BACKGROUND:

Field:

[0001] Embodiments of the invention generally relate to wireless or cellular communications networks, such as, but not limited to, the Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access Network (UTRAN), Long Term Evolution (LTE) Evolved UTRAN (E-UTRAN), LTE-Advanced (LTE-A), LTE-A Pro, and/or 5G radio access technology or new radio (NR) access technology. Some embodiments may generally relate, for example, to quantization codebook(s) for channel state information (CSI) feedback in such networks.

Description of the Related Art:

[0002] Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access Network (UTRAN) refers to a communications network including base stations, or Node Bs, and for example radio network controllers (RNC). UTRAN allows for connectivity between the user equipment (UE) and the core network. The RNC provides control functionalities for one or more Node Bs. The RNC and its corresponding Node Bs are called the Radio Network Subsystem (RNS). In case of E- UTRAN (Evolved-UTRAN), the air interface design, protocol architecture and multiple-access principles are new compared to that of UTRAN, and no RNC exists and radio access functionality is provided by an evolved Node B (eNodeB or eNB) or many eNBs. Multiple eNBs are involved for a single UE connection, for example, in case of Coordinated Multipoint Transmission (CoMP) and in dual connectivity (DC). [0003] Long Term Evolution (LTE) or E-UTRAN improved efficiency and services, offers lower costs, and provides new spectrum opportunities, compared to the earlier generations. In particular, LTE is a 3 GPP standard that provides for uplink peak rates of at least, for example, 75 megabits per second (Mbps) per carrier and downlink peak rates of at least, for example, 300 Mbps per carrier. LTE supports scalable carrier bandwidths from 20 MHz down to 1.4 MHz and supports both Frequency Division Duplexing (FDD) and Time Division Duplexing (TDD). Carrier aggregation or said dual connectivity further allows operating on multiple component carriers at the same time hence multiplying the performance such as data rates per user.

[0004] As mentioned above, LTE may also improve spectral efficiency in networks, allowing carriers to provide more data and voice services over a given bandwidth. Therefore, LTE is designed to fulfill the needs for high speed data and media transport in addition to high capacity voice support. Advantages of LTE include, for example, high throughput, low latency, FDD and TDD support in the same platform, an improved end-user experience, and a simple architecture resulting in low operating costs.

[0005] Certain further releases of 3 GPP LTE (e.g., LTE Rel-lO, LTE Rel-l 1) are targeted towards international mobile telecommunications advanced (IMT-A) systems, referred to herein for convenience simply as LTE- Advanced (LTE- A).

[0006] LTE-A is directed toward extending and optimizing the 3GPP LTE radio access technologies. A goal of LTE-A is to provide significantly enhanced services by means of higher data rates and lower latency with reduced cost. LTE-A is a more optimized radio system fulfilling the international telecommunication union-radio (ITU-R) requirements for IMT- Advanced while maintaining backward compatibility. One of the key features of LTE-A, introduced in LTE Rel-lO, is carrier aggregation, which allows for increasing the data rates through aggregation of two or more LTE carriers. The next releases of 3GPP LTE (e.g. LTE Rel-l2, LTE Rel-l3, LTE Rel-l4, LTE Rel-l5) are targeted for further improvements of specialized services, shorter latency and meeting requirements approaching the 5G.

[0007] 5 ^th generation (5G) or new radio (NR) wireless systems refer to the next generation (NG) of radio systems and network architecture. 5G is also known to appear as the IMT-2020 system. It is estimated that 5G will provide bitrates on the order of 10-20 Gbit/s or higher. 5G will support at least enhanced mobile broadband (eMBB) and ultra-reliable low-latency- communication (URLLC). 5G is also expected to increase network expandability up to hundreds of thousands of connections. The signal technology of 5 G is anticipated for greater coverage as well as spectral and signaling efficiency. 5G is expected to deliver extreme broadband and ultra- robust, low latency connectivity and massive networking to support the Internet of Things (IoT). With IoT and machine-to-machine (M2M) communication becoming more widespread, there will be a growing need for networks that meet the needs of lower power, low data rate, and long battery life. In 5G or NR, the Node B or eNB may be referred to as a next generation or 5G Node B (gNB).

SUMMARY:

[0008] One embodiment is directed to a method, which may include computing, by a user equipment, one or more quantized codebooks. The method may also include selecting a quantized codebook, from the one or more computed quantized codebooks, that has at least one of an optimum number of feedback coefficients or optimum coefficient resolution for the user equipment, and sending an index of the selected quantized codebook to a network node.

[0009] Another embodiment is directed to an apparatus, which may include computing means for computing one or more quantized codebooks. The apparatus may also include selecting means for selecting a quantized codebook, from the one or more computed quantized codebooks, that has at least one of an optimum number of feedback coefficients or an optimum coefficient resolution for the apparatus, and transmitting means for sending an index of the selected quantized codebook to a network node.

[0010] Another embodiment is directed to an apparatus including at least one processor and at least one memory comprising computer program code. The at least one memory and computer program code are configured, with the at least one processor, to cause the apparatus at least to compute one or more quantized codebooks, select a quantized codebook, from said one or more computed quantized codebooks, that has at least one of an optimum number of feedback coefficients or an optimum coefficient resolution for the apparatus, and transmit an index of the selected quantized codebook to a network node.

[0011] Another embodiment is directed to a method, which may include receiving, by a network node, an index of a selected quantized codebook. The method may also include receiving a calculated mean square error of channel compression for the quantized codebook, and, based on at least one of the received index or the calculated mean square error, determining whether to allocate a higher or lower feedback overhead budget to a user equipment.

[0012] Another embodiment is directed to an apparatus, which may include receiving means for receiving an index of a selected quantized codebook, receiving means for receiving a calculated mean square error of channel compression for the quantized codebook, and determining means for determining, based on at least one of the received index or the calculated mean square error, whether to allocate a higher or lower feedback overhead budget to a user equipment.

[0013] Another embodiment is directed to an apparatus including at least one processor and at least one memory comprising computer program code. The at least one memory and computer program code are configured, with the at least one processor, to cause the apparatus at least to receive an index of a selected quantized codebook, receive a calculated mean square error of channel compression for the quantized codebook, and determine, based on at least one of the received index or the calculated mean square error, whether to allocate a higher or lower feedback overhead budget to a user equipment.

BRIEF DESCRIPTION OF THE DRAWINGS:

[0014] For proper understanding of the invention, reference should be made to the accompanying drawings, wherein:

[0015] Fig. 1 illustrates a block diagram of a system depicting explicit CSI feedback in FDD;

[0016] Fig. 2 illustrates an example signal flow chart for fixed quantization and tap selection, according to an embodiment;

[0017] Fig. 3 illustrates an example flow chart for multi-quantization codebook and tap selection, according to one embodiment;

[0018] Fig. 4 illustrates an example flow chart for multi-quantization codebook and tap selection, according to another embodiment; and

[0019] Fig. 5a illustrates a block diagram of an apparatus, according to one embodiment; and

[0020] Fig. 5b illustrates a block diagram of an apparatus, according to another embodiment.

DETAILED DESCRIPTION:

[0021] It will be readily understood that the components of the invention, as generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of systems, methods, apparatuses, and computer program products relating to multi quantization codebook(s) for explicit channel state information (CSI) feedback in new radio (NR), as represented in the attached figures and described below, is not intended to limit the scope of the invention but is representative of selected embodiments of the invention. [0022] The features, structures, or characteristics of the invention described throughout this specification may be combined in any suitable manner in one or more embodiments. For example, the usage of the phrases “certain embodiments,”“some embodiments,” or other similar language, throughout this specification refers to the fact that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present invention. Thus, appearances of the phrases “in certain embodiments,” “in some embodiments,” “in other embodiments,” or other similar language, throughout this specification do not necessarily all refer to the same group of embodiments, and the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0023] Additionally, if desired, the different functions or steps discussed below may be performed in a different order and/or concurrently with each other. Furthermore, if desired, one or more of the described functions or steps may be optional or may be combined. As such, the following description should be considered as merely illustrative of the principles, teachings and embodiments of this invention, and not in limitation thereof.

[0024] Fig. 1 illustrates a block diagram of a system 100 depicting explicit CSI feedback in FDD. In FDD (or some TDD systems, e.g., without proper calibration), the UE 101 has to send back the downlink (DL) channel information to the gNB 102 due to the absence of channel reciprocity. The gNB 102 uses this information to build the DL precoding matrices. In LTE and NR phase I, the UE 101 sends back one or more indices called Precoding Matrix Indicators (PMIs), which point to one or more codeword(s) in a predetermined codebook known at the UE 101 and gNB 102 sides. The codebook may be based on discrete fourier transform (DFT) precoding. For NR phase II, in order to obtain a more accurate description of the channel at the gNB 102, which is needed for improved multi-user multiple input multiple output (MU-MIMO) performance and more advanced schemes such as non-linear precoding, COMP or Interference Alignment (IF A), one proposal is for the UE 101 to send back the channel impulse response (CIR) 105 in the time domain. Because of the sparsity of the communication signal, many taps do not have to be reported which eventually reduces the feedback overhead. It is noted that, in some embodiments described herein, the terms“tap” and“coefficient” may be used interchangeably, as coefficients are channel taps.

[0025] The explicit feedback of the CIR 105 can also be reported for an effective beamformed channel. By, for example, employing a grid-of-beams (GoB) f _j precoder 107, the dimensions of the channel are reduced from

M A ⁷ , where M is the number of transmit antennas and N is the number of receive antennas, to B X N, where B is the number of beams employed. A natural consequence from that is having narrower beams with higher gains (compared to single element patterns), and a sparser CIR 105 in the time domain, due to channel hardening. In addition, the number of reference signals needed to train the whole system is reduced accordingly. The CIR 105 that is sent back is then of dimension , where K _T is the

whole time delay range of the CIR 105 (sampled in taps). It is noted that the sparsity of the time domain signal means that N _T is much higher than the actual number of significant channel taps, which is denoted here

[0026] Fig. 2 illustrates an example signal flow chart for fixed quantization and tap selection, according to an embodiment. In the example of Fig. 2, the signal flow chart of the preprocessing done on is shown before being fed back to the gNB. Assuming a fixed quantization codebook, which dictates using a fixed number of coefficients or taps (A' _{a j s} out of N _T taps) and quantization levels for amplitude 2 ^¾¾ and phase ^. Alternatively, quantization may be possible by quantizing in- phase (I) and quadrature (Q) component separately, instead of amplitude and phase.

[0027] For example, as illustrated in Fig. 2, quantization is performed at 205, coefficient or tap selection is performed at 210, mean square error (MSE) may be computed at 215, and the codebook feedback to the gNB at 220. After a first step of quantization at 205, for some UEs the channel may be very sparse and, therefore, if the resolution is not high enough, many coefficients or taps will be approximated to 0. Hence, starting from the true (but unknown) sparsity order of the propagation channel , we denote the number of non-zero amplitude taps after the first step of quantization as the number of active coefficients or taps k _l ^a _aps . The number of active coefficients or taps, which are eventually transmitted, may then be less than N _tav - and zeros are transmitted to fit the overhead budget. For other UEs, the fixed number may be too low, and for those UEs, increasing N _{ta s} and using a lower resolution quantization per complex tap coefficient provides a better result.

[0028] One problem that arises is that the optimum quantizer which matches the feedback overhead budget is different from one UE to another. Whereas some UEs may prefer to reduce the number of feedback coefficients or taps N _tap3 and use a higher resolution N _a N _p , other UEs may prefer to use a higher number of feedback coefficients or taps and reduce the resolution. (This may e.g. also depend on the scattering propagation environment in which the UEs are in.)

[0029] Therefore, for a certain given total number of feedback bits, one embodiment is directed to standardizing several or multiple quantization codebooks, for example where the codebooks may have a predetermined set of overhead budgets or may all have the same overhead budget: Ni _{aps X} + N^). In an embodiment, a UE may select the best or preferred quantization codebook (from the several quantization codebooks) and may send back an index of the selected quantization codebook i. In other words, the UE is quantizing the quantization codebook for selecting the best trade-off in terms of number of reported dominant coefficients or taps and respective coefficient or tap resolution. To send back the index of the quantization codebook, only a few bits are needed (e.g., 2 bits for 3 or 4 quantization codebooks). Therefore, this information can be sent with every short-term feedback (in the order of lOms). According to an embodiment, the UE may feedback the MSE of channel compression which can be easily computed at the UE side. It is noted that, according to certain embodiments described herein, the feedback can be carried out efficiently in a self- contained way, with a UE reporting both codebook index followed by the associated quantized feedback.

[0030] Fig. 3 illustrates an example flow chart for multi-quantization codebook and tap selection, according to one embodiment. More specifically, Fig. 3 illustrates an example of an embodiment where the UE computes all and selects the one which gives the minimum

value of mean square error MSE,. As illustrated in the example of Fig. 3, three quantization codebooks may be calculated, as shown at blocks 301, 302, 303. Tap or coefficient selection may then be performed, as shown at blocks 311, 312, 313, for each of the calculated quantization codebooks. Respective MSEs may also be computed, as shown at blocks 321, 322, 333, for each of the calculated quantization codebooks. Then, as shown at block 340, the quantization codebook that provides the minimum value of mean square error MSE _t may be selected. In addition, the UE may, as shown at block 350, feed back to the gNB the index of the selected quantization codebook i.

[0031] Fig. 4 illustrates another example of a flow chart for multi quantization codebook and tap selection, according to another embodiment. In the example of Fig. 4, the quantizers may be ordered according to the number of coefficients or taps N~ _si-is, This embodiment starts with the middle quantization codebook, i.e., where the number of coefficients or taps is in the middle of the range of all y], and records the number of active (significant) non-zero coefficients or taps after the first step of quantization and before tap selection.

[0032] On one hand, if the number of active (significant) coefficients or taps iiT _jjjy of the radio channel is too low with respect to the taps considered in the respective quantization codebook Nl _a , then this embodiment is configured to switch to a quantizer which assumes a fewer number of significant coefficients or taps and to invest more bits in quantizing every complex coefficient.

[0033] On the other hand, if the number of active coefficients or taps of the radio channel k _aps before tap selection is very large compared to this means many significant coefficients or taps will be clipped to zero which could lead to a loss in signal quality. For a UE in this situation, it may make sense to decrease the resolution per tap and to select a higher number of complex coefficients

[0034] Therefore, as illustrated in the example of Fig. 4, a tree selection process may be performed based on some predetermined thresholds, T and T ₂ , to determine the best or optimum quantization codebook for a UE, without the need to complete the whole chain of quantization (based on computed time domain coefficients) and MSE computation for all quantization options. In particular, as illustrated in Fig. 4, the process may include, at 400, computing a quantization codebook that has a number of coefficients or taps in the middle of the range of all taps and, at 405, determining the number of active non-zero coefficients or taps. Then, at 410, it is determined whether the number of active coefficients or taps is less than a first threshold. If the number of active coefficients or taps is less than a first threshold, then, at 420, Q ₂ is selected as the quantization codebook. If the number of active coefficients or taps is not less than a first threshold, then, at 415, it is determined whether the number of active coefficients or taps is greater than a second threshold. If the number of active coefficients or taps is greater than a second threshold, then, at 425, Q ₃ is selected as the quantization codebook. If the number of active coefficients or taps is not greater than a second threshold, then, at 430, Qi is selected as the quantization codebook. Tap selection may then be performed, at 440, for the selected quantization codebook. At 450, a MSE may be computed for the selected quantization codebook. In addition, at 460, the index of the selected quantization codebook i and the MSE may be fed back to the gNB.

[0035] According to an embodiment, another criterion for checking the optimum quantizer may be to examine the amount of CIR energy that will be clipped to zero after quantization and before tap selection. The embodiment depicted in Fig. 4 may reduce complexity, but the thresholds, T _t and T ₂ , may also need to be carefully chosen.

[0036] In addition, for both the embodiments illustrated in Figs. 3 and 4, the UE may also be configured to send back MSE.. to the network (i.e., gNB), where MSE, is a measure of how good the CIR compression is. According to an embodiment, feeding back the MSE can apply to any method, which does not have to be time domain. For example, in certain embodiments, feeding back the MSE may also be generalized to any case where the channel frequency response is approximated (compressed) to a sparser form and fed back to the gNB, i.e., not necessarily when the channel compression technique is using time domain transform. This may be useful, for example, in case the UE is reporting very high MSE. In this case, the gNB may then decide to allocate a higher feedback overhead budget to that UE or to switch to another CSI feedback mechanism, because the reported CSI is not reliable enough. If the reported MSE is too low, the gNB may decide to allocate a lesser number of feedback overhead bits to that UE so as to save spectral efficiency by reducing signalling overhead of the reverse link.

[0037] Fig. 5a illustrates an example of an apparatus 10 according to an embodiment. In an embodiment, apparatus 10 may be a node, host, or server in a communications network or serving such a network. For example, apparatus 10 may be a base station, a Node B, an evolved Node B (eNB), 5G Node B or access point, next generation Node B (NG-NB or gNB), WLAN access point, mobility management entity (MME), or subscription server associated with a radio access network, such as a GSM network, LTE network, 5G or NR.

[0038] It should be understood that apparatus 10 may be comprised of an edge cloud server as a distributed computing system where the server and the radio node may be stand-alone apparatuses communicating with each other via a radio path or via a wired connection, or they may be located in a same entity communicating via a wired connection. It should be noted that one of ordinary skill in the art would understand that apparatus 10 may include components or features not shown in Fig. 5a.

[0039] As illustrated in Fig. 5a, apparatus 10 may include a processor 12 for processing information and executing instructions or operations. Processor 12 may be any type of general or specific purpose processor. In fact, processor 12 may include one or more of general-purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs), field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), and processors based on a multi-core processor architecture, as examples. While a single processor 12 is shown in Fig. 5a, multiple processors may be utilized according to other embodiments. For example, it should be understood that, in certain embodiments, apparatus 10 may include two or more processors that may form a multiprocessor system (i.e., in this case processor 12 represents a multiprocessor) that may support multiprocessing. In certain embodiments, the multiprocessor system may be tightly coupled or loosely coupled (e.g., to form a computer cluster).

[0040] Processor 12 may perform functions associated with the operation of apparatus 10 which may include, for example, precoding of antenna gain/phase parameters, encoding and decoding of individual bits forming a communication message, formatting of information, and overall control of the apparatus 10, including processes related to management of communication resources.

[0041] Apparatus 10 may further include or be coupled to a memory 14 (internal or external), which may be coupled to processor 12, for storing information and instructions that may be executed by processor 12. Memory 14 may be one or more memories and of any type suitable to the local application environment, and may be implemented using any suitable volatile or nonvolatile data storage technology such as a semiconductor- based memory device, a magnetic memory device and system, an optical memory device and system, fixed memory, and removable memory. For example, memory 14 can be comprised of any combination of random access memory (RAM), read only memory (ROM), static storage such as a magnetic or optical disk, hard disk drive (HDD), or any other type of non- transitory machine or computer readable media. The instructions stored in memory 14 may include program instructions or computer program code that, when executed by processor 12, enable the apparatus 10 to perform tasks as described herein.

[0042] In an embodiment, apparatus 10 may further include or be coupled to (internal or external) a drive or port that is configured to accept and read an external computer readable storage medium, such as an optical disc, USB drive, flash drive, or any other storage medium. For example, the external computer readable storage medium may store a computer program or software for execution by processor 12 and/or apparatus 10. [0043] In some embodiments, apparatus 10 may also include or be coupled to one or more antennas 15 for transmitting and receiving signals and/or data to and from apparatus 10. Apparatus 10 may further include or be coupled to a transceiver 18 configured to transmit and receive information. The transceiver 18 may include, for example, a plurality of radio interfaces that may be coupled to the antenna(s) 15. The radio interfaces may correspond to a plurality of radio access technologies including one or more of GSM, NB-IoT, LTE, 5G, WLAN, Bluetooth, BT- LE, NFC, radio frequency identifier (RFID), ultrawideband (UWB), MulteFire, and the like. The radio interface may include components, such as filters, converters (for example, digital-to-analog converters and the like), mappers, a Fast Fourier Transform (FFT) module, and the like, to generate symbols for a transmission via one or more downlinks and to receive symbols (for example, via an uplink). As such, transceiver 18 may be configured to modulate information on to a carrier waveform for transmission by the antenna(s) 15 and demodulate information received via the antenna(s) 15 for further processing by other elements of apparatus 10. In other embodiments, transceiver 18 may be capable of transmitting and receiving signals or data directly.

[0044] In an embodiment, memory 14 may store software modules that provide functionality when executed by processor 12. The modules may include, for example, an operating system that provides operating system functionality for apparatus 10. The memory may also store one or more functional modules, such as an application or program, to provide additional functionality for apparatus 10. The components of apparatus 10 may be implemented in hardware, or as any suitable combination of hardware and software.

[0045] In certain embodiments, apparatus 10 may be a network node or RAN node, such as a base station, access point, Node B, eNB, gNB, WLAN access point, or the like. According to certain embodiments, apparatus 10 may be controlled by memory 14 and processor 12 to perform the functions associated with any of the embodiments described herein, such as the flow diagrams illustrated in Figs. 2-4.

[0046] In an embodiment, apparatus 10 may be controlled by memory 14 and processor 12 to receive an index of a quantized codebook selected by a UE. According to certain embodiments, the quantized codebook may describe or include, in a compressed manner, the CSI of an effective precoded/beamformed propagation channel with complex coefficients representing the significant taps of the CIR. In an embodiment, the quantized codebook may be selected by the UE to optimize or provide the best trade-off in terms of the number of significant coefficients or taps and/or in terms of coefficient resolution or tap resolution. For instance, in some embodiments, the optimum codebook may be selected by the UE according to either of the processes depicted in Figs. 3 or 4 discussed above.

[0047] According to one embodiment, apparatus 10 may also be controlled by memory 14 and processor 12 to receive a MSE of channel compression calculated by the UE for the quantized codebook it selected. Based on the received index and/or MSE, apparatus 10 may also be controlled by memory 14 and processor 12 to decide whether to allocate a higher or lower feedback overhead budget to the user equipment.

[0048] For example, in one embodiment, when the MSE reported by the UE is higher than a predetermined threshold, apparatus 10 may be controlled by memory 14 and processor 12 to allocate a higher number of feedback overhead bits to the UE or to switch to another CSI feedback mechanism. In another embodiment, when the MSE reported by the UE is lower than a predetermined threshold, apparatus 10 may be controlled by memory 14 and processor 12 to allocate a lower number of feedback overhead bits to the user equipment so as to reduce signaling overhead.

[0049] Fig. 5b illustrates an example of an apparatus 20 according to another embodiment. In an embodiment, apparatus 20 may be a node or element in a communications network or associated with such a network, such as a UE, mobile equipment (ME), mobile station, mobile device, stationary device, IoT device, or other device. As described herein, UE may alternatively be referred to as, for example, a mobile station, mobile equipment, mobile unit, mobile device, user device, subscriber station, wireless terminal, tablet, smart phone, IoT device or NB-IoT device, or the like. As one example, apparatus 20 may be implemented in, for instance, a wireless handheld device, a wireless plug-in accessory, or the like.

[0050] In some example embodiments, apparatus 20 may include one or more processors, one or more computer-readable storage medium (for example, memory, storage, and the like), one or more radio access components (for example, a modem, a transceiver, and the like), and/or a user interface. In some embodiments, apparatus 20 may be configured to operate using one or more radio access technologies, such as GSM, LTE, LTE-A, NR, 5G, WLAN, WiFi, NB-IoT, Bluetooth, NFC, MulteFire, and any other radio access technologies. It should be noted that one of ordinary skill in the art would understand that apparatus 20 may include components or features not shown in Fig. 5b.

[0051] As illustrated in Fig. 5b, apparatus 20 may include or be coupled to a processor 22 for processing information and executing instructions or operations. Processor 22 may be any type of general or specific purpose processor. In fact, processor 22 may include one or more of general-purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs), field-programmable gate arrays (FPGAs), application- specific integrated circuits (ASICs), and processors based on a multi-core processor architecture, as examples. While a single processor 22 is shown in Fig. 5b, multiple processors may be utilized according to other embodiments. For example, it should be understood that, in certain embodiments, apparatus 20 may include two or more processors that may form a multiprocessor system (i.e., in this case processor 22 represents a multiprocessor) that may support multiprocessing. In certain embodiments, the multiprocessor system may be tightly coupled or loosely coupled (e.g., to form a computer cluster).

[0052] Processor 22 may perform functions associated with the operation of apparatus 20 including, without limitation, precoding of antenna gain/phase parameters, encoding and decoding of individual bits forming a communication message, formatting of information, and overall control of the apparatus 20, including processes related to management of communication resources.

[0053] Apparatus 20 may further include or be coupled to a memory 24 (internal or external), which may be coupled to processor 22, for storing information and instructions that may be executed by processor 22. Memory 24 may be one or more memories and of any type suitable to the local application environment, and may be implemented using any suitable volatile or nonvolatile data storage technology such as a semiconductor- based memory device, a magnetic memory device and system, an optical memory device and system, fixed memory, and removable memory. For example, memory 24 can be comprised of any combination of random access memory (RAM), read only memory (ROM), static storage such as a magnetic or optical disk, or any other type of non-transitory machine or computer readable media. The instructions stored in memory 24 may include program instructions or computer program code that, when executed by processor 22, enable the apparatus 20 to perform tasks as described herein.

[0054] In an embodiment, apparatus 20 may further include or be coupled to (internal or external) a drive or port that is configured to accept and read an external computer readable storage medium, such as an optical disc, USB drive, flash drive, or any other storage medium. For example, the external computer readable storage medium may store a computer program or software for execution by processor 22 and/or apparatus 20. [0055] In some embodiments, apparatus 20 may also include or be coupled to one or more antennas 25 for receiving a downlink signal and for transmitting via an uplink from apparatus 20. Apparatus 20 may further include a transceiver 28 configured to transmit and receive information. The transceiver 28 may also include a radio interface (e.g., a modem) coupled to the antenna 25. The radio interface may correspond to a plurality of radio access technologies including one or more of GSM, LTE, LTE-A, 5G, NR, WLAN, NB-IoT, Bluetooth, BT-LE, NFC, RFID, UWB, and the like. The radio interface may include other components, such as filters, converters (for example, digital-to-analog converters and the like), symbol demappers, signal shaping components, an Inverse Fast Fourier Transform (IFFT) module, and the like, to process symbols, such as OFDMA symbols, carried by a downlink or an uplink.

[0056] For instance, transceiver 28 may be configured to modulate information on to a carrier waveform for transmission by the antenna(s) 25 and demodulate information received via the antenna(s) 25 for further processing by other elements of apparatus 20. In other embodiments, transceiver 28 may be capable of transmitting and receiving signals or data directly. Apparatus 20 may further include a user interface, such as a graphical user interface or touchscreen.

[0057] In an embodiment, memory 24 stores software modules that provide functionality when executed by processor 22. The modules may include, for example, an operating system that provides operating system functionality for apparatus 20. The memory may also store one or more functional modules, such as an application or program, to provide additional functionality for apparatus 20. The components of apparatus 20 may be implemented in hardware, or as any suitable combination of hardware and software. According to an embodiment, apparatus 20 may be configured to communicate with apparatus 10 via a wireless or wired communications link 70 according to any radio access technology, such as NR. [0058] According to one embodiment, apparatus 20 may be a UE, mobile device, mobile station, ME, IoT device and/or NB-IoT device, for example. According to certain embodiments, apparatus 20 may be controlled by memory 24 and processor 22 to perform the functions associated with embodiments described herein. For example, in some embodiments, apparatus 20 may be configured to perform one or more of the processes depicted in any of the flow charts or signaling diagrams described herein, such as the flow diagrams illustrated in Figs. 2-4.

[0059] According to one embodiment, apparatus 20 may be controlled by memory 24 and processor 22 to compute one or more quantized codebooks. According to certain embodiments, the quantized codebook(s) may describe or include, in a compressed manner, the CSI of an effective precoded/beamformed propagation channel with complex coefficients representing the significant coefficients or taps of the CIR. In one embodiment, apparatus 20 may be controlled by memory 24 and processor 22 to compute a plurality of quantized codebooks as illustrated in Fig. 3. In other embodiments, as illustrated in the example of Fig. 4 and discussed in further detail below, apparatus 20 may be controlled by memory 24 and processor 22 to first select one quantized codebook to compute.

[0060] In an embodiment, apparatus 20 may then be controlled by memory 24 and processor 22 to determine or select the optimum or best quantized codebook(s), from among the computed quantized codebook(s), in terms of the number of (active) feedback coefficients or taps and/or coefficient resolution or tap resolution for the apparatus 20.

[0061] In one embodiment, for example as illustrated in the example flow diagram of Fig. 4, apparatus 20 may be controlled by memory 24 and processor 22 to select the optimum quantized codebook by first placing the computed quantized codebook(s) in order according to their number of coefficients or taps, and then selecting the quantized codebook that is in a middle of the ordered quantized codebooks in terms of the number of coefficients or taps. As one example, if there were 11 quantized codebooks placed in order from 1 through 11 according their number of coefficients or taps, apparatus 20 may be controlled by memory 24 and processor 22 to first select the 6 ^th quantized codebook in the ordered list. In this embodiment, apparatus 20 may then be controlled by memory 24 and processor 22 to determine the number of active coefficients or taps for that quantized codebook that is in the middle of the ordered list of quantized codebooks, and to determine, based on the number of active coefficients or taps, whether to switch the selected quantized codebook to another quantized codebook that is more optimum in terms of the number of feedback coefficients or taps and/or in terms of coefficient resolution or tap resolution.

[0062] For example, apparatus 20 may be controlled to determine whether to switch the selected quantized codebook to another quantized codebook by comparing the number of active coefficients or taps for the initially selected quantized codebook to one or more pre-defined thresholds, and then determining whether to switch the selected quantized codebook to another quantized codebook based on a result of the comparison.

[0063] According to an embodiment, apparatus 20 may also be controlled by memory 24 and processor 22 to send an index of the selected quantized codebook to a network node, e.g., a gNB. In certain embodiments, apparatus 20 may be further controlled by memory 24 and processor 22 to compute the MSE for all of the computed quantized codebooks or for just the selected quantized codebook, and to feedback, to the network node, the computed MSE of the selected quantized codebook. In one embodiment, apparatus 20 may be controlled by memory 24 and processor 22 to select, as the optimum quantized codebook, the quantized codebook that provides a minimum value of the MSE from among the MSEs of all the computed quantized codebooks. In some embodiments, apparatus 20 may also be controlled by memory 24 and processor 22 to perform tap selection for all of the computed quantized codebooks or for just the selected quantized codebook. [0064] Therefore, embodiments of the invention provide several technical improvements, enhancements, and/or advantages. For example, as a result of certain embodiments, an optimum quantizer may be selected, spectral efficiency improved, and signaling overhead and processing load can be reduced. As such, embodiments of the invention can improve performance and throughput of network nodes including, for example, base stations/eNBs/gNBs and UEs. Accordingly, the use of embodiments of the invention result in improved functioning of communications networks and their nodes.

[0065] In some embodiments, the functionality of any of the methods, processes, signaling diagrams, or flow charts described herein may be implemented by software and/or computer program code or portions of code stored in memory or other computer readable or tangible media, and executed by a processor.

[0066] In some embodiments, an apparatus may be included or be associated with at least one software application, module, unit or entity configured as arithmetic operation(s), or as a program or portions of it (including an added or updated software routine), executed by at least one operation processor. Programs, also called program products or computer programs, including software routines, applets and macros, may be stored in any apparatus-readable data storage medium and include program instructions to perform particular tasks.

[0067] A computer program product may comprise one or more computer- executable components which, when the program is run, are configured to carry out embodiments. The one or more computer-executable components may be at least one software code or portions of it. Modifications and configurations required for implementing functionality of an embodiment may be performed as routine(s), which may be implemented as added or updated software routine(s). Software routine(s) may be downloaded into the apparatus. [0068] Software or a computer program code or portions of it may be in a source code form, object code form, or in some intermediate form, and it may be stored in some sort of carrier, distribution medium, or computer readable medium, which may be any entity or device capable of carrying the program. Such carriers include a record medium, computer memory, read only memory, photoelectrical and/or electrical carrier signal, telecommunications signal, and software distribution package, for example. Depending on the processing power needed, the computer program may be executed in a single electronic digital computer or it may be distributed amongst a number of computers. The computer readable medium or computer readable storage medium may be a non-transitory medium.

[0069] In other embodiments, the functionality may be performed by hardware or circuitry included in an apparatus (e.g., apparatus 10 or apparatus 20), for example through the use of an application specific integrated circuit (ASIC), a programmable gate array (PGA), a field programmable gate array (FPGA), or any other combination of hardware and software. In yet another embodiment, the functionality may be implemented as a signal, a non-tangible means that can be carried by an electromagnetic signal downloaded from the Internet or other network.

[0070] According to an embodiment, an apparatus, such as a node, device, or a corresponding component, may be configured as circuitry, a computer or a microprocessor, such as single-chip computer element, or as a chipset, including at least a memory for providing storage capacity used for arithmetic operation and an operation processor for executing the arithmetic operation.

[0071] One having ordinary skill in the art will readily understand that the invention as discussed above may be practiced with steps in a different order, and/or with hardware elements in configurations which are different than those which are disclosed. Therefore, although the invention has been described based upon these preferred embodiments, it would be apparent to those of skill in the art that certain modifications, variations, and alternative constructions would be apparent, while remaining within the spirit and scope of the invention. In order to determine the metes and bounds of the invention, therefore, reference should be made to the appended claims.