Channel state information reporting method, base station and user equipment

Abstract

An embodiment of the present invention provides a channel state information reporting method, which is performed in a system having a central controller, multiple transmission and reception points TRP, and multiple user equipment in a cloud radio access network CRAN. The embodiment of the present invention uses the macro diversity of CRAN to solve the difficulty of CSI feedback in a large antenna system. The base station estimates the channel autocorrelation coefficient and the large-scale channel fading coefficient, and obtains a CSI feedback configuration for the user equipment. Each user equipment reports or does not report CSI feedback according to the configuration, and the base station predicts the CSI not reported by the user equipment.

Description

[Technical field]

[0001] The present invention relates to the field of communication systems, and in particular to obtaining channel state information (CSI) in frequency division duplexing (FDD) cloud radio access networks (CRAN). [Background technology]

[0002] Wireless communication systems such as the third generation 3G mobile phone standards and technologies are well known, and such 3G standards and technologies have been developed by the 3rd Generation Partnership Project (3GPP). The third generation of wireless communications has generally been developed to support macrocellular mobile phone communications, and communication systems and networks have been developed in the direction of broadband and mobile systems. In a cellular wireless communication system, a user equipment (UE) is connected to a radio access network (RAN) via a wireless link. The RAN includes a set of base stations (BS), which can provide wireless links to UEs located in cells covered by the base stations and an interface to the core network (CN), which is used to provide control of the overall network. It is easy to understand that the RAN and CN each perform different functions related to the overall network. The 3rd Generation Partnership Project developed the so-called Long Term Evolution (LTE) system, i.e., the Evolved Universal Mobile Telecommunication System Territorial Radio Access Network (E-UTRAN), for a mobile access network of one or more macro cells supported by a base station called eNodeB or eNB (evolved NodeB). Recently, LTE has further evolved towards so-called 5G or NR (New Radio) systems, in which one or more cells are supported by a base station called a gNB.

[0003] With the proliferation of smart devices and the emergence of new capacity-demanding services, wireless networks are facing a whole new set of challenges in terms of technology and business models.

[0004] In fact, the next generation of mobile networks must meet diverse needs with different key performance indicators (KPIs). 5G mobile networks support three emerging services: enhanced mobile broadband (eMBB), ultra-reliable and low-latency communication (URLLC), and massive machine type communication (mMTC).

[0005] Technical issues:

[0006] The current mobile network architecture has proven to be inadequate to meet the needs of 5G services, with previous generations of networks designed to meet the requirements of voice and traditional mobile broadband services. As 5G networks are expected to provide diverse services, support current standards including LTE and Wireless Local Area Network (WLAN), and coordinate different site types, a more flexible and distributed service-driven architecture is required.

[0007] Cloud Radio Access Networks (CRAN) / Virtualized Radio Access Network (VRAN) technology is envisioned as a key technology for the next generation network. CRAN provides the required flexibility to adapt to the ever-changing traffic volume and its increasingly dynamic characteristics. Coupled with a large number of antennas at the access point (AP), CRAN / VRAN is able to provide energy and spectrum efficiency gains in large antenna systems. In addition, by leveraging a centralized pool of baseband units (BBU) and network functions virtualization (NFV), CRAN / VRAN is able to quickly deploy additional value-added mobile services and reduce network operating costs.

[0008] However, large CRAN / VRAN systems require channel state information (CSI) acquisition in large antenna systems. The CSI estimation overhead increases with the number of antennas at the receiver and transmitter. In order to adapt to the CRAN / VRAN architecture characterized by low estimation / feedback overhead, a suitable CSI estimation scheme is desired.

[0009] In a Frequency Division Duplexing (FDD) system, since the uplink (UL) and downlink (DL) may use different frequency bands, it is necessary to estimate the CSI of both links. UL CSI is obtained by using the user equipment to send different pilot sequences. In DL, CSI estimation is obtained using DL training, which is accompanied by explicit or implicit CSI feedback. As the number of base station BS antennas increases, FDD channel estimation becomes very difficult because the CSI feedback overhead increases linearly with the number of system antennas.

[0010] Different schemes have been developed to solve the CSI estimation problem in both Time-division Duplex (TDD) and FDD large antenna systems. For FDD systems, Joint Spatial Division and Multiplexing (JSDM) of Multi-User Multiple-Input Multiple-Output (MU-MIMO) DL has been studied to address the CSI feedback bottleneck. JSDM is a scheme that aims to serve user equipment by grouping UEs so that the user equipment within a group has almost similar channel covariance, while the user equipment across groups have nearly orthogonal covariance feature spaces.

[0011] In addition, for FDD systems with JSDM, K-means clustering based on chord distance is proposed, and a series of similarity measures such as similarity measures based on weighted likelihood, subspace projection, and Fubini-Study are also studied. Two clustering methods, namely hierarchical clustering and K-medoid clustering, are proposed for UE grouping using the above similarity measures.

[0012] The proposed grouping methods are compared and the combination that achieves the maximum capacity is derived. A new similarity measure is combined with a new clustering method to achieve appropriate user equipment grouping based on the second-order statistics of the channel. Using the same two-stage beamforming principle as in JSDM, a graph-theory based UE grouping method is developed to alleviate the shortcomings of previously proposed UE clustering methods. The spatial characteristics of the channel are exploited to obtain CSI estimates in the mmWave range. Due to a series of special challenges brought by mmWave, some solutions have been proposed to show the temporal correlation between two consecutive block frames in the program. Using compressed sensing and channel sparsity, the feedback overhead can also be reduced. Sparse channel modeling is used to show that compressed sensing (CS) can effectively save DL time-frequency training resources.

[0013] In general, most of these schemes exploit wireless channel properties, such as sparsity and low rank, to reduce the feedback overhead required to obtain CSI at the transmitter. When considering CRAN / VRAN, additional properties of the wireless channel can be exploited to reduce the CSI estimation overhead. [Summary of the invention]

[0014] The embodiment of the present invention provides a channel state information reporting method, a base station and a user equipment.

[0015] In a first aspect, an embodiment of the present invention provides a channel state information CSI reporting method executable in a central controller of a base station, comprising:

[0016] estimating a plurality of channel autocorrelation coefficients and a plurality of large-scale channel fading coefficients of all channels between the user equipment UE u and the M distributed wireless nodes, where M is a positive integer;

[0017] The channel state information CSI feedback configuration of the user equipment UE u is derived, and the CSI feedback configuration includes the following: u,m represents a set of channel feedback indicator parameters, the variable x u,m represents the channel C between the user equipment UE u and the wireless node m u,m Whether the CSI is to be predicted or fed back, the wireless node m is one of the M distributed wireless nodes; the variable x u,m The CSI feedback configuration of a set of channel feedback indicator parameters represented by is sent to the user equipment UE u;

[0018] When the variable x u,m Indicates that the channel C u,m When the CSI of the channel C is to be fed back, the channel C is received in a specific time slot. u,m CSI; and

[0019] When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be predicted, the channel C is obtained by CSI prediction. u,m The CSI in the specific time slot.

[0020] In a second aspect, an embodiment of the present invention provides a channel state information CSI reporting method executable in a user equipment, including:

[0021] Receive a CSI feedback configuration of a user equipment UE u, wherein the CSI feedback configuration includes a variable x u,m represents a set of channel feedback indicator parameters, the variable x u,mrepresents the channel C between the user equipment UE u and the wireless node m u,m whether the CSI is to be predicted or to be fed back, the wireless node m is one of the M distributed wireless nodes of the base station;

[0022] When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be fed back, the channel C is sent in a specific time slot. u,m CSI; and

[0023] When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be predicted, the channel C is not sent in the specific time slot. u,m of CSI.

[0024] In a third aspect, an embodiment of the present invention provides a channel state information CSI reporting method executable in a user equipment, including:

[0025] Estimate multiple channel autocorrelation coefficients and multiple large-scale channel fading coefficients of all channels between the user equipment UE u and the M distributed wireless nodes of the base station, where M is a positive integer; derive the CSI feedback configuration of the user equipment UE u, the CSI feedback configuration includes the variable x u,m represents a set of channel feedback indicator parameters, the variable x u,m represents the channel C between the user equipment UE u and the wireless node m u,m whether the CSI of the wireless node m is to be predicted or to be fed back, and the wireless node m is one of the M distributed wireless nodes;

[0026] When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be fed back, the channel C is sent in a specific time slot. u,m CSI; and

[0027] When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be predicted, the channel C is not sent in the specific time slot. u,m of CSI.

[0028] In a fourth aspect, an embodiment of the present invention provides a base station, including a transceiver and a processor connected to the transceiver, wherein the processor is configured to perform the following steps, including:

[0029] estimating a plurality of channel autocorrelation coefficients and a plurality of large-scale channel fading coefficients of all channels between the user equipment UE u and the M distributed wireless nodes, where M is a positive integer;

[0030] The CSI feedback configuration of the user equipment UE u is derived, and the CSI feedback configuration includes the variable x u,m represents a set of channel feedback indicator parameters, the variable x u,m represents the channel C between the user equipment UE u and the wireless node m u,m Whether the CSI is to be predicted or fed back, the wireless node m is one of the M distributed wireless nodes; the variable x u,m A CSI feedback configuration of a set of channel feedback indicator parameters represented by is sent to the user equipment UE u;

[0031] When the variable x u,m Indicates that the channel C u,m When the CSI of the channel C is to be fed back, the channel C is received in a specific time slot. u,m CSI; and

[0032] When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be predicted, the channel C is obtained by CSI prediction. u,m The CSI in the specific time slot.

[0033] In a fifth aspect, an embodiment of the present invention provides a user equipment, including a transceiver and a processor connected to the transceiver, wherein the processor is configured to perform the following steps, including:

[0034] Receive a CSI feedback configuration of a user equipment UE u, wherein the CSI feedback configuration includes a variable x u,m represents a set of channel feedback indicator parameters, the variable x u,m represents the channel C between the user equipment UE u and the wireless node m u,m whether the CSI is to be predicted or to be fed back, the wireless node m is one of the M distributed wireless nodes of the base station;

[0035] When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be fed back, the channel C is sent in a specific time slot. u,m CSI; and

[0036] When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be predicted, the channel C is not sent in the specific time slot. u,m of CSI.

[0037] In a sixth aspect, an embodiment of the present invention provides a user equipment, including a transceiver and a processor connected to the transceiver, wherein the processor is configured to perform the following steps, including:

[0038] estimating a plurality of channel autocorrelation coefficients and a plurality of large-scale channel fading coefficients of all channels between the user equipment UE u and the M distributed wireless nodes, where M is a positive integer;

[0039] The CSI feedback configuration of the user equipment UE u is derived, and the CSI feedback configuration includes the variable x u,m represents a set of channel feedback indicator parameters, the variable x u,m represents the channel C between the user equipment UE u and the wireless node m u,m whether the CSI is to be predicted or to be fed back, the wireless node m is one of the M distributed wireless nodes;

[0040] When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be fed back, the channel C is sent in a specific time slot. u,m CSI; and

[0041] When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be predicted, the channel C is not sent in the specific time slot. u,m of CSI.

[0042] The above method disclosed in the embodiment of the present invention can be implemented in a chip. The chip may include a processor, and the processor is configured to call and run a computer program stored in a memory so that a device equipped with the chip executes the above method.

[0043] The above method disclosed in the embodiment of the present invention can be programmed as computer executable instructions stored in a non-transitory computer-readable medium. When the non-transitory computer-readable medium is loaded into a computer, it instructs the processor of the computer to execute the above method.

[0044] The non-transitory computer readable medium may include at least one of a hard disk, a CD-ROM, an optical storage device, a magnetic storage device, a read-only memory, a programmable read-only memory, an erasable programmable read-only memory, an EPROM, an electrically erasable programmable read-only memory, and a flash memory.

[0045] The above method disclosed in the embodiment of the present invention may be programmed into a computer program product, and the computer program product enables a computer to execute the above method.

[0046] The above method disclosed in the embodiment of the present invention may be programmed into a computer program, and the computer program enables a computer to execute the above method.

[0047] CRAN enables users to enjoy diversified services with high energy efficiency, high spectrum efficiency and lower network operating costs. However, CRAN faces many technical challenges due to the connection of massive users, increasingly severe spectrum scarcity and energy-constrained devices. When the number of antennas increases, CRAN / VRAN faces the same CSI estimation challenges as traditional large-scale Multiple Input Multiple Output (MIMO) systems. In FDD mode, since the feedback overhead increases with the increase in the number of transmitting antennas and receiving antennas, the CSI estimation problem becomes critical. The present invention provides an optimized CSI acquisition solution for FDD CRAN / VRAN to achieve massive connections in high-density scenarios. The solution of the present invention mainly reduces the required CSI feedback overhead through linear prediction on the network side and opportunistic feedback on the user side. By utilizing the macro-diversity of the cell-free architecture of CRAN / VRAN, user equipment is allowed to perform limited CSI feedback, and the network improves the CSI through linear prediction of slowly changing channels.

Brief Description of the Drawings

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or related embodiments, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0049] Figure 1 is a schematic diagram of a communication system provided by an embodiment of the present invention;

[0050] Figure 2 is a schematic diagram of a CRAN having a baseband unit pool, a remote radio head and a user equipment provided by an embodiment of the present invention;

[0051] Figure 3 is a flowchart of a method performed on a base station side provided by an embodiment of the present invention;

[0052] Figure 4 is a flowchart of a method performed on a user equipment side provided by an embodiment of the present invention;

[0053] Figure 5 is a flowchart of a method performed on multiple user equipments provided by an embodiment of the present invention;

[0054] Figure 6is a flow chart of a method for jointly determining a channel feedback indicator by a base station and a user equipment provided by another embodiment of the present invention;

[0055] Figure 7 is a schematic diagram showing the influence of the method provided in an embodiment of the present invention on the spectrum efficiency SE;

[0056] Figure 8 is another schematic diagram showing the influence of the method provided in an embodiment of the present invention on the spectrum efficiency SE;

[0057] Fig. 9 It is a schematic diagram of the framework of a wireless communication system provided by an embodiment of the present invention. [Specific implementation method]

[0058] The technical content, structural features, objectives and effects of the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. It is particularly noted that the terms in the embodiments of the present invention are only used to illustrate the purpose of the embodiments of the present invention and are not used to limit the present invention.

[0059] Leveraging software defined networking (SDN) and network function virtualization (NFV), cloud network architecture can effectively cope with diverse 5G services with various KPIs. Cloud Radio Access Network (CRAN) with flexible base station function splitting options has been proposed to address the limitations of traditional network architecture.

[0060] The user equipment signal is limited by heterogeneous Doppler spread at the antennas of different wireless access points (APs), which means that the channel between a given user equipment and the served AP does not evolve at the same rate. In this case, the slowly changing channel can be accurately predicted without channel state information (CSI) feedback. Based on the above research, an embodiment of the present invention provides a flexible CSI feedback method in which the network and the user equipment limit the amount of CSI feedback and perform CSI prediction.

[0061] Please refer to Figure 1 The communication system includes a user equipment group 100a, a base station (BS) 200a and a network entity device 300. The communication system is used to perform the method provided in the embodiment of the present invention. The user equipment group 100a may include UE10a, UE10b and other UEs. Figure 1It is shown for the purpose of illustrating the present invention but not for limitation, and the communication system may include more user equipment, BS and network entities. The connection between the device and the device components is shown as lines and arrows in the figure. The connection between the device and the device may be realized by wireless connection. The connection between the device components and the device components may be realized by wire, bus, routing, cable or optical fiber. UE 10a may include a processor 11a, a memory 12a and a transceiver 13a. UE 10b may include a processor 11b, a memory 12b and a transceiver 13b. Base station 200a may include a baseband unit (Baseband Unit, BBU) 204a. Baseband unit 204a may include a processor 201a, a memory 202a and a transceiver 203a. Network entity device 300 may include a processor 301, a memory 302 and a transceiver 303. Processors 11a, 11b, 201a and 301 may all be configured to implement the intended functions, processes and / or methods described in the embodiments of the present invention. The layers of the wireless interface protocol may be implemented in processors 11a, 11b, 201a, and 301. Memories 12a, 12b, 202a, and 302 each store various programs and information to operate the connected processors. Transceivers 13a, 13b, 203a, and 303 are each coupled to the connected processors and transmit and / or receive wireless signals or wired signals. UE 10a may communicate with UE 10b via a side link. Base station 200a may be one of an eNB (evolved NodeB), a gNB, or other types of wireless nodes.

[0062] Processors 11a, 11b, 201a and 301 may include a central processing unit CPU, an application specific integrated circuit (ASIC), other chipsets, logic circuits and / or data processing devices. Memories 12a, 12b, 202a and 302 may include read-only memory (ROM), random access memory (RAM), flash memory, memory card, storage medium and / or other storage devices. Transceivers 13a, 13b, 203a and 303 may include baseband circuits and radio frequency (RF) circuits to process radio frequency signals. When the embodiment of the present invention is implemented in software, the technical solutions described herein may be implemented by modules, units, programs, functions and entities that perform the functions described herein. These modules may be stored in a memory and executed by a processor. The memory may be implemented within a processor or outside a processor, and it may be coupled to the processor in communication in various ways known in the art.

[0063] The network entity device 300 may be a node in a core network (CN). CN may include an LTE CN or a 5G core (5GC), including a user plane function (UPF), a session management function (SMF), a mobility management function (AMF), a unified data management (UDM), a policy control function (PCF), a control plane (CP) / user plane (UP) separation (CUPS), an authentication server (AUSF), a network slice selection function (NSSF), and a network exposure function (NEF).

[0064] Please refer to Figure 2 Base station 200b is an embodiment of base station 200a, and base station 200b includes a central controller (CC) 210, and access points 211-1, 211-2, ... and 211-M, where M is a positive integer. Central controller 210 can be implemented as a central unit (CU), and can include a baseband unit BBU associated with access points (AP) 211-1, 211-2, ... and 211-M, such as BBU 204a. Access points 211-1, 211-2, ... and 211-M can all be implemented as wireless nodes, remote units (RU) or remote radio heads (RRH), and can include transmission and reception points (TRP). Access points 211-1, 211-2, ... and 211-M can be located at different locations.

[0065] The central controller 210 receives wireless signals from a group 100b including V user equipments (UE) through M distributed wireless nodes, where V is a positive integer. The V user equipments include user equipments 10-1, 10-2, 10-3, ... and 10-V. The user equipments 10-1, 10-2, 10-3 ... and 10-V may be located at different locations.

[0066] The embodiment of the present invention processes uplinks from V user equipments to M single-antenna access points AP. In each time slot, each AP independently performs uplink channel estimation.

[0067] Access points AP 211-1, 211-2, ... and 211-M are distributed in the coverage area and managed by a central controller 210, which contains a centralized BBU pool and handles the physical layer and the medium access control (MAC) layer, such as data decoding and encoding, scheduling and power allocation. The access point AP is linked to the central controller 210 via a high-performance transmission link called forward backhaul. Forward backhaul can be implemented through optical cables or high-bandwidth wireless channels. Figure 2 The system in is a simplified example of a CRAN, which includes a base station 200b and the above-mentioned user equipment. Access points 211-1, 211-2, ... and 211-M perform channel estimation and link-level transmission chain equalization. The central controller 210 performs signal decoding, encoding, modulation, demodulation, scheduling and MAC layer operations.

[0068] In FDD CRAN systems, user equipment needs to obtain the channel CSI of different APs through downlink training and then feed back the CSI. This task can be very complex because the CSI feedback overhead increases with the number of APs and user equipment antennas. However, serving user equipment from multiple APs has been shown to provide high performance gains, mainly due to the large number of transmit antennas directly leading to channel orthogonality and channel hardening.

[0069] Embodiments of the present invention facilitate CSI reporting in a large CRAN system operating in FDD mode. Since CSI reporting is a basic component of a communication system with a large number of antenna units, in addition to reducing CSI calculations on the user equipment side, an effective reporting process is also required to minimize feedback overhead.

[0070] The embodiment of the present invention mainly includes two parts: channel feedback selection at a base station and adaptive linear channel prediction.

[0071] The main idea of ​​the embodiment of the present invention is to reduce the CSI feedback overhead by utilizing the macro diversity of the CRAN system. Compared with the traditional communication network, Figure 2 A system with distributed antennas in

[0045] provides macrodiversity as an additional degree of freedom. Macrodiversity is the diversity of slowly changing channel statistics at each AP.

[0072] Doppler spread, or equivalently, channel autocorrelation in time, can be used to exploit this macrodiversity and reduce CSI feedback overhead. Doppler spread reflects the rate at which the channel changes and can be accurately predicted with minimal error. Well-established Doppler spread characterizes the channel correlation between two given time slots.

[0073] The embodiment of the present invention utilizes channel aging at different rates to reduce the amount of CSI feedback. The features of the embodiment of the present invention include:

[0074] ●At each CSI reporting opportunity, the user equipment feeds back a limited number of channel coefficients, namely, CSI.

[0075] ●The channel coefficients not reported by the user equipment are predicted by the base station.

[0076] ● Feedback and predicted channel coefficient indicators are available at both the central controller CC and the user equipment. Using a low-complexity optimization problem, the CC and the user equipment can obtain CSI feedback and prediction in each time slot to minimize the total mean square error of the channel prediction. In other alternative embodiments, CSI feedback and prediction are performed only by the CC and then transmitted to the user equipment.

[0077] ● In each time slot, the CC generates a channel feedback indicator parameter related to the maximum feedback capacity.

[0078] The embodiments of the present invention utilize Doppler spread information at user equipment and base stations to minimize signaling overhead. The Doppler spread between each access point AP and user equipment can be effectively estimated based on a simple correlation procedure for the cyclic prefix of each orthogonal frequency division multiplexing (OFDM) symbol.

[0079] Please refer to Figure 4 and Figure 3 , the base station and UE u perform the CSI reporting method. An example of UE u in this embodiment may include UE 10a or UE 10b. An example of the base station in this embodiment may include base station 200a or 200b. The following steps may be performed or controlled by a central controller of the base station.

[0080] The base station estimates a plurality of channel autocorrelation coefficients and a plurality of large-scale channel fading coefficients of all channels between UE u and M distributed wireless nodes 211-1, 211-2, ..., and 211-M, where M is a positive integer (step 310).

[0081] The base station derives the CSI feedback configuration of UE u (step 311). The CSI feedback configuration includes the variables x u,mrepresents a set of channel feedback index parameters, the variable x u,m represents the channel C between UE u and wireless node m u,m The CSI of is to be predicted or fed back. The wireless node m is one of the M distributed wireless nodes. The variable x u,m It can be a binary variable. For example, as shown in Table 1, the variable x u,m The value of 0 indicates that the channel C between UE u and wireless node m u,m The CSI is to be predicted, the variable x u,m A value of 1 indicates that the channel C between UE u and wireless node m u,m The CSI is pending feedback.

[0082] Table 1

[0083] <![CDATA[Variable x u,m > CSI reporting operation of user equipment 0 Do not send CSI feedback 1 Send CSI feedback

[0084] The base station will consist of the variable x u,m A CSI feedback configuration representing a set of channel feedback indicator parameters is sent to UE u (step 312).

[0085] UE u receives the above CSI feedback configuration and performs CSI reporting according to the CSI feedback configuration (step 320). u,m Indicates channel C u,m When the CSI of UE u is to be fed back, UE u sends channel C in a specific time slot. u,m CSI (step 321). When the variable x u,m Indicates channel C u,m When the CSI of UE u is to be predicted, UE u does not send channel C in a specific time slot. u,m 's CSI (step 322).

[0086] When the variable x u,m Indicates channel C u,m When the CSI of channel C is to be fed back, the base station receives the CSI of channel C in a specific time slot. u,m CSI (step 313). When the variable x u,m Indicates channel C u,m When the CSI of the channel is to be predicted, the base station obtains the channel C in the specific time slot through CSI prediction. u,m 's CSI (step 314).

[0087] UE u is one of V user equipments 10-1, 10-2, 10-3, and ... 10-V served by the base station through the M distributed wireless nodes, where V is a positive integer. Similarly, the base station can perform the above steps for each of the V user equipments. Figure 5, the base station obtains CSI feedback configurations for all V user equipments (step 330), and sends the CSI feedback configurations to all V user equipments (step 331). Each of the V user equipments receives the CSI feedback configuration and reports CSI to the base station according to the received configuration. The base station receives the CSI of the channels fed back by the V user equipments (step 332), and predicts the CSI of the channels that the V user equipments have not fed back (step 333). The prediction of the channel state information can be performed using a p-order Wiener linear predictor.

[0088] The value of the channel feedback index parameter in a specific time slot is the variable x in the following optimization problem: u,m Solution:

[0089]

[0090] Constrained by

[0091] Where B represents the limited feedback capacity of B bits;

[0092] B m is the feedback capacity of wireless node m; and

[0093] is the mean square error of CSI prediction.

[0094] P1 is an optimization problem with constraint C1. This problem states that the CSI feedback procedure aims to minimize the mean square error of channel prediction. In CSI prediction, the channel vector h is given by u,m( t n+1) is calculated as channel C u,m At a specific time slot t n+1 The CSI of

[0095]

[0096] in,

[0097]

[0098]

[0099] ρ represents a channel autocorrelation coefficient among multiple channel autocorrelation coefficients;

[0100] β u,m represents the channel C in multiple large-scale channel fading coefficients u,m A large-scale channel fading coefficient;

[0101] t n+1 Indicates channel Cu,m A timeslot number when the CSI is predicted; and

[0102] is in time slot t n+1 Predicted channel C u,m of CSI.

[0103] The channel vector can be initialized For example, the central controller sets the channel vector The value assigned to channel C u,m The latest CSI value. ρ is a constant representing the channel autocorrelation coefficient, which is independent of the time slot number. The elements in the matrix is ρt n+1 +1-t n-p The first row of the matrix can be The indices of the elements in this row increase by unit. The first row of the matrix is ​​shifted left to form the second row of the matrix, the second row of the matrix is ​​shifted left to form the third row of the matrix, and so on. The left shift of the matrix elements in each row is a left rotation of the matrix elements in that row, which rearranges the leftmost element to the rightmost. The first column of the matrix can be The indices of the elements in this column increase by unit.

[0104] Based on known Problem P1 has been solved. Mean square error of CSI prediction It can be updated according to the following formula:

[0105]

[0106] Where tr(.) represents the trace operation; and

[0107] The asterisk "*" denotes the matrix conjugate transpose operator.

[0108] Mean square error of CSI prediction The optimal p-order Wiener linear predictor can be used to update. It should be noted that the prediction error decreases with the prediction time slot t n+1 The delay between the time slot of the channel feedback reported and the explicit channel feedback increases. This means that if explicit feedback is not performed, the performance of channel prediction will decay over time. Channel prediction reduces CSI feedback overhead, but it will cause the channel estimation error to increase over time, and the trade-off should be addressed.

[0109] The limited CSI feedback optimization problem P1 is used to minimize the mean square error of channel prediction. This optimization problem involves the prediction error evolving over time. The performance degradation of CSI prediction and the aging of the latest feedback channel are also considered.

[0110] The method provided by the embodiment of the present invention changes the feedback decision from one time slot to the next time slot to strike a balance between the constraint of limited feedback capacity and the error of channel prediction. It should be noted that due to the low prediction error, the system is suitable for predicting channel coefficients with high time correlation.

[0111] The embodiment of the present invention determines a channel index having a predicted channel coefficient while taking into account an increase in prediction error.

[0112] Embodiments of the present invention solve the problem of using Doppler spread at the AP to obtain optimized CSI feedback decisions. Considering the limited feedback capacity of the system, the base station and the user equipment select the channel to be fed back. When the channel coefficients are not sent to the base station, the base station uses a linear p-order Wiener predictor to predict the channel coefficients. That is, the base station uses a linear combination of the last p feedback channel coefficients in question to predict the CSI.

[0113] In one example, the problem is solved by the CC and the obtained solution is sent to the V user equipments. Alternatively, both the CC and the user equipments can solve the problem, so that since both the CC and the user equipments solve the same problem and obtain the same solution, there is no need to transmit the signaling required for CSI feedback configuration. A flowchart of this embodiment is given below.

[0114] Please refer to Figure 6 , the base station and UE u estimate a plurality of channel autocorrelation coefficients and a plurality of large-scale channel fading coefficients of all channels between a UE u and M distributed wireless nodes 211-1, 211-2, ... and 211-M, where M is a positive integer (step 340). The base station and UE u derive a CSI feedback configuration for UE u (step 341). The base station does not need to send the CSI feedback configuration to UE u. When the variable x u,m Indicates channel C u,m When the CSI of UE u is to be fed back, UE u sends channel C in a specific time slot. u,m CSI (step 342). u,m Indicates channel C u,m When the CSI of UE u is to be predicted, UE u does not send channel C in a specific time slot. u,m 's CSI (step 343).

[0115] The results of numerical simulation demonstrate the effect of the embodiment of the present invention. The performance of the CSI reporting method proposed in the embodiment of the present invention is compared with the traditional explicit CSI feedback framework as a benchmark. The same limited feedback capacity is set in both cases. The method proposed in the embodiment of the present invention avoids the feedback capacity limitation by selecting the CSI feedback index, thereby minimizing the total CSI mean square error (MSE).

[0116] In one example, a distributed antenna system includes 12 access points, each with 10 antennas, and provides services for 5 UE devices that share the same frequency resources. The access points AP and UE are distributed in a disk with a radius of 300m. The UE device moves according to a randomly generated direction and speed, with a maximum speed of 500Km / h.

[0117] Figure 7 A comparison of the achievable mean spectral efficiency is shown, and a considerable improvement in spectral efficiency can be obtained by the embodiments of the present invention. The gains from the optimized feedback and prediction framework effectively circumvent the limited feedback capacity mentioned above. Since CSI is not obtained for all APs, the above baseline scheme cannot serve user equipment with all APs. On the other hand, the method proposed in the embodiments of the present invention can optimize the feedback and prediction decisions so as to provide a more comprehensive CSI applicable to all APs.

[0118] Figure 8 A comparison of the cumulative spectral efficiency of 36 time slots (i.e., 36 prediction and feedback opportunities) is shown. Again, the embodiments of the present invention achieve a significant improvement in spectral efficiency. Since the gain in efficiency remains constant over a long period of time, the feedback selection and prediction framework proposed in the embodiments of the present invention is applicable to channel aging effects.

[0119] Fig. 9 7 is a schematic diagram of a system 700 for wireless communication provided by an embodiment of the present invention. The embodiment of the present invention can apply any appropriately configured hardware and / or software to the system. Fig. 9 In the embodiment, the system 700 includes a radio frequency (RF) circuit 710, a baseband circuit 720, a processing unit 730, a memory / storage 740, a display 750, a camera 760, a sensor 770, and an input / output (I / O) interface 780 that are coupled to each other.

[0120] Processing unit 730 may include circuitry such as, but not limited to, one or more single-core or multi-core processors. The processor may include any combination of general-purpose processors and special-purpose processors, such as a graphics processor and an application processor. The processor may be coupled to a memory / storage and configured to execute instructions stored in the memory / storage to enable various applications and / or operating systems running on the system.

[0121] The baseband circuit 720 may include circuits, such as but not limited to one or more single-core or multi-core processors. The processor may include a baseband processor. The baseband circuit may handle various wireless control functions that can communicate with one or more wireless networks through RF circuits. The wireless control functions may include but are not limited to signal modulation, encoding, decoding, radio frequency offset, etc. In some embodiments, the baseband circuit may provide communications compatible with one or more wireless technologies. For example, in some embodiments, the baseband circuit may support communications with 5G NR, LTE, Evolved Universal Terrestrial Radio Access Network (EUTRAN) and / or other wireless metropolitan area networks (WMAN), wireless local area networks (WLAN), and wireless personal area networks (WPAN). In some embodiments, a baseband circuit configured to support wireless communications of at least one wireless protocol may be referred to as a multimode baseband circuit. In various embodiments, the baseband circuit 720 may include circuits for operating signals that are not strictly considered in the baseband frequency. For example, in some embodiments, baseband circuitry may include circuitry for operating on signals having an intermediate frequency that is between the baseband frequency and the radio frequency.

[0122] The RF circuit 710 can communicate with a wireless network using modulated electromagnetic radiation through a non-solid medium. In various embodiments, the RF circuit may include switches, filters, amplifiers, etc. to facilitate communication with the wireless network. In various embodiments, the RF circuit 710 may include circuits for operating signals that are not strictly considered in radio frequency. For example, in some embodiments, the RF circuit may include circuits for operating signals with an intermediate frequency that is between the baseband frequency and the radio frequency.

[0123] In various embodiments, the transmitter circuit, control circuit or receiver circuit described herein for the UE, eNB or gNB may be embodied in whole or in part in one or more of the RF circuit, baseband circuit and / or RF circuit. The "circuit" used herein may relate to, belong to or include an Application Specific Integrated Circuit (ASIC), an electronic circuit, a (shared, dedicated or grouped) processor and / or a (shared, dedicated or grouped) memory to execute one or more software or firmware programs, combinational logic circuits and / or other suitable hardware components that provide the functions. In some embodiments, the electronic device circuit may be implemented in one or more software or firmware modules, or the functions associated with the circuit may be implemented by one or more software or firmware modules. In some embodiments, some or all of the constituent components of the baseband circuit, processing unit and / or memory / storage may be implemented together on a system-on-a-chip (SOC).

[0124] Memory / storage 740 can be used for, for example, system, to load and store data and / or instructions.In one embodiment, memory / storage can include suitable volatile memory, such as dynamic random access memory (DRAM), and / or any combination of non-volatile memory (such as flash memory).In various embodiments, I / O interface 780 can include one or more user interfaces and / or peripheral component interfaces, and the user interface is designed to allow the user to interact with the system, and the peripheral component interface is designed to allow peripheral components to interact with the system.The user interface can include but is not limited to physical keyboard or keypad, touch pad, loud speaker, microphone, etc.The peripheral component interface can include but is not limited to non-volatile memory port, universal serial bus (USB) port, audio jack and power interface.

[0125] In various embodiments, the sensor 770 may include one or more sensing devices to determine environmental conditions and / or location information associated with the system. In some embodiments, the sensor may include, but is not limited to, a gyroscope sensor, an accelerometer, a proximity sensor, an ambient light sensor, and a positioning unit. The positioning unit may also be part of or interact with a baseband circuit and / or an RF circuit to communicate with components of a positioning network, such as a global positioning system GPS satellite. In various embodiments, the display 750 may include a display, such as a liquid crystal display and a touch screen display. In various embodiments, the system 700 may be a mobile computing device, such as, but not limited to, a laptop device, a tablet device, a netbook, an ultrabook, a smart phone, etc. In various embodiments, the system may have more or fewer components, and / or different architectures. Where appropriate, the method provided by an embodiment of the present invention may be implemented as a computer program. The computer program may be stored on a storage medium, such as a non-temporary storage medium.

[0126] An embodiment of the present invention is a combination of techniques / processes that can be adopted in 3GPP specifications to create a final product.

[0127] It will be appreciated by those skilled in the art that the various units, algorithms and steps described and disclosed in the embodiments of the present invention are implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether each function is run in hardware or software depends on the application conditions and the design requirements of the technical solution. Those skilled in the art can use different methods to implement the functions for each specific application, but such implementation should not exceed the scope of protection of the present invention. It will be appreciated by those skilled in the art that since the working processes of the above-mentioned systems, devices and units are basically the same, they can refer to the working processes of the systems, devices and units in the above-mentioned embodiments. For ease of description and simplification, these working processes will not be described in detail.

[0128] It is to be understood that the systems, devices and methods disclosed in the embodiments of the present invention may be implemented in other ways, and the above embodiments are merely exemplary. The division of the above units is based only on logical functions, and other divisions may also exist in implementation. Multiple units or components may be combined or integrated in another system, and certain features may be omitted or skipped. On the other hand, the mutual coupling, direct coupling or communication coupling shown or discussed above is implemented through some ports, devices or units, whether indirectly or through electrical, mechanical or other types of communication.

[0129] The units explained as separate components may be physically separate or not separate. The units used for demonstration may be physical units or not, i.e., located in one place or distributed in multiple network units. According to the purpose of the embodiments of the present invention, some or all of the above units are used. In addition, the various functional units in various embodiments may be integrated into one processing unit, or may be physically independent, or two or more units may be integrated into one processing unit.

[0130] If the software functional unit is used and sold as a product, it can be stored in a readable storage medium in a computer. Based on this understanding, the technical solution proposed in the present invention can be implemented basically or partially in the form of a software product. Alternatively, some technical solutions that are advantageous to the prior art can be implemented in the form of a software product. The software product in the computer is stored in a storage medium, which includes multiple commands for a computer device (such as a personal computer, a server, or a network device) to run all or part of the steps disclosed in the embodiment of the present invention. The present disclosure. The storage medium includes a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a floppy disk, or other medium capable of storing program code.

[0131] The embodiment of the present invention optimizes CSI feedback in a cell-free network operating in FDD mode to reduce CSI estimation overhead and thus improve efficiency.

[0132] The key of the embodiments of the present invention is to use the macro diversity of CRAN / VRAN architecture to solve the difficulty of CSI feedback in large antenna systems. Taking advantage of the diversity of mature channel conditions, especially Doppler spread, and the linear prediction framework for slowly varying channels, the embodiments of the present invention propose an effective CSI feedback framework for FDD CRAN / VRAN.

[0133] Since the network can predict slowly changing channels without the need for implicit or explicit CSI feedback of these channels, the embodiments of the present invention reduce CSI feedback overhead.

[0134] Although the embodiments disclosed in the present invention have been considered to be the most practical and preferred embodiments, it should be understood that the embodiments of the present invention are not limited to the disclosed embodiments, but are intended to cover various arrangements made without departing from the scope of protection of the broadest interpretation of the attached claims.

Claims

1. A channel state information (CSI) reporting method executable in a central controller of a base station, comprising: estimating a plurality of channel autocorrelation coefficients and a plurality of large-scale channel fading coefficients of all channels between the user equipment UEu and the M distributed wireless nodes, where M is a positive integer; The channel state information CSI feedback configuration of the user equipment UEu is derived, and the CSI feedback configuration includes the following: u,m represents a set of channel feedback indicator parameters, the variable x u,m represents the channel C between the user equipment UEu and the wireless node m u,m whether the CSI of the wireless node m is to be predicted or to be fed back, and the wireless node m is one of the M distributed wireless nodes; will include the variable x u,m The CSI feedback configuration of a set of channel feedback indicator parameters represented by is sent to the user equipment UEu; When the variable x u,m Indicates that the channel C u,m When the CSI of the channel C is to be fed back, the channel C is received in a specific time slot. u,m CSI; as well as When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be predicted, the channel C is obtained by CSI prediction. u,m CSI in the specific time slot; The value of the channel feedback index parameter in the specific time slot is the variable x in the following optimization problem: u,m Solution: Constrained by Where B represents the limited feedback capacity of B bits; B m is the feedback capacity of wireless node m; and is the mean square error of CSI prediction.

2. The channel state information reporting method according to claim 1, characterized in that: The user equipment UEu is one of V user equipments served by the base station through M distributed wireless nodes, where V is a positive integer; the method further includes: deriving CSI feedback configurations for all of the V user equipments; Sending the CSI feedback configuration to all the V user equipments; Receiving CSI of the channel fed back by the V user equipments; Predict CSIs of channels that are not fed back by the V user equipments.

3. The channel state information reporting method according to claim 1, characterized in that: The channel C u,m The channel prediction of CSI is performed by a p-order Wiener linear predictor.

4. The channel state information reporting method according to claim 1, characterized in that: In the formula In the channel vector h u,m( t n+1) is calculated as channel C u,m At a specific time slot t n+1 CSI; in, ρ represents a channel autocorrelation coefficient among the multiple channel autocorrelation coefficients; β u,m represents the channel C in the plurality of large-scale channel fading coefficients u,m A large-scale channel fading coefficient; t n+1 Indicates channel C u,m A timeslot number when the CSI is predicted; and is in time slot t n+1 Predicted channel C u,m of CSI.

5. The channel state information reporting method according to claim 4, characterized in that: Mean square error of CSI prediction Update according to the following formula: Where tr(.) represents the trace operation; and The asterisk * denotes the matrix conjugate transpose operator.

6. A channel state information (CSI) reporting method executable in a user equipment, characterized in that: include: Receive a CSI feedback configuration of a user equipment UEu, wherein the CSI feedback configuration includes a variable x u,m represents a set of channel feedback indicator parameters, the variable x u,m represents the channel C between the user equipment UEu and the wireless node m u,m whether the CSI is to be predicted or to be fed back, the wireless node m is one of the M distributed wireless nodes of the base station; When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be fed back, the channel C is sent in a specific time slot. u,m CSI; as well as When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be predicted, the channel C is not sent in the specific time slot. u,m CSI; The value of the channel feedback index parameter in the specific time slot is the variable x in the following optimization problem: u,m Solution: Constrained by Where B represents the limited feedback capacity of B bits; B m is the feedback capacity of wireless node m; and is the mean square error of CSI prediction.

7. The channel state information reporting method according to claim 6, characterized in that: The channel C u,m The channel prediction of CSI is performed by a p-order Wiener linear predictor.

8. A channel state information (CSI) reporting method executable in a user equipment, characterized in that: include: Estimate multiple channel autocorrelation coefficients and multiple large-scale channel fading coefficients of all channels between the user equipment UEu and M distributed wireless nodes of the base station, where M is a positive integer; The CSI feedback configuration of the user equipment UEu is derived, and the CSI feedback configuration includes the variable x u,m represents a set of channel feedback indicator parameters, the variable x u,m represents the channel C between the user equipment UEu and the wireless node m u,m whether the CSI of the wireless node m is to be predicted or to be fed back, and the wireless node m is one of the M distributed wireless nodes; When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be fed back, the channel C is sent in a specific time slot. u,m CSI; as well as When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be predicted, the channel C is not sent in the specific time slot. u,m CSI; The value of the channel feedback index parameter in the specific time slot is the variable x in the following optimization problem: u,m Solution: Constrained by Where B represents the limited feedback capacity of B bits; B m is the feedback capacity of wireless node m; and is the mean square error of CSI prediction.

9. The channel state information reporting method according to claim 8, characterized in that: The channel C u,m The channel prediction of CSI is performed by a p-order Wiener linear predictor.

10. The channel state information reporting method according to claim 8, characterized in that: In the formula In the channel vector h u,m( t n+1) is calculated as channel C u,m At a specific time slot t n+1 CSI; in, ρ represents a channel autocorrelation coefficient among the multiple channel autocorrelation coefficients; β u,m represents the channel C in the plurality of large-scale channel fading coefficients u,m A large-scale channel fading coefficient; t n+1 Indicates channel C u,m A timeslot number when the CSI is predicted; and is in time slot t n+1 Predicted channel C u,m of CSI.

11. The channel state information reporting method according to claim 10, characterized in that: Mean square error of CSI prediction Update according to the following formula: Where tr(.) represents the trace operation; and The asterisk * denotes the matrix conjugate transpose operator.

12. A base station, characterized in that: The invention comprises a transceiver and a processor connected to the transceiver, wherein the processor is configured to perform the following steps, the steps comprising: estimating a plurality of channel autocorrelation coefficients and a plurality of large-scale channel fading coefficients of all channels between the user equipment UEu and the M distributed wireless nodes, where M is a positive integer; The CSI feedback configuration of the user equipment UEu is derived, and the CSI feedback configuration includes the variable x u,m represents a set of channel feedback indicator parameters, the variable x u,m represents the channel C between the user equipment UEu and the wireless node m u,m whether the CSI is to be predicted or to be fed back, the wireless node m is one of the M distributed wireless nodes; will include the variable x u,m A CSI feedback configuration of a set of channel feedback indicator parameters represented by is sent to the user equipment UEu; When the variable x u,m Indicates that the channel C u,m When the CSI of the channel C is to be fed back, the channel C is received in a specific time slot. u,m CSI; and When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be predicted, the channel C is obtained by CSI prediction. u,m CSI in the specific time slot; The value of the channel feedback index parameter in the specific time slot is the variable x in the following optimization problem: u,m Solution: Constrained by Where B represents the limited feedback capacity of B bits; B m is the feedback capacity of wireless node m; and is the mean square error of CSI prediction.

13. The base station according to claim 12, characterized in that: The user equipment UEu is one of V user equipments served by the base station through M distributed wireless nodes, where V is a positive integer; the processor is further configured to perform the following steps: deriving CSI feedback configurations for all of the V user equipments; Sending the CSI feedback configuration to all the V user equipments; Receiving CSI of the channel fed back by the V user equipments; Predict CSIs of channels that are not fed back by the V user equipments.

14. The base station according to claim 12, characterized in that: Channel prediction is performed by a p-th order Wiener linear predictor.

15. The base station according to claim 12, characterized in that: In the formula In the channel vector h u,m( t n+1) is calculated as channel C u,m At a specific time slot t n+1 CSI; in, ρ represents a channel autocorrelation coefficient among the multiple channel autocorrelation coefficients; β u,m represents the channel C in the plurality of large-scale channel fading coefficients u,m A large-scale channel fading coefficient; t n+1 Indicates channel C u,m A timeslot number when the CSI is predicted; and is in time slot t n+1 Predicted channel C u,m of CSI.

16. The base station according to claim 15, characterized in that: Mean square error of CSI prediction Update according to the following formula: Where tr(.) represents the trace operation; and The asterisk * denotes the matrix conjugate transpose operator.

17. A user equipment, characterized in that: The invention comprises a transceiver and a processor connected to the transceiver, wherein the processor is configured to perform the following steps, the steps comprising: Receive a CSI feedback configuration of a user equipment UEu, wherein the CSI feedback configuration includes a variable x u,m represents a set of channel feedback indicator parameters, the variable x u,m represents the channel C between the user equipment UEu and the wireless node m u,m whether the CSI is to be predicted or to be fed back, the wireless node m is one of the M distributed wireless nodes of the base station; When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be fed back, the channel C is sent in a specific time slot. u,m CSI; and When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be predicted, the channel C is not sent in the specific time slot. u,m CSI; The value of the channel feedback index parameter in the specific time slot is the variable x in the following optimization problem: u,m Solution: Constrained by Where B represents the limited feedback capacity of B bits; B m is the feedback capacity of wireless node m; and is the mean square error of CSI prediction.

18. The user equipment according to claim 17, characterized in that: The channel C u,m The channel prediction of CSI is performed by a p-order Wiener linear predictor.

19. A user equipment, characterized in that: The invention comprises a transceiver and a processor connected to the transceiver, wherein the processor is configured to perform the following steps, the steps comprising: estimating a plurality of channel autocorrelation coefficients and a plurality of large-scale channel fading coefficients of all channels between the user equipment UEu and the M distributed wireless nodes, where M is a positive integer; The CSI feedback configuration of the user equipment UEu is derived, and the CSI feedback configuration includes the variable x u,m represents a set of channel feedback indicator parameters, the variable x u,m represents the channel C between the user equipment UEu and the wireless node m u,m whether the CSI is to be predicted or to be fed back, the wireless node m is one of the M distributed wireless nodes; When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be fed back, the channel C is sent in a specific time slot. u,m CSI; and When the variable x u,m Indicates that the channel C u,m When the CSI of the channel is to be predicted, the channel C is not sent in the specific time slot. u,m CSI; The value of the channel feedback index parameter in the specific time slot is the variable x in the following optimization problem: u,m Solution: Constrained by Where B represents the limited feedback capacity of B bits; B m is the feedback capacity of wireless node m; and is the mean square error of CSI prediction.

20. The user equipment according to claim 19, characterized in that The channel C u,m The channel prediction of CSI is performed by a p-order Wiener linear predictor.

21. The user equipment according to claim 19, characterized in that In the formula In the channel vector h u,m( t n+1) is calculated as channel C u,m At a specific time slot t n+1 CSI; in, ρ represents a channel autocorrelation coefficient among the multiple channel autocorrelation coefficients; β u,m represents the channel C in the plurality of large-scale channel fading coefficients u,m A large-scale channel fading coefficient; t n+1 Indicates channel C u,m A timeslot number when the CSI is predicted; and is in time slot t n+1 Predicted channel C u,m of CSI.

22. The user equipment according to claim 21, characterized in that Mean square error of CSI prediction Update according to the following formula: Where tr(.) represents the trace operation; and The asterisk * denotes the matrix conjugate transpose operator.

23. A chip, characterized in that: The device comprises a processor configured to call and run a computer program stored in a memory so as to enable a device equipped with the chip to perform a method according to any one of claims 1 to 5.

24. A chip, characterized in that: The device comprises a processor configured to call and run a computer program stored in a memory so as to enable a device equipped with the chip to execute a method according to any one of claims 6 to 11.

25. A computer-readable non-transitory storage medium storing a computer program, characterized in that: The computer program controls the computer to execute the method according to any one of claims 1 to 5.

26. A computer-readable non-transitory storage medium storing a computer program, characterized in that: The computer program controls the computer to execute the method according to any one of claims 6 to 11.

27. A computer program product comprising a computer program, characterized in that The computer program controls the computer to execute the method according to any one of claims 1 to 5.

28. A computer program product comprising a computer program, characterized in that The computer program controls the computer to execute the method according to any one of claims 6 to 11.

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