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CN-122003817-A - Apparatus and method for beamforming for downlink data transmission in a wireless communication system

CN122003817ACN 122003817 ACN122003817 ACN 122003817ACN-122003817-A

Abstract

The present disclosure relates to 5G or 6G communication systems for supporting higher data transmission rates. A method includes a base station transmitting configuration information including CSI configuration, the base station also transmitting (e.g., periodically) CSI-RS from all its CSI antenna ports, a user equipment performing measurements for the received CSI-RS, after receiving CSI feedback indications from the base station, the user equipment performing calculations based on the performed measurements and the received configuration to generate CSI.

Inventors

  • ALEXEI VLADIMIROVICH DAVYDOV
  • GREGORY VLADIMIROVICH MOROZOV
  • Dennis Viktorovich Ye Xiuning
  • Dmitry Sergeyevich Dicarev
  • Gregory Alexandrovich Yermolayev
  • Maxim Viktorovich Ye Xiuning
  • Vladimir Alexandrovich Pestlezov

Assignees

  • 三星电子株式会社

Dates

Publication Date
20260508
Application Date
20240528
Priority Date
20231018

Claims (15)

  1. 1.A method performed by a user equipment, UE, supporting beamforming in a wireless communication system, the method comprising: receiving configuration information about channel state information, CSI, from a base station, the configuration information including parameters of a codebook and a parameter N DFT indicating a maximum number of discrete fourier transform, DFT, vectors with one signal polarization in a precoding matrix; receiving CSI reference signal CSI-RS from base station, and Based on the received CSI-RS, transmitting CSI to the base station, the CSI comprising at least one of a rank indicator RI and a precoding matrix indicator PMI of a number L of selected multiple-input multiple-output MIMO layers.
  2. 2. The method of claim 1, further comprising: selecting the number L of MIMO layers; In the case of L≤N DFT , by generating L precoding vectors using L different DFT vectors, each employing one signal polarization, In the case of N DFT < L ≤ 2N DFT , N DFT precoding vectors are generated by using N DFT different DFT vectors, each DFT vector employing one signal polarization and another N next precoding vectors are generated by N next DFT vectors of the N DFT DFT vectors, wherein N next = L - N DFT , each of the N next DFT vectors employing a signal polarization different from the one signal polarization that the DFT vector has used in the precoding matrix, or In the case of L > 2N DFT , generating L precoding vectors by using N DFT = ceil (L/2) different DFT vectors, wherein each of the floor (L/2) DFT vectors of the N DFT DFT vectors employs two different signal polarizations to generate 2-floor (L/2) precoding vectors, and, if mod (L, 2) =1, the remaining DFT vectors of the N DFT DFT vectors employ one signal polarization to generate corresponding precoding vectors, Wherein the parameters of the codebook include at least one of a number of antenna ports N 1 and a corresponding oversampling parameter O 1 of the base station along a first spatial dimension, and a number of antenna ports N 2 and a corresponding oversampling parameter O 2 of the base station along a second spatial dimension, wherein a number of DFT vectors defined by the codebook is equal to (N 1 ×O 1 ）×（N 2 ×O 2 ), Wherein the different DFT vectors are orthogonal DFT vectors, Wherein the different signal polarizations are orthogonal signal polarizations, an Wherein the configuration information is transmitted by using at least one of data control information DCI, medium access control MAC, radio resource control RRC signaling.
  3. 3. The method of claim 1, further comprising: L independent normalization parameters are determined, wherein the independent normalization parameters are independent for the L MIMO layers, respectively.
  4. 4. A method according to claim 3, Wherein determining the independent normalization parameters comprises: For each precoding vector of the precoding matrix, determining an independent normalization parameter depending on whether the same DFT vector is applied to the MIMO layer associated with the precoding vector and the MIMO layer associated with another precoding vector in the precoding matrix with different signal polarizations, and Setting an independent normalization parameter for each precoding vector of the precoding matrix to 1, and Wherein applying the normalization parameter further comprises: And multiplying the precoding vectors of the precoding matrix by corresponding determined independent normalization parameters.
  5. 5. A method performed by a base station supporting beamforming in a wireless communication system, the method comprising: Generating configuration information about channel state information, CSI, comprising parameters of a codebook and a parameter N DFT indicating a maximum number of discrete fourier transform, DFT, vectors with one signal polarization in a precoding matrix; Transmitting the configuration information about the CSI to User Equipment (UE); transmitting CSI reference signal CSI-RS to the UE, and Receiving CSI from the UE, the CSI comprising at least one of a rank indicator RI and a precoding matrix indicator PMI of a number L of selected multiple-input multiple-output MIMO layers.
  6. 6. The method of claim 5, further comprising: Determining normalization parameters for the generated precoding matrix by using normalization information, wherein the determined normalization parameters include a common normalization parameter applied to the entire precoding matrix and independent normalization parameters respectively applied to individual precoding vectors or groups of precoding vectors in the precoding matrix, and The determined normalization parameters are applied to the generated precoding matrix, Wherein the configuration information further comprises information for power normalization of the precoding matrix, and Wherein L is selected from a plurality of preset values, and the maximum value of L is 16.
  7. 7. The method of claim 5, further comprising: For each L value of the plurality of preset values, calculating a corresponding common normalization parameter based on at least one of a predefined EIRP constraint, antenna gain, transmit power, and L value, and And the calculated public normalization parameters are contained in the normalization information.
  8. 8. The method according to claim 6, wherein the method comprises, Wherein determining the normalization parameter comprises: Selecting common normalization parameters corresponding to the number L of the selected MIMO layers from the calculated common normalization parameters for application to the generated precoding matrix, and Wherein applying the common normalization parameter comprises: multiplying a precoding matrix by a normalization coefficient, the normalization coefficient comprising the common normalization parameter.
  9. 9. A user equipment, UE, supporting beamforming in a wireless communication system, the UE comprising: Transceiver, and A controller configured to: receiving configuration information about channel state information, CSI, from a base station, the configuration information including parameters of a codebook and a parameter N DFT indicating a maximum number of discrete fourier transform, DFT, vectors with one signal polarization in a precoding matrix; receiving CSI reference signal CSI-RS from base station, and Based on the received CSI-RS, transmitting CSI to the base station, the CSI comprising at least one of a rank indicator RI and a precoding matrix indicator PMI of a number L of selected multiple-input multiple-output MIMO layers.
  10. 10. The UE of claim 9, wherein the controller is further configured to: selecting the number L of MIMO layers; In the case of L≤N DFT , by generating L precoding vectors using L different DFT vectors, each employing one signal polarization, In the case of N DFT < L ≤ 2N DFT , N DFT precoding vectors are generated by using N DFT different DFT vectors, each DFT vector employing one signal polarization and another N next precoding vectors are generated by N next DFT vectors of the N DFT DFT vectors, wherein N next = L - N DFT , each of the N next DFT vectors employing a signal polarization different from one signal polarization that the DFT vector has used in the precoding matrix, or In the case of L > 2N DFT , generating L precoding vectors by using N DFT = ceil (L/2) different DFT vectors, wherein each of the floor (L/2) DFT vectors of the N DFT DFT vectors employs two different signal polarizations to generate 2-floor (L/2) precoding vectors, and, if mod (L, 2) =1, the remaining DFT vectors of the N DFT DFT vectors employ one signal polarization to generate corresponding precoding vectors, Wherein the parameters of the codebook include at least one of a number of antenna ports N 1 and a corresponding oversampling parameter O 1 of the base station along a first spatial dimension, and a number of antenna ports N 2 and a corresponding oversampling parameter O 2 of the base station along a second spatial dimension, wherein a number of DFT vectors defined by the codebook is equal to (N 1 ×O 1 ）×（N 2 ×O 2 ), Wherein the different DFT vectors are orthogonal DFT vectors, Wherein the different signal polarizations are orthogonal signal polarizations, an Wherein the configuration information is transmitted by using at least one of data control information DCI, medium access control MAC, radio resource control RRC signaling.
  11. 11. The UE of claim 10, wherein the controller is further configured to: L independent normalization parameters are determined, wherein the independent normalization parameters are independent for the L MIMO layers, respectively.
  12. 12. The UE of claim 11, wherein the controller is further configured to: For each precoding vector of the precoding matrix, determining an independent normalization parameter depending on whether the same DFT vector is applied to the MIMO layer associated with the precoding vector and the MIMO layer associated with another precoding vector in the precoding matrix with different signal polarizations, and Setting an independent normalization parameter for each precoding vector of the precoding matrix to 1, and And multiplying the precoding vectors of the precoding matrix by corresponding determined independent normalization parameters.
  13. 13. A base station supporting beamforming in a wireless communication system, the base station comprising: Transceiver, and A controller configured to: Generating configuration information about channel state information, CSI, comprising parameters of a codebook and a parameter N DFT indicating a maximum number of discrete fourier transform, DFT, vectors with one signal polarization in a precoding matrix, Transmitting the configuration information regarding CSI to the user equipment UE, Transmitting a CSI reference signal (CSI-RS) to the UE, and Receiving CSI from the UE, the CSI comprising at least one of a rank indicator RI and a precoding matrix indicator PMI of a number L of selected multiple-input multiple-output MIMO layers.
  14. 14. The base station of claim 13, wherein the controller is further configured to: determining normalization parameters for the generated precoding matrix by using normalization information, wherein the determined normalization parameters include a common normalization parameter applied to the entire precoding matrix and independent normalization parameters respectively applied to individual precoding vectors or groups of precoding vectors in the precoding matrix, and The determined normalization parameters are applied to the generated precoding matrix, Wherein the configuration information further comprises information for power normalization of the precoding matrix, and Wherein L is selected from a plurality of preset values, and the maximum value of L is 16.
  15. 15. The base station of claim 13, wherein the controller is further configured to: For each L value of the plurality of preset values, calculating a corresponding common normalization parameter based on at least one of a predefined EIRP constraint, antenna gain, transmit power, and L value, The calculated common normalization parameters are included in the normalization information, Selecting common normalization parameters corresponding to the number L of the selected MIMO layers from the calculated common normalization parameters for application to the generated precoding matrix, and Multiplying a precoding matrix by a normalization coefficient, the normalization coefficient comprising the common normalization parameter.

Description

Apparatus and method for beamforming for downlink data transmission in a wireless communication system Technical Field The present disclosure relates to wireless communications. More particularly, the present disclosure relates to an apparatus and method for beamforming for downlink data transmission. Background The 5G mobile communication technology defines a wide frequency band so as to enable high transmission rate and new services, and the technology can be deployed not only in a "below 6 GHz" frequency band such as 3.5GHz but also in a "above 6 GHz" frequency band called millimeter waves including 28GHz and 39 GHz. In addition, in order to achieve the goal that the transmission rate is improved by 50 times compared with the 5G mobile communication technology and the ultra-low delay is reduced to one tenth of the 5G mobile communication technology, the industry has considered to implement the 6G mobile communication technology (hereinafter referred to as ultra-5G system) in the terahertz frequency band (for example, the 95GHz to 3THz frequency band). In the early stages of 5G mobile communication technology development, for supporting enhanced mobile broadband (eMBB), ultra-high reliability low-latency communication (URLLC) and mass machine type communication (mMTC) related services and satisfying performance requirements thereof, related standardization work has been continuously advancing, and related technologies include beamforming and massive MIMO technology for alleviating radio wave path loss in millimeter waves and increasing radio wave transmission distance, parameter set supporting technology (e.g., operating multiple subcarrier intervals) for dynamic operation with millimeter wave resources and slot formats efficiently, initial access technology for supporting multi-beam transmission and broadband, definition and operation technology of BWP (bandwidth part), novel channel coding methods such as LDPC (low density parity check) codes suitable for mass data transmission and polarization codes suitable for highly reliable transmission of control information, L2 preprocessing technology, and network slicing technology for providing a specific service with a private network. Currently, in view of services to be supported by the 5G mobile communication technology, the industry is under discussion for improvement and performance improvement of the initial 5G mobile communication technology and has advanced standardization work at the physical layer, involving technologies such as V2X (internet of vehicles) technology aimed at assisting an autonomous vehicle in making driving decisions and improving user convenience based on own position and state information transmitted by the vehicle, NR-U (new air interface unlicensed) technology aimed at making system operation meet various regulatory requirements of unlicensed bands, NR UE energy saving technology, non-terrestrial network (NTN) technology serving areas that cannot be covered by terrestrial network communication as UE-satellite direct communication, and positioning technology. In addition, standardization work at the air interface architecture/protocol level is ongoing, involving technologies including industrial internet of things (IIoT) technology for supporting new services by interworking convergence with other industries, integrated Access Backhaul (IAB) technology for providing nodes for the extension of network service areas by supporting wireless backhaul links and access links in an integrated manner, mobility enhancement technology including conditional handover and DAPS (dual active protocol stack) handover, and two-step random access technology (2-step RACH of NR) for simplifying random access procedures. At the system architecture/traffic level, related standardization work is also advancing, involving 5G infrastructure (e.g., service-based architecture or service-based interface) for combining Network Function Virtualization (NFV) and Software Defined Network (SDN) technologies and Mobile Edge Computing (MEC) for receiving services based on UE location. With commercialization of the 5G mobile communication system, the number of networking devices accessing the communication network increases exponentially, so that enhancement of functions and performances of the 5G mobile communication system and integrated operation of the networking devices are also necessary. For this reason, the industry has planned a new research direction including XR (augmented reality) technology for efficiently supporting AR (augmented reality), VR (virtual reality), MR (mixed reality) and the like, 5G performance improvement and complexity reduction technology by using Artificial Intelligence (AI) and Machine Learning (ML), AI service support technology, metauniverse service support technology, and unmanned aerial vehicle communication technology. In addition, the development results of the 5G mobile communication system lay a foundation for the development