Network device controller, base station and method for network device controller

Abstract

A network device controller (104) configured to generate one or more initial Channel State Information, CSI, representative configuration(s) indicating parameters of a CSI representative computation algorithm, transmit the one or more initial CSI representative configuration(s) in one or more first CSI-ReportConfig message(s) to one or more User Equipment(s) (110), UEs, receive a feedback message(s) from at least one of the one or more UEs (110), the feedback message(s) comprising indicators of measurements, perform an evaluation of the measurements and decide if the CSI representative configuration(s) need(s) to be updated, and if so generate an updated CSI representative configuration(s) and transmit the updated CSI representative configuration(s) in one or more second CSI-ReportConfig message(s) to the at least one of the one or more UEs (110).

Description

[0001] NETWORK DEVICE CONTROLLER, BASE STATION AND METHOD FOR NETWORK DEVICE CONTROLLER

[0002] TECHNICAL FIELD

[0003] The present disclosure relates generally to the field of wireless communication network management and, more specifically, to a network device controller, a base station, and a method for the network device controller, such as for network-aided CSI representative computation.

[0004] BACKGROUND

[0005] In modem wireless communication networks, efficient downlink transmission from base stations to user equipment (UE) is critical for achieving high data rates and robust connectivity. Precoding is a widely used signal processing technique designed to optimize the transmission of data by shaping signals before transmission. The precoding is particularly essential in technologies like Massive Multiple Input and Multiple Output (MIMO), Multi-User Multiple Input and Multiple Output (MU-MIMO), beamforming, and the like, where base stations and user devices, both with multiple antennas, operate simultaneously. Existing methods for precoding often depend on the accuracy of the Channel State Information (CSI) representative, which provides details of the communication channel. The CSI representative provides a channel representation or estimate that is used to calculate the precoding matrix, ensuring optimal signal transmission. However, the process of computing a CSI representative, particularly for sub-bands consisting of multiple physical resource blocks (PRBs), poses challenges, such as maintaining accuracy while reducing computational complexity.

[0006] Certain attempts have been made to improve the accuracy of the CSI representative and reduce computational complexity in wireless communication systems, which includes the development of advanced algorithms for calculating the CSI representative. Such algorithms utilize advance techniques such as interpolation, machine learning, and statistical modelling to improve the approximation of the channel behaviour over sub-bands, capturing critical features required for efficient precoding. However, the advanced algorithms often come with increased computational complexity, which can be burdensome for user equipment, especially in real-time applications. Thus, there exists a need of how to provide an efficient method for CSI representative computation that balances accuracy and computational load of the UE while ensuring optimal performance in real-time applications.

[0007] Therefore, in light of the foregoing discussion, there exists a need to overcome the aforementioned drawbacks associated with the conventional network device controller, the conventional base station, and the conventional method for the network device controller, such as for network-aided CSI representative computation.

[0008] SUMMARY

[0009] The present disclosure provides a network device controller, a base station, and a method for the network device controller, such as for network-aided CSI representative computation. The present disclosure provides a solution to the existing problem of how to provide an efficient method for CSI representative computation that balances the accuracy and computational load of the User Equipments (UEs) while ensuring optimal performance in real-time applications. An objective of the present disclosure is to provide a solution that overcomes at least partially the problems encountered in the prior art and provides the network device controller, the base station, and the method for the network device controller, such as for network-aided CSI representative computation.

[0010] One or more objectives of the present disclosure are achieved by the solutions provided in the enclosed independent claims. Advantageous implementations of the present disclosure are further defined in the dependent claims.

[0011] In one aspect, the present disclosure provides the network device controller configured to generate one or more initial CSI representative configuration(s) indicating parameters of a CSI representative computation algorithm. Further, the network device controller is configured to transmit one or more initial CSI representative configurations in one or more first CSI-ReportConfig messages to one or more UEs. Furthermore, the network device controller is configured to receive feedback messages from at least one of the one or more UEs. The feedback messages comprise indicators of measurements. Moreover, the network device controller is configured to perform an evaluation of the measurements and decide if the CSI representative configurations need to be updated, and if so, generate updated CSI representative configurations. Furthermore, the network device controller is configured to transmit the updated CSI representative configurations in one or more second CSI-ReportConfig messages to at least one of the one or more UEs.

[0012] Advantageously, by generating the optimal CSI representative configurations, the network device controller ensures a balance between accuracy and computational efficiency, accommodating varying network conditions and user requirements. Moreover, the network device controller collects the measurements from the one or more UEs and analyzes a collective key performance indicator (KPI). Based on the collective KPI, the network device controller dynamically adjusts the CSI representative configurations to ensure sustained network performance, which ultimately minimizes performance degradation caused by fluctuating network conditions and enhances overall communication performance. The CSI representative configuration parameters, which include representation domain’s shapes and ranks for time, frequency, and antenna port domains, allow fine-grained control over the CSI representative computation algorithm steps at each UE of the at least one of the one or more UEs. Furthermore, the CSI representative configuration introduces a comprehensive framework that provides the network controller with precise control over the CSI representative computation algorithm's operation. This is enabled through carefully structured parameters across multiple domains. The inclusion of a collective KPI, such as the (weighted) sum or product of the individual Signal-to-Interference-plus-Noise Ratio (SINR) for the served UEs or the (weighted) sum of the individual rates over the served UEs or complexity or a combination thereof, enables the network device controller to evaluate the overall communication performance comprehensively. By considering a collective KPI, the network device controller ensures that network optimizations are not biased toward individual metrics but reflect an overall performance improvement. The ability to generate the uniform CSI parameters for the one or more UEs, simplifies resource allocation and reduces the computational complexity of wireless communication. Alternatively, the network device controller can create distinct CSI representative configurations tailored to specific subsets of UEs or individual devices, thereby optimizing performance based on unique roles, locations, or technical constraints. Thus, the CSI representative configuration is used by the CSI representative computation algorithm, such as by utilizing the parameters provided in the CSI representativeconfiguration for the efficient computation of the channel representative through the multi-domain parameter structure.

[0013] In another aspect, the present disclosure provides a base station comprising the network device controller.

[0014] The base station achieves all the advantages and technical effects of the network device controller of the present disclosure.

[0015] In yet another aspect, there is provided a method for the network device controller. The method includes generating one or more initial CSI representative configuration(s) indicating parameters of a CSI representative computation algorithm. Furthermore, the method includes transmitting the one or more initial CSI representative configurations in one or more first CSI-ReportConfig messages to one or more UEs. Moreover, the method includes receiving feedback messages from at least one of the one or more UEs. The feedback messages comprise indicators of measurements. Furthermore, the method includes continuously performing an evaluation of the measurements and deciding if the CSI representative configurations need to be updated. Moreover, the method 100 includes generating an updated CSI representative configuration(s) and transmitting the updated CSI representative configurations in one or more second CSI-ReportConfig messages to the at least one of the one or more UEs.

[0016] The method achieves all the advantages and technical effects of the network device controller of the present disclosure.

[0017] It is to be appreciated that all the aforementioned implementation forms can be combined.

[0018] It has to be noted that all devices, elements, circuitry, units, and means described in the present application could be implemented in the software or hardware elements or any kind of combination thereof. All steps which are performed by the various entities described in the present application, as well as the functionalities described to be performed by the various entities are intended to mean that the respective entity is adapted to or configured to perform the respective steps and functionalities. Even if, in the following description of specific embodiments, a specific functionality or step to be performed by external entities is not reflected in the description of a specific detailed element of that entity that performs that specific step or functionality, it should be clear for a skilled person that these methods and functionalities can be implemented in respective software or hardware elements or any kind of combination thereof. It will be appreciated that features of the present disclosure are susceptible to being combined in various combinations without departing from the scope of the present disclosure as defined by the appended claims.

[0019] Additional aspects, advantages, features, and objects of the present disclosure would be made apparent from the drawings and the detailed description of the illustrative implementations construed in conjunction with the appended claims that follow.BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The summary above, as well as the following detailed description of illustrative embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the present disclosure, exemplary constructions of the disclosure are shown in the drawings. However, the present disclosure is not limited to specific methods and instrumentalities disclosed herein. Moreover, those in the art will understand that the drawings are not to scale. Wherever possible, like elements have been indicated by identical numbers.

[0021] Embodiments of the present disclosure will now be described, by way of example only, with reference to the following diagrams wherein:

[0022] FIG. 1 is a diagram that illustrates a base station comprising a network device controller, in accordance with an embodiment of the present disclosure;

[0023] FIG. 2 is another diagram that illustrates a base station, in accordance with an embodiment of the present disclosure;

[0024] FIG. 3 is a flowchart that illustrates a method for a network device controller, in accordance with an embodiment of the present disclosure; and

[0025] FIG. 4 is a diagram that illustrates a sequence of signalling between a base station and a UE, in accordance with an embodiment of the present disclosure.

[0026] In the accompanying drawings, an underlined number is employed to represent an item over which the underlined number is positioned or an item to which the underlined number is adjacent. A non-underlined number relates to an item identified by a line linking the non-underlined number to the item. When a number is non-underlined and accompanied by an associated arrow, the non-underlined number is used to identify a general item at which the arrow is pointing.

[0027] DETAILED DESCRIPTION OF EMBODIMENTS

[0028] The following detailed description illustrates embodiments of the present disclosure and ways in which they can be implemented. Although some modes of carrying out the present disclosure have been disclosed, those skilled in the art would recognize that other embodiments for carrying out or practicing the present disclosure are also possible.

[0029] FIG. 1 is a diagram that illustrates a base station comprising a network device controller, in accordance with an embodiment of the present disclosure. With reference to FIG. 1, there is shown the diagram 100 that includes the base station 102 comprising the network device controller 104. Furthermore, the drawing 100 includes a plurality of (or one or more) UEs 110, and a communication network 112.

[0030] There is provided the base station 102, which includes the network device controller 104. The base station 102 refers to an access point for different UEs in a wireless network to communicate within the coverage area of the base station 102. The base station 102 handles tasks such as managing the radio connection, transmitting and receiving data, and ensuring that devices (or UEs) within the coverage area of the base station 102 can communicate effectively via the wireless network. The base station 102 is equipped with the network devicecontroller 104. In an implementation, the base station 102 facilitates the efficient serving of multiple users at a high rate, particularly in advanced systems like 5G and 6G.

[0031] The network device controller 104 is a component of the base station 102 that manages and coordinates the operation of network devices, such as base stations and user equipment. Examples of the network device controller 104 may include but are not limited to a central data processing device, a microprocessor, a microcontroller, a complex instruction set computing (CISC) processor, an application-specific integrated circuit (ASIC) processor, a reduced instruction set (RISC) processor, a very long instruction word (VLIW) processor, a central processing unit (CPU), a state machine, a data processing unit, and other processors or circuitry. The network device controller 104 includes a memory 202 and a network interface 204.

[0032] The one or more UEs 110 (i.e., the first UE 110A, the second UE 110B, the third UE 110C, and up to the Nth UE 110N) refers to the devices, such as mobile phones, tablets, laptops, wearable devices, Internet of Things (IoT) devices, and the like, which are used by end users to connect to the wireless communication network. The one or more UEs 110 is configured to communicate with the base station 102 to send and receive data, enabling various applications such as voice calls, video streaming, internet access, and the like.

[0033] The communication network 112 includes a medium, such as a communication channel, that facilitates the exchange of data, voice, video, or other forms of information between devices or entities. Examples of the communication network 112 may include, but are not limited to, a cellular network (e.g., a 5G, or 5G NR network, such as sub 6 GHz, cmWave, or mmWave communication network), a cloud network, a Local Area Network (LAN), a vehicle-to-network (V2N) network, a Metropolitan Area Network (MAN), and / or the Internet. Modem communication networks incorporate advanced technologies like packet switching, encryption, and error correction to enable efficient and secure communication.

[0034] Advantageously, by generating the initial CSI representative configurations and transmitting the initial CSI representative configurations to one or more UEs 110, the base station 102 ensures that communication begins with parameters tailored to the prevailing network conditions, thereby facilitating efficient data processing and enhancing signal clarity. Furthermore, the base station 102 receives feedback from the one or more UEs 110, such as, Precoding Matrix Indicator (PMI), signal quality metrics and interference levels, which allows for continuous monitoring of the communication environment and enables the base station to update the CSI representative configurations as needed dynamically, ensuring optimal performance despite changing network conditions. Additionally, the base station 102 evaluates overall network performance metrics combined in the collective KPI, to refine resource allocation and optimize precoding strategies, thereby enhancing the data throughput, and ensuring an effective utilization of network resources.

[0035] FIG. 2 is another diagram that illustrates a base station, in accordance with an embodiment of the present disclosure. FIG. 2 is described in conjunction with the FIG. 1. With reference to FIG. 2, there is shown a diagram 200 that shows the base station 102, which includes the network device controller 104, a memory 204, and a network interface 202.The memory 204 is configured to store the instructions for the signal processing. Examples of implementation of the memory 204 may include, but are not limited to, Electrically Erasable Programmable Read-Only Memory (EEPROM), Dynamic Random-Access Memory (DRAM), Random Access Memory (RAM), Read-Only Memory (ROM), Hard Disk Drive (HDD), Flash memory, a Secure Digital (SD) card, Solid-State Drive (SSD), and / or CPU cache memory.

[0036] The network interface 202 includes hardware or software that is configured to establish communication between the network device controller 104 and the one or more UEs 110. Examples of the network interface card 108 may include, but are not limited to, a computer port, a network socket, a network interface controller (NIC), and any other network interface device.

[0037] There is provided the network device controller 104 configured to generate one or more initial CSI representative configurations indicating parameters of a CSI representative computation algorithm. The one or more initial CSI representative configurations specify certain parameters that define the process of transforming complex channel state data into a manageable representation. The network device controller 104 is configured to assess various factors related to the communication environment, including network conditions, user-specific requirements, and collective KPI such as the sum rate. By analyzing such factors, the network device controller 104 is configured to identify optimal parameter values for the CSI representative computation algorithm. The optimal parameters may include the representation domain’s shapes and ranks across multiple domains (i.e., time-domain representation shapes and ranks that defines the processing according to the Orthogonal Frequency Division Multiplexing (OFDM) symbols, frequency-domain representation shapes and ranks for the processing according to the subcarriers, RX-antenna-port-domain representation shapes and ranks according to receiver spatial processing, and TX-antenna-port-domain representation shapes and ranks according to transmitter spatial processing. Thus, the network device controller 104 ensures that the generated CSI representative configurations provide a balance between accuracy and computational efficiency. By determining and providing these parameters, the network device controller 104 enables consistent and effective processing of CSI data at the UE, facilitating improved overall network performance.

[0038] Furthermore, the network device controller 104 is configured to transmit the one or more initial CSI representative configurations in one or more first CSI-ReportConfig messages to one or more UEs 110. The transmission of CSI representative configurations through CSI-ReportConfig messages is necessary to establish network-controlled CSI representative computation at the one or more UEs 110. The network device controller 104 includes the CSI representative configuration as a new field within the structure of the CSI-ReportConfig message. For each UE or group of UEs, the network device controller 104 generates specific configuration parameters defining the shapes and ranks across all domains. For example, in the TX-antenna-port domain with 256 antennas, the configuration might specify a shape of (2,4, 8,4) with corresponding ranks (2, 2, 6, 3), providing precise control over the transmitter spatial domain.Furthermore, the network device controller 104 is configured to receive the feedback messages from at least one of the one or more UEs 110. The feedback messages comprising indicators of measurements. The feedback messages include indicators of measurements, such as Precoding Matrix Indicators (PMIs), channel quality metrics, signal strength, interference levels, and other performance-related parameters observed by the one of more UEs 110 during wireless communication. In an implementation, the one or more of UEs 110 are configured to perform measurements based on the received signals, which include channel quality indicators (CQI), signal-to-noise ratios (SNRs), and other relevant metrics. Such measurements are compiled into the feedback messages and transmitted back to the network device controller 104. The feedback messages enable the network device controller 104 to assess the effectiveness of the current network configuration, optimize resource allocation, and adjust communication parameters dynamically.

[0039] Furthermore, the network device controller 104 is configured to perform, continuously, an evaluation of the measurements and decide if the CSI representative configurations need to be updated. In operation, the network device controller 104 is configured to process the feedback messages received from the UEs, which contain detailed measurements of the current channel conditions. The measurements of the current channel conditions include PMIs, channel quality metrics, interference levels, and other performance indicators that reflect the current state of the communication environment. Furthermore, by using various algorithms and predefined thresholds, the network device controller 104 is configured to analyze the measurements of the current channel conditions to identify deviations from the expected performance. If the evaluation indicates that the current CSI representative configurations no longer meet the desired performance standards, the network device controller 104 decides that the CSI representative configurations need to be updated. Thus, the dynamic approach of updating the CSI representative configurations ensures that the wireless communication between the base station 102 and the one or more UEs 110 remains responsive to network changes.

[0040] In accordance with an embodiment, the network device controller 104 is further configured to perform the evaluation of the measurements by evaluating a collective KPI based on the combined impact of all received measurements on the downlink precoding efficiency, with the aim of optimizing performances at the network devices (or the one or more UEs 110). In operation, the network device controller 104 is configured to aggregate the received measurements from the one or more UEs 110 and calculate the collective KPI. The collective KPI may be derived using statistical or algorithmic methods to combine various metrics into a single KPI. The calculation of the collective KPI incorporates parameters like PMIs, signal quality, interference levels, and channel behavior to estimate the joint impact of such parameters to the efficiency of downlink precoding. Based on the collective KPI, the network device controller 104 determines whether adjustments to precoding strategies or the CSI representative configurations are needed to optimize communication. By virtue of evaluating the collective KPI, the network device controller 104 ensures a balanced and efficient approach to performance optimization of the wireless communication network. Further, the network device controller 104 reduces the likelihood of overemphasizing individual metrics, allowing for a more accurate and adaptive approach to managing network performance and resource allocation.In accordance with an embodiment, the collective KPI includes the (weighted) sum or product of the individual SINR for all of the one or more UEs or the (weighted) sum of the individual rates over all of the one or more UEs or complexity or a combination thereof. Such metrics represent essential indicators of the performance of the wireless communication network, particularly in terms of signal clarity, data throughput, and communication reliability. In operation, the network device controller 104 is configured to gather feedback from the one or more UEs 110, including measurements of SINR, data rates, and channel conditions. Furthermore, the network device controller 104 evaluates the metrics collectively to determine the overall network performance. The evaluation enables the network device controller 104 to identify areas for improvement, such as reducing interference, optimizing resource allocation, or updating the CSI representative configurations to enhance precoding.

[0041] Furthermore, the network device controller 104 is configured to generate an updated CSI representative configuration and transmit the updated CSI representative configuration in one or more second CSI-ReportConfig messages to the at least one of the one or more UEs 110. After evaluating the feedback from the one or more UEs 110 and analyzing the measurements, the network device controller 104 identifies whether the current CSI representative configuration parameters, specifically the shapes and ranks across time, frequency, and antenna port domains require adjustment to optimize the process of CSI representative computation. For example, if the network conditions change, the network device controller 104 might update the TX-antenna-port domain configuration from a shape of (2,4, 8,4) with ranks (2, 2, 6, 3) to a new configuration that better balances representation accuracy and computational efficiency. Similarly, adjustments to time-domain shapes and ranks might be needed to better capture temporal channel variations, or frequency-domain parameters might be modified to optimize the representation of frequency -related characteristics. If the update is necessary, the network device controller 104 recalculates the optimal parameters for the CSI representative computation algorithm, considering the new channel conditions. The updated CSI representative configuration is then packaged into one or more second CSI-ReportConfig messages, which are sent to the one or more UEs 110 for further application. By transmitting the updated configuration, the network device controller 104 allows the one or more UEs 110 to adjust the CSI representative computation algorithm parameters accordingly, improving performance, thereby minimizes the risk of performance degradation caused by the CSI representative not correctly capturing the actual CSI because of the outdated CSI representative configuration used to compute it and ensures that the communication between the base station 102 and the one or more UEs 110 remains efficient and includes minimal interference.

[0042] In accordance with an embodiment, the network device controller 104 is further configured to generate the CSI representative computation algorithm parameters as part of the initial CSI representative configuration. The CSI representative computation algorithm parameters comprise parameters relating to representation domain shapes (i.e., dimensions) and representation domain ranks (i.e., main components, variations, or features of the domain over its dimensions). The CSI representative computation algorithm parameters are specifically related to representation domain shapes and representation domain ranks, which determine how the CSI is arranged and processed in order to obtain the CSI representative. The representation domain shapes refer to the structure or arrangement of the channel data, such as whether the structure of obtained channel data (e.g., channel estimates) is organized in a vector, matrix, higher-dimensional array (tensor), or other formats. Furthermore, the parameters are incorporated into the initial CSI representative configuration, which is then transmitted to the UEs for use intheir CSI calculations. By including representation domain shapes and ranks as part of the CSI representative computation algorithm parameters, the network device controller 104 allows for more tailored and efficient CSI processing.

[0043] In accordance with an embodiment, the CSI representative computation algorithm parameters comprise at least one of Time-domain representation shape, Time-domain representation ranks, Frequency-domain representation shape, Frequency-domain representation ranks, Receiver RX-antenna-port-domain representation shape, Receiver RX-antenna-port-domain representation ranks, Transmitter TX-antenna-port-domain representation shape, and Transmitter TX-antenna-port-domain representation ranks. In an example, the CSI representative computation algorithm parameters may include the Time-domain representation shape. In another example, the CSI representative computation algorithm parameters may include the Time-domain representation ranks. In yet another example, the CSI representative computation algorithm parameters may include the Frequency -domain representation shape. In yet another example, the CSI representative computation algorithm parameters may include the Frequency-domain representation ranks. In yet another example, the CSI representative computation algorithm parameters may include the Receiver RX-antenna-port-domain representation shape. In yet another example, the CSI representative computation algorithm parameters may include the Receiver RX-antenna-port-domain representation ranks. In yet another example, the CSI representative computation algorithm parameters may include the Transmitter TX-antenna-port-domain representation shape. In yet another example, the CSI representative computation algorithm parameters may include the Transmitter TX-antenna-port-domain representation ranks. Such parameters control how channel information is processed and represented in each domain. In an exemplary scenario, for the time domain, given M time measurements, the time-domain representation shape can be the tuple (s‘, s, s ), where M =

[0044]

[0045] x s x s, with corresponding ranks (r*, r^, r3), where < s-. For example, with M = 100 OFDM symbols, a shape (5,4,5) with ranks (3,2,3) defines how temporal channel variations are captured. In another exemplary scenario, for the frequency domain, given N subcarriers, the frequency-domain representation shape (s1f, s2f), where N = s1f × s2f, with ranks (r1f, r2f), where rif ≤ sif, controls how frequency-related characteristics are processed. For example, with N = 60 subcarriers, a shape of (4,3,5) with ranks (3, 2, 5) defines how frequency-domain patters are handled. In another exemplary scenario, for the TX-antenna-port domain, with Nt transmit antennas shape (s1tx, s2tx, s3tx, s4tx), where Nt = s1tx × s2tx × s3tx × s4tx, and ranks (r1tx, r2tx, r3tx, r4tx), where ritx ≤ sitx determines transmitter-side spatial processing. For example, with Nt= 256 transmit antennas, the TX-antenna-port-domain shape might be (2, 4, 8, 4) with ranks (2, 2, 6, 3), enabling precise control over transmitter-side spatial processing. In another exemplary scenario, for the RX-antenna-port domain, with Nr receive antennas shape (s1rx, s2rx), where Nr = s1rx × s2rx, and ranks (r1rx, r2rx), where rirx ≤ sirx determines receiver-side spatial processing. For example, with Nr= 16 receive antennas, the RX-antenna-port-domain shape might be (4,4) with ranks (2,3), enabling precise control over receiver-side spatial processing. At this juncture, it should be noted that the Doppler domain is equivalent to the time domain, the beam domain is equivalent to the antenna port domain, and the polarization domain is equivalent to the antenna port domain. By virtue of specifying both shapes and ranks across these domains, the network device controller 104 achieves precise control over the CSI representative computation algorithm parameters while preserving essential characteristics. The ranks determine how much variation each representation can capture in its respective domain, enabling optimization of the collective KPI.In accordance with an embodiment, the network device controller 104 is further configured to perform, as a continuous control loop, the evaluation of the measurements by evaluating the collective KPI using the received measurements for the parameters indicated in the sent CSI representative configurations, decide if the CSI representative configurations need to be updated by utilizing a function to assess if a different set of parameters of the CSI representative computation algorithm is required and to transmit the updated CSI representative configuration in the CSI-ReportConfig messages. In other words, the network device controller 104 monitors the incoming feedback from the one or more UEs 110, which includes measurements of parameters like PMIs, signal quality, interference levels, and data throughput. Furthermore, the network device controller 104 evaluates the measurements of parameters using the collective KPI to assess the current network performance. Moreover, the network device controller 104 applies a function to determine whether the existing parameters of the CSI representative computation algorithm are still suitable. If improvements are required, the network device controller 104 updates the parameters and transmits the updated CSI representative configurations back to the one or more UEs 110 in CSI-ReportConfig messages. Thus, by implementing the evaluation in a continuous control loop, the network device controller 104 enables on-the-fly optimization of CSI representative configurations, ensuring the wireless communication network adapts to fluctuating conditions.

[0046] In accordance with an embodiment, the network device controller 104 is further configured to generate a same set of parameters in the updated CSI representative configuration for one or more UEs 110. In operation, the network device controller 104 evaluates the wireless communication environment by analyzing feedback from the one or more UEs, network conditions, and performance indicators. Based on the analysis, the network device controller 104 identifies optimal parameters for the CSI representative computation algorithm, such as representation domain shapes and ranks, and applies them uniformly across the one or more UEs 110. The updated CSI representative configuration with such parameters is then transmitted to the targeted UEs through CSI-ReportConfig messages. Thus, the adoption of a same set of parameters for the one or more UEs 110 reduces the computational complexity associated with handling diverse configurations.

[0047] In accordance with an embodiment, the network device controller 104 is further configured to generate a first set of parameters in the updated CSI representative configuration for a first subset of the one or more UEs 110 and generate a second set of parameters in the updated CSI representative configuration for a second subset of the one or more UEs 110. In an implementation, the network device controller 104 evaluates the collective KPI involving measurements of the one or more UEs 110 in the wireless network. Based on the evaluation, the network device controller 104 categorizes the one or more UEs 110 into subsets (i.e., the first subset and the second subset) on the basis of roles, locations, or technical constraints of the one or more UEs 110. For each subset, the network device controller 104 generates a unique set of CSI representative parameters that define aspects like representation domain shapes and ranks. Thus, by computing for different set of the one or more UEs a different set of the CSI representative parameters, the network device controller 104 reduces the computational overhead for the one or more UEs 110 with limited processing power while maintaining high-quality the CSI representation for the one or more UEs 110 requiring precise data.In accordance with an embodiment, the network device controller 104 is further configured to generate one set of parameters in the updated CSI representative configuration for each of the one or more UEs 110. In an implementation, the network device controller 104 evaluates key metrics, including ones based on the PMIs, channel quality, interference levels, and device-specific constraints, for each UE of the one or more UEs 110. Based on the evaluation, the network device controller 104 determines the optimal set of parameters for the CSI representative computation algorithm for each UE of the one or more UEs 110. The configuration includes parameters like representation the domain shapes and ranks. Once generated, the unique parameter sets are transmitted to the respective UEs through the updated CSI-ReportConfig messages. By virtue of generating a unique set of parameters for the CSI representative configuration for each of the UE of the one or more UEs, the network device controller 104 ensures that each UE operates at the peak efficiency.

[0048] Advantageously, by generating the optimal CSI representative configurations, the network device controller 104 ensures a balance between accuracy and computational efficiency, accommodating varying network conditions and user requirements. Moreover, the network device controller 104 collects feedback, such as PMIs, signal strength and interference levels, from the one or more UEs 110 and analyses the collective KPI. Based on such metric, the network device controller 104 dynamically adjusts the CSI representative configurations to ensure sustained network performance, which ultimately minimizes performance degradation caused by fluctuating network conditions and enhances overall communication performance. The inclusion of collective performance indicators, such as the (weighted) sum or product of the individual SINR for the served UEs or the (weighted) sum of the individual rates over the served UEs or a combination thereof, enables the network device controller to evaluate the overall communication performance comprehensively. By considering a collective KPI, the network device controller 104 ensures that network optimizations are not biased toward individual metrics but reflect an overall performance improvement. The ability of generating the uniform CSI representative configuration parameters for the one or more UEs 110, simplifies the resource allocation and reduces computational complexity of the wireless communication. Alternatively, the network device controller 104 can create distinct configurations tailored to specific subsets of UEs or individual devices, thereby optimizing performance based on unique roles, locations, or technical constraints.

[0049] FIG. 3 is a flowchart that illustrates for a method for a network device controller, in accordance with an embodiment of the present disclosure. FIG. 3 is described in conjunction with the FIGs. 1 and 2. With reference to FIG. 3, there is shown a method 300 for the network device controller 104. The method 300 includes steps 302 to 312.

[0050] There is provided the method 300 for the network device controller 104. The method 300 is designed to adapt to dynamic network conditions, ensuring efficient resource allocation and improved performance. The method 300 focuses on improving communication performance by generating optimal CSI representative configurations based on current network conditions, transmitting such configurations to the one or more UEs 110, and adjusting such configuration as needed.At step 302, the method 300 includes generating one or more initial CSI representative configurations indicating parameters of the CSI representative computation algorithm. The CSI representative configurations indicate parameters that define the operation of the CSI representative computation algorithm. In order to generate the initial CSI representative configurations, the network device controller 104 analyzes the current network conditions, for example, using the Sounding Reference Signal (SRS). In addition, initial CSI representative configurations can be generated based on previous measurements or configurations.

[0051] At step 304, the method 300 includes transmitting the one or more initial CSI representative configurations in one or more first CSI-ReportConfig messages to one or more UEs 110. The one or more initial CSI representative configurations includes certain parameters that guide the one or more UEs 110 in computing the CSI representative and thus reporting CSI efficiently. Furthermore, the method 300 utilizes the CSI-ReportConfig messages as the communication medium to deliver the initial CSI representative configurations to the one or more UEs 110. Thus, transmitting the CSI representative configurations in a structured manner ensures that the one or more UEs 110 can immediately begin collecting and reporting channel information in alignment with the network's requirements.

[0052] At step 306, the method 300 includes receiving the feedback messages from at least one of the one or more UEs 110. The feedback messages comprising indicators of measurements. The indicators provide measurements related to the channel's performance and condition. The measurements may involve parameters such as PMIs, signal strength, interference levels, SNRs, or other metrics that help assess the quality of the communication link between the one or more UEs 110 and the base station 102. In an implementation, the base station 102 receives the feedback messages from at least one of the one or more UEs 110. In an example, the base station 102 receives the feedback messages from the first UE 110A. In another example, the base station 102 receives the feedback messages from the second UE 110B. In yet another example, the base station 102 receives the feedback messages from the third UE 110C. In yet another example, the base station 102 receives the feedback messages from the nth UE 110N. By virtue of receiving the feedback messages from one of the one or more UEs 110, the base station 102 gains current insights into the channel conditions, thereby allows the network to respond dynamically to changes in the environment, enhancing the reliability and efficiency of data transmission.

[0053] At step 308, the method 300 includes continuously performing an evaluation of the measurements and decide if the CSI representative configuration(s) needs to be updated. In operation, the network device controller 104 within the base station 102 performs the continuous evaluation of the received measurement indicators. The continuous evaluation involves analyzing the feedback messages received from the one or more UEs 110 to extract relevant measurement indicators, such as the PMI, the signal strength, the interference levels, or the SNRs. The network device controller 104 compares the relevant measurement indicators against predefined thresholds or criteria. If deviation threshold is met, the network device controller 104 determines that an update to the CSI representative configurations is necessary, thereby improving the accuracy of channel modelling and the efficiency of resource utilization.

[0054] At step 310, the method 300 includes generating an updated CSI representative configurations. The updated CSI representative configurations include parameters that redefine the CSI representative computation algorithm toalign with the latest feedback or measurement indicators received from the one or more UEs 110. The generation of the updated CSI representative configurations ensures that the network remains adaptive to the channel conditions changes. At step 312, the method 300 includes transmitting the updated CSI representative configurations in one or more second CSI-ReportConfig messages to the at least one of the one or more UEs 110. In operation, the base station 102, after generating the updated CSI representative configurations in response to feedback messages and analysis, includes the updated CSI representative configurations in the one or more second CSI-ReportConfig messages. The one or more second CSI-ReportConfig messages are then transmitted to the relevant UEs from the one or more UEs 110 via established communication protocols. Furthermore, the one or more UEs 110 receive and apply the updated CSI representative configurations to align with the revised network parameters. By virtue of transmitting the updated CSI representative configurations enables the network to maintain a dynamic and responsive communication between the base station 102 and the one or more UEs 110.

[0055] In accordance with an embodiment, the method 300 further comprises generating the CSI representative computation algorithm parameters as part of the initial CSI representative configurations. The CSI representative computation algorithm parameters comprise parameters relating to representation domain shapes and representation domain ranks. In an implementation, the base station 102 utilizes the predefined algorithms and network conditions to calculate the representation domain shapes and the representation domain ranks. The calculated representation domain shapes and the representation domain ranks are incorporated into the initial CSI representative configurations and then transmitted to the one or more UEs 110, thereby ensuring that the initial communication setup is aligned with the network's operational objectives and current conditions.

[0056] In accordance with an embodiment, the CSI representative computation algorithm parameters comprise at least one of the Time-domain representation shape, the Time-domain representation ranks, the Frequency-domain representation shape, the Frequency-domain representation ranks, the Receiver RX-antenna-port-domain representation shape, the Receiver RX-antenna-port-domain representation ranks, the Transmitter TX-antenna-port-domain representation shape, and the Transmitter TX-antenna-port-domain representation ranks.

[0057] In an example, the CSI representative computation algorithm parameters may include the Time-domain representation shape. In another example, the CSI representative computation algorithm parameters may include the Time-domain representation ranks. In yet another example, the CSI representative computation algorithm parameters may include the Frequency-domain representation shape. In yet another example, the CSI representative computation algorithm parameters may include the Frequency -domain representation ranks. In yet another example, the CSI representative computation algorithm parameters may include the Receiver RX-antenna-port-domain representation shape. In yet another example, the CSI representative computation algorithm parameters may include the Receiver RX-antenna-port-domain representation ranks. In yet another example, the CSI representative computation algorithm parameters may include the Transmitter TX-antenna-port-domain representation shape. In yet another example, the CSI representative computation algorithm parameters may include the Transmitter TX-antenna-port-domain representation ranks. Such parameters control how channel information is processed and represented in each domain. In an exemplary scenario, for the time domain, given M time measurements, the time-domain representation shape can be the tuple (s‘, s, s ), where M = x s x s,with corresponding ranks (r^, r^, ). where r- < s-. For example, with M = 100 OFDM symbols, a shape (5,4,5) with ranks (3,2,3) defines how temporal channel variations are captured. In another exemplary scenario, for the frequency domain, given N subcarriers, the frequency -domain representation shape (sf, s^), where N =

[0058]

[0059] sf x with ranks (r, r2f), where r- < s-, controls how frequency -related characteristics are processed. For example, with N = 60 subcarriers, a shape of (4,3,5) with ranks (3, 2, 5) defines how frequency-domain patters are handled. In another exemplary scenario, for the TX-antenna-port domain, with Nttransmit antennas shape (sjx, stx, s^x, stx). where Nt= S;xx s)xx s“ x s“. and ranks (r1tx,r2tx,ritx,r1tx). wherex< s-xdetermines transmitter-side spatial processing. For example, with Nt= 256 transmit antennas, the TX-antenna-port-domain shape might be (2,4, 8,4) with ranks (2, 2, 6, 3), enabling precise control over transmitter-side spatial processing. In another exemplary scenario, for the RX-antenna-port domain, with Nrreceive antennas shape (s['x, s2x), where Nr= s['xx s' '. and ranks (r1rx,r2rx), where r 'x< s'xdetermines receiver-side spatial processing. For example, with Nr= 16 receive antennas, the RX-antenna-port-domain shape might be (4,4) with ranks (2,3), enabling precise control over receiver-side spatial processing. At this juncture, it should be noted that the Doppler domain is equivalent to the time domain, the beam domain is equivalent to the antenna port domain, and the polarization domain is equivalent to the antenna port domain. By virtue of specifying both shapes and ranks across these domains, the network device controller 104 achieves precise control over how channel information dimensionality is reduced while preserving essential characteristics. The ranks determine how much variation each representation can capture in its respective domain, enabling optimization of the collective KPI.

[0060] In accordance with an embodiment, the method 300 further comprises performing the evaluation of the measurements by evaluating a collective KPI based on the combined impact of all received measurements on the downlink precoding efficiency, with the aim of optimizing performance at the network device and / or the UEs. In an implementation, the base station 102 utilizes predefined algorithms and network conditions to calculate the representation domain shapes and the representation domain ranks. The calculated parameters are further incorporated into the initial CSI representative configurations and then transmitted to the one or more UEs 110, which ensures that the initial communication setup is aligned with the network's operational objectives and current conditions.

[0061] Advantageously, by selecting and configuring the initial parameters for generating the CSI representative configurations, the method 300 ensures that the one or more UEs 110 begin the respective operation with well-suited configurations for the specific network environment. Moreover, the transmission of the CSI representative configurations through CSI-ReportConfig messages ensures seamless integration with existing wireless communication protocols while providing the flexibility needed for advanced parameter control. Additionally, by virtue of receiving and processing measurement indicators from the one or more UEs 110, the method 300 enables the continuous monitoring of network performance. Moreover, the feedback system allows the network to maintain an up-to-date understanding of channel conditions, signal quality, and overall communication efficiency.

[0062] The steps 302 to 312 are only illustrative, and other alternatives can also be provided where one or more steps are added, one or more steps are removed, or one or more steps are provided in a different sequence without departing from the scope of the claims herein.There is provided a computer program comprising instructions that, when executed by a computer system or the diffusion model system, cause the computer system or the diffusion model system to implement the method 300. In an example, the instructions are implemented on the computer-readable media, which include, but are not limited to, Electrically Erasable Programmable Read-Only Memory (EEPROM), Random Access Memory (RAM), Read-Only Memory (ROM), Hard Disk Drive (HDD), Flash memory, a Secure Digital (SD) card, Solid-State Drive (SSD), a computer-readable storage medium, and / or CPU cache memory. In an example, the instructions are generated by a computer program, which is implemented in view of the method 300 for the network device controller 104.

[0063] FIG. 4 is a diagram that illustrates a sequence of signalling between a base station and a UE, in accordance with an embodiment of the present disclosure. FIG. 4 is described in conjunction with the FIGs. 1 to 3. With reference to FIG. 4, there is shown the diagram 400 that includes the sequence of signalling between the base station 102 and a UE (for example the first UE 110A) from the one or more UEs 110 in the wireless network. The sequence of signalling between the base station 102 and the first UE 110A includes operations 402 to 412.

[0064] At operation 402, the base station 102 transmits the CSI-ReportConfig message containing the initialized parameters to the first UE 110A. The CSI-ReportConfig message includes the newly introduced CSI-RepresentativeConfiguration parameter along with standard configuration elements such as CSI-ReportConfigld, carrier information, and various resource allocations for channel measurement and interference assessment, enabling the first UE 110A to perform channel measurements and estimations.

[0065] At operation 404, the base station 102 transmits a CSI Reference Signal (CSI-RS) to the one or more UEs.

[0066] At operation 406, based on the received CSI-RS and CSI-ReportConfig message, including CSI representative computation algorithm parameters, the first UE 110A performs CSI representative computation and computes the CSI feedback. The process of the CSI representative computation includes estimating the downlink channel conditions and applying the received CSI representative computation algorithm parameters for computing the channel representative information. Computation of the CSI feedback can include, using the obtained channel representative for computing a PMI.

[0067] At operation 408, the first UE 110A transmits the CSI feedback to the base station 102. The CSI feedback can include and is not limited to PMI feedback that is generated after the first UE 110A performs the CSI representative computation based on the received CSI-RS measurements and the configuration parameters specified in the CSI-ReportConfig message, including the CSI representative parameters. The PMI feedback includes the information about the preferred precoding matrix that should be used for downlink transmission, which facilitates the base station 102 optimize its MIMO transmission strategies.

[0068] At operation 410, the base station 102 evaluates the overall performance and the complexity of precoding using the transmitted parameters based on the CSI feedback received from the first UE 110A, including for example thePMI feedback from the first UE 110A. The comprehensive evaluation involves analyzing multiple factors such as PMIs, signal quality, interference levels, computational resource utilization, and the collective impact on network performance. In an implementation, the base station 102 assesses the collective KPI including, the (weighted) sum or product of the individual SINR for the served UEs or the (weighted) sum of the individual rates over the served UEs or complexity, to determine the effectiveness of the current CSI representative computation algorithm configuration. Moreover, through, for example, a mapping function, the base station 102 can assess whether a different set of parameters for the CSI representative computation algorithm is required. The assessment is particularly flexible as the parameters are not necessarily uniform across all UEs depending on the chosen strategy, the base station 102 can either assign the same set of parameters to all scheduled UEs or implement distinctive parameter sets across UEs.

[0069] At operation 412, when a new set of parameters is needed, the base station 102 transmits the new CSI representative configuration through a new CSI-ReportConfig message to the first UE 110A. The updated CSI-ReportConfig message can maintain the same structure as the initial configuration message, including the CSI-RepresentativeConfiguration field, where the parameters are the newly optimized parameters. In an implementation, the channel can be described in various domains - primarily time, frequency, and spatial (antenna) domains - where representation processing operates distinctly in each domain, with each domain being defined by a subset of parameters. For a representation algorithm that aims to represent the channel through its principal components (eigenvectors and values) in each domain, where the channel in each domain is defined following a given shape, the minimum required parameters for the algorithm include time-domain representation shape and ranks, frequency -domain representation shape and ranks, receiver-antenna-port-domain representation shape and ranks, and transmitter-antenna-port-domain representation shape and ranks. The parameters are embedded in the structure of the CSI-ReportConfig message.

[0070] The antenna ports represent the channel in the spatial domain, both at the transmitter and receiver. Consider the base station 102 transmitting through / Vtantennas and the first UE 110A with / Vrantennas. For example, with lVt=256, the TX-antenna-port-domain representation shape parameter can be (2, 4, 8, 4), or (16,16), or any shape where the product of elements equals / Vt. The number of elements represents the dimensionality (i.e., the number of dimensions in that domain). Consequently, the TX-antenna-port-domain representation ranks parameter can be (2, 2, 6, 3) and (11,8) according to the shapes (2,4, 8,4) and (16,16), respectively. Each shape element has a corresponding rank that must be less than or equal to the shape element. This same logic applies to the RX-antenna-port domain; for instance, with / Vr=16, the ranks (2,4) and (7,2) corresponding to the shapes (4,4) and (8,2), respectively, are valid choices.

[0071] For implementations using OFDM, the frequency domain represents the subcarriers, while the time domain represents the OFDM symbols in time. For example, considering a channel with 100 OFDM symbols over 60 subcarriers, valid choices include the shape (15,4) with corresponding ranks (7,2) in the frequency domain, and the shape (5,4,5) with corresponding ranks (3,2,2) in the time domain. To ensure validity in each domain, the products of shape elements must equal the domain size. Thus, the input of the CSI representative computation algorithm is a multi-dimensional array with a total number of elements equal to:time_domain_shape[i] x J~^frequency_domain_shape[j] ‘ 7 x RX_antenna_port_domain_shape [ / <] x J~^ TX_antenna_port_domain_shape[l]

[0072]

[0073] k I

[0074] and the output is a multi-dimensional array with a total number of elements lower or equal to:

[0075] time _domain j~anks[i] x J~^frequency_domain_ranks[j] ‘ 7 x J^RX_antenna_port_domain_ranks[k] x J~^ TX_antenna_port_domain_ranks[l]

[0076]

[0077] k I

[0078] The final rank per domain is an additional parameter that can be considered in the context as well. For example, for a CSI representative computation algorithm whose process ends with an SVD at each domain (after processing each dimension singularly), thus a rank per domain is additionally needed, and the CSI-RepresentativeConfiguration can consider those new parameters, i.e., time-domain representation final rank, frequency-domain representation final rank, TX-antenna-port-domain representation final rank, and RX-antenna-port-domain representation final rank.

[0079] Advantageously, the signalling between the base station 102 and the one or more UE 110 enables the dynamic and adaptive CSI reporting through the introduction of the CSI-RepresentativeConfiguration parameter, allowing for flexible channel representation across multiple domains (time, frequency, and spatial). The sequence implements a feedback loop mechanism that continuously optimizes transmission parameters based on current channel conditions and communication performance. The base station 102 can evaluate and adjust the CSI representative computation algorithm parameters based on comprehensive performance metrics, including SINR, sum rate, and overall channel quality. The signalling further supports personalized parameter configuration, where the base station 102 can either implement uniform parameters across all UEs or assign distinctive parameter sets to different UEs based on their specific conditions and requirements to optimize resource utilization while maintaining communication quality.

[0080] Modifications to embodiments of the present disclosure described in the foregoing are possible without departing from the scope of the present disclosure as defined by the accompanying claims. Expressions such as "including", "comprising", "incorporating", "have", "is" used to describe and claim the present disclosure are intended to be construed in a non-exclusive manner, namely allowing for items, components or elements not explicitly described also to be present. Reference to the singular is also to be construed to relate to the plural. The word "exemplary" is used herein to mean "serving as an example, instance or illustration". Any embodiment described as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments or to exclude the incorporation of features from other embodiments. The word "optionally" is used herein to mean "is provided in some embodiments and not provided in other embodiments". It is appreciated that certain features of the present disclosure, which are, for clarity, described in the context of separate embodiments, may also be provided incombination in a single embodiment. Conversely, various features of the invention, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable combination or as suitable in any other described embodiment of the disclosure.

Claims

CLAIMS1. A network device controller (104) configured to:generate one or more initial Channel State Information, CSI, representative configuration(s) indicating parameters of a CSI representative computation algorithm,transmit the one or more initial CSI representative configuration(s) in one or more first CSI-ReportConfig message(s) to one or more User Equipment(s) (110), UEs,receive a feedback message(s) from at least one of the one or more UEs (110), the feedback message(s) comprising indicators of measurements,perform an evaluation of the measurements and decide if the CSI representative configuration(s) need(s) to be updated, and if sogenerate an updated CSI representative configuration(s) andtransmit the updated CSI representative configuration(s) in one or more second CSI-ReportConfig message(s) to the at least one of the one or more UEs (110).

2. The network device controller (104) according to claim 1, wherein the network device controller (104) is further configured togenerate CSI representative computation algorithm parameters as part of the initial CSI representative configuration(s), wherein the CSI representative computation algorithm parameters comprise parameters relating torepresentation domain shapes and representation domain ranks.

3. The network device controller (104) according to claim 2, wherein the CSI representative computation algorithm parameters comprise at least one ofTime-domain representation shape,Time-domain representation ranks,Frequency-domain representation shape,Frequency-domain representation ranks,receiver, RX-antenna-port-domain representation shape,receiver, RX- antenna-port-domain representation ranks,transmitter, TX- antenna-port-domain representation shape, andtransmitter, TX- antenna-port-domain representation ranks.

4. The network device controller (104) according to any preceding claim, wherein the network device controller (104) is further configured to perform the evaluation of the measurements by evaluating a collective key performance indicator (KPI) based on the combined impact of all received measurements on the downlink precoding efficiency, with the aim of optimizing performance at the network device and / or the UEs.

5. The network device controller (104) according to claim 4, wherein the collective KPI includes signal-to-interference-plus-noise ratio (SINR), sum rate, and overall channel quality across all of the one or more UEs (110).

6. The network device controller (104) according to claim 4 or 5, wherein the network device controller (104) is further configured toperform, as a continuous control loop, the evaluation of the measurements by evaluating a collective KPI using the received measurements for the parameters indicated in the sent CSI representative configurations, decide if the CSI representative configuration(s) need(s) to be updated byutilizing a function to assess if a different set of parameters of the CSI representative(s) algorithm is required and totransmit the updated CSI representative configuration(s) in a CSI-ReportConfig message(s).

7. The network device controller (104) according to claim 6, wherein the network device controller (104) is further configured togenerate a same set of parameters in the updated CSI representative configuration for one or more UEs (110).

8. The network device controller (104) according to any of claims 4 to 7, wherein the network device controller (104) is further configured togenerate a first set of parameters in the updated CSI representative configuration for a first subset of the one or more UEs (110) andgenerate a second set of parameters in the updated CSI representative configuration for a second subset of the one or more UEs (110).

9. The network device controller (104) according to any of claims 4 to 7, wherein the network device controller (104) is further configured togenerate one set of parameters in the updated CSI representative configuration for each of the one or more UEs (110).

10. Abase station (102) comprising the network device controller (104) according to any preceding claim.

11. A method (300) for a network device controller (104), the method (300) comprising:generating one or more initial Channel State Information, CSI, representative configuration(s) indicating parameters of a CSI representative computation algorithm,transmitting the one or more initial CSI representative configuration(s) in one or more first CSI-ReportConfig message(s) to one or more User Equipment(s), UEs (110),receiving a feedback message(s) from at least one of the one or more UEs (110), the feedback message(s) comprising indicators of measurements,continuously performing an evaluation of the measurements and decide if the CSI representative configuration(s) needs to be updated, and if sogenerating an updated CSI representative configuration(s) andtransmitting the updated CSI representative configuration(s) in one or more second CSI-ReportConfig message(s) to the at least one of the one or more UEs (110).

12. The method (300) according to claim 11, wherein the method (300) further comprisesgenerating CSI representative computation algorithm parameters as part of the initial CSI representative configuration(s), wherein the CSI representative computation algorithm parameters comprise parameters relating torepresentation domain shapes and representation domain ranks.

13. The method (300) according to claim 12, wherein the CSI representative computation algorithm parameters comprise at least one ofTime-domain representation shape,Time-domain representation ranks,Frequency-domain representation shape,Frequency-domain representation ranks,Receiver, RX-antenna-port-domain representation shape,Receiver, RX- antenna-port-domain representation ranks,Transmitter, TX- antenna-port-domain representation shape, andTransmitter, TX- antenna-port-domain representation ranks.

14. The method (300) according to any of claims 11 to 13, wherein the method (300) further comprises: performing the evaluation of the measurements by evaluating a collective key performance indicator (KPI) based on the combined impact of all received measurements on the downlink precoding efficiency, with the aim of optimizing performance at the network device and / or the UEs.

15. A computer program product comprising program instructions for performing the method according to any of claims 11 to 13, when executed by one or more processors in a network device.

Images