Random phase calibration methods, apparatus, network-side equipment, and storage media

Abstract

Embodiments of the present application provide a random phase calibration method and device, a network side equipment and a storage medium. The method comprises: determining a first channel estimation time sequence of a target port in a target time period, the first channel estimation time sequence comprising vectors corresponding to at least three time points in the target time period respectively; performing phase correction on a plurality of second vectors based on a first vector in the vectors corresponding to the at least three time points respectively, to obtain a third vector corresponding to each of the plurality of second vectors, the third vector having a same vector direction as the first vector; and determining a second channel estimation time sequence of the target port based on the first vector and the third vector corresponding to each of the plurality of second vectors. Embodiments of the present application perform phase correction on a plurality of second vectors to determine a second channel estimation time sequence of a target port, thereby achieving continuous change in phase of the second channel estimation time sequence and ensuring effectiveness of channel prediction.

Description

Technical Field

[0001] This application relates to the field of wireless communication technology, and in particular to a random phase calibration method, apparatus, network-side device, and storage medium. Background Technology

[0002] In related technologies, channel prediction, whether based on multipath Doppler estimation or filtering theory, requires that the time series of channel estimates obtained from multiple channel soundings must have a continuous phase change. That is, the phase change of the channel estimate should reflect the Doppler frequency generated by user movement.

[0003] However, in related technologies, when the terminal switches between uplink and downlink, it introduces a random phase into the Sounding Reference Signal (SRS), and this random phase appears randomly in the range of 0 to 2π. This causes the channel estimation time series calculated at the base station to have a phase discontinuity, resulting in the failure of the channel prediction method. Summary of the Invention

[0004] This application provides a random phase calibration method, apparatus, network-side device, and storage medium to address the shortcomings of existing technologies where phase discontinuities in channel estimation time series lead to the failure of channel prediction methods, thereby enabling channel estimation time series to maintain continuous phase variation.

[0005] In a first aspect, embodiments of this application provide a random phase calibration method, including:

[0006] Determine the first channel estimation time series of the target port within the target time period. The first channel estimation time series includes vectors corresponding to at least three moments within the target time period.

[0007] Based on the first vector among the vectors corresponding to at least three time points, phase correction is performed on multiple second vectors to obtain the third vectors corresponding to the multiple second vectors respectively. The direction of the vector corresponding to the third vector is the same as the direction of the vector corresponding to the first vector. The first vector corresponds to the first time point among at least three time points, and the second vectors correspond to any time point other than the first time point among at least three time points.

[0008] Based on the first vector and the third vectors corresponding to the multiple second vectors, the second channel estimation time series of the target port is determined.

[0009] Optionally, according to a random phase calibration method of one embodiment of this application, phase correction is performed on a plurality of second vectors to obtain third vectors corresponding to the plurality of second vectors respectively, including:

[0010] For each of the multiple second vectors, perform a phase correction process to obtain the third vector corresponding to each second vector;

[0011] The phase correction process includes:

[0012] Based on the first vector and each of the plurality of second vectors, obtain the phase difference between the first vector and each of the plurality of second vectors;

[0013] Based on the phase difference, phase correction is performed on each of the multiple second vectors to obtain the third vector corresponding to each of the multiple second vectors.

[0014] Optionally, according to one embodiment of the random phase calibration method of this application, based on a first vector and each of a plurality of second vectors, the phase difference between the first vector and each of the plurality of second vectors is obtained, including:

[0015] Determine the correlation coefficient between the first vector and each of the plurality of second vectors;

[0016] Based on the correlation coefficient, the phase difference between the first vector and each of the plurality of second vectors is determined.

[0017] Optionally, according to a random phase calibration method of one embodiment of this application, determining the correlation coefficient between a first vector and each of a plurality of second vectors includes:

[0018] According to the formula c(p)=H(1) H ×H(p), determine the correlation coefficient c(p);

[0019] H(1) represents the first vector, and H(p) represents any one of the multiple second vectors, where p∈(2~P), P represents the number of time points corresponding to the first channel estimation time series, and H(1) H This represents the conjugate transpose of the first vector.

[0020] Optionally, according to one embodiment of the random phase calibration method of this application, determining the phase difference between a first vector and each of a plurality of second vectors based on a correlation coefficient includes:

[0021] According to the formula Determine the phase difference θ(p);

[0022] real(c(p)) represents the real part of the complex number c(p), imag(c(p)) represents the imaginary part of the complex number c(p), and c(p) is the correlation coefficient, where p∈(2~P), and P represents the number of time points corresponding to the first channel estimation time series.

[0023] Optionally, according to one embodiment of the random phase calibration method of this application, based on the phase difference, phase correction is performed on each of the plurality of second vectors to obtain a third vector corresponding to each of the plurality of second vectors, including:

[0024] According to the formula Determine the third vector

[0025] H(p) represents any one of the multiple second vectors, θ(p) represents the phase difference between the first vector and each of the multiple second vectors, where p∈(2~P), P represents the number of time points corresponding to the first channel estimation time series, and j represents the imaginary unit.

[0026] Optionally, according to one embodiment of the random phase calibration method of this application, before determining the first channel estimation time series of the target port within the target time period, the method further includes:

[0027] Obtain historical channel estimates for N ports within a target time period. The historical channel estimates include the channel estimate time series corresponding to each of the N ports.

[0028] Determine the channel estimation time series corresponding to K ports out of N ports, which are the channel estimation time series to be subjected to random phase calibration;

[0029] Where N and K are both positive integers, 1≤K≤N, N is the number of antennas of the terminal in the MIMO system, and the target port is any one of the K ports.

[0030] Optionally, according to one embodiment of the random phase calibration method of this application, after determining the second channel estimation time series of the target port based on the third vector corresponding to the first vector and the plurality of second vectors respectively, the method further includes:

[0031] Based on the second channel estimation time series, channel prediction is performed to obtain the target channel estimate for the target port.

[0032] Secondly, embodiments of this application also provide a network-side device, including a memory, a transceiver, and a processor:

[0033] Memory is used to store computer programs; transceiver is used to send and receive data under the control of the processor; processor is used to read the computer programs from memory and perform the following operations:

[0034] Determine the first channel estimation time series of the target port within the target time period. The first channel estimation time series includes vectors corresponding to at least three moments within the target time period.

[0035] Based on the first vector among the vectors corresponding to at least three time points, phase correction is performed on multiple second vectors to obtain the third vectors corresponding to the multiple second vectors respectively. The direction of the vector corresponding to the third vector is the same as the direction of the vector corresponding to the first vector. The first vector corresponds to the first time point among at least three time points, and the second vectors correspond to any time point other than the first time point among at least three time points.

[0036] Based on the first vector and the third vectors corresponding to the multiple second vectors, the second channel estimation time series of the target port is determined.

[0037] Thirdly, embodiments of this application also provide a random phase calibration device, including a first determining unit, a first acquiring unit, and a second determining unit, wherein:

[0038] The first determining unit is used to determine the first channel estimation time series of the target port within the target time period. The first channel estimation time series includes vectors corresponding to at least three moments within the target time period.

[0039] The first acquisition unit is used to perform phase correction on multiple second vectors based on the first vector among the vectors corresponding to at least three times, and acquire the third vectors corresponding to the multiple second vectors respectively. The vector direction of the third vector is the same as the vector direction of the first vector. The first vector corresponds to the first time among at least three times, and the second vector corresponds to any time other than the first time among at least three times.

[0040] The second determining unit is used to determine the second channel estimation time series of the target port based on the first vector and the third vectors corresponding to the multiple second vectors respectively.

[0041] Fourthly, embodiments of this application also provide a processor-readable storage medium storing a computer program for causing the processor to perform the steps of the random phase calibration method described in the first aspect above.

[0042] The random phase calibration method, apparatus, network-side device, and storage medium provided in this application determine a first channel estimation time series of a target port within a target time period. The first channel estimation time series includes a first vector and multiple second vectors. By performing phase correction on the multiple second vectors, a third vector corresponding to each of the multiple second vectors can be obtained, so that the vector direction corresponding to the third vector is the same as the vector direction corresponding to the first vector. Based on the first vector and the third vectors corresponding to the multiple second vectors, a second channel estimation time series of the target port can be determined. This ensures that the second channel estimation time series maintains continuous phase change, guaranteeing the effectiveness of channel prediction. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a schematic diagram of a random phase calibration method provided by related technologies;

[0045] Figure 2 This is one of the flowcharts illustrating the random phase calibration method provided in the embodiments of this application;

[0046] Figure 3 This is the second schematic flowchart of the random phase calibration method provided in the embodiments of this application;

[0047] Figure 4 This is a schematic diagram of the network-side device provided in an embodiment of this application;

[0048] Figure 5 This is a schematic diagram of the structure of the random phase calibration device provided in the embodiments of this application. Detailed Implementation

[0049] To facilitate a clearer understanding of the various embodiments of this application, some relevant background knowledge will be introduced as follows.

[0050] In beamforming, the base station adjusts the amplitude and phase gain of each element in the antenna array to equivalently decompose the channel into several parallel transmission streams. This ensures that the multipath signals at the target user's location can be superimposed and enhanced in phase, while also ensuring that the transmission streams interact positively without interference. When the user moves, the phase of each propagation multipath changes in a short period of time. At the user's location, the transmission streams cannot maintain orthogonality, leading to increased inter-stream interference and a degraded transmission performance. In this case, the base station needs to recalculate the beamforming weights based on the uplink channel estimation to restore the orthogonality of the streams.

[0051] However, there is a certain time interval between each uplink channel estimation and downlink beamforming update by the base station, during which beamforming performance degrades sharply. The faster the channel changes, the more severe the impact on beamforming performance.

[0052] The method for random phase calibration in sounding channel estimation in related technologies is based on the phase continuity across multiple uplink time slots. It extrapolates the phase estimate for the next sounding moment and compares it with the actual channel estimation phase to obtain the random phase introduced by the terminal's uplink / downlink handover at the second sounding moment. This random phase is then calibrated off based on this value, ensuring the phase continuity of the channel estimation time series.

[0053] Figure 1 This is a schematic diagram of a random phase calibration method provided by related technologies, such as... Figure 1 As shown, the random phase calibration method in related technologies requires at least three consecutive uplink time slots, and each uplink time slot must have an uplink reference signal, including at least one SRS signal. Other reference signals can be the demodulation reference signal (DMRS) of the Physical Uplink Shared Channel (PUSCH), i.e., PUSCH-DMRS, such as... Figure 1 As shown, the frame structure of this DDDDDDDSUU satisfies the requirements of this random phase calibration method, in which the SRS signal is transmitted on time slot 7 / 17.

[0054] For example, firstly, three uplink reference signals—SRS, PUSCH-DMRS, and PUSCH-DMRS—are configured in time slots 7, 8, and 9, respectively. Then, channel estimation time series with continuous phase are obtained in the three consecutive time slots. Next, based on the channel estimations in time slots 7, 8, and 9, the channel estimation phase at the next sounding time (i.e., time slot 17) is estimated by extrapolation. This phase is compared with the actual channel estimation phase in time slot 17 to obtain the random phase in time slot 17. Finally, the random phase in time slot 17 is calibrated. Similarly, the random phase in the next time slot 7 can be calibrated based on the reference signals in time slots 17, 18, and 19.

[0055] However, this method has significant limitations on frame structure configuration and requires a DMRS signal corresponding to Sounding in the uplink time slot in order to calibrate the random phase at the next moment. If the User Equipment (UE) has no service in the uplink time slot, it cannot calibrate the random phase. Even if there is uplink service, the DMRS and SRS of the PUSCH need to be configured on the same symbol in the time slot.

[0056] To overcome the above-mentioned defects, various embodiments of this application provide a random phase calibration method, apparatus, network-side device, and storage medium. By performing phase correction on multiple second vectors in the first channel estimation time series, the channel estimation time series can be made to maintain continuous phase variation.

[0057] In the embodiments of this application, the term "and / or" describes the relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following associated objects have an "or" relationship.

[0058] In the embodiments of this application, the term "multiple" refers to two or more, and other quantifiers are similar.

[0059] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0060] The technical solutions provided in this application can be applied to various systems, especially 5G systems. For example, applicable systems include Global System for Mobile Communication (GSM), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA) General Packet Radio Service (GPRS), Long Term Evolution (LTE), LTE Frequency Division Duplex (FDD), LTE Time Division Duplex (TDD), Long Term Evolution Advanced (LTE-A), Universal Mobile Telecommunication System (UMTS), Worldwide Interoperability for Microwave Access (WiMAX), and 5G New Radio (NR). All of these systems include terminal equipment and network equipment. The systems may also include a core network component, such as Evolved Packet System (EPS) and 5G systems (5GS).

[0061] The terminal devices involved in the embodiments of this application can be devices that provide voice and / or data connectivity to users, handheld devices with wireless connectivity, or other processing devices connected to a wireless modem. The names of the terminal devices may differ in different systems; for example, in a 5G system, a terminal device can be called User Equipment (UE). Wireless terminal devices can communicate with one or more core networks (CNs) via a Radio Access Network (RAN). Wireless terminal devices can be mobile terminal devices, such as mobile phones (or "cellular" phones) and computers with mobile terminal devices, for example, portable, pocket-sized, handheld, computer-embedded, or vehicle-mounted mobile devices that exchange voice and / or data with the RAN. Examples include Personal Communication Service (PCS) phones, cordless phones, Session Initiated Protocol (SIP) phones, Wireless Local Loop (WLL) stations, and Personal Digital Assistants (PDAs). Wireless terminal equipment can also be referred to as a system, subscriber unit, subscriber station, mobile station, mobile station, remote station, access point, remote terminal, access terminal, user terminal, user agent, or user device, but is not limited to these terms in the embodiments of this application.

[0062] The network device involved in this application embodiment can be a base station, which may include multiple cells providing services to terminals. Depending on the specific application, a base station may also be called an access point, or a device in an access network that communicates with a wireless terminal device through one or more sectors on the air interface, or other names. The network device can be used to exchange received air frames with Internet Protocol (IP) packets, acting as a router between the wireless terminal device and the rest of the access network, where the rest of the access network may include an Internet Protocol (IP) communication network. The network device can also coordinate the attribute management of the air interface. For example, the network equipment involved in the embodiments of this application can be a base transceiver station (BTS) in a Global System for Mobile communications (GSM) or Code Division Multiple Access (CDMA), a NodeB in a Wide-band Code Division Multiple Access (WCDMA) system, an evolved Node B (eNB or e-NodeB) in a long term evolution (LTE) system, a 5G base station (gNB) in a next generation system, a Home evolved Node B (HeNB), a relay node, a femto, a pico, etc., and is not limited in the embodiments of this application. In some network structures, the network equipment may include centralized unit (CU) nodes and distributed unit (DU) nodes, and the centralized unit and distributed unit may be geographically separated.

[0063] Network devices and terminal devices can each use one or more antennas for multiple-input multiple-output (MIMO) transmission. MIMO transmission can be single-user MIMO (SU-MIMO) or multiple-user MIMO (MU-MIMO). Depending on the configuration and number of antenna combinations, MIMO transmission can be 2D-MIMO, 3D-MIMO, FD-MIMO, or massive-MIMO, and can also be diversity transmission, precoding transmission, or beamforming transmission, etc.

[0064] Figure 2 This is one of the flowcharts illustrating the random phase calibration method provided in the embodiments of this application, such as... Figure 2 As shown, the entity performing the random phase calibration method can be a network-side device, such as a base station. The method includes:

[0065] Step 201: Determine the first channel estimation time series of the target port within the target time period. The first channel estimation time series includes vectors corresponding to at least three moments within the target time period.

[0066] Specifically, a target port can be determined from the ports corresponding to one or more antennas, and then the first channel estimation time series of the target port in the target time period can be determined.

[0067] Optionally, in a MIMO system, the number of base station antennas can be M, and the terminal can include N antennas. The network-side device can determine a target port from the ports corresponding to the N antennas, and then determine the first channel estimation time series of the target port in the target time period.

[0068] Optionally, for the target port, the target time period may include at least three moments, and the first channel estimation time series may include vectors corresponding to the at least three moments, which may be channel estimation vectors.

[0069] For example, in a MIMO system, the number of base station antennas can be M, and the terminal can include N antennas. The first channel estimation time series H(1~P) can be the channel estimation vectors on the M antennas corresponding to times 1 to P in the target time period. H(1~P) can be a matrix that can include 1 to P column vectors, and each column vector can be a vector with M elements. The expression for the first channel estimation time series H(1~P) can be:

[0070]

[0071] Where h1(1) can be the channel estimate of the first antenna at the first time point, h2(1) can be the channel estimate of the second antenna at the first time point, and so on. M (1) can be the channel estimate of the Mth antenna at the first moment, h M (P) can be the channel estimate of the M-th antenna at time P.

[0072] Step 202: Based on the first vector in the vectors corresponding to at least three times, perform phase correction on multiple second vectors to obtain the third vectors corresponding to the multiple second vectors respectively. The direction of the vector corresponding to the third vector is the same as the direction of the vector corresponding to the first vector. The first vector corresponds to the first time in at least three times, and the second vector corresponds to any time other than the first time in at least three times.

[0073] Specifically, after determining the first channel estimation time series, the first vector corresponding to the first time step can be used as a reference vector to perform phase correction on multiple second vectors, thereby obtaining the third vectors corresponding to multiple second vectors, so that the vector direction corresponding to the third vector is the same as the vector direction corresponding to the first vector. That is, the phase alignment of spatial vectors can be performed on the channel estimation vectors (second vectors) at different times.

[0074] Optionally, the first moment can be the earliest of at least three moments corresponding to the first channel estimated time series.

[0075] Optionally, the second vector can correspond to any of the above at least three time points other than the first time point, and the second vector can have a random phase, which can be introduced due to the terminal's uplink / downlink switching.

[0076] It is understandable that the random phase introduced by the terminal's uplink / downlink handover behaves the same on each antenna element at the base station, meaning that the random phase manifests as a spatial common phase in the channel estimation of different antennas.

[0077] Applying a common phase rotation to the spatial vector does not affect the vector's spatial directivity. Furthermore, the random phase introduced into the Sounding channel estimation during terminal uplink / downlink switching is a common phase for each antenna and does not alter the spatial characteristics of the channel estimation vector. Therefore, correcting a phase on the vector at any given time in the channel estimation time series does not affect the spatial characteristics of the entire sequence.

[0078] Step 203: Based on the first vector and the third vectors corresponding to the multiple second vectors, determine the second channel estimation time series of the target port.

[0079] Specifically, after obtaining the third vectors corresponding to the multiple second vectors, a new channel estimation time series, namely the second channel estimation time series, can be obtained by combining the first vector and the third vectors corresponding to the multiple second vectors.

[0080] It is understandable that by aligning the spatial vectors (second vectors) at different times, the random phase on each second vector can be eliminated, and the channel estimation time series can be made to maintain continuous phase variation, resulting in a set of spatially phase-aligned channel estimation vectors. This set of channel estimation vectors can eliminate the random phase problem and retain the main Doppler information that causes the degradation of time-varying channel performance. Thus, channel prediction can be performed on the phase-aligned channel estimation time series.

[0081] Understandably, compared to the random phase calibration method in related technologies, the random phase calibration method provided in this application can perform phase alignment of spatial vectors on channel estimation vectors at different times without needing to perform phase extrapolation on channel estimation over multiple consecutive uplink time slots, thus reducing resource overhead. Moreover, it does not require configuration of frame structure and PUSCH, which reduces the implementation factors of channel prediction and improves the practicality of channel prediction.

[0082] The random phase calibration method provided in this application determines the first channel estimation time series of the target port within a target time period. The first channel estimation time series includes a first vector and multiple second vectors. By performing phase correction on the multiple second vectors, a third vector corresponding to each of the multiple second vectors can be obtained, so that the vector direction corresponding to the third vector is the same as the vector direction corresponding to the first vector. Based on the first vector and the third vectors corresponding to the multiple second vectors, the second channel estimation time series of the target port can be determined. This ensures that the second channel estimation time series maintains continuous phase change, guaranteeing the effectiveness of channel prediction.

[0083] Optionally, phase correction is performed on multiple second vectors to obtain third vectors corresponding to each of the multiple second vectors, including:

[0084] For each of the multiple second vectors, perform a phase correction process to obtain the third vector corresponding to each second vector;

[0085] The phase correction process includes:

[0086] Based on the first vector and each of the plurality of second vectors, obtain the phase difference between the first vector and each of the plurality of second vectors;

[0087] Based on the phase difference, phase correction is performed on each of the multiple second vectors to obtain the third vector corresponding to each of the multiple second vectors.

[0088] Specifically, after determining the first channel estimation time series of the target port within the target time period, a phase correction process can be performed on each of the multiple second vectors to eliminate the random phase on each second vector and obtain the third vector corresponding to each second vector so that the vector direction corresponding to the third vector is the same as the vector direction corresponding to the first vector.

[0089] Specifically, in the above-mentioned phase correction process, the first vector can be used as a reference vector to obtain the phase difference corresponding to each of the multiple second vectors. This phase difference can be used to correct the phase of the corresponding second vector to eliminate the random phase on each of the multiple second vectors.

[0090] Specifically, in the above-mentioned phase correction process, after obtaining the phase difference corresponding to each of the multiple second vectors, the phase of each of the multiple second vectors can be corrected based on the phase difference, and then the third vector corresponding to each of the multiple second vectors can be obtained so that the vector direction corresponding to the third vector is the same as the vector direction corresponding to the first vector.

[0091] Therefore, by performing a phase correction process on each of the multiple second vectors, the random phase on each second vector can be eliminated, so that the vector direction corresponding to the third vector is the same as the vector direction corresponding to the first vector. Then, based on the first vector and the third vectors corresponding to the multiple second vectors, the second channel estimation time series of the target port can be determined. This can ensure that the second channel estimation time series maintains continuous phase change and guarantee the effectiveness of channel prediction.

[0092] Optionally, based on the first vector and each of the plurality of second vectors, the phase difference between the first vector and each of the plurality of second vectors is obtained, including:

[0093] Determine the correlation coefficient between the first vector and each of the plurality of second vectors;

[0094] Based on the correlation coefficient, the phase difference between the first vector and each of the plurality of second vectors is determined.

[0095] Specifically, in a phase correction process, the first vector can be used as a reference vector to obtain the correlation coefficient between the first vector and each of the multiple second vectors. Based on the correlation coefficient, the phase difference corresponding to each of the multiple second vectors can be obtained. This phase difference can be used to correct the phase of the corresponding second vector to eliminate the random phase on each of the multiple second vectors.

[0096] Therefore, by determining the correlation coefficient between the first vector and each of the multiple second vectors, the phase difference corresponding to each of the multiple second vectors can be determined. The phase difference can be used to correct the phase of the corresponding second vector, and the random phase on each of the multiple second vectors can be eliminated so that the vector direction corresponding to the third vector is the same as the vector direction corresponding to the first vector. Then, based on the third vectors corresponding to the first vector and the multiple second vectors respectively, the second channel estimation time series of the target port can be determined. The second channel estimation time series can be made to maintain continuous phase change, which can ensure the effectiveness of channel prediction.

[0097] Optionally, determining the correlation coefficient between the first vector and each of the plurality of second vectors includes:

[0098] According to the formula c(p)=H(1) H ×H(p), determine the correlation coefficient c(p);

[0099] H(1) represents the first vector, and H(p) represents any one of the multiple second vectors, where p∈(2~P), P represents the number of time points corresponding to the first channel estimation time series, and H(1) H This represents the conjugate transpose of the first vector.

[0100] Specifically, in a phase correction process, the first vector can be used as a reference vector, and the correlation coefficient c(p) between the first vector H(1) and any one of the multiple second vectors H(p) can be obtained through the above formula for the correlation coefficient c(p).

[0101] Understandably, H(1) H ×H(p) can represent H(1) H The cross product operation between H(p) and H(p).

[0102] For example, when p is 2, the first vector can be used as the reference vector, and the correlation coefficient c(2) between the first vectors H(1) and H(2) can be obtained by using the above formula for the correlation coefficient c(p).

[0103] For example, when p is 3, the first vector can be used as the reference vector, and the correlation coefficient c(3) between the first vectors H(1) and H(3) can be obtained by using the above formula for the correlation coefficient c(p).

[0104] For example, when p is P, the first vector can be used as the reference vector, and the correlation coefficient c(P) between the first vector H(1) and H(P) can be obtained by using the above formula for the correlation coefficient c(p).

[0105] Therefore, by using the formula for the correlation coefficient c(p), the correlation coefficient between the first vector H(1) and H(p) can be obtained. Then, the phase difference corresponding to each of the multiple second vectors can be determined. The phase difference can be used to correct the phase of the corresponding second vector and eliminate the random phase on each of the multiple second vectors so that the vector direction corresponding to the third vector is the same as the vector direction corresponding to the first vector. Based on the first vector and the third vectors corresponding to the multiple second vectors, the second channel estimation time series of the target port can be determined. The second channel estimation time series can be made to keep the phase continuously changing, which can ensure the effectiveness of channel prediction.

[0106] Optionally, based on the correlation coefficient, the phase difference between the first vector and each of the plurality of second vectors is determined, including:

[0107] According to the formula Determine the phase difference θ(p);

[0108] real(c(p)) represents the real part of the complex number c(p), imag(c(p)) represents the imaginary part of the complex number c(p), and c(p) is the correlation coefficient, where p∈(2~P), and P represents the number of time points corresponding to the first channel estimation time series.

[0109] Specifically, in a phase correction process, the first vector can be used as a reference vector to obtain the correlation coefficient c(p) between the first vector H(1) and any one of the multiple second vectors H(p). Then, the phase difference θ(p) corresponding to H(p) can be obtained through the above formula for phase difference θ(p).

[0110] For example, when p is 2, the first vector can be used as the reference vector, and the phase difference θ(2) corresponding to H(2) can be obtained by using the above formula for phase difference θ(p).

[0111] For example, when p is 3, the first vector can be used as the reference vector, and the phase difference θ(3) corresponding to H(3) can be obtained by using the above formula for phase difference θ(p).

[0112] For example, when p is P, the first vector can be used as the reference vector, and the phase difference θ(P) corresponding to H(P) can be obtained through the above formula for phase difference θ(p).

[0113] Therefore, the phase difference θ(p) corresponding to H(p) can be obtained through the formula of phase difference θ(p). The phase difference can be used to correct the phase of the corresponding second vector, and can eliminate the random phase on each of the multiple second vectors, so that the vector direction corresponding to the third vector is the same as the vector direction corresponding to the first vector. Then, based on the first vector and the third vectors corresponding to the multiple second vectors respectively, the second channel estimation time series of the target port can be determined. The second channel estimation time series can be made to keep the phase continuously changing, which can ensure the effectiveness of channel prediction.

[0114] Optionally, based on the phase difference, phase correction is performed on each of the plurality of second vectors to obtain a third vector corresponding to each of the plurality of second vectors, including:

[0115] According to the formula Determine the third vector

[0116] H(p) represents any one of the multiple second vectors, θ(p) represents the phase difference between the first vector and each of the multiple second vectors, where p∈(2~P), P represents the number of time points corresponding to the first channel estimation time series, and j represents the imaginary unit.

[0117] Specifically, in a phase correction process, after obtaining the phase difference θ(p) corresponding to any one of the multiple second vectors H(p), the third vector can be used. The formula, by performing phase correction on H(p), can yield the third vector corresponding to H(p). Make the third vector The direction of the corresponding vector is the same as that of the first vector H(1).

[0118] It is understandable that H(p)·exp(-j·θ(p)) can represent the multiplication between H(p) and exp(-j·θ(p)).

[0119] For example, when p is 2, it can be achieved through a third vector. By applying the formula to H(2) with phase correction, the third vector corresponding to H(2) can be obtained.

[0120] For example, when p is 3, it can be achieved through the third vector. By applying the formula to H(3) with phase correction, the third vector corresponding to H(3) can be obtained.

[0121] For example, when p is P, it can be done through a third vector. By applying the formula to H(P) with phase correction, we can obtain the third vector corresponding to H(P).

[0122] Therefore, through the third vector The formula can perform phase correction on each of the multiple second vectors H(p), eliminate random phase on each of the multiple second vectors, so that the vector direction corresponding to the third vector is the same as the vector direction corresponding to the first vector. Then, based on the first vector and the third vectors corresponding to the multiple second vectors respectively, the second channel estimation time series of the target port can be determined. The second channel estimation time series can be made to keep the phase continuously changing, which can ensure the effectiveness of channel prediction.

[0123] Optionally, before determining the first channel estimation time series for the target port within the target time period, the method further includes:

[0124] Obtain historical channel estimates for N ports within a target time period. The historical channel estimates include the channel estimate time series corresponding to each of the N ports.

[0125] Determine the channel estimation time series corresponding to K ports out of N ports, which are the channel estimation time series to be subjected to random phase calibration;

[0126] Where N and K are both positive integers, 1≤K≤N, N is the number of antennas of the terminal in the MIMO system, and the target port is any one of the K ports.

[0127] Specifically, in a MIMO system, the number of base station antennas can be M, and the terminal can include N antennas. Before determining the first channel estimation time series of the target port in the target time period, the historical channel estimation in the target time period can be obtained. The historical channel estimation can include the channel estimation time series corresponding to N ports, where N ports can correspond to N antennas of the terminal.

[0128] Specifically, after obtaining historical channel estimates, the channel estimation time series corresponding to K ports out of N ports can be determined as channel estimation time series to be randomly phase calibrated. Then, random phase calibration can be performed on the channel estimation time series corresponding to each of the K ports, so that the channel estimation time series corresponding to each of the K ports can maintain continuous phase change.

[0129] Therefore, by determining the channel estimation time series to be randomly phase-calibrated, random phase calibration can be performed on the channel estimation time series corresponding to multiple ports. This ensures that the second channel estimation time series corresponding to multiple ports maintains continuous phase variation and guarantees the effectiveness of channel prediction.

[0130] Optionally, after determining the second channel estimation time series of the target port based on the third vector corresponding to the first vector and multiple second vectors respectively, the method further includes:

[0131] Based on the second channel estimation time series, channel prediction is performed to obtain the target channel estimate for the target port.

[0132] Specifically, after obtaining the second channel estimation time series, a channel prediction method based on the second channel estimation time series and related technologies can predict the channel estimation at future times.

[0133] Optionally, the channel prediction method of the relevant technology can be a channel prediction method based on an autoregressive (AR) model.

[0134] Therefore, after obtaining the second channel estimation time series, since the second channel estimation time series maintains continuous phase change, it can meet the premise of channel prediction. Thus, based on the second channel estimation time series, the channel estimation at future times can be predicted.

[0135] Figure 3 This is the second schematic flowchart of the random phase calibration method provided in the embodiments of this application. Figure 3 This is an optional example of this application, but not intended to limit it; Figure 3 As shown, it includes steps 301 to 306, wherein:

[0136] Step 301: Store the channel estimates CH(1~P) for P historical moments of the user;

[0137] Optionally, the target time period may include P historical moments.

[0138] Optionally, in a MIMO system, the number of base station antennas can be M, and the terminal can include N antennas. The channel estimate of the user at the p-th time point at a certain frequency is CH(p), where p∈(1~P) is an M*N matrix. The total channel estimate time series length is P, and there can be a random phase on the channel estimate vector at each time point.

[0139] Optionally, CH(1~P) may include historical channel estimates of N ports within the target time period. The historical channel estimates may include channel estimation time series corresponding to the N ports respectively, where the N ports may correspond to the N antennas of the terminal.

[0140] Step 302: Determine the first channel estimation time series H(1~P) corresponding to the target port from CH(1~P);

[0141] Optionally, if the target port is the first port among the N ports corresponding to CH(1~P), then the first channel estimation time series H(1~P) corresponding to the target port can be the channel estimation time series corresponding to the first column of CH(1~P); if the target port is the second port among the N ports corresponding to CH(1~P), then the first channel estimation time series H(1~P) corresponding to the target port can be the channel estimation time series corresponding to the second column of CH(1~P); and so on, if the target port is the Nth port among the N ports corresponding to CH(1~P), then the first channel estimation time series H(1~P) corresponding to the target port can be the channel estimation time series corresponding to the Nth column of CH(1~P).

[0142] Step 303: Determine the first vector H(1) corresponding to the first moment, and multiple second vectors H(2~P);

[0143] Optionally, the first moment can be the earliest of at least three moments corresponding to H(1~P).

[0144] Optionally, the second vector can correspond to any of the at least three time points mentioned above, except for the first time point.

[0145] Optionally, in a MIMO system, when the number of base station antennas can be M, the first vector H(1) can be the channel estimation vector on the M antennas corresponding to the first time step, which can be a column vector containing M elements. The expression of the first vector H(1) can be:

[0146] H(1) = [h1(1),h2(1),…h m (1),…,h M (1)] T ;

[0147] Where h1(1) can be the channel estimate of the first antenna at the first time point, h2(1) can be the channel estimate of the second antenna at the first time point, and so on. M (1) can be the channel estimate of the Mth antenna corresponding to the first time step, where the superscript T indicates transpose.

[0148] Optionally, in a MIMO system, when the number of base station antennas can be M, the multiple second vectors H(2~P) can be channel estimation vectors on the M antennas corresponding to times 2~P in the target time period. H(2~P) can be a matrix that can include 2~P column vectors, each column vector can be a vector including M elements, and the expression for the multiple second vectors H(2~P) can be:

[0149]

[0150] Step 304: Determine the correlation coefficients c(2~P) of multiple second vectors H(2~P) and H(1), and obtain the phase θ(2~P) corresponding to the correlation coefficients c(2~P);

[0151] Optionally, H(1) can be used as a reference vector to calculate the correlation between multiple second vectors H(2~P) and H(1), and obtain the correlation coefficients c(2~P) corresponding to the multiple second vectors. Then, based on the correlation coefficients c(2~P) corresponding to the multiple second vectors, the phase difference θ(2~P) corresponding to the multiple second vectors can be determined.

[0152] Optionally, for each of the multiple second vectors H(2~P), the process of obtaining the phase difference can be performed once to obtain the phase difference corresponding to each second vector, that is, the phase difference θ(p), p∈(2~P).

[0153] Optionally, the process of obtaining the phase difference at one time may include: based on the first vector H(1) and any one of the multiple second vectors H(p), p∈(2~P), the correlation coefficient c(p) between the first vector H(1) and H(p) can be determined, and based on the correlation coefficient c(p), the phase difference θ(p) corresponding to each of the multiple second vectors H(p) can be determined.

[0154] Optionally, the correlation coefficient c(p) between the first vector H(1) and each of the plurality of second vectors H(p) can be determined by the following formula:

[0155] c(p)=H(1) H ×H(p);

[0156] Where p∈(2~P), P represents the number of times corresponding to the first channel estimation time series H(1~P), H(1) H This represents the conjugate transpose of the first vector.

[0157] Optionally, the phase difference θ(p) corresponding to each of the plurality of second vectors H(p) can be determined by the following formula:

[0158]

[0159] Where real(c(p)) represents the real part of the complex number c(p), imag(c(p)) represents the imaginary part of the complex number c(p), c(p) is the correlation coefficient, where p∈(2~P), and P represents the number of time points corresponding to the first channel estimation time series H(1~P).

[0160] Step 305: H(2~P) is corrected based on the phase difference θ(2~P), and then the corrected H(2~P) is combined with H(1) to obtain the second channel estimation time series;

[0161] Optionally, based on the phase difference θ(2~P) corresponding to multiple second vectors, the vector direction of H(2~P) can be corrected to obtain the corrected H(2~P), that is... Make Since the vector direction is the same as that of H(1), random phase on H(2~P) can be removed.

[0162] Optionally, based on the phase difference θ(2~P) corresponding to multiple second vectors, a phase correction process can be performed for each second vector to obtain the third vector corresponding to each second vector.

[0163] Alternatively, during a phase correction process, the third vector can be determined using the following formula.

[0164]

[0165] Where p∈(2~P), P represents the number of times corresponding to the first channel estimation time series H(1~P), and j represents the imaginary unit.

[0166] Optionally, H(1) and Combining these methods yields a new channel estimation time series, also known as the second channel estimation time series. This sequence eliminates the influence of random phase and meets the conditions for channel prediction. The channel estimation at future times can then be predicted based on channel prediction methods in related technologies.

[0167] Step 306: Perform channel prediction based on the second channel estimation time series.

[0168] Optionally, a channel prediction method based on a second channel estimation time series and correlation techniques can predict channel estimates at future times.

[0169] Optionally, the channel prediction method of the relevant technology can be a channel prediction method based on an autoregressive (AR) model.

[0170] The random phase calibration method provided in this application determines a first channel estimation time series for a target port within a target time period. The first channel estimation time series may include a first vector and multiple second vectors. By performing phase correction on the multiple second vectors, third vectors corresponding to the multiple second vectors can be obtained, so that the vector direction corresponding to the third vector is the same as the vector direction corresponding to the first vector. Based on the first vector and the third vectors corresponding to the multiple second vectors, a second channel estimation time series for the target port can be determined. This method can ensure that the second channel estimation time series maintains continuous phase change and guarantee the effectiveness of channel prediction.

[0171] Figure 4 This is a schematic diagram of the network-side device provided in the embodiments of this application, such as... Figure 4 As shown, the network-side device includes a memory 420, a transceiver 400, and a processor 410, wherein:

[0172] The memory 420 is used to store computer programs; the transceiver 400 is used to send and receive data under the control of the processor 410; the processor 410 is used to read the computer program in the memory 420 and perform the following operations:

[0173] Determine the first channel estimation time series of the target port within the target time period, wherein the first channel estimation time series includes vectors corresponding to at least three moments within the target time period;

[0174] Based on the first vector among the vectors corresponding to the at least three times, phase correction is performed on multiple second vectors to obtain the third vectors corresponding to the multiple second vectors, wherein the direction of the vector corresponding to the third vector is the same as the direction of the vector corresponding to the first vector, the first vector corresponds to the first time among the at least three times, and the second vector corresponds to any time among the at least three times other than the first time.

[0175] Based on the first vector and the third vectors corresponding to the plurality of second vectors, the second channel estimation time series of the target port is determined.

[0176] The network-side device provided in this application determines a first channel estimation time series of a target port within a target time period. The first channel estimation time series may include a first vector and multiple second vectors. By performing phase correction on the multiple second vectors, a third vector corresponding to each of the multiple second vectors can be obtained, so that the vector direction corresponding to the third vector is the same as the vector direction corresponding to the first vector. Based on the first vector and the third vectors corresponding to the multiple second vectors, a second channel estimation time series of the target port can be determined. This can ensure that the second channel estimation time series maintains continuous phase change and guarantee the effectiveness of channel prediction.

[0177] Specifically, transceiver 400 is used to receive and send data under the control of processor 410.

[0178] Among them, Figure 4 In this context, the bus architecture can include any number of interconnected buses and bridges, specifically linking various circuits together, represented by one or more processors (processor 410) and memory (memory 420). The bus architecture can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. The bus interface provides an interface. The transceiver 400 can be multiple elements, including transmitters and receivers, providing units for communicating with various other devices over transmission media, including wireless channels, wired channels, optical fibers, etc. The processor 410 is responsible for managing the bus architecture and general processing, and the memory 420 can store data used by the processor 410 during operation.

[0179] The processor 410 can be a central processing unit (CPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a complex programmable logic device (CPLD). The processor can also adopt a multi-core architecture.

[0180] Optionally, the step of performing phase correction on the plurality of second vectors to obtain the third vectors corresponding to the plurality of second vectors respectively includes:

[0181] For each of the plurality of second vectors, a phase correction process is performed to obtain the third vector corresponding to each second vector;

[0182] The phase correction process includes:

[0183] Based on the first vector and each of the plurality of second vectors, obtain the phase difference between the first vector and each of the plurality of second vectors;

[0184] Based on the phase difference, phase correction is performed on each of the plurality of second vectors to obtain the third vector corresponding to each of the plurality of second vectors.

[0185] Optionally, obtaining the phase difference between the first vector and each of the plurality of second vectors based on the first vector and each of the plurality of second vectors includes:

[0186] Determine the correlation coefficient between the first vector and each of the plurality of second vectors;

[0187] Based on the correlation coefficient, the phase difference between the first vector and each of the plurality of second vectors is determined.

[0188] Optionally, determining the correlation coefficient between the first vector and each of the plurality of second vectors includes:

[0189] According to the formula c(p)=H(1) H ×H(p), determine the correlation coefficient c(p);

[0190] H(1) represents the first vector, and H(p) represents any one of the plurality of second vectors, where p∈(2~P), and P represents the number of time points corresponding to the first channel estimation time series. H This represents the conjugate transpose of the first vector.

[0191] Optionally, determining the phase difference between the first vector and each of the plurality of second vectors based on the correlation coefficient includes:

[0192] According to the formula Determine the phase difference θ(p);

[0193] real(c(p)) represents the real part of the complex number c(p), imag(c(p)) represents the imaginary part of the complex number c(p), and c(p) is the correlation coefficient, where p∈(2~P), and P represents the number of time points corresponding to the first channel estimation time series.

[0194] Optionally, the step of performing phase correction on each of the plurality of second vectors based on the phase difference to obtain a third vector corresponding to each of the plurality of second vectors includes:

[0195] According to the formula Determine the third vector

[0196] H(p) represents any one of the plurality of second vectors, θ(p) represents the phase difference between the first vector and each of the plurality of second vectors, where p∈(2~P), P represents the number of time points corresponding to the first channel estimation time series, and j represents the imaginary unit.

[0197] Optionally, before determining the first channel estimation time series of the target port within the target time period, the operation further includes:

[0198] Obtain historical channel estimates for N ports within the target time period, wherein the historical channel estimates include the channel estimate time series corresponding to each of the N ports;

[0199] The channel estimation time series corresponding to K ports out of the N ports are determined as the channel estimation time series to be subjected to random phase calibration;

[0200] Where N and K are both positive integers, 1≤K≤N, N is the number of antennas of the terminal in the MIMO system, and the target port is any one of the K ports.

[0201] Optionally, after determining the second channel estimation time series of the target port based on the third vector corresponding to the first vector and the plurality of second vectors respectively, the operation further includes:

[0202] Based on the second channel estimation time series, channel prediction is performed to obtain the target channel estimate for the target port.

[0203] The network-side device provided in this application determines a first channel estimation time series of a target port within a target time period. The first channel estimation time series may include a first vector and multiple second vectors. By performing phase correction on the multiple second vectors, a third vector corresponding to each of the multiple second vectors can be obtained, so that the vector direction corresponding to the third vector is the same as the vector direction corresponding to the first vector. Based on the first vector and the third vectors corresponding to the multiple second vectors, a second channel estimation time series of the target port can be determined. This can ensure that the second channel estimation time series maintains continuous phase change and guarantee the effectiveness of channel prediction.

[0204] It should be noted that the network-side device provided in this application embodiment can implement all the method steps implemented by the method embodiment with the network-side device as the execution subject, and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0205] Figure 5 This is a schematic diagram of the structure of the random phase calibration device provided in the embodiments of this application, as shown below. Figure 5 As shown, the device includes: a first determining unit 501, a first acquiring unit 502, and a second determining unit 503, wherein:

[0206] The first determining unit 501 is used to determine the first channel estimation time series of the target port in the target time period, the first channel estimation time series including: vectors corresponding to at least three moments in the target time period;

[0207] The first acquisition unit 502 is used to perform phase correction on a plurality of second vectors based on the first vector among the vectors corresponding to the at least three times respectively, and to acquire the third vectors corresponding to the plurality of second vectors respectively, wherein the vector direction corresponding to the third vector is the same as the vector direction corresponding to the first vector, the first vector corresponds to the first time among the at least three times, and the second vector corresponds to any time other than the first time among the at least three times;

[0208] The second determining unit 503 is used to determine the second channel estimation time series of the target port based on the first vector and the third vectors corresponding to the plurality of second vectors respectively.

[0209] The random phase calibration device provided in this application determines a first channel estimation time series of a target port within a target time period. The first channel estimation time series may include a first vector and multiple second vectors. By performing phase correction on the multiple second vectors, a third vector corresponding to each of the multiple second vectors can be obtained, so that the vector direction corresponding to the third vector is the same as the vector direction corresponding to the first vector. Then, based on the first vector and the third vectors corresponding to the multiple second vectors, a second channel estimation time series of the target port can be determined. This can ensure that the second channel estimation time series maintains continuous phase change and guarantee the effectiveness of channel prediction.

[0210] Optionally, the first acquisition unit is specifically used for:

[0211] For each of the plurality of second vectors, a phase correction process is performed to obtain the third vector corresponding to each second vector;

[0212] The phase correction process includes:

[0213] Based on the first vector and each of the plurality of second vectors, obtain the phase difference between the first vector and each of the plurality of second vectors;

[0214] Based on the phase difference, phase correction is performed on each of the plurality of second vectors to obtain the third vector corresponding to each of the plurality of second vectors.

[0215] Optionally, the first acquisition unit is specifically used for:

[0216] Determine the correlation coefficient between the first vector and each of the plurality of second vectors;

[0217] Based on the correlation coefficient, the phase difference between the first vector and each of the plurality of second vectors is determined.

[0218] Optionally, the first acquisition unit is specifically used for:

[0219] According to the formula c(p)=H(1) H ×H(p), determine the correlation coefficient c(p);

[0220] H(1) represents the first vector, and H(p) represents any one of the plurality of second vectors, where p∈(2~P), and P represents the number of time points corresponding to the first channel estimation time series. H This represents the conjugate transpose of the first vector.

[0221] Optionally, the first acquisition unit is specifically used for:

[0222] According to the formula Determine the phase difference θ(p);

[0223] real(c(p)) represents the real part of the complex number c(p), imag(c(p)) represents the imaginary part of the complex number c(p), and c(p) is the correlation coefficient, where p∈(2~P), and P represents the number of time points corresponding to the first channel estimation time series.

[0224] Optionally, the first acquisition unit is specifically used for:

[0225] According to the formula Determine the third vector

[0226] H(p) represents any one of the plurality of second vectors, θ(p) represents the phase difference between the first vector and each of the plurality of second vectors, where p∈(2~P), P represents the number of time points corresponding to the first channel estimation time series, and j represents the imaginary unit.

[0227] Optionally, the apparatus further includes a third determining unit, the third determining unit being used for:

[0228] Obtain historical channel estimates for N ports within the target time period, wherein the historical channel estimates include the channel estimate time series corresponding to each of the N ports;

[0229] The channel estimation time series corresponding to K ports out of the N ports are determined as the channel estimation time series to be subjected to random phase calibration;

[0230] Where N and K are both positive integers, 1≤K≤N, N is the number of antennas of the terminal in the MIMO system, and the target port is any one of the K ports.

[0231] Optionally, the apparatus further includes a second acquisition unit, the second acquisition unit being used to:

[0232] Based on the second channel estimation time series, channel prediction is performed to obtain the target channel estimate for the target port.

[0233] The random phase calibration device provided in this application determines a first channel estimation time series of a target port within a target time period. The first channel estimation time series may include a first vector and multiple second vectors. By performing phase correction on the multiple second vectors, a third vector corresponding to each of the multiple second vectors can be obtained, so that the vector direction corresponding to the third vector is the same as the vector direction corresponding to the first vector. Then, based on the first vector and the third vectors corresponding to the multiple second vectors, a second channel estimation time series of the target port can be determined. This can ensure that the second channel estimation time series maintains continuous phase change and guarantee the effectiveness of channel prediction.

[0234] It should be noted that the division of units in the embodiments of this application is illustrative and only represents one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units.

[0235] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a processor-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0236] It should be noted that the apparatus provided in this embodiment of the invention can implement all the method steps implemented in the above method embodiment and can achieve the same technical effect. Therefore, the parts and beneficial effects that are the same as those in the method embodiment will not be described in detail here.

[0237] On the other hand, embodiments of this application also provide a processor-readable storage medium storing a computer program for causing the processor to execute the methods provided in the above embodiments, such as including:

[0238] Determine the first channel estimation time series of the target port within the target time period, wherein the first channel estimation time series includes vectors corresponding to at least three moments within the target time period;

[0239] Based on the first vector among the vectors corresponding to the at least three times, phase correction is performed on multiple second vectors to obtain the third vectors corresponding to the multiple second vectors, wherein the direction of the vector corresponding to the third vector is the same as the direction of the vector corresponding to the first vector, the first vector corresponds to the first time among the at least three times, and the second vector corresponds to any time among the at least three times other than the first time.

[0240] Based on the first vector and the third vectors corresponding to the plurality of second vectors, the second channel estimation time series of the target port is determined.

[0241] The processor-readable storage medium can be any available medium or data storage device that the processor can access, including but not limited to magnetic memory (e.g., floppy disk, hard disk, magnetic tape, magneto-optical disk (MO)), optical memory (e.g., CD, DVD, BD, HVD), and semiconductor memory (e.g., ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drive (SSD)).

[0242] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0243] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-executable instructions. These computer-executable instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0244] These processor-executable instructions may also be stored in a processor-readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the processor-readable memory produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0245] These processors can execute instructions that can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable device for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0246] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A random phase calibration method, characterized by, The method comprises: determining a first channel estimation time sequence of a target port in a target time period, the first channel estimation time sequence comprising vectors corresponding to at least three time points in the target time period respectively; performing phase correction on a plurality of second vectors based on a first vector in the vectors corresponding to the at least three time points respectively, to obtain a third vector corresponding to each of the plurality of second vectors, wherein the third vector has the same direction as the first vector, the first vector corresponds to a first time point in the at least three time points, and the second vector corresponds to any time point in the at least three time points except the first time point; determining a second channel estimation time sequence of the target port based on the first vector and the third vector corresponding to each of the plurality of second vectors.

2. The random phase calibration method of claim 1, wherein, The phase correction on the plurality of second vectors to obtain the third vector corresponding to each of the plurality of second vectors comprises: performing a phase correction process on each of the plurality of second vectors respectively to obtain a third vector corresponding to each of the plurality of second vectors respectively; wherein the phase correction process comprises: obtaining a phase difference between the first vector and each of the plurality of second vectors based on the first vector and each of the plurality of second vectors; performing phase correction on each of the plurality of second vectors based on the phase difference to obtain a third vector corresponding to each of the plurality of second vectors.

3. The random phase calibration method of claim 2, wherein, The obtaining of the phase difference between the first vector and each of the plurality of second vectors based on the first vector and each of the plurality of second vectors comprises: determining a correlation coefficient between the first vector and each of the plurality of second vectors; determining the phase difference between the first vector and each of the plurality of second vectors based on the correlation coefficient.

4. The random phase calibration method of claim 3, wherein, The determination of the correlation coefficient between the first vector and each of the plurality of second vectors comprises: The correlation coefficient c(p) is determined according to the formula c(p) = H(l) H x H(p). The H(1) represents a first vector, and the H(p) represents any one of the plurality of second vectors, where p∈(2~P), the P represents a quantity of time points corresponding to the first channel estimation time series, and the H(1) H represents a conjugate transpose vector of the first vector.

5. The random phase calibration method of claim 3, wherein, The determination of the phase difference between the first vector and each of the plurality of second vectors based on the correlation coefficient comprises: According to the formula determining the phase difference θ(p); real(c(p)) represents the real part of a complex number c(p), imag(c(p)) represents the imaginary part of the complex number c(p), and c(p) is a correlation coefficient, wherein p∈(2~P), and P represents the number of time points corresponding to the first channel estimation time sequence.

6. The random phase calibration method of claim 2, wherein, The phase correction on each of the plurality of second vectors based on the phase difference to obtain a third vector corresponding to each of the plurality of second vectors comprises: According to the formula determining the third vector H(p) represents any one of the plurality of second vectors, θ(p) represents the phase difference between the first vector and each of the plurality of second vectors, wherein p∈(2~P), P represents the number of time points corresponding to the first channel estimation time sequence, and j represents an imaginary unit.

7. The random phase calibration method according to any of claims 1-6, characterized by, Before the determining the first channel estimation time sequence of the target port in the target time period, the method further comprises: obtaining historical channel estimations of N ports in the target time period, the historical channel estimations comprising channel estimation time sequences respectively corresponding to the N ports; determining channel estimation time sequences respectively corresponding to K ports in the N ports as channel estimation time sequences to be subjected to random phase calibration; wherein N and K are positive integers, 1≤K≤N, the N is the number of antennas of a terminal in a multiple-input multiple-output (MIMO) system, and the target port is any one of the K ports.

8. The random phase calibration method according to any of claims 1-6, characterized by, After the determining the second channel estimation time sequence of the target port based on the first vector and the third vectors respectively corresponding to the plurality of second vectors, the method further comprises: performing channel prediction based on the second channel estimation time sequence to obtain a target channel estimation of the target port.

9. A network-side device, characterized by, The apparatus comprises a memory, a transceiver, and a processor: the memory is configured to store a computer program; the transceiver is configured to transceive data under control of the processor; and the processor is configured to read the computer program in the memory and perform the following operations: determining a first channel estimation time sequence of a target port in a target time period, the first channel estimation time sequence comprising vectors respectively corresponding to at least three time instants in the target time period; performing phase correction on a plurality of second vectors based on a first vector in the vectors respectively corresponding to the at least three time instants to obtain third vectors respectively corresponding to the plurality of second vectors, wherein the third vectors have the same direction as the first vector, the first vector corresponding to a first time instant in the at least three time instants, and the second vectors corresponding to any time instant in the at least three time instants except the first time instant; determining a second channel estimation time sequence of the target port based on the first vector and the third vectors respectively corresponding to the plurality of second vectors.

10. The network-side device of claim 9, wherein, The performing phase correction on the plurality of second vectors to obtain the third vectors respectively corresponding to the plurality of second vectors comprises: performing a phase correction process on each of the plurality of second vectors respectively to obtain a third vector respectively corresponding to each of the plurality of second vectors; wherein the phase correction process comprises: obtaining a phase difference between the first vector and each of the plurality of second vectors based on the first vector and each of the plurality of second vectors; performing phase correction on each of the plurality of second vectors based on the phase difference to obtain a third vector respectively corresponding to each of the plurality of second vectors.

11. The network-side device of claim 10, wherein, The obtaining the phase difference between the first vector and each of the plurality of second vectors based on the first vector and each of the plurality of second vectors comprises: determining a correlation coefficient between the first vector and each of the plurality of second vectors; determining the phase difference between the first vector and each of the plurality of second vectors based on the correlation coefficient.

12. The network-side device of claim 11, wherein, The determining the correlation coefficient between the first vector and each of the plurality of second vectors comprises: The correlation coefficient c(p) is determined according to the formula c(p) = H(l) H x H(p). The H(1) represents a first vector, and the H(p) represents any one of the plurality of second vectors, where p∈(2~P), the P represents a quantity of time points corresponding to the first channel estimation time series, and the H(1) H represents a conjugate transpose vector of the first vector.

13. The network-side device of claim 11, wherein, The determining the phase difference between the first vector and each of the plurality of second vectors based on the correlation coefficient comprises: According to the formula determining the phase difference θ(p); real(c(p)) represents the real part of the complex number c(p), imag(c(p)) represents the imaginary part of the complex number c(p), c(p) is a correlation coefficient, wherein p∈(2~P), and P represents the number of time points corresponding to the first channel estimation time sequence.

14. The network-side device of claim 10, wherein, The phase correcting each of the plurality of second vectors based on the phase difference, to obtain a third vector corresponding to each of the plurality of second vectors, comprises: According to the formula determining the third vector The H(p) represents any one of the plurality of second vectors, and the θ(p) represents the phase difference between the first vector and each of the plurality of second vectors, wherein p∈(2~P), P represents the number of time points corresponding to the first channel estimation time sequence, and j represents an imaginary unit.

15. The network-side device of any of claims 9-14, wherein, Before the determining the first channel estimation time sequence of the target port in the target time period, the operations further comprise: obtaining historical channel estimations of N ports in the target time period, the historical channel estimations comprising channel estimation time sequences respectively corresponding to the N ports; determining that channel estimation time sequences respectively corresponding to K ports in the N ports are channel estimation time sequences to be subjected to random phase calibration; wherein N and K are positive integers, 1≤K≤N, N is the number of antennas of a terminal in a multiple-input multiple-output (MIMO) system, and the target port is any one of the K ports.

16. The network-side device of any of claims 9-14, wherein, After the determining the second channel estimation time sequence of the target port based on the third vectors respectively corresponding to the first vector and the plurality of second vectors, the operations further comprise: performing channel prediction based on the second channel estimation time sequence to obtain a target channel estimation of the target port.

17. A random phase calibration apparatus, characterized by comprise: a first determining unit, configured to determine a first channel estimation time sequence of a target port in a target time period, the first channel estimation time sequence comprising vectors respectively corresponding to at least three time points in the target time period; a first obtaining unit, configured to perform phase correction on a plurality of second vectors based on a first vector in the vectors respectively corresponding to the at least three time points, to obtain third vectors respectively corresponding to the plurality of second vectors, wherein the third vectors correspond to the same direction as the first vector, the first vector corresponds to a first time point in the at least three time points, and the second vector corresponds to any time point in the at least three time points except the first time point; a second determining unit, configured to determine a second channel estimation time sequence of the target port based on the first vector and the third vectors respectively corresponding to the plurality of second vectors.

18. A processor-readable storage medium, comprising: The processor readable storage medium stores a computer program, and the computer program is used to make the processor execute the method in any one of claims 1 to 8.

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