Device and method for variable sounding reference signal pilots density

Abstract

The present disclosure relates to entities and methods for transmitting and receiving SRSs. The disclosure proposes a network node for a wireless communication system, the network node being configured to provide configuration information to a UE. The configuration information includes an initial transmission comb parameter and a transmission resource index, which indicates a granularity for SRS transmission in the space and frequency domains. This granularity encompasses a spatial granularity associated with a bundle of antenna ports of the UE and a frequency granularity associated with sub-band sizes within a frequency band of the UE. Further, the disclosure proposes a UE being configured to receive the configuration information from the network node, accordingly.

Description

[0001] DEVICE AND METHOD FOR VARIABLE SOUNDING REFERENCE SIGNAL PILOTS DESITY

[0002] TECHNICAL FIELD

[0003] The present disclosure relates to wireless communication systems, particularly the transmission of sounding reference signal (SRS) in wireless networks. More specifically, the disclosure focuses on the efficient allocation and adaptation of SRS resources to improve channel estimation accuracy while minimizing resource overhead.

[0004] BACKGROUND

[0005] In modem wireless communication systems, such as 5G New Radio (NR) networks, Sounding Reference Signals (SRSs) play a crucial role in Time Division Duplex (TDD) enabling the next-generation NodeB (gNB) to estimate the uplink (UL) channel conditions of the user equipment (UE) and transpose this estimation for the downlink (DL) by exploiting channel reciprocity. The SRS transmissions are critical for the gNB's efficient downlink precoding and scheduling performance, as they provide essential information about the channel's frequency response.

[0006] A challenge with existing SRS frameworks, as defined by the 3rd Generation Partnership Project (3GPP) standards, lies in the allocation of orthogonal resources across a wide frequency range and multiple antenna ports for each UE. As the number of UEs in a cell increases, this requirement results in a rapid rise in SRS transmission periodicity, leading to outdated channel state information at the gNB, which can degrade the efficiency of DL scheduling and precoding.

[0007] To address these issues, prior art approaches rely on parameters defined in 3GPP TS 38.211 and TS 38.331. These technical specifications specify mechanisms for controlling the SRS resource allocation in both the time and frequency domains. The gNB communicates the number of SRS symbols (nofSymbols) and the transmission comb parameter (transmissionComb) to each UE, allowing efficient multiplexing of SRS signals across multiple UEs on the same frequency band. Furthermore, SRS signals from different antenna ports of the same UE or multiple UEs are multiplexed using Code Division Multiplexing (CDM) techniques based on Zadoff-Chu (ZC) sequences, with cyclic shifts applied to ensure signal orthogonality. However, with the current design, the SRS resource requirement increases linearly with the bandwidth and the number of antenna ports. This scaling issue becomes unsustainable as network deployments incorporate larger bandwidths and higher-layer configurations. High periodicity in SRS transmission can lead to outdated channel information at the gNB, causing suboptimal resource scheduling and reduced network performance.

[0008] Thus, there is a need for a more flexible and adaptive SRS allocation methodology that balances resource demand, computational complexity, and channel estimation accuracy to support the expanding requirements of modem networks.

[0009] SUMMARY

[0010] In view of the above, this disclosure aims to introduce a solution that enables efficient SRS transmission by dynamically selecting and adapting the transmission comb parameters and resource granularities based on the channel conditions of the UE. An objective is optimize efficiency and reduce the resource demands of SRS transmissions, particularly in scenarios involving large bandwidths and multiple antenna ports. Another objective is to enhance the precision of channel estimation by tailoring the density of SRS pilots to the UE’s real-time channel characteristics, such as delay spread and signal-to-noise ratio (SNR), thereby improving signal quality and mitigating interference in noisy or congested environments. These and other objectives are achieved by the solution of the present disclosure as provided in the enclosed independent claims. Advantageous implementations are further defined in the dependent claims.

[0011] A first aspect of the disclosure provides a network node for a wireless communication system, the network node being configured to provide configuration information to a UE. The configuration information includes an initial transmission comb parameter and a transmission resource index, which indicates a granularity for SRS transmission in the space and frequency domains. This granularity encompasses a spatial granularity associated with a bundle of antenna ports of the UE and a frequency granularity associated with sub-band sizes within a frequency band of the UE.

[0012] This disclosure proposes a solution where the network node defines how the UE’s antenna ports and frequency sub-bands should be bundled for transmitting SRS signals and provides this bundling configuration to the UE. The ability to control the granularity of SRS transmission enables: flexibility in bundling antenna ports to share transmission resources, dynamic adaptation to real-time channel conditions, enhanced spectral efficiency and reduced interference, and scalable solutions for large bandwidths and Multiple-Input Multiple-Output (MIMO) scenarios.

[0013] In an implementation form of the first aspect, the network node is configured to receive one or more SRSs from the UE based on the initial transmission comb parameter and the indicated granularity; collect channel-related information based on one or more measurements on the one or more SRSs; and determine an updated transmission comb parameter for a respective bundle of antenna ports and a respective sub-band, based on the collected channel-related information.

[0014] The network node collects channel statistics from the SRS transmissions sent by the UE or other sources and, based on this information, dynamically adjusts the transmission comb parameter configuration to optimize future transmissions. Collecting such detailed channel-related information allows the network node to optimize resource allocation dynamically, reducing the overall SRS resource demand without compromising performance.

[0015] In an implementation form of the first aspect, wherein the channel-related information includes at least one of the following information related to the UE: a delay spread, a signal-to-noise ratio, a signal-to-interference-plus-noise ratio, a covariance matrix of the UE’s channel, and a Doppler shift.

[0016] The network node can use a wide range of channel metrics collected from the UE's SRS transmissions or other means of feedback to determine the optimal SRS transmission granularity. Leveraging detailed channel statistics allows for more precise adaptation of the transmission comb parameters, ensuring efficient utilization of SRS resources.

[0017] In an implementation form of the first aspect, the network node is configured to determine the updated transmission comb parameter for each bundle of antenna ports and each sub-band using a lookup table, or an algorithm.

[0018] Possibly, the lookup table may contain precomputed mappings of transmission comb parameters to specific channel conditions (e.g., SNR, SINR, fading conditions, etc.). By leveraging precomputed mappings, the network node efficiently adjusts SRS configurations to align with changing channel conditions, ensuring optimal system performance. This also reduces computational complexity and allows for quick and adaptive updates based on predefined mappings. Alternatively, instead of a lookup table, the network node uses a mathematical algorithm or a trained neural network (NN) to compute the transmission comb parameters in real time.

[0019] In an implementation form of the first aspect, the network node is configured to notify the UE of the updated transmission comb parameter according to one of the following options: signaling indexed tuples to the UE, wherein each indexed tuple contains an index and a corresponding updated transmission comb parameter, each index mapping to a specific antenna port bundle and a sub-band; signaling all updated transmission comb parameters for all antenna port bundles and sub-bands to the UE; selecting between the previous two options based on a number of transmission comb parameters to be updated.

[0020] Notably, the network node can notify the UE of the updated transmission comb parameters through multiple methods. Offering multiple methods of updating transmission comb configuration increases flexibility in how updates are communicated, ensuring quick and efficient adaptation to new channel conditions without wasting resources.

[0021] In an implementation form of the first aspect, the network node is configured to select the first option if NbLB < I(Nb+ [log2LB')]'), wherein Nbis a number of bits required to encode a transmission comb parameter, LB is a number of the indices, and I is the number of transmission comb parameters to be updated.

[0022] This configuration ensures the signaling approach is dynamically optimized for the scenario, balancing the trade-off between signaling efficiency and resource constraints.

[0023] In an implementation form of the first aspect, the network node is configured to notify the UE of the updated transmission comb parameters using a downlink control information, (DCI) field of a Physical Downlink Control Channel (PDCCH), or a reconfiguration command for radio resource control (RRC).

[0024] This ensures compatibility with existing 3GPP standards and facilitates seamless integration into 5G systems or futher communication systems.

[0025] In an implementation form of the first aspect, the network node is configured to periodically or dynamically adjust the transmission comb parameter based on real-time or ongoing channel measurements.

[0026] Optionally, ongoing adaptation allows the system to maintain optimal performance in the face of fluctuating channel conditions.

[0027] A second aspect of the disclosure provides a UE for a wireless communication system. The UE is configured to receive configuration information from a network node, wherein the configuration information comprises an initial transmission comb parameter and a transmission resource index, wherein the transmission resource index indicates a granularity for SRS transmission in the space and frequency domains, wherein the granularity includes: a spatial granularity associated with a bundle of antenna ports of the UE, and a frequency granularity associated with a size of sub-bands within a frequency band of the UE.

[0028] In this aspect of the disclosure, the UE receives and interprets the configuration information to determine how its antenna ports and sub-bands should be bundled for SRS transmission. This enables efficient utilization of available resources by transmitting SRSs according to the indicated granularity, compatibility with dynamic updates from the network node, ensuring adaptability to changing channel conditions, and reduced computational complexity through predefined mappings.

[0029] In an implementation form of the second aspect, the UE is configured to determine the spatial granularity and the frequency granularity for the SRS transmission using a predefined mapping table, wherein the predefined mapping table associates each transmission resource index with a corresponding bundle of antenna ports, and a corresponding size of sub-bands. The UE uses a predefined mapping table to interpret the transmission resource index and determine spatial and frequency granularities for SRS transmission. Predefined mappings simplify the UE’s operations by standardizing granularity determination, allowing for efficient and consistent interpretation of configuration parameters without extensive computations.

[0030] In an implementation form of the second aspect, the UE is configured to transmit one or more SRSs to the network node based on the initial transmission comb parameter, the determined spatial granularity and the frequency granularity.

[0031] The transmission of SRSs aligned with the configured granularity ensures accurate channel measurements with minimal resource usage.

[0032] In an implementation form of the second aspect, the UE is configured to obtain a notification from the network node regarding one or more updated transmission comb parameters, wherein each updated transmission comb parameter corresponds to a respective bundle of antenna ports and a respective sub-band, wherein the notification comprises: indexed tuples, each containing an index and a corresponding updated transmission comb parameter, with each index mapping to a specific antenna port bundle and sub-band, or all updated transmission comb parameters for all antenna port bundles and sub-bands to the UE.

[0033] The UE can receive an updated transmission comb parameter configuration from the gNB as needed, ensuring that its SRS transmission remains optimized for the channel conditions. This allows the UE to adapt to changing channel environments in real-time, enhancing the quality of the SRS signal and the overall communication link.

[0034] In an implementation form of the second aspect, the UE is configured to receive the notification through a DCI field of a PDCCH, or a reconfiguration command for RRC.

[0035] Multiple methods for receiving the updated transmission comb parameter provide flexibility and ensure that the UE can quickly adapt its SRS transmission. It also provides compatibility with existing signaling channels, thereby ensuring seamless integration into current wireless communication systems.

[0036] In an implementation form of the second aspect, the UE is configured to transmit one or more updated SRSs using the updated transmission comb parameters to the network node.

[0037] Once the updated transmission comb parameter is received, the UE adjusts its SRS transmission accordingly and transmits using the new configuration. This allows for continuous optimization of the SRS transmissions, ensuring that they are always aligned with the current channel conditions and minimizing interference or resource inefficiency.

[0038] A third aspect of the disclosure provides a method performed by a network node for a wireless communication system, comprising: providing configuration information to the UE, wherein the configuration information comprises an initial transmission comb parameter and a transmission resource index, wherein the transmission resource index indicates a granularity for SRS transmission in the space and frequency domains, wherein the granularity includes: a spatial granularity associated with a bundle of antenna ports of the UE, and a frequency granularity associated with a size of sub-bands within a frequency band of the UE.

[0039] Implementation forms of the method of the third aspect may correspond to the implementation forms of the network node of the first aspect described above. The method of the third aspect and its implementation forms achieve the same advantages and effects as described above for the network node of the first aspect and its implementation forms. A fourth aspect of the disclosure provides a method performed by a UE for a wireless communication system, comprising: receiving configuration information from a network node, wherein the configuration information comprises an initial transmission comb parameter and a transmission resource index, wherein the transmission resource index indicates a granularity for SRS transmission in the space and frequency domains, wherein the granularity includes: a spatial granularity associated with a bundle of antenna ports of the UE, and a frequency granularity associated with a size of sub-bands within a frequency band of the UE.

[0040] Implementation forms of the method of the fourth aspect may correspond to the implementation forms of the UE of the second aspect described above. The method of the fourth aspect and its implementation forms achieve the same advantages and effects as described above for the UE of the second aspect and its implementation forms.

[0041] A fifth aspect of the disclosure provides a computer program product comprising a program code for carrying out, when implemented on a processor, the method according to the third aspect and any implementation forms of the third aspect, or the fourth aspect and any implementation forms of the fourth aspect.

[0042] It has to be noted that all devices, elements, units and means described in the present application could be implemented in 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 which 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.

[0043] BRIEF DESCRIPTION OF DRAWINGS

[0044] The above-described aspects and implementation forms of the present disclosure will be explained in the following description of specific embodiments in relation to the enclosed drawings, in which:

[0045] FIG. 1 shows a network entity according to an embodiment of the disclosure;

[0046] FIG. 2 shows a UE according to an embodiment of the disclosure;

[0047] FIG. 3 shows current procedure to transmit SRS in the uplink;

[0048] FIG. 4 shows an example of message exchanges between gNB and UE according to an embodiment of the disclosure;

[0049] FIG. 5 shows a method according to an embodiment of the disclosure; and

[0050] FIG. 6 shows a method according to an embodiment of the disclosure. DETAILED DESCRIPTION OF EMBODIMENTS

[0051] Illustrative embodiments of a network node, a UE and corresponding methods are described with reference to the figures. Although this description provides a detailed example of possible implementations, it should be noted that the details are intended to be exemplary and in no way limit the scope of the application.

[0052] Moreover, an embodiment or example may refer to other embodiments or examples. For example, any description including but not limited to terminology, element, process, explanation, and / or technical advantage mentioned in one embodiment / example is applicative to the other embodiments or examples.

[0053] FIG. 1 shows a network node 100 adapted for a wireless communication system according to an embodiment of the disclosure. The network node 100 is configured to provide configuration information 101 to a UE 200, wherein the configuration information 101 comprises an initial transmission comb parameter and a transmission resource index: In particular, the transmission resource index indicates a granularity for SRS transmission in the space and frequency domains, wherein the granularity includes: a spatial granularity associated with a bundle of antenna ports of the UE, and a frequency granularity associated with a size of sub-bands within a frequency band of the UE.

[0054] The network node 100 may comprise processing circuitry (not shown) configured to perform, conduct or initiate the various operations of the network node 100 described herein. The processing circuitry may comprise hardware and software. The hardware may comprise analog circuitry or digital circuitry, or both analog and digital circuitry. The digital circuitry may comprise components such as application-specific integrated circuits (ASICs), field-programmable arrays (FPGAs), digital signal processors (DSPs), or multi-purpose processors. The network node 100 may further comprise memory circuitry, which stores one or more instruction(s) that can be executed by the processor or by the processing circuitry, in particular under the control of the software. For instance, the memory circuitry may comprise a non-transitory storage medium storing executable software code which, when executed by the processor or the processing circuitry, causes the various operations of the network node 100 to be performed. In one embodiment, the processing circuitry comprises one or more processors and a non-transitory memory connected to the one or more processors. The non-transitory memory may carry executable program code which, when executed by the one or more processors, causes network node 100 to perform, conduct or initiate the operations or methods described herein.

[0055] It may be understood that this network node forms part of the wireless communication infrastructure, such as a gNB in a 5G or beyond network, capable of supporting downlink and uplink communications.

[0056] This disclosure proposes methods and systems for enabling adaptive and variable SRS pilot density for SRS transmission in a wireless communication system. The network node 100 is responsible for configuring and updating the SRS pilot density used by the UE 200 for SRS transmission. The network node 100 can dynamically adapt these configurations based on real-time channel conditions to optimize communication performance.

[0057] In one implementation, the network node 100 collects channel-related information based on measurements from the SRS transmissions sent by the UE 200. This information includes, but is not limited to, a delay spread, a SNR, SINR, a covariance matrix of the UE 200’s channel, and a Doppler shift. Using these statistics, the network node 100 can determine the optimal transmission comb parameter for a respective bundle of antenna ports and a respective sub-band of the UE 200 to improve the accuracy of channel estimation and transmission efficiency. In a further implementation, if the channel conditions change, the network node 100 can determine the updated transmission comb parameter for each bundle of antenna ports and each sub-band using a look up table, or an algorithm. When the transmission comb parameter needs to be updated, the network node 100 notifies the UE 200 of this updated configuration. The notification can be provided via DCI, or a RRC reconfiguration message.

[0058] FIG. 2 illustrates a UE 200 according to an embodiment of this disclosure, which is configured to receive configuration information 101 from a network node 100. The configuration information 101 comprises an initial transmission comb parameter and a transmission resource index: In particular, the transmission resource index indicates a granularity for SRS transmission in the space and frequency domains, wherein the granularity includes: a spatial granularity associated with a bundle of antenna ports of the UE, and a frequency granularity associated with a size of sub-bands within a frequency band of the UE 200.

[0059] The UE 200 may comprise processing circuitry (not shown) configured to perform, conduct or initiate the various operations of the UE 200 described herein. The processing circuitry may comprise hardware and software. The hardware may comprise analog circuitry or digital circuitry, or both analog and digital circuitry. The digital circuitry may comprise components such as ASICs, FPGAs, DSPs, or multi-purpose processors. The UE 200 may further comprise memory circuitry, which stores one or more instructions) that can be executed by the processor or by the processing circuitry, in particular under the control of the software. For instance, the memory circuitry may comprise a non-transitory storage medium storing executable software code which, when executed by the processor or the processing circuitry, causes the various operations of the UE 200 to be performed. In one embodiment, the processing circuitry comprises one or more processors and a non-transitory memory connected to the one or more processors. The non-transitory memory may carry executable program code which, when executed by the one or more processors, causes the UE 200 to perform, conduct or initiate the operations or methods described herein.

[0060] This disclosure further describes a UE 200 responsible for receiving the configuration from the network node 100, determining the spatial granularity and the frequency granularity for the SRS transmission based on the received information, and transmitting the SRS following the determined spatial granularity and the frequency granularity.

[0061] In a further implementation, based on the received configuration information 101 , the UE 200 determines the spatial granularity and the frequency granularity for the SRS transmission using a predefined mapping table. The predefined mapping table associates each transmission resource index with a corresponding bundle of antenna ports, and a corresponding size of subbands.

[0062] Optionally, if the network node 100 determines a new transmission comb parameter setting for the UE 200, the UE can obtain a notification from the network node 100 regarding one or more updated transmission comb parameters, wherein each updated transmission comb parameter corresponds to a respective bundle of antenna ports and a respective sub-band. The notification may be received through one of the following methods: DCI signaling, or an RRC reconfiguration command.

[0063] Optionally, the notification may include indexed tuples, each containing an index and a corresponding updated transmission comb parameter, with each index mapping to a specific antenna port bundle and sub-band. Alternatively, the notification may include all updated transmission comb parameters for all antenna port bundles and sub-bands to the UE.

[0064] Once the updated transmission comb parameter is received, the UE 200 may adjust its SRS transmission parameters according to the transmission comb parameter.

[0065] FIG. 3 illustrates the current procedure to transmit SRS in the uplink according to SRS-Re sourceConfig information. It can be described as follows: Step 1. SRS-ResourceConfig Transmission:

[0066] The gNB (network node) communicates the SRS-ResourceConfig to the UE via the RRC protocol, as defined in 3GPP TS 38.331, clause 6.2.3. The SRS-ResourceConfig includes parameters such as: nofSymbols, transmissionComb as shown in Table 1.

[0067] Notably, transmissionComb specifies the density of SRS pilots in the frequency domain. For example: a transmissionComb of 2 means the UE transmits pilots in every second resource element (RE), a transmissionComb of 4 or 8 corresponds to every fourth or eighth RE, respectively. This configuration ensures efficient pilot allocation and enables multiplexing of multiple UEs by varying the starting frequency index.

[0068] Table 1

[0069] Step 2. UL Data and SRS Transmission:

[0070] After receiving the SRS-ResourceConfig, the UE transmits uplink data alongside the configured SRS signals. The SRS signals are transmitted with the frequency domain granularity defined by the transmissionComb parameter.

[0071] Step 3. Channel Estimation by gNB:

[0072] The gNB uses the received SRS to estimate the channel conditions.

[0073] Step 4. Pre-Coder Calculation:

[0074] Based on the channel estimation, the gNB computes an appropriate pre-coder to optimize downlink transmissions for the UE.

[0075] Step 5. Downlink Transmission and Configuration Update:

[0076] Step 5a: The gNB sends pre-coded downlink data to the UE based on the calculated pre-coder.

[0077] Step 5b: If needed, the gNB updates the SRS configuration by transmitting updated parameters (including a new transmissionComb) using a DCI field in the PDCCH. In the existing design, the transmissionComb parameter is applied globally across all sub-bands and antenna ports of the UEs. It is not possible to select different transmissionComb values for different sub-band regions or antenna port groups. This uniform approach does not take into account the varying channel conditions (e.g., SNR, delay spread) across different subbands or antenna ports related to different UEs, potentially leading to suboptimal performance.

[0078] The transmissionComb parameter is treated as semi-static, meaning it is rarely updated during the course of operation. This restricts its ability to adapt dynamically to real-time channel conditions. Consequently, the system cannot optimize SRS configurations in response to changing environments, such as variations in Doppler shift or interference levels.

[0079] Since the same transmissionComb is applied across the entire bandwidth and all antenna ports, the system may allocate SRS pilots inefficiently. For example, sub-bands or antenna ports experiencing high SNR may not require dense pilot configurations, leading to unnecessary overhead. Conversely, regions with low SNR may require a denser pilot configuration to ensure accurate channel estimation, which the static transmissionComb cannot provide.

[0080] The inability to adapt transmissionComb to specific sub-bands or antenna ports limits the granularity of channel estimation. For the same number of SRS pilots, the current framework cannot fully exploit the diversity in channel conditions, resulting in reduced spectral efficiency and degraded communication performance.

[0081] FIG. 4 illustrates a proposed procedure for dynamically selecting and adapting the transmissionComb parameter across subbands and antenna ports to optimize SRS transmission. This approach leverages the insight that different combinations of channel statistics — such as SNR and DS — require varying pilot densities to achieve optimal channel estimation performance. By tailoring the transmissionComb parameter to these conditions, the system achieves superior channel estimation while maintaining the same number of SRS pilots.

[0082] The procedure relies on a a transmission resource index, or namely a TransmissionComb Granularity Index (TCGI), which enables flexibility in configuring SRS transmissions. The TCGI specifies the granularity of SRS transmission in both the spatial (antenna port bundling) and frequency (sub-band size) domains. It allows the gNB to assign different pilot densities for each sub-band and antenna port bundle, reflecting the specific channel conditions. It also supports dynamic updates, ensuring the transmissionComb parameter adapts to real-time variations in network conditions.

[0083] The steps depicted in FIG. 4 outline the following process:

[0084] 0. Configuration of TCGI:

[0085] The network node 100, e.g., gNB, sends an SRS-ResourceConfig message, i.e., the configuration information 101 as shown in FIG. 1 or 2, to the UE 200, which includes the TCGI. The network node 100 may be the network node shown in FIG. 1, and the UE 200 may be the UE shown in FIG. 2. This index specifies the space and frequency granularity for SRS transmission, enabling the UE to determine: the size of sub-bands (e.g., per Resource Block, Precoding Resource Block, or Bandwidth Part), and the bundling of antenna ports (e.g., unbundled, paired, or grouped).

[0086] 1. Initial SRS Transmission:

[0087] The UE 200 determines the space and frequency (i.e., layer I and sub-band bw) granularity based on a granularity mapping table.

[0088] 2. Initial SRS Transmission: The UE 200 transmits SRS signals 102 according to the initial SRS-ResourceConfig, adhering to the granularity defined by the TCGI.

[0089] 3. Channel Statistics Estimation:

[0090] The gNB estimates relevant channel statistics from the received SRS, including: DS, SNR, Covariance matrix of the channel, and Doppler shift and SINR. These measurements are made per sub-band and antenna port bundle.

[0091] 4. Mapping Optimal TransmissionComb:

[0092] Based on the channel statistics, the gNB looks up a precomputed table to determine the optimal transmissionComb parameter ki, for each layer I and sub-band bw. For example, the table is derived from simulations and maps channel statistics such as DS and SNR to the ideal pilot density.

[0093] 5. Updating TransmissionComb:

[0094] The gNB communicates the updated transmissionComb 103 (fcp>) for each antenna port bundle p and sub-band bw to the UE. This ensures that SRS configurations align with current channel conditions.

[0095] 6. UE Adaptation:

[0096] Upon receiving the updated configuration, i.e., the updated transmissionComb 103, the UE 200 adjusts its SRS transmission to the new transmissionComb fcp„ adapting both frequency and spatial pilot densities.

[0097] 7. Transmission with New Configuration:

[0098] The UE 200 transmits SRS using the updated transmissionComb, enabling the gNB to achieve improved channel estimation accuracy while minimizing resource usage.

[0099] This procedure shown in FIG. 4 overcomes the limitations of prior art (as shown in FIG. 3) by:

[0100] Enabling variable pilot densities for different sub-bands and antenna ports, improving channel estimation for the same number of SRS pilots.

[0101] Dynamically adapting configurations to real-time channel statistics, enhancing system efficiency and spectral utilization.

[0102] Supporting scalable and flexible operation for large bandwidths and multi-layer MIMO systems.

[0103] By incorporating the TCGI and dynamic transmissionComb adaptation, the proposed solution provides a more efficient and adaptable framework for SRS transmission in advanced wireless communication systems.

[0104] All embodiments of the present disclosure align with the 5G Radio Access Network (RAN) architecture as defined by the 3GPP standards, specifically those documented in TS 38.211 and TS 38.331. These embodiments focus on enhancements and modifications related to the RRC protocol for configuring SRS and the generation of SRS signals.

[0105] Furthermore, all embodiments are designed to seamlessly integrate within the established 5G RAN framework, aligning with and extending existing specifications. This ensures compatibility with current systems and facilitates effortless adaptation to future advancements in 5G technology.

[0106] The SRS-ResourceConfig message, as outlined in Clause 6.2.3 of TS 38.331, is extended in this disclosure to include the TCGI and its related configurations. This enhancement ensures that the UE can efficiently determine the spatial and frequency granularity for SRS transmission. Clause 6.4.1.4 of TS 38.211 outlines the framework for SRS generation. The proposed embodiments adapt this framework to allow for variable pilot densities across sub-bands and antenna ports, improving channel estimation accuracy and spectral efficiency.

[0107] In one implementation, the TCGIindex may be included in the SRS-ResourceSet Information Element (IE), which is part of the SRS-Config IE and can be configured or reconfigured based on changing channel conditions. One example to encode this information into the SRS-Config IE using ASN.1 encoding is as follows:

[0108] The TCGIindex field specifies the index for the granularity configuration. This enables the UE to determine both the spatial and frequency granularities using a predefined mapping table, ensuring the UE transmits SRS according to the TCGI. Encoding the TCGI within the SRS-Config message ensures compatibility with existing RRC protocols while supporting efficient signaling of complex SRS configurations.

[0109] As part of the procedure (step 4) shown in FIG. 4, the network node 100 selects the optimal TransmissionComb based on the UE’s channel conditions, including parameters such as DS and SNR. The network node 100 can use a lookup table to map these channel conditions to a specific TransmissionComb for a respective sub-band and a respective set of antenna ports of the UE. An example of such a table is provided below :

[0110] Table 2: Example of look-up table mapping DS and SNR to an optimal transmissionComb parameter

[0111] Such a table can be generated through either measurement campaigns or simulations and provides a way to select the optimal transmissionComb based on real-time channel characteristics.

[0112] According to a further embodiment of this disclosure, the updated transmissionComb can be communicated to the UE 200 using one of the following methods: Option 1 : Indexed Tuples

[0113] In this option, the gNB communicates tuples (i, / <,■). where: i is an index, fc;is the transmissionComb parameter associated with that index. A predefined mapping between i and (p, fcfcw) allows the UE to derive the corresponding antenna port bundle and sub-band. This option provide efficient for scenarios with sparse updates since only the indices and corresponding fc;values need to be transmitted.

[0114] Option 2: Full Set Communication

[0115] The gNB communicates the entire set of kp bwparameters k0,... , kPB, where P is the number of antenna port bundles and B is the number of sub-bands. This option ensures all updated transmissionComb parameters are available at the UE, but it may incur higher signaling overhead.

[0116] Option 3: Conditional Selection

[0117] A hybrid approach where the gNB selects between Option 1 (indexed tuples) and Option 2 (full set communication) based on the number of updates required. The decision is based on the following condition: NbLB < l(Nb+ [ log2(LB)]), where

[0118] • Nb: Number of bits to encode the transmissionComb parameter (typically 2 bits).

[0119] • LB : Number of indices.

[0120] • I Number of transmissionComb parameters to be updated.

[0121] This option requires an extra bit to indicate whether Option 1 or Option 2 is selected. It optimizes signaling overhead based on the number of updates, providing a balance between efficiency and completeness.

[0122] This flexible communication strategy ensures that the UE 200 can quickly adapt its SRS transmission configuration in response to changing channel conditions, allowing the system to maintain optimal performance across a wide range of environments.

[0123] According to a further embodiment of this disclosure, the UE 200 can optimize its SRS transmission configuration dynamically based on the configuration provided by the gNB. The TCGI is an index that uniquely identifies: a sub-band Size, and antenna port bundling.

[0124] The sub-band size refers to the size of the frequency sub-band over which the SRS pilots are transmitted. Sub-band sizes can be defined at various granularities, such as:

[0125] Resource Block (RB): the smallest unit of frequency in 5G, typically spanning 12 subcarriers.

[0126] Precoding Resource Block (PRE): a group of RBs defined for specific precoding purposes.

[0127] Bandwidth Part (BWP): A larger unit that aggregates multiple PRBs or RBs within the allocated spectrum.

[0128] Antenna Port Bundling represents the way antenna ports are bundled together for SRS transmission. For example: Unbundled: Each transmissionComb parameter corresponds to a single antenna port.

[0129] Paired Bundle: Two consecutive antenna ports (e.g., Port 0 and Port 1) are bundled together under one transmissionComb parameter, or two non-consecutive antenna ports (e.g., Port 0 and Port 2) are bundled together under one transmissionComb parameter, offering additional flexibility to optimize SRS transmission based on antenna-specific conditions.

[0130] Grouped: All four antenna ports are bundled together, meaning one transmissionComb parameter applies to all four ports. According to a further embodiment of this disclosure, the mapping process allows the UE to interpret the TCGI and determine its SRS configuration. In particular, the UE uses a predefined mapping table as Table 3 to interpret the TCGI and derive the corresponding spatial and frequency granularity.

[0131] Table 3: Example of table mapping TCGI to sub-band size and port bundling

[0132] Notably, Table 3 merely presents an example, it can be expanded to include different altervatives for the 2 ports situations. By allowing custom bundling options (e.g., consecutive and non-consecutive antenna ports), the system can tailor SRS pilot density to specific network and channel conditions.

[0133] Based on the TCGI mapping, the UE 200 determines the sub-band size (e.g., 1 RB, 2 RBs, 1 PRE), and determines the spatial granularity (e.g., single port, paired ports, or all four ports bundled). Using the derived granularity, the UE 200 configures its SRS transmission to match the specified sub-band size and antenna port bundling. For example, if the TCGI specifies 2 RBs and all four antenna ports bundled, the UE 200 transmits SRS pilots across 2 RBs with all antenna ports sharing the same transmissionComb parameter.

[0134] If the network conditions change (e.g., due to variations in SNR or delay spread), the gNB may send an updated TCGI to the UE 200. The UE 200 uses the updated TCGI to reconfigure its SRS transmission dynamically, ensuring optimal pilot density and resource allocation.

[0135] By enabling the mapping of TCGI to sub-band size and antenna port bundling, this invention provides a robust and flexible mechanism for optimizing SRS transmission in 5G systems, ensuring efficient resource utilization and high channel estimation accuracy across diverse network scenarios.

[0136] FIG. 5 shows a method 500 according to an embodiment of the disclosure. In a particular embodiment, the method 500 is performed by a network node 100 for a wireless communication system shown in FIG. 1, FIG. 2, or FIG. 4. The method 500 comprises a step 501 of providing configuration information 101 to the UE 200, wherein the configuration information 101 comprises an initial transmission comb parameter and a transmission resource index, wherein the transmission resource index indicates a granularity for SRS transmission in the space and frequency domains, wherein the granularity includes: a spatial granularity associated with a bundle of antenna ports of the UE, and a frequency granularity associated with a size of sub-bands within a frequency band of the UE. Possibly, the UE 200 are the UE shown in FIG. 1, FIG. 2, or FIG. 4. FIG. 6 shows a method 600 according to an embodiment of the disclosure. In a particular embodiment, the method 600 is performed by the UE 200 for a wireless communication system shown in FIG. 1 , FIG. 2, or FIG. 4. The method 600 comprises a step 601 of receiving configuration information 101 from a network node 100, wherein the configuration information 101 comprises an initial transmission comb parameter and a transmission resource index, wherein the transmission resource index indicates a granularity for SRS transmission in the space and frequency domains, wherein the granularity includes: a spatial granularity associated with a bundle of antenna ports of the UE, and a frequency granularity associated with a size of sub-bands within a frequency band of the UE. Possibly, the network node 100 is the network node for a wireless communication system shown in FIG. 1, FIG. 2, or FIG. 4.

[0137] To summarize, the embodiments described herein demonstrate how the present disclosure extends and optimizes the 5G RAN architecture by introducing dynamic SRS adaptation. The network node 100 can select among different configurations of subband size and antenna ports bundling for optimal balance between performance and feedback requirements for UEs. Further, transmissionComb can be adapted for optimal performance in terms of channel estimation error without increasing the total number of pilots SRS.

[0138] The present disclosure has been described in conjunction with various embodiments as examples as well as implementations. However, other variations can be understood and effected by those persons skilled in the art and practicing the claimed embodiments of the disclosure, from the studies of the drawings, this disclosure and the independent claims. In the claims as well as in the description the word “comprising” does not exclude other elements or steps and the indefinite article “a” or “an” does not exclude a plurality. A single element or other unit may fulfill the functions of several entities or items recited in the claims. The mere fact that certain measures are recited in the mutual different dependent claims does not indicate that a combination of these measures cannot be used in an advantageous implementation.

[0139] Furthermore, any method according to embodiments of the disclosure may be implemented in a computer program, having code means, which when run by processing means causes the processing means to execute the steps of the method. The computer program is included in a computer-readable medium of a computer program product. The computer-readable medium may comprise essentially any memory, such as a ROM (Read-Only Memory), a PROM (Programmable Read-Only Memory), an EPROM (Erasable PROM), a Flash memory, an EEPROM (Electrically Erasable PROM), or a hard disk drive.

[0140] Moreover, it is realized by the skilled person that embodiments of the network node 100, or the UE 200, comprise the necessary communication capabilities in the form of e.g., functions, means, units, elements, etc., for performing the solution. Examples of other such means, units, elements, and functions are: processors, memory, buffers, control logic, encoders, decoders, rate matchers, de-rate matchers, mapping units, multipliers, decision units, selecting units, switches, interleavers, de-interleavers, modulators, demodulators, inputs, outputs, antennas, amplifiers, receiver units, transmitter units, DSPs, trellis-coded modulation (TCM) encoder, TCM decoder, power supply units, power feeders, communication interfaces, communication protocols, etc. which are suitably arranged together for performing the solution.

[0141] Especially, the processor(s) of the network node 100, or the UE 200 may comprise, e.g., one or more instances of a Central Processing Unit (CPU), a processing unit, a processing circuit, a processor, an Application Specific Integrated Circuit (ASIC), a microprocessor, or other processing logic that may interpret and execute instructions. The expression “processor” may thus represent a processing circuitry comprising a plurality of processing circuits, such as, e.g., any, some or all of the ones mentioned above. The processing circuitry may further perform data processing functions for inputting, outputting, and processing of data comprising data buffering and device control functions, such as call processing control, user interface control, or the like.

Claims

CLAIMS1. A network node (100) for a wireless communication system, the network node (100) being configured to: provide configuration information (101) to the UE (200), wherein the configuration information (101) comprises an initial transmission comb parameter and a transmission resource index, wherein the transmission resource index indicates a granularity for sounding reference signal, SRS, transmission in the space and frequency domains, wherein the granularity includes: a spatial granularity associated with a bundle of antenna ports of the UE, and a frequency granularity associated with a size of sub-bands within a frequency band of the UE.

2. The network node (100) according to claim 1, configured to: receive one or more SRSs (102) from the UE (200) based on the initial transmission comb parameter and the indicated granularity; collect channel-related information based on one or more measurements on the one or more SRSs; and determine an updated transmission comb parameter (103) for a respective bundle of antenna ports and a respective sub-band, based on the collected channel-related information.

3. The network node (100) according to claim 2, wherein the channel-related information includes at least one of the following information related to the UE (200): a delay spread, a signal-to-noise ratio, a signal-to-interference-plus-noise ratio, a covariance matrix of the UE (200)’s channel, and a Doppler shift.

4. The network node (100) according to claims 2 or 3, configured to: determine the updated transmission comb parameter (103) for each bundle of antenna ports and each sub-band using a look up table, or an algorithm.

5. The network node (100) according to one of the claims 2 to 4, configured to: notify the UE (200) of the updated transmission comb parameter (103) according to one of the following options: signaling indexed tuples to the UE, wherein each indexed tuple contains an index and a corresponding updated transmission comb parameter, each index mapping to a specific antenna port bundle and a sub-band; signaling all updated transmission comb parameters for all antenna port bundles and sub-bands to the UE; selecting between the previous two options based on a number of transmission comb parameters to be updated.

7. The network node (100) according to one of the claims 2 to 6, configured to: notify the UE (200) of the updated transmission comb parameters (103) using a downlink control information, DCI, field of a Physical Downlink Control Channel, PDCCH, or a reconfiguration command for radio resource control.

8. The network node (100) according to claims 2 to 7, configured to: periodically or dynamically adjust the transmission comb parameter based on real-time or ongoing channel measurements.

9. A user equipment, UE (200), for a wireless communication system, the UE (200) being configured to:receive configuration information (101) from a network node (100), wherein the configuration information (101) comprises an initial transmission comb parameter and a transmission resource index, wherein the transmission resource index indicates a granularity for sounding reference signal, SRS, transmission in the space and frequency domains, wherein the granularity includes: a spatial granularity associated with a bundle of antenna ports of the UE, and a frequency granularity associated with a size of sub-bands within a frequency band of the UE.

10. The UE (200) according to claim 9, configured to: determine the spatial granularity and the frequency granularity for the SRS transmission using a predefined mapping table, wherein the predefined mapping table associates each transmission resource index with a corresponding bundle of antenna ports, and a corresponding size of sub-bands.

11. The UE (200) according to claim 10, configured to: transmit one or more SRSs (102) to the network node (100) based on the initial transmission comb parameter, the determined spatial granularity and the frequency granularity.

12. The UE (200) according to one of the claims 9 to 11, configured to: obtain a notification from the network node (100) regarding one or more updated transmission comb parameters (103), wherein each updated transmission comb parameter (103) corresponds to a respective bundle of antenna ports and a respective sub-band, wherein the notification comprises: indexed tuples, each containing an index and a corresponding updated transmission comb parameter (103), with each index mapping to a specific antenna port bundle and sub-band, or all updated transmission comb parameters (103) for all antenna port bundles and sub-bands to the UE.

13. The UE (200) according to claim 12, configured to: receive the notification through a downlink control information, DCI, field of a Physical Downlink Control Channel, PDCCEI, or a reconfiguration command for radio resource control.

14. The UE (200) according to claim 12 or 13, configured to: transmit one or more updated SRSs using the updated transmission comb parameters to the network node (100).

15. A method (500) performed by a network node (100) for a wireless communication system, comprising: providing (501) configuration information (101) to the UE (200), wherein the configuration information (101) comprises an initial transmission comb parameter and a transmission resource index, wherein the transmission resource index indicates a granularity for sounding reference signal, SRS, transmission in the space and frequency domains, wherein the granularity includes: a spatial granularity associated with a bundle of antenna ports of the UE, and a frequency granularity associated with a size of sub-bands within a frequency band of the UE.

16. A method (600) performed by a user equipment, UE (200), for a wireless communication system, comprising: receiving (601) configuration information (101) from a network node (100), wherein the configuration information(101) comprises an initial transmission comb parameter and a transmission resource index, wherein the transmission resource index indicates a granularity for sounding reference signal, SRS, transmission in the space and frequency domains, wherein the granularity includes: a spatial granularity associated with a bundle of antenna ports of the UE, and a frequency granularity associated with a size of sub-bands within a frequency band of the UE.

17. A computer program product comprising a program code for carrying out, when implemented on a processor, the method (500, 600) according to claim 15 or 16.

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