WO2018115966A1

WO2018115966A1 - Method and device for performing pre-combining processing on uplink massive mimo signals

Info

Publication number: WO2018115966A1
Application number: PCT/IB2017/001694
Authority: WO
Inventors: 何大中
Original assignee: 阿尔卡特朗讯
Priority date: 2016-12-19
Filing date: 2017-12-18
Publication date: 2018-06-28
Also published as: CN108206712B; CN108206712A

Abstract

Provided are a method and device for performing pre-combining processing on uplink massive MIMO signals in a base station. The method comprises the following steps: breaking down a covariance array signal of an uplink channel estimation from a UE into a plurality of sub-array signals; respectively solving an eigenvalue and an eigenvector of a long-term channel estimation covariance matrix corresponding to each sub-array signal via a recursive algorithm, until the algorithm recursive to a basic pre-combining device can be solved. The present invention has the following advantages compared to the prior art: large-scale array signal processing is performed by breaking down and grouping an array signal corresponding to an uplink signal and respectively performing long-term smooth pre-combining processing on each array group, thereby reducing the computational complexity of a multi-antenna uplink massive MIMO receiver, and increasing signal processing efficiency.

Description

Method and apparatus for pre-merging processing of uplink large-scale MIM 0 signals

The present invention relates to the field of mobile communication technologies, and in particular, to a method and apparatus for pre-merging large-scale MIMO signals in a base station. Background technique

In the best existing large-scale (MASSIVE) MIMO schemes, the traditional design of these receivers generally must follow three main factors: high performance, low cost, and the use of multiple antennas at the transmitter and receiver to handle wireless complexities. Receive signal.

In existing receivers, digital signal processors (DSPs), application specific integrated circuits (ASICs), and field programmable gate arrays can be used.

A large amount of signal processing is implemented in (FPGAs). By using a frequency synthesizer (FS), a power amplifier (ower amplifiers, PA), a low noise amplifier

(low noise amplifiers, LNA), uplink and downlink conversion circuits, RF front-ends, and transmit/receive antennas. The baseband part of the signal is connected to the RF circuit. This type of processing of existing receivers can easily lead to excessive signal processing and signal detection. This method is poor in performance, high in cost, and more complicated.

In a fading environment, the performance of the wireless link can be greatly improved by using multiple antennas at the transmitting and receiving ends. These benefits include increased reliability and high data rates.

In traditional single-user or multi-user MIMO (8T8R) systems, the physical antenna array and MIMO channel are two-dimensional—such as 2*4 cross-polarized array antennas. Based on this design, horizontal use can only be achieved on the UE side.

If a three-dimensional antenna array such as 64, 128 or 256 or more is used, the complexity of the signal processing process becomes high, and at the same time, the cost is increased. Summary of the invention

It is an object of the present invention to provide a method and apparatus for pre-merging uplink massive MIMO signals in a base station.

According to an aspect of the present invention, a method for pre-merging uplink massive MIMO signals in a base station is provided, wherein the method comprises the following steps: a covariance array of uplink channel estimation from a UE The signal is decomposed into a plurality of sub-array signals;

b The eigenvalues and eigenvectors of the long-term channel estimation covariance matrix corresponding to each sub-array signal are respectively solved by a recursive algorithm.

According to an aspect of the present invention, a pre-merging apparatus for pre-merging processing an uplink massive MIMO signal in a base station is provided, wherein the pre-merging apparatus includes: a decomposing apparatus, configured to: The covariance array signal of the uplink channel estimation is decomposed into a plurality of sub-array signals in a reduced order;

A plurality of sub-pre-combining means are respectively used for respectively solving the eigenvalues and eigenvectors of the long-term covariance matrix corresponding to each sub-array signal by a recursive algorithm until recursive to the basic pre-merge device algorithm.

According to an aspect of the invention, there is provided a receiver device in a base station, the receiver device comprising one or more pre-merging devices according to the invention.

Compared with the prior art, the present invention has the following advantages: Decomposing and grouping the signal array corresponding to the uplink signal, and performing long-term smooth pre-merging processing on each array group respectively, thereby realizing processing of the large array signal, thereby reducing the processing The computational complexity of multi-antenna uplink massive MIMO receivers improves the efficiency of signal processing. DRAWINGS

Other features, objects, and advantages of the present invention will become more apparent from the Detailed Description of Description

1 is a flow chart showing a method for pre-merging uplink large-scale MIMO signals in a base station according to the present invention;

2 illustrates a method for uplinking massive MIMO signals in accordance with the present invention. Schematic diagram of the pre-merging device of the pre-merging process;

Figure 3a shows a schematic view of an exemplary pre-merging device in accordance with the present invention; Figure 3b shows a schematic view of an exemplary basic pre-merging device in accordance with the present invention;

4 is a block diagram showing an exemplary antenna array in accordance with the present invention; and FIG. 5 is a flowchart showing an exemplary process for solving a channel covariance matrix in accordance with the present invention;

Figure 6 shows a grouping diagram of an exemplary antenna array in accordance with the present invention; Figure 7 shows a schematic diagram of a process for solving a channel covariance matrix in accordance with the present invention.

The same or similar reference numerals in the drawings denote the same or similar components. detailed description

The invention is further described in detail below with reference to the accompanying drawings.

1 is a flow chart showing a method for pre-merging uplink massive MIMO signals in a base station in accordance with the present invention. The method according to the invention comprises a step S1 and a step S2.

Therein, the method according to the invention is implemented by a pre-merging device included in the base station.

The base station of the present invention includes, but is not limited to, a macro base station, a micro base station, a pico base station, a home base station, and the like. The user equipment includes electronic devices that can communicate directly or indirectly with the base station in a wireless manner, including but not limited to mobile phones, PDAs, and the like.

Preferably, the base station is included in a MIMO system.

Referring to FIG. 1, in step S1, the pre-merge device decomposes the covariance array signal of the uplink channel estimation from the UE into a plurality of sub-array signals.

Preferably, the array signal is a large antenna array signal, such as an array signal of 64x64 or 128x128.

Preferably, the pre-merge device continues to group each group of array signals to obtain more sub-array signals, thereby performing pre-combination operations on the respective sub-array signals in each group of array signals. Work. For example, 128x128 is divided into two sets of 64x64 array signals, and each 64x64 signal is divided into four 16x16 signals, respectively, to pre-merge each 16x16 array signal separately.

Preferably, the pre-merge device can decompose the covariance array signal of the uplink channel estimate multiple times, thereby 264x256 or even higher order antenna array signals.

In step S2, the pre-merging device separately solves the eigenvalues and eigenvectors of the long-term covariance matrix corresponding to each sub-array signal by a recursive algorithm until the algorithm recursively to the basic pre-merging device can solve.

Wherein the basic pre-merge device is used to indicate a minimum pre-merging device that processes array signals that cannot be decomposed.

For example, reference is made to an exemplary pre-merging device in accordance with the present invention as shown in Figure 3a. The pre-merging device shown in FIG. 3a includes four sub-pre-combining devices Precombiner1 to Precombiner4 and their corresponding receiving devices, and Precombiner1 to Precombiner4 are basic pre-merging devices. Figure 3b shows a schematic illustration of the structure of each of the basic pre-combining devices of Figure 3a. Referring to Figure 3a, the array signal input to the pre-merge device is divided into four 16AxC sub-array signals. Each 16AxC sub-array signal is decomposed into 4AxC or 8AxC array signals by sub-pre-merge device. At the receiving end, for multiple users (MU) scenarios, 8 receiver MMSE algorithms (8R x MU) can be used. For the single user (SU) scenario, the IRC algorithm (4R x IRC) of 4 receivers can be used.

According to a preferred embodiment of the present invention, the pre-merging device performs pre-merge processing on the array signal in a user specific manner, the method comprising the step S1, the step S201 (not shown) and the step S3 (not shown) ).

In step S201, the pre-merge device solves the feature values and feature vectors of the long-term channel estimation co-variance matrix corresponding to the specific UE.

Next, in step S3, the pre-merge device solves the precoding matrix corresponding to the specific UE such that the beamforming gain for the UE is maximized.

Preferably, in order to reduce the interference of a specific UE to other UEs, the method includes the steps

S4.

In step S4, the pre-merging device solves the long-term channel estimation association corresponding to the specific UE. The eigenvalues and eigenvectors of the difference matrix, such that the UE obtains the maximum SINR

Preferably, it is assumed that 3⁄4 represents the receiving end signal, then 3⁄4 can be expressed by the following formula:

y _k =P _k H _k x _k +∑ _j≠k P _kj x _j ^n _k ( 1 ) where represents the user k (user k) , indicating the signal after the pre-merging process, representing from user k to the base station Upstream channel estimation matrix.

Based on the formula (1), the signal power that satisfies the user is the largest, then:

Preferably, in order to reduce the signal leakage of the user to other UEs, considering the tapering of the side lobe reduction and maximizing the SINR of the user k,

AHH According to a preferred embodiment of the present invention, the pre-merge device performs pre-merge processing on the array signals in a group specific manner, the method comprising the steps S1, S202 (not shown) and step S5 (Fig. Show).

In step S202, the pre-merge device solves the feature values and feature vectors of the long-term channel estimation covariance matrix corresponding to a group of UEs.

Next, in step S5, the pre-merge device solves the precoding matrix corresponding to the group of UEs such that the beamforming gain for the group of UEs is maximized.

Preferably, based on the formula (1), for a group of users m} satisfying the signal power of k, m is the largest, then: ma "(Hf H _3⁄4 + _m ^H H _m ) P _k J → ₍₄₎ preferably, for Reduce user signal leakage to other UEs, considering the gradual change of sidelobe suppression. According to a preferred embodiment of the invention, after the S2, the method comprises a step S6 (not shown)

In step S6, the pre-merging device performs a signal scaling operation on the plurality of sub-array signals to perform subsequent equalization and combining processing on the scaled sub-signal matrices. The following description is made by five exemplary algorithms based on the present invention.

Example 1: Pre-merging algorithm for a specific user ( user specific )

Referring to Figure 4, the antenna array is divided into four groups of arrays, the interior of which is highly correlated. specifically:

- The antenna array is grouped according to the following antenna signals: { 1,2,...,8, 17,18,...,24}, {9,10,...,16, 25,26,..., 32},..., and {41,42,...,48,57,58, ...,64};

- The channel covariance matrix of user i and sub-array m is R^^ E · 3⁄4, ], where 3⁄4, _m is the channel estimation matrix of user i and sub-array m measured based on the uplink reference signal (SRS) (in this example) Medium, m=16).

- the long-term weight matrix of each sub-array, ^ is the first eigenvector of ^;

- The full-length option weight matrix M _im is the block diagonal matrix of w^., _m .

The process of solving the channel covariance matrix in the algorithm is shown in FIG. 5.

For the multi-user (MU) scenario, the receiver can use the MMSE algorithm (8R x MU) of 8 receivers. For the single-user (SU) scenario, 4 receivers can be used.

IRC algorithm (4R x IRC). Example 2: Gradient algorithm for a specific user ( user specific )

Continuing to refer to the grouping manner of the antenna array shown in FIG. 4, the long-term covariance matrix of each group of antenna arrays is obtained based on the following steps:

- The long-term covariance matrix of the horizontal and vertical domains is expressed as and ;

- Find the channel covariance matrix for each row of antennas based on SRS measurements. The covariance matrix of each row (column) is a plurality of rows (columns), and the polarization and physical resource blocks (PRBs) are averaged and filtered in the time domain to obtain a covariance matrix in the horizontal direction;

- The horizontal covariance matrix of the UE is expressed as R ≡ [(/^)*/^], where h is for each row of antennas per polarized antenna and each PRB, from the UE uplink reference signal (SRS) port to 8 TRX 1x8 channel vector of the eNB;

- Similarly, the vertical direction covariance matrix of the UE is expressed as ^^ /! ⁷ ) ⁷ ], where 7 is a 1x4 channel vector for each polarized antenna and each PRB for each column of antennas based on SRS measurements;

For the multi-user (MU) scenario, the receiver can use the MMSE algorithm (8R x MU) of 8 receivers. For the single-user (SU) scenario, the IRC algorithm (4RxIRC) of 4 receivers can be used.

Among them, the precoding matrix of the beamforming (BF) weight can be obtained by the following steps:

S is expressed as:

Where n is the antenna number and N is the number of TRXs connected to the antenna. In this example, the number of TRXs in the horizontal direction is 8, and the number of TRXs in the vertical direction is 4.

- Chebyshev window (or Chebwin window) with a sidelobe suppression of 30dB;

- i§iW→W = {s.*chebwin,sG S];

- Find the maximum beamforming gain for UEi, then ^ I

Horizontal direction: wf )* R w ^H \\

Vertical direction: w = argmax ^ , G _i ^v _w ≡

- Get the BF weight by the Kronecker product of and (take the 2x1 vector corresponding to ®).

Example 3: Maximum SINR algorithm for a specific user (user specific )

Continuing with reference to the antenna grouping scheme shown in Figure 4, as shown, the antenna array is divided into four groups of arrays, the interior of which is highly correlated. specifically:

- The antenna array is grouped according to the following antenna signals: {1, 2, ..., 8, 17, 18, ..., 24}, {9,10,...,16, 25,26,...,32},..., and {41,42,...,48,57,58, ...,64};

- The channel covariance matrix of user i and sub-array m is R _3⁄43⁄4 ,, _m = E[3⁄4, _m ·3⁄4, ], where 3⁄4, _m is the channel estimation matrix based on the SRS measurement and the sub-array m.

- The long-term weight matrix M of each sub-array, _m is a generalized eigenvector corresponding to the largest generalized eigenvalue of the matrix, expressed as:

_R y ⁸ R <==>

PowerMethod—f ( ( ^ ^A3⁄4 ' ^{J Rk i} ' , the algorithm for maximizing received power - the block diagonal matrix of the long-term weight matrix M^, _m w^, _m .

For the multi-user (MU) scenario, the receiver can use the MMSE algorithm (8R x MU) of 8 receivers. For the single-user (SU) scenario, the IRC algorithm (4RxIRC) of 4 receivers can be used. Example 4: Pre-merging algorithm for a specific group ( group specific )

Referring to Figure 6, the antenna array is divided into eight sub-arrays, and the interior of the sub-array is highly correlated. specifically:

- Group the antenna array according to the following antenna signals: {1,2,3,4,5,6,7,8}, {17,18,19,20,21,22,23,24}, {33,34 , 35, 36, 37, 38, 39, 40},..., and {41,42,43,44,45,46,47,48}, {57,58,59,60,61,62, 63,64};

- The channel covariance matrix of user i and subarray m is R _3⁄43⁄4 , _M

·3⁄4, ], where 3⁄4, _m

(8x8) is a channel estimation matrix of user i and sub-array m based on SRS measurements.

- for user groups 1^61^ and j, the long-term weight matrix ^ .TM (8x1) of each sub-array is the first eigenvector of (8x8+8x8);

- For the user groups user i and j, the full length option weight matrix is the block diagonal matrix of ^,^. The process of solving the de-channel covariance matrix in the algorithm is shown in Fig. 7.

For the multi-user (MU) scenario, the receiver can use the MMSE algorithm (8R x MU) of 8 receivers. For the single-user (SU) scenario, the IRC algorithm (4RxIRC) of 4 receivers can be used. Example 5: Gradation algorithm for a group specific

Referring to the antenna grouping manner shown in FIG. 6, the long-term covariance matrix of each group of antenna arrays is obtained based on the following steps:

- The long-term covariance matrices for the horizontal and vertical domains are expressed as (8x8) and (4x4);

- Find the channel covariance matrix for each row of antennas based on SRS measurements. The covariance matrix of each row (column) is a plurality of rows (columns), and the polarization and physical resource block (PRB) are filtered by a long-term average and smoothed in the time domain to obtain a horizontal square covariance matrix;

- The horizontal covariance matrix of the UE is expressed as ≡ [(/^)*/^], where h is 1×8 of 8 TRX from the UE SRS port to the eNB for each polarized antenna and each PRB for each row of antennas Channel vector

- Similarly, the vertical covariance matrix of the UE is expressed as ≡E[(/3⁄4W], where 7 is the SRS measurement based on each polarized antenna and each PRB for each column of antennas.

1x4 channel vector;

- For user group useri j, set R ₌ R + R / S

Also, in this example, the precoding matrix of the beamforming (BF) weight is obtained such that the step of maximizing the beamforming gain for the group of UEs is the same as or similar to the steps in the example 1, and will not be described herein.

According to a preferred embodiment of the present invention, with reference to the antenna array shown in the figure, the power difference after gradualization of each UE and the pre-combined power difference are considered, wherein for 16 antennas in a sub-array, The ideal antenna signal power of the UE can be expressed as ^→ ∑ I; multiplied by the pre-merging matrix of each user to obtain the equivalent antenna power of each UE, expressed as \h_― Ideal * PreComb _user .

Preferably, after pre-combination, a power change is generated, and the PUSCH receiving end compensates the final RSSI of the 16 weights used, which is expressed as: According to the method of the present invention, the signal array corresponding to the uplink signal is decomposed and grouped, and each array group is subjected to long-term smooth pre-merging processing, thereby realizing processing of large-scale array signals and reducing multi-antenna uplink large-scale. The computational complexity of the MIMO receiver improves the efficiency of signal processing.

2 is a block diagram showing the structure of a pre-merge device for performing pre-merging processing on an uplink large-scale MIMO signal according to the present invention.

Referring to Figure 1, the decomposition device decomposes the covariance array signal of the uplink channel estimate from the UE into a plurality of sub-array signals.

Preferably, the array signal is a large array signal, such as a 64x64 or 128x128 array signal.

Preferably, the decomposition means continues to group each set of array signals to obtain more sub-array signals, thereby performing pre-merge operations on the respective sub-array signals in each set of array signals. For example, 128x128 is divided into two sets of 64x64 array signals, and each 64x64 signal is divided into four 16x16 signals, respectively, to pre-merge each 16x16 array signal separately.

Preferably, the decomposing means can decompose the covariance array signal of the uplink channel estimation multiple times, thereby 264x256 or even higher order antenna array signals.

The sub-pre-merge device respectively solves the eigenvalues and eigenvectors of the long-term covariance matrix corresponding to each sub-array signal by a recursive algorithm, until the algorithm recursively to the basic pre-merging device can solve.

For example, reference is made to an exemplary pre-merging device in accordance with the present invention as shown in Figure 3a. The pre-merging device shown in FIG. 3a includes four sub-pre-combining devices Precombiner1 to Precombiner4 and their corresponding history devices, and Precombiner1 to Precombiner4 are basic pre-combining devices. Figure 3b shows a schematic block diagram of each of the basic pre-combining devices of Figure 3a. Referring to Figure 3a, the array signal input to the pre-merge device is divided into four 16AxC sub-array signals. Each 16AxC sub-array signal is decomposed into 4AxC or 8AxC array signals by sub-pre-merge device, and is used by multiple users (Multiusers) at the receiving end. For the scenario, 8 receivers' MMSE algorithm (8R x MU) can be used. For single user (SU) scenarios, 4 receiver IRC algorithms ( 4R x IRC ) can be used.

In accordance with a preferred embodiment of the present invention, the pre-merge device pre-merge the array signals in a user specific manner.

The sub-pre-merge device solves the feature values and feature vectors of the long-term channel estimation covariance matrix corresponding to a particular UE.

Next, the pre-merge device solves the precoding matrix corresponding to the particular UE such that the beamforming gain for the UE is maximized.

Preferably, in order to reduce the interference of the specific UE to other UEs, the pre-merging device finds the feature value and the feature vector corresponding to the long-term covariance matrix of the specific UE, so that the UE obtains the maximum SINR.

In accordance with a preferred embodiment of the present invention, the pre-merge device performs pre-merge processing on the array signals in a group specific manner.

The sub-pre-merge device solves the feature values and eigenvectors of the long-term channel estimation covariance matrix corresponding to a group of UEs.

Next, the pre-merge device solves the precoding matrix corresponding to the set of UEs such that the beamforming gain for the set of UEs is maximized.

According to the solution of the present invention, the signal array corresponding to the uplink signal is decomposed and grouped, and the long-term smooth pre-merge processing is performed on each array group, thereby processing the large-scale array signal, thereby reducing the multi-antenna uplink large-scale. The computational complexity of the MIMO receiver improves the efficiency of signal processing.

It is obvious to those skilled in the art that the present invention is not limited to the details of the above-described exemplary embodiments, and the present invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the present embodiments are to be considered as illustrative and not restrictive, and the scope of the invention is defined by the appended claims All changes in the meaning and scope of equivalent elements are included in the present invention. Any reference signs in the claims should not be construed as limiting the claim. In addition, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. Multiple units or devices as set forth in the system claims It can also be implemented by software or hardware by a unit or device. The first, second, etc. words are used to denote names, and do not denote any particular order.

Claims

Claim

A method for performing pre-merge processing on an uplink large-scale MIM0 signal in a base station, where the method includes the following steps:

a decomposing the covariance array signal of the uplink channel estimate from the UE into a plurality of sub-array signals;

b The eigenvalues and eigenvectors of the long-term channel estimation covariance matrix corresponding to each sub-array signal are respectively solved by a recursive algorithm until the algorithm recursively to the basic pre-merging device can be solved.

2. The method according to claim 1, wherein the method performs a pre-merge operation on each array signal in a manner of a specific UE, and the step b includes the following steps:

- solving eigenvalues and eigenvectors of the long-term channel estimation covariance matrix corresponding to a particular UE;

The method further includes the following steps:

- Solving the precoding matrix corresponding to a particular UE such that the beamforming gain for the UE is maximized.

The method according to claim 2, wherein in order to reduce the interference of a specific UE to other UEs, the method comprises the following steps:

- Solving the eigenvalues and eigenvectors of the long-term channel estimation covariance matrix corresponding to a particular UE, such that the UE obtains the maximum SINR.

The method according to claim 1, wherein the method pre-combines each sub-signal matrix in a specific group manner, and the step b includes the following steps:

- solving eigenvalues and eigenvectors of a long-term channel estimation covariance matrix corresponding to a group of UEs;

The method further includes the following steps:

- Solving a precoding matrix corresponding to the set of UEs such that the beamforming gain for the set of UEs is maximized.

5. The method according to claim 1, wherein after the step b, the method comprises the following steps: - Performing a signal scaling operation on a plurality of sub-array signals to perform subsequent equalization and combining processing on the scaled sub-signal matrices.

6. The method according to claim 1, wherein the step a comprises the following steps:

- Continuing grouping of each set of array signals to obtain more sub-array signals, thereby pre-combining the respective sub-array signals in each set of array signals.

A pre-merging device for pre-merging processing of an uplink large-scale MIMO signal in a base station, wherein the pre-merging device is configured to:

Decomposing means, configured to decompose an uplink channel estimation covariance array signal from the UE into a plurality of sub-array signals;

A plurality of sub-pre-merging means are respectively configured to respectively solve the eigenvalues and eigenvectors of the long-term channel estimation covariance matrix corresponding to each sub-array signal by a recursive algorithm until recursive to the basic pre-merge device algorithm.

The pre-merging device according to claim 7, wherein the pre-merging device performs a pre-merging operation on each array signal in a manner of a specific UE, wherein the sub-pre-combining device is used to:

The pre-merging device is further configured to:

The pre-merging device according to claim 8, wherein, in order to reduce the interference of a specific UE to other UEs, the pre-merging device is configured to:

- Solving the eigenvalues and eigenvectors of the long-term channel estimation covariance matrix corresponding to a particular UE such that the UE obtains the maximum SINR.

The pre-merging device according to claim 7, wherein the pre-merging device performs a pre-merging operation on each sub-signal matrix in a specific group manner, and the sub-pre-combining device is configured to:

- solving eigenvalues and eigenvectors of a long-term channel estimation covariance matrix corresponding to a group of UEs; The pre-merging device is further configured to:

The pre-merging device according to claim 7, wherein the pre-merging device comprises:

And a scaling device, configured to perform signal scaling operations on the plurality of sub-array signals to perform subsequent equalization and combining processing on the scaled sub-signal matrices.

12. The pre-merging device according to claim 7, wherein the decomposing device is configured to: - continue grouping each group of array signals to obtain more sub-array signals, thereby respectively respectively sub-groups in each group of array signals The array signal performs a pre-merge operation.

A receiver device in a base station, the receiver device comprising one or more pre-merging devices according to any one of claims 7 to 12.