) is defined to be 4 TDD slots and the number of dOLLA instances may equal to 5 (n=5), there may be in total 5 different consecutive dOLLA instances of 4 TDD slots for a TDD pattern duration of 20 TDD slots (as it can be observed in the example of Figure 9).

For example, the BLER target may be defined or adapted within a specific range based on information reported from the user terminal as part of the OLLA. The OLLA may be performed by an OLLA algorithm and is described in more detail below. The specific range may be defined by the initial BLER target. The information reported from the user terminal may be information on the current radio channel condition. The current radio channel condition may indicate a (current) position of the user terminal, expected mobility of the user terminal, expected radio quality conditions, a level of exposure to interference with respect to the user terminal, and/or traffic profiles. The traffic profiles may include requirements on throughput, latency, data traffic volume, priority class, etc. The current radio channel condition may indicate RRM cell measurements, like RSRP, RSSI, RSRQ, SINR, or the like.

Thus, a BLER target, for example a BLER target range, may be selected as the initial BLER target for an initial radio channel condition and the BLER target may be adapted over time at a granular level, i.e. at a per time interval level, with regard to current radio channel conditions received from the user terminal. For example, a wide initial BLER target range may be narrowed down over time by adapting the BLER target at a granular level by the OLLA algorithm. According to an embodiment, the BLER target may be adapted whenever the current radio channel condition is updated. In other words, the BLER target may be updated after every radio channel condition update.

As explained above, the UE Assistance Information, CSI, or SRS may indicate the initial radio channel condition. The initial radio channel condition, for example the UE Assistance Information, CSI, or SRS indicating the initial radio channel condition, may be used in a connection establishment between the radio network node and the user terminal. Thus, the initial radio channel condition may be received, by the radio network node, from the user terminal when establishing a connection between the radio network node and the user terminal.

Without limitations, the UE Assistance Information may not only be used in a connection establishment procedure but may also be used to send an update on the user terminal position, its vulnerability to interference exposure, etc. from time to time with the existing RRC signalling mechanism. If the UE Assistance Information is same from previous UE Assistance Information received, the BLER target may be adapted by the radio network node as herewith enclosed. However, if the radio network node receives another UE Assistance Information which is different from previously received UE Assistance Information, the other UE Assistance Information is treat as an initial BLER target, i.e. the UE Assistance Information is used for setting the initial BLER target. Thus, the reception of the other UE Assistance Information may be interpreted as if the user terminal has just established a new connection.

However, as the UE Assistance Information is not transmitted very frequently and the initial BLER target selected based on the initial radio channel condition, for example the UE Assistance Information, is often very coarse, the initial BLER target should not be used by the radio network node to determine modulation and coding schemes (MCS) and resource blocks (RBs). When the initial BLER target is used, the MCS and RBs may not adhere to channel conditions and/or interference patterns from a coexisting network based on the TDD frame structure. Thus, in order to obtain finer granular BLER targets for accurately determining MCS and RBs, it is advisable that the radio network node adapts the BLER target as part of the OLLA at a granular level as described herein.

As explained above, a dynamic BLER target adaption is proposed that optimizes the transmission in the presence of interference or due to changes on the radio channel conditions. The dynamic BLER target adaption may be a combination of setting an initial BLER target using, for example, the previously mentioned table or any other mapping technique and dynamically adapting or updating the BLER target by an OLLA algorithm at a granular level, i.e. at a per time interval level. The OLLA algorithm herewith enclosed comprises a step of dynamically adapting the BLER target at a granular level and will be called a dynamic OLLA (dOLLA) algorithm below to distinguish this algorithm from any other OLLA algorithm which does not dynamically update the BLER target. The dOLLA algorithm is described in more detail below.

Figure 6 illustrates an embodiment for dynamic BLER target assignment according to UE Assistance Information. In Figure 6, the information collected on the radio network node from the user terminal, i.e. the initial radio channel condition like the UE Assistance Information received by the radio network node from the user terminal, is used to set the initial BLER target. For instance, for time-critical applications, the initial BLER target may be set rather low in order to start transmitting very robustly, wherein the radio network node may adapt the BLER target to higher BLER target values over time if possible. Hence, if the initial BLER target is a BLER target range as exemplary indicated in the table of Figure 5, the initial BLER target being set according to, for example, a table assigning UE Assistance Information values to specific BLER targets, the lowest value within the BLER target range may be selected as the initial BLER target. The initial BLER target may be used as input in a first step of the dOLLA algorithm. According to an embodiment, on every radio channel condition update, i.e. a radio channel feedback, the dOLLA algorithm may fine-tune an estimated SINR and the BLER target according to the estimated SINR as explained below. Thus, the radio network node is able to dynamically adapt the BLER target and to accurately determine MCS and RBs using the dOLLA algorithm.

Figure 7 illustrates a diagram of a link adaptation algorithm for dynamic BLER target assignment. The dynamic adaptation of the BLER target at a granular level by the radio network node may be performed within the dOLLA.

In Figure 7, the dashed line outlines the processes which are performed within the radio network node. The processes may be performed by the radio network node to accurately determine MCS and/or RBs for a user terminal.

As illustrated in Figure 7, the radio network node may perform a dOLLA algorithm 730 and an Inner Loop Link Adaptation (ILLA) algorithm 710. The ILLA algorithm 710 and the dOLLA algorithm 730 may comprise different feedback loops which constitute a link adaptation mechanism. For the link adaptation mechanism, information about the channel quality of the user terminals using information on the radio channel condition, like CSI, is received from the user terminal in order to generate, by the radio network node, an MCS and RBs. The generated or determined MCS and RBs may be transmitted to the user terminal to be used in a next transmission in order to keep the BLER below a target.

Thus, information on the radio channel conditions, i.e. radio channel feedback, works as an input to the link adaptation algorithm including dOLLA and ILLA. This information may be received at every radio channel condition, for example CSI or SRS, update period, i.e. time period between every radio channel condition message, CSI message, or SRS message per user terminal. In particular, the radio channel condition, like the CSI or SRS, may be used to estimate the SINR for the ILLA. The radio channel condition, like CSI or SRS, may be transmitted within Physical Uplink Shared Channels (PUSCHs) or in Synchronization Signal/PBCH Blocks (SSBs) depending on, for example, a CSI/SRS Report configuration as specified in 3GPP technical specifications (see, for example TS 38.331 V17.0.0 (2022-03)). A CSI report granularity or SRS report granularity may be configured flexibly. The dOLLA algorithm allows updating the CSI or SRS report according to the status reported itself and dynamically adapting the BLER target at a granular level, for example, per TDD slot or per radio channel condition granularity.

For instance, for those non-variant scenarios where SINR is stable, the CSI or SRS granularity may be increased. When variations occur, the CSI or SRS granularity may be reduced in order to optimize data transmissions and update resource assignment more frequently. In other words, lowering the CSI or SRS report granularity, i.e. the periodicity for transmitting CSI or SRS reports, and using the dOLLA algorithm described herein may help the LA algorithm to select appropriate MCS and RBs, because the radio channel conditions can be frequently updated and the BLER target can be accurately determined.

According to an embodiment, the user terminal may report radio channel condition to the radio network node. For example, the user terminal reports CSI including at least one CSI parameter, such as a Channel Quality Indicator (CQI), to the radio network node. This reported CQI may be associated with a particular estimated instantaneous SINR. Thus, the radio network node may be able to determine an estimated instantaneous SINR based on the reported CQI, see also box 720 in Figure 7. For determining the estimated instantaneous SINR, the radio network node may use fixed look-up tables. However, any other mapping technique than look-up tables may be used to determine the estimated instantaneous SINR.

According to another example, the user terminal may report SRS or Demodulation Reference Signals (DRS) instead of CSI to the radio network node. Based on the reported SRS or DRS, the radio network node may be able to determine an estimated instantaneous SINR, see again box 720 in Figure 7.

However, mapping the reported and received radio channel condition to the estimated instantaneous SINR is often not a good practice due to transmission delays and link conditions that are inherently variant. Therefore, OLLA is used in the prior art to cope with time-varying link conditions and transmission delays. By using OLLA, the estimated instantaneous SINR determined from the radio channel condition can be adjusted. In particular, an offset is calculated with the OLLA using Hybrid Automatic Repeat Request (HARQ) Acknowledgment (ACK) and HARQ NonAcknowledgment (NACK) for downlink link adaptation or using ACK and NACK using uplink link adaptation, wherein the offset may then be added to or subtracted from the estimated instantaneous SINR. The offset may be updated continuously based on the acknowledgment feedback. In other words, OLLA algorithms may modify the estimated instantaneous SINR by an offset, wherein the offset is continuously updated based on the reliability of received data blocks. However, in known OLLA algorithms, the BLER target is not dynamically and automatically updated at a granular level, i.e. at a per time interval level.

Thus, Figure 7 illustrates an embodiment of an OLLA algorithm which comprises dynamic BLER target adaptation at a granular level. The OLLA algorithm may be one of multiple dOLLA algorithms running for one TDD pattern.

As shown in Figure 7, according to an embodiment, the radio network node may receive (HARQ) ACK and/or (HARQ) NACK from a user terminal. The radio network node may then calculate an offset ^ ^0LLA using the dOLLA algorithm 730, wherein parameter n denotes the instance number of dOLLA n and parameter k denotes the time interval (dOLLA time interval, see Figure 6) of each dOLLA instance and its value is defined by the maximum number of dOLLA instances (n) and the dOLLA period. The inputs to the dOLLA algorithm 730 may be the received (HARQ) ACK/NACK, a previous offset, and a BLER target. The previous offset may be an offset determined at time interval k — 1 and instance n. The BLER target may be an initial BLER target obtained as explained above or a BLER target BLER^ which has been determined by the radio network node at time interval k and instance n. The radio network node may adapt the BLER target at time interval k and instance n as explained above in order to determine BLER .

The radio network node may calculate, using the dOLLA algorithm 730, a corrected SINR value based on the offset and an estimated SINR value. The estimated SINR value may be obtained from box 720 which maps the radio channel condition to an estimated instantaneous SINR. Thus, the estimated SINR value may be obtained from current radio channel conditions received from the user terminal. The corrected SINR value may be calculated by adding/subtracting the offset to/from the estimated SINR value.

The corrected SINR value may be input to an ILLA algorithm 710, wherein the ILLA algorithm 710 may determine an MCS and/or RBs based on the corrected SINR value. The MCS and/or RBs may be output to the user terminal for future transmission . The offset may be a function of a previous offset at time interval k — 1 and instance n, the (HARQ) ACK/NACK received from the user terminal, and the BLER target. The previous offset may be a predefined initial offset or an offset previously calculated at time interval k — 1 and instance n. The offset may be indicated with the following equation: is an offset at time interval k and instance n, an offset at previous time interval k — 1 and instance n, Δ ^up a predefined fixed up step, and Δ ^down a predefined fixed down step. e _k is determined based on the received (HARQ) ACK/NACK. For (HARQ) ACK, e _k = 0. For (HARQ) NACK, e _k = 1. Thus, the equation for offset may be written as follows:

Offset may then be fed back to dOLLA algorithm 730 to calculate offset at time interval k + 1.

As mentioned above, Δ ^up and Δ ^down may be predefined fixed up and fixed down steps which may be defined based on the BLER target to fulfil the following equation:

Thus, the offset is further a function of the BLER target at time interval k.

However, when an inaccurate BLER target with regard to current radio channel conditions or a coarse initial BLER target is used for calculating the offset the corrected SINR value may be inaccurate leading to incorrect MCS and RBs determination. Thus, the dOLLA algorithm is performed such that the radio network node dynamically adapts the BLER target at a granular level, i.e. at a per time interval level, as explained above. As mentioned above, the BLER target adaptation may be done automatically for time intervals which may be reoccur periodically (dOLLA interval), and the interval length may be the same fixed length throughout the dOLLA algorithm. The adaption may be performed with the rate of the dOLLA time interval. In other words, each time when the dOLLA algorithm runs and outputs an offset a is calculated which is used in the dOLLA algorithm for offset . The value of can remain the same in an update, since is possible, see equation below.

According to an embodiment, adapting the BLER target may comprise increasing the BLER target by a step-up value or decreasing the BLER target by a step-down value The BLER target at time interval k may be dynamically adapted as follows: wherein is the BLER target at time interval k — 1. Thus, the BLER target may be either increased by the step-up value or decreased by the step-down value When the BLER target is not adapted, i.e. updated, B . This may be the case when the current BLER target already satisfies the requirements and an update is currently not needed .

When the BLER target is adapted for the first time, BLER target may be equal to the initial BLER target. The initial BLER target may be determined as explained above, for example based on the initial radio channel condition received from a user terminal.

The step-up value and step-down value may each be predefined or configured using a utility function. For example, the step-up value and the step-down value may each be based on an appropriate user-defined or auto-configured utility function. For instance, the step-up value may be lower in order to slowly increase the BLER target, wherein an increased BLER target may mean more retransmissions, while the step-down value may be higher in order to quickly reduce the BLER target and do more robust transmissions quickly when interference is detected.

Various techniques may be applied to determine whether the BLER target is increased or decreased or whether no adaption, i.e. no update, is necessary. According to an embodiment, the SINR value estimated or derived in box 720 from the current radio channel condition may be used for this determination. For example, a SINR threshold may be defined, wherein the BLER target may be increased by the step-up value if the SINR value is higher than the defined SINR threshold and wherein the BLER target may be decreased by the step-down value if the SINR value is lower than the defined SINR threshold. No adaption of the BLER target may be necessary when the SINR value is equal to the SINR threshold. By using a SINR threshold, the procedure is robust to outliers. As already mentioned above, the SINR value may be estimated from the current radio channel condition, i.e. from information on the current radio channel condition, like CSI or SRS, wherein the current radio channel condition is associated with a particular SINR value or SINR value range. In Box 720, the SINR value may be determined using the CQI.

For example, a difference diff _SINR n between a current SINR value at time interval k and a previous SINR value at time interval k — 1 is calculated, wherein the current SINR value at time interval k is estimated from the current radio channel condition received at time interval k and the previous SINR value is estimated from a previous radio channel condition received at time interval k — 1. The current SINR value may be determined or derived from CSI or SRS obtained at time interval k. The previous SINR value may be determined or derived from CSI or SRS obtained at time interval k— 1.

The SINR threshold may then be defined according to the calculated difference. For example, the SINR threshold is defined flexibly either pre-configured or adapted on-the-fly e.g., based on the dynamism/fluctuation in the radio conditions, empirical basis or analytical model. For example, the SINR threshold is set to 3dB.

The difference diff _SINR n may be calculated by subtracting the previous SINR value from the current SINR value

The BLER target may be increased by the step-up value if the calculated difference diff _SINR n is positive and the absolute value of the calculated difference diff _SINR n is higher than the defined SINR threshold, i.e. if diff _SINR n> 0 and \diff _SINR n|> SINR _threshold , wherein SINR _threshold indicates the SINR threshold.

The BLER target may be decreased by the step-down value if the calculated difference diff _SINR n is negative and the absolute value of the calculated difference diff _SINR n is higher than the defined SINR threshold, i.e. if diff _SINR n< 0 and |diffsiNR ⁿ |> SINRthreshold, wherein SINR _threshold indicates the SINR threshold.

The BLER target may not be adapted or updated if the absolute value of the calculated difference diff _SINR n is lower than the defined SINR threshold, i.e. if |diff _SINR n|< SINR _threshold , wherein SINR _threshold indicates the SINR threshold.

According to another embodiment, a time difference equation may be used for the SINR that estimates SINR behaviour. With the time difference equation, it is possible to determine whether the BLER target should be increased or decreased or whether no BLER target adaption, i.e. update, is necessary. Here, estimated SINR in link adaptation may be used. The estimated SINR may be acquired from CSI for downlink link adaptation and from SRS for uplink link adaptation. The estimated SINR may also be acquired at the radio network node from other sources like some dedicated spectrum sensors, radio environmental maps, SINR heatmap, etc.

According to another embodiment, machine learning algorithms may be used to estimate the SINR over time and decide whether the BLER target should be increased or decreased or whether no BLER target adaption, i.e. update, is necessary.

By providing a dOLLA algorithm as described above, the BLER target may be dynamically adapted at a granular level, i.e. at a per time interval level. The minimum granular level may be a slot duration. For example, the BLER target is dynamically adapted per TDD slot or per radio channel condition granularity. The radio channel condition granularity may indicate the radio channel condition periodicity, i.e. how often information on the radio channel condition is reported or transmitted from, for example, the user terminal to the radio network node. In order to report the radio channel condition, CSI or SRS may be used. In such a case, the BLER target may be dynamically adapted per CSI or SRS granularity indicating the CSI or SRS periodicity, i.e. how often CSI or SRS is, for example, reported or transmitted from the user terminal to the radio network node. Figure 8 illustrates examples for performing the dOLLA algorithm at various granular levels. In Figure 8, the TDD pattern for an NPN and a PN is shown, wherein D refers to a DL slot, U refers to a UL slot, and S refers to a special slot. The slots marked with horizontal lines may exhibit more interference than the slots marked with dashed outlines.

By performing the dOLLA algorithm per TDD slot, as shown in Figure 8a), all types of interferences can be independently addressed and the BLER target can be dynamically adapted per TDD slot, resulting in a more accurate offset calculation and more accurate MCS and RBs determination. As further shown in Figure 8b), the dOLLA algorithm may be performed per radio channel condition granularity, for example CSI or SRS granularity. For example, if the CSI or SRS granularity is 4, the dOLLA algorithm is performed per four slots. Thus, the BLER target can be adapted per CSI or SRS granularity, for example per four slots. This means that the offset can still be calculated accurately while reducing the load for performing the dOLLA algorithm.

Furthermore, by dynamically adapting the BLER target per slot or per radio channel condition granularity, for example CSI or SRS granularity, it is possible exploiting the cross- correlation between unsynchronized TDD patterns in order to identify which slot constellations within every radio channel condition update, for example CSI or SRS update, are subject to interference. Thus, the optimal BLER target can be assigned for each slot or group of slots.

This is further shown in Figure 9 which illustrates an example of the functionality of dynamic BLER target assignment per four TDD slots. In total five dOLLA instances are shown for a duration of 20 TDD slots. Thus, the dOLLA period in which the dOLLA and the BLER target are fixed is four slots in Figure 9. The update happens at the time instances t, t+1, t+2, ... t+N, i.e., every dOLLA time interval of 20 slots. These time instances are separated by the dOLLA interval (see Figure 6). Again, as in Figure 8, the TDD pattern of NPN and PN are shown over time T, wherein D refers to a DL slot, U refers to a UL slot, and S refers to a special slot. Here, the special slots are mainly composed by DL symbols, hence mainly creating DL interference. Near-far interference is illustrated with solid arrows and cross-link interference is illustrated with dashed arrows. The slots marked with horizontal lines may exhibit more interference than the slots marked with dashed outlines.

Figure 9 shows an example where the NPN and PN TDD patterns are DDSU and DDDSU respectively. One can observe that the DL slots of the NPN are affected by both near-far and cross-link interference, wherein the cross-link interference is higher than the near-far interference. This means that the slots exhibiting cross-link interference, i.e. some of the DL and special slots of the NPN, may have more interference than the slots exhibiting near-far interference, see the slots marked with horizontal lines and the slots marked with dashed outlines.

In Figure 9, the dOLLA period is set to 4 slots, which means that the radio network node is capable of receiving radio channel feedback from the user terminal every 4 slots. The dOLLA period is not limited to this value and the dOLLA period can be set to any other value.

Since the dOLLA period is different to the combination of TDD pattern lengths of the NPN, i.e. the indoor network, and the PN, i.e. the outdoor network, the dOLLA algorithm allows identifying those TDD slots that suffer from more interference than the other TDD slots. Such behaviour of identifying the TDD slots with more interference can be seen by the SINR values reported every 4 slots. Assuming that the worst case of interference is, for example, where an UL slot of the outdoor network collides with a DL slot of the indoor network, the worst SINR values may eventually appear on those periods where such interference occurs. Here, one period comprises 4 slots.

In the example illustrated in Figure 9, the SINR value of the first period is 15dB, because interference only occurs from the DL slots of the PN. On the second and third periods, the SINR values is 5dB and 7dB, because the interference comes from both UL and DL PN transmissions. On the fourth period, the SINR value is 8dB, because the impact from UL PN transmission on the special slots is lower compared to the DL.

By performing the dOLLA algorithm as described above, different BLER targets may be assigned in order to get a reliable and low bounded latency per every TDD slot. The dOLLA algorithm may initially set a BLER target as an initial BLER target within a range according to an initial radio channel condition, for example according to reported CSI, SRS, or UE Assistance Information, in order to get more robust transmissions. Then, after receiving the current radio channel condition, the dOLLA algorithm may dynamically adapt the BLER target at a granular level, i.e. at a per time interval level, by, for example, increasing or decreasing the BLER target using step-up and step-down values. After some iterations, thanks to the radio channel condition granularity, for example the CSI or SRS report granularity, it is possible to identify which slots suffer more from interference and hence the BLER target can be assigned accordingly to maximize the physical resource allocation for a reliable and lower bounded latency transmission. This is shown in Figure 9 where BLER targets are assigned to every period in every iteration T=t, T=t+1, T=t+2, ... T=t+N. Over time, the BLER target for the first period converges to 10%, the BLER target for the second period converges to 2%, the BLER target for the third and fourth periods converges to 3%, and the BLER target for the fifth period converges to 10%. Figure 10 illustrates example candidates on dOLLA periods measured in number of TDD slots for three different TDD patterns. In the shown examples, dOLLA vary between 2 slots and 9 slots. The three different TDD patterns are DDSU, DDDSU, and DDDSUDDSUU. However, these TDD pattens are just examples and any other TDD pattern may be used. The dOLLA algorithm as explained above substantially improves the resource assignment for every transmission. The dOLLA period may be defined as a duration of dOLLA instances in TDD slots. The minimum dOLLA period may be a single slot duration.

The dOLLA period may correspond to a CSI periodicity or SRS periodicity, wherein CSI and SRS feedback may be independent and different. For example, for lower CSI or SRS periodicities between 2 and 9, see Figure 10, the CSI or SRS granularity helps identifying more specifically the SINR of every TDD slot. As described above, due to interference, every TDD slot may have very different SINR depending on the user terminal location, user terminal exposure to interference, and/or TDD pattern on the indoor and outdoor networks. Therefore, getting a CSI and/or SRS report more frequently may help identifying the TDD slots which suffer from more interference and mitigating the impact of interference or variant radio channel conditions.

However, there is a trade-off between reducing the CSI and SRS periodicity, as the total available throughput may be affected and reduced, because physical resources are used for signalling instead of data transmission creating overheads. Hence, a method for dynamic BLER target adaption which can be performed per TDD slot or per radio channel condition granularity has been proposed above which may assign different resources according to every TDD slot or according to radio channel condition granularity, for example CSI or SRS granularity. The BLER target may be dynamically adapted at a granular level with regard to an initial BLER target, for example within BLER target ranges which may be obtained based on UE Assistance Information and a table as exemplary shown in Figure 5. For every TDD slot or CSI/SRS granularity, an offset may be calculated using the dOLLA algorithm and a specific BLER target, wherein the BLER target may be fine- tuned by the dOLLA algorithm as described above to obtain a BLER target with finer granularity compared to a coarse initial BLER target. Every assignment of physical resources made by the radio network node may comprise information on the MCS and RBs allocation of every TDD slot within a CSI or SRS update period.

Figure 11 illustrates an exemplary radio network node. As shown in Figure 11, the radio network node 1100 may comprise a processor 1110 and a memory 1120. The radio network node 1100 may be any radio network node described above. The memory 1120 may store instructions which may be executed by the processor 1110. The instructions may cause the processor 1110 to perform the method described above. For example, the instructions cause the processor 1110 to receive an initial radio channel condition from a user terminal. The initial radio channel condition may be received from a receiving unit (not shown) of the radio network node 1100, wherein the receiving unit transmits the initial radio channel condition to the processor 1110 so that the processor 1110 is able to receive the initial radio channel condition from the user terminal. The instructions may further cause the processor 1110 to set a BLER target based on the initial radio channel condition as an initial BLER target, and adapt the BLER target according to a current radio channel condition as part of an outer loop link adaptation at a granular level, i.e. at a per time interval level.

Figure 12 illustrates an exemplary user terminal. As shown in Figure 11, the user terminal 1200 may comprise a processor 1210 and a memory 1220. The user terminal 1200 may be any user terminal, user equipment, or terminal device as described above. For example, the user terminal 1200 is equal to the user equipment UE1, UE2, UE3, UE4, and UE5 described with regard to Figure 2. The instructions may cause the processor 1210 to perform any steps described above. For example, the instructions may cause the processor 1210 to instruct a transmitting unit (not shown) to transmit an initial radio channel condition and a current radio channel condition to the radio network node 1100.

Figure 13 illustrates an embodiment of a method performed by a communication system comprising a radio network node and at least one user terminal. The radio network node may be the radio network node 1100 illustrated in Figure 11 or any other radio network node described above. The user terminal may be the user terminal 1200 illustrated in Figure 12 or any other user terminal, user equipment, or terminal device as described above.

As shown in Figure 13, the method may comprise transmitting, by the user terminal 1200, an initial radio channel condition to the radio network node 1100 (see S1301), and receiving, by the radio network node 1100, the initial radio channel condition from the user terminal 1200 (see S1302). The method may further comprise setting, by the radio network node 1100, a BLER target based on the initial radio channel condition as an initial BLER target (see S1303). The user terminal 1200 may transmit a current radio channel condition to the radio network node 1100 (see S1304) and the radio network node 1100 may adapt the BLER target according to the current radio channel condition as part of an outer loop link adaptation at a granular level, i.e. at a per time interval level (see S1305).

Above, a radio network node and a method performed by the radio network node have been described for dynamically adapting BLER targets at a finer granularity to satisfy the application QoS targets even in the presence of interference from coexisting networks. By dynamically adapting BLER targets, efficient Physical Resource Block (PRB) allocation is enabled, wherein cell-edge user terminals can be specifically protected. This allows meeting the QoS targets of mission critical traffic (requiring low latency and high reliability), which otherwise suffer from interference issues. Furthermore, the herewith disclosed method leads to highly efficient use of radio resources to satisfy the application QoS targets. The method can flexibly target user terminal groups and traffic types for granular and adaptive BLER target selection leading to efficient resource utilization, and can be easily implemented.

It will be apparent to those skilled in the art that various modifications and variations can be made in the entities and methods of this invention as well as in the construction of this invention without departing from the scope or spirit of the invention.

The invention has been described in relation to particular embodiments and examples which are intended in all aspects to be illustrative rather than restrictive. Those skilled in the art will appreciate that many different combinations of hardware, software and/or firmware will be suitable for practicing the present invention.

Moreover, other implementations of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. It is intended that the specification and the examples be considered as exemplary only. To this end, it is to be understood that inventive aspects lie in less than all features of a single foregoing disclosed implementation or configuration. Thus, the true scope and spirit of the invention is indicated by the following claims.