CN108206712B

CN108206712B - Method and device for carrying out pre-combination processing on uplink massive MIMO signals

Info

Publication number: CN108206712B
Application number: CN201611177507.XA
Authority: CN
Inventors: 何大中
Original assignee: Nokia Shanghai Bell Co Ltd
Current assignee: Nokia Shanghai Bell Co Ltd
Priority date: 2016-12-19
Filing date: 2016-12-19
Publication date: 2021-04-27
Anticipated expiration: 2036-12-19
Also published as: WO2018115966A1; CN108206712A

Abstract

The invention aims to provide a method and a device for carrying out pre-combination processing on uplink massive MIMO signals in a base station. The method according to the invention comprises the following steps: decomposing a covariance array signal of uplink channel estimation from the UE into a plurality of sub-array signals; and respectively solving the eigenvalue and the eigenvector of the long-term channel estimation covariance matrix corresponding to each subarray signal through a recursion algorithm until the algorithm of the basic pre-combination device can be solved in a recursion manner. Compared with the prior art, the invention has the following advantages: by decomposing and grouping the signal arrays corresponding to the uplink signals and respectively carrying out long-term smooth pre-combination processing on each array group, the processing of large-scale array signals is realized, the computational complexity of the multi-antenna uplink large-scale MIMO receiver is reduced, and the signal processing efficiency is improved.

Description

Method and device for carrying out pre-combination processing on uplink massive MIMO signals

Technical Field

The present invention relates to the field of mobile communications technologies, and in particular, to a method and an apparatus for performing pre-combining processing on uplink massive MIMO signals in a base station.

Background

In the best large-scale (massize) MIMO scheme available, the conventional design of these receivers generally has to follow three main factors, high performance, low cost, and the use of multiple antennas at the transmitting and receiving ends to process the wireless complex received signal.

In conventional receivers, a large amount of signal processing may be implemented in Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), and Field Programmable Gate Arrays (FPGAs). By using a Frequency Synthesizer (FS), a Power Amplifier (PA), a Low Noise Amplifier (LNA), an uplink and downlink converting circuit, a radio frequency front end and a transmitting/receiving antenna, and connecting signals of a baseband part to a radio frequency circuit, such a processing manner of the existing receiver easily causes excessive signal processing and signal detection, resulting in poor performance, high cost and more complexity of the processing manner.

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

In a conventional single-user or multi-user MIMO (8T8R) system, the physical antenna array and MIMO channels are two-dimensional — such as 2x 4 cross-polarized array antennas. Based on the design, the use in the horizontal direction can be realized only at the UE end.

If three-dimensional antenna arrays such as 64, 128 or 256 or more are used, the complexity of the signal processing becomes high, and the cost increases.

Disclosure of Invention

The invention aims to provide a method and a device for carrying out pre-combination processing on uplink massive MIMO signals in a base station.

According to an aspect of the present invention, there is provided a method for pre-combining uplink massive MIMO signals in a base station, wherein the method comprises the following steps:

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

and b, respectively solving the eigenvalue and the eigenvector of the long-term channel estimation covariance matrix corresponding to each subarray signal through a recursion algorithm.

According to an aspect of the present invention, there is provided a pre-combining apparatus for pre-combining uplink massive MIMO signals in a base station, wherein the pre-combining apparatus comprises:

decomposing means for decomposing the covariance array signal of the high-order uplink channel estimation from the UE into a plurality of sub-array signals in a reduced order;

and the plurality of sub-precombinations are used for respectively solving the eigenvalues and the eigenvectors of the long-term covariance matrix corresponding to each subarray signal through a recursion algorithm until the algorithm of the basic precombinations can be solved through recursion.

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

Compared with the prior art, the invention has the following advantages: by decomposing and grouping the signal arrays corresponding to the uplink signals and respectively carrying out long-term smooth pre-combination processing on each array group, the processing of large-scale array signals is realized, the computational complexity of the multi-antenna uplink large-scale MIMO receiver is reduced, and the signal processing efficiency is improved.

Drawings

Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments made with reference to the following drawings:

fig. 1 shows a flowchart of a method for pre-combining uplink massive MIMO signals in a base station according to the present invention;

fig. 2 is a schematic structural diagram of a pre-combining apparatus for pre-combining uplink massive MIMO signals according to the present invention;

FIG. 3a shows a schematic diagram of an exemplary pre-merge device according to the present invention;

FIG. 3b shows a schematic diagram of an exemplary basic precombinations apparatus according to the present invention;

fig. 4 shows a packet diagram of an exemplary antenna array according to the present invention;

FIG. 5 is a diagram illustrating an exemplary process of solving a channel covariance matrix according to the invention;

fig. 6 shows a packet diagram of an exemplary antenna array according to the present invention;

fig. 7 shows a schematic diagram of an exemplary process for solving the channel covariance matrix according to the present invention.

The same or similar reference numbers in the drawings identify the same or similar elements.

Detailed Description

The present invention is described in further detail below with reference to the attached drawing figures.

Fig. 1 shows a flowchart of a method for pre-combining uplink massive MIMO signals in a base station according to the present invention. The method according to the present invention includes step S1 and step S2.

The method according to the present invention is implemented by a pre-combining apparatus included in a 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, including but not limited to cell phones, PDAs, etc., that can communicate with the base station directly or indirectly in a wireless manner.

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

Referring to fig. 1, in step S1, the precombining 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 a 64x64 or 128x128 array signal.

Preferably, the precombining means continues to group each group of array signals to obtain more sub-array signals, so as to perform precombining operation on each sub-array signal in each group of array signals. For example, 128x128 is divided into two groups of 64x64 array signals, and each 64x64 signal is divided into 4 16x16 signals, so that each 16x16 array signal is pre-combined.

Preferably, the pre-combining means may decompose the covariance array signal of the uplink channel estimation multiple times, so as to obtain 256 × 256 or even higher order antenna array signals.

In step S2, the pre-combining device solves the eigenvalue and eigenvector of the long-term covariance matrix corresponding to each subarray signal by a recursive algorithm, respectively, until the algorithm of the basic pre-combining device can be solved by recursion.

Wherein the basic precombining means is used to indicate the minimum precombining means that processes the array signals that cannot be decomposed.

For example, reference is made to an exemplary pre-merge device according to the present invention shown in fig. 3 a. The precombining means shown in fig. 3a includes 4 sub-precombiners 1 to Precombiner4 and their corresponding receiving end devices, and precombiners 1 to Precombiner4 are basic precombining means. Fig. 3b shows a schematic structure diagram of each basic pre-merging device in fig. 3 a. Referring to fig. 3a, the array signal input to the precombining means is divided into 4 sub-array signals of 16 AxC. Each 16AxC sub-array signal is decomposed into a 4AxC or 8AxC array signal by a sub-precombining device, and for a multi-User (MU) scene at a receiving end, an MMSE algorithm (8 rx MU) of 8 receiving ends can be adopted, and for a Single-User (SU) scene, an IRC algorithm (4rx IRC) of 4 receiving ends can be adopted.

According to a preferred embodiment of the present invention, the pre-combining means performs a pre-combining process on the array signal in a user specific manner, and the method includes step S1, step S201 (not shown), and step S3 (not shown).

In step S201, the pre-combining apparatus solves eigenvalues and eigenvectors of the long-term channel estimation covariance matrix corresponding to a particular UE.

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

Preferably, in order to reduce interference of a specific UE to other UEs, the method includes step S4.

In step S4, the pre-combining means solves the eigenvalues and eigenvectors of the long-term channel estimation covariance matrix corresponding to a particular UE so that the UE obtains the maximum SINR.

Preferably, let y be_kRepresents the receiving end signal, then y_kCan be expressed by the following formula:

y_k＝P_kH_kx_k+∑_j≠kP_kH_jx_j+n_k (1)

wherein, represents user k (user k), P_kRepresenting the signal after pre-combining, H_kRepresenting the uplink channel estimation matrix from the user k to the base station.

Based on equation (1), if the signal power satisfying user k is maximum, we obtain:

preferably, in order to reduce signal leakage of the user k to other UEs, considering tapering (tapering) of side lobe reduction (side lobe reduction) and making SINR of the user k maximum, then we obtain:

according to a preferred embodiment of the present invention, the pre-combining means performs pre-combining processing on the array signals in a group specific manner, and the method includes step S1, step S202 (not shown), and step S5 (not shown).

In step S202, the pre-combining apparatus solves eigenvalues and eigenvectors of the long-term channel estimation covariance matrix corresponding to a group of UEs.

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

Preferably, based on equation (1), for a set of users { k, m }, the signal power satisfying user k, m is maximum, which results in:

preferably, to reduce the signal leakage of user k, m to other UEs, a gradual change of sidelobe suppression is considered.

According to a preferred embodiment of the present invention, after the step S2, the method includes a step S6 (not shown)

In step S6, the precombining means performs a signal scaling operation on the plurality of sub-array signals to perform subsequent equalization and combination processing on the scaled sub-signal matrices.

The following is illustrated by 5 exemplary algorithms based on the present invention.

Example 1: pre-merging algorithm of specific user (user specific)

Referring to fig. 4, the antenna array is divided into 4 groups of arrays, the interior of which are highly correlated. Specifically, the method comprises the following steps:

-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

Wherein the content of the first and second substances,

is a channel estimation matrix based on user i and sub-array m (in this example, m is 16) measured by an uplink reference signal (SRS).

-a long-term weight matrix w for each sub-array_LT,i,mIs R_hh,i,mThe first feature vector of (a);

-a full long-term weight matrix w_LT,i,mIs W_LT,i,mBlock diagonal matrix (block diagonal matrix).

Wherein the process of solving the channel covariance matrix in the algorithm is shown in fig. 5.

For a multi-user (MU) scenario, the receiving end may use an MMSE algorithm (8R x MU) with 8 receiving ends, and for a single-user (SU) scenario, an IRC algorithm (4R x IRC) with 4 receiving ends.

Example 2: gradual change algorithm of specific user (user specific)

Continuing with the grouping of antenna arrays shown in fig. 4, the long-term covariance matrix for each antenna array group is obtained based on the following steps:

-long-term covariance matrix of horizontal and vertical domains expressed as

And

-deriving a channel covariance matrix for each row of antennas based on the 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 the covariance matrix in the horizontal direction

-the horizontal direction covariance matrix of UE i is represented as

Wherein h is_i ^HIs a 1x8 channel vector from the UE uplink reference signal (SRS) port to the eNB's 8TRX for each polarized antenna and each PRB for each row of antennas;

similarly, the vertical covariance matrix of UE i is expressed as

Wherein h is_i ^VIs a 1x4 channel vector for each polarized antenna and each PRB for each column of antennas based on SRS measurements;

for a multi-user (MU) scenario, the receiving end may use an MMSE algorithm (8R × MU) with 8 receiving ends, and for a single-user (SU) scenario, an IRC algorithm (4Rx IRC) with 4 receiving ends.

Wherein, a precoding matrix of Beamforming (BF) weights can be obtained by the following steps:

-setting a set of beam steering vectors S, S being expressed as:

where N denotes an antenna number, N denotes the number of TRXs connected to the antenna, and 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), sidelobe suppression of 30 dB;

-W → W ═ S · chebwin, S ∈ S };

finding the maximum beamforming gain for UE i, then we get:

horizontal direction:

vertical direction:

-through wiH and

the kronecker product of (K) is weighted by BF (taken to correspond to

2x1 vector).

Example 3: maximum SINR algorithm for specific user (user specific)

With continued reference to the antenna grouping shown in fig. 4, the antenna array is shown divided into 4 arrays, which are highly correlated within the array. Specifically, the method comprises the following steps:

the channel covariance matrix of-user i and sub-array m is

Wherein the content of the first and second substances,

the channel estimation matrix is based on user i and subarray m obtained by SRS measurement.

-a long-term weight matrix w for each sub-array_LT,i,mIs the generalized eigenvector corresponding to the largest generalized eigenvalue of the matrix, expressed as:

<＝＝>

i.e. algorithm under received power maximization

A long-term weight matrix w_LT,i,mIs W_LT,i,mThe block diagonal matrix of (2).

Example 4: group specific (group specific) pre-merging algorithm

Referring to fig. 6, the antenna array is divided into 8 sub-arrays, inside which are highly correlated. Specifically, the method comprises the following steps:

-grouping the antenna arrays 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 sub-array m is

Wherein the content of the first and second substances,

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

-for user groups user i and j, a long-term weight matrix w for each subarray_LT,ij,m(8x1) is R_hh,i,m+R_hh,j,mA first eigenvector of (8x8+8x 8);

-for user groups user i and j, the full-length term weight matrix w_LT,ijIs w_LT,ij,mThe block diagonal matrix of (2).

Wherein the process of solving the solution channel covariance matrix in the algorithm is shown in fig. 7.

Example 5: group specific (group specific) fading algorithm

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

-long-term covariance matrix of horizontal and vertical domains expressed as

And

-deriving a channel covariance matrix for each row of antenna columns 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 subjected to long-term averaging and filtering smoothing in the time domain, so that a horizontal covariance matrix is obtained

-the horizontal direction covariance matrix of UE i is represented as

Wherein h is_i ^HIs a 1x8 channel vector of 8TRX by UE SRS port to eNB for each polarized antenna and each PRB per row antenna;

similarly, the vertical covariance matrix of UE i is expressed as

-for user groups user i and j, let R_i ^H＝R_i ^H+R_j ^H，R_i ^V＝R_i ^V+R_j ^V。

Also, in this example, the precoding matrix for obtaining Beamforming (BF) weights makes the step of maximizing beamforming gain for the group of UEs the same as or similar to the step in example 1, and is not repeated here.

In accordance with a preferred embodiment of the present invention, with reference to the antenna array shown in fig. a, the power difference of each UE after being faded and the power difference after being precombined are considered, wherein for 16 antennas in a sub-array, the ideal antenna signal power of the UE can be expressed as,

obtaining the equivalent antenna power of each UE through the multiplication of the precombination matrix of each user, and the equivalent antenna power is expressed as | h _ Ideal } PreComb_user|²。

Preferably, after the pre-combining, power variation occurs, and the PUSCH receiving end compensates for the final RSSI with 16 weights, which is represented as:

according to the method, the signal arrays corresponding to the uplink signals are decomposed and grouped, and the array groups are subjected to long-term smooth pre-combination processing respectively, so that the large-scale array signals are processed, the calculation complexity of the multi-antenna uplink large-scale MIMO receiver is reduced, and the signal processing efficiency is improved.

Fig. 2 is a schematic structural diagram of a pre-combining apparatus for pre-combining uplink massive MIMO signals according to the present invention.

Referring to fig. 1, the decomposition apparatus decomposes a covariance array signal of uplink channel estimation from a 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 decomposing means continues to group each group of array signals to obtain more sub-array signals, so as to perform a precombining operation on each sub-array signal in each group of array signals. For example, 128x128 is divided into two groups of 64x64 array signals, and each 64x64 signal is divided into 4 16x16 signals, so that each 16x16 array signal is pre-combined.

Preferably, the decomposition means may decompose the covariance array signal of the uplink channel estimation a plurality of times, so as to obtain 256 × 256 or even higher order antenna array signals.

The sub-pre-combination device solves the eigenvalue and the eigenvector of the long-term covariance matrix corresponding to each subarray signal through a recursion algorithm until the algorithm of the basic pre-combination device can solve the eigenvalue and the eigenvector in a recursion manner.

According to a preferred embodiment of the present invention, the pre-combining means performs a pre-combining process on the array signals in a user specific manner.

The sub-precombining means solves eigenvalues and eigenvectors of the long-term channel estimation covariance matrix corresponding to a particular UE.

Then, the pre-combining means solves a pre-coding matrix corresponding to a specific UE so that a beamforming gain for the UE is maximized.

Preferably, in order to reduce interference of a specific UE to other UEs, the pre-combining device solves eigenvalues and eigenvectors of a long-term covariance matrix corresponding to the specific UE so that the UE obtains the maximum SINR.

According to a preferred embodiment of the present invention, the pre-combining means performs pre-combining processing on the array signals in a group specific manner.

The sub-precombining means solves eigenvalues and eigenvectors of the long-term channel estimate covariance matrix corresponding to a group of UEs.

Then, the pre-combining means solves the pre-coding matrix corresponding to the group of UEs such that the beamforming gain for the group of UEs is maximized.

According to the scheme of the invention, the signal arrays corresponding to the uplink signals are decomposed and grouped, and the array groups are subjected to long-term smooth pre-combination processing respectively, so that the processing of large array signals is realized, the calculation complexity of the multi-antenna uplink large-scale MIMO receiver is reduced, and the signal processing efficiency is improved.

It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.

Claims

1. A method for pre-combining uplink massive MIMO signals in a base station, wherein the method comprises the steps of:

b, respectively solving the eigenvalue and the eigenvector of the long-term channel estimation covariance matrix corresponding to each subarray signal through a recursion algorithm until the algorithm of the basic pre-combination device can be solved in a recursion manner;

wherein the array signal is a large antenna array signal.

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

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

wherein the method further comprises the steps of:

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

3. The method of claim 2, wherein to reduce interference of a particular UE to other UEs, the method comprises:

-solving eigenvalues and eigenvectors of the long-term channel estimate covariance matrix corresponding to a particular UE so that the UE obtains the maximum SINR.

4. The method of claim 1, wherein the method precombinations the respective sub-signal matrices in a specific group, the step b comprising the steps of:

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

wherein the method further comprises the steps of:

-solving the precoding matrix corresponding to the group of UEs such that the beamforming gain is maximal for the group of UEs.

5. The method of claim 1, wherein after the step b, the method comprises the steps of:

-performing a signal scaling operation on the plurality of sub-array signals to perform subsequent equalization and combining processing on the scaled respective sub-signal matrices.

6. The method of claim 1, wherein the step a comprises the steps of:

and continuously grouping each group of array signals to obtain more sub-array signals, so as to respectively perform pre-combination processing on each sub-array signal in each group of array signals.

7. A pre-combining apparatus for pre-combining uplink massive MIMO signals in a base station, wherein the pre-combining apparatus is configured to:

decomposing means for decomposing an uplink channel estimation covariance array signal from the UE into a plurality of sub-array signals;

the sub-precombining devices are used for respectively solving the eigenvalue and the eigenvector of the long-term channel estimation covariance matrix corresponding to each subarray signal through a recursion algorithm until the algorithm of the basic precombining device can be solved through recursion;

wherein the array signal is a large antenna array signal.

8. The precombining device as claimed in claim 7, wherein the precombining device performs precombining operation on each array signal in a UE-specific manner, and the sub-precombining device is configured to:

wherein the pre-combining means is further configured to:

9. The pre-combining apparatus of claim 8, wherein to reduce interference of a particular UE to other UEs, the pre-combining apparatus is configured to:

10. The pre-combining apparatus as claimed in claim 7, wherein the pre-combining apparatus performs the pre-combining operation on the sub-signal matrices in a specific group manner, and the sub-pre-combining apparatus is configured to:

wherein the pre-combining means is further configured to:

11. The precombinations device of claim 7, wherein the precombinations device comprises:

and the scaling device is used for carrying out signal scaling operation on the plurality of sub-array signals so as to carry out subsequent equalization and combination processing on each scaled sub-signal matrix.

12. The precombining device of claim 7, wherein the decomposing device is configured to:

-continuing to group each group of array signals for obtaining more sub-array signals, thereby performing a precombining operation on each sub-array signal in each group of array signals.

13. Receiver apparatus in a base station, the receiver apparatus comprising one or more precombinations apparatus as claimed in any one of claims 7 to 12.