CN107566020B - Sea area downlink multi-user hybrid precoding method and equipment - Google Patents

Sea area downlink multi-user hybrid precoding method and equipment Download PDF

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CN107566020B
CN107566020B CN201710571997.XA CN201710571997A CN107566020B CN 107566020 B CN107566020 B CN 107566020B CN 201710571997 A CN201710571997 A CN 201710571997A CN 107566020 B CN107566020 B CN 107566020B
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冯伟
刘承骁
葛宁
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Tsinghua University
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Abstract

The invention provides a sea area downlink multi-user hybrid precoding method and equipment, which are used for solving the problems that a part of users are far away from a shore base station, the small-scale effect of channels of the users is difficult to estimate, and the communication quality cannot be ensured. The sea area downlink multi-user hybrid pre-coding method comprises the following steps: calculate one by one
Figure DDA0001349914460000011
Obtaining a digital precoding matrix of
Figure DDA0001349914460000012
Wherein the content of the first and second substances,
Figure DDA0001349914460000013
is the downlink power vector and is the downlink power vector,
Figure DDA0001349914460000014
is a complex unit vector. The invention ensures the fairness among the downlink users by utilizing the originating precoding, thereby ensuring that the speed of all the downlink users can be higher than a certain standard line and realizing the broadband coverage of the downlink users.

Description

Sea area downlink multi-user hybrid precoding method and equipment
Technical Field
The invention relates to a communication technology, in particular to a sea area downlink multi-user hybrid precoding method and equipment.
Background
The sea area range of China is wide, the continental coastline is long, and the ocean economy is very active. In order to meet the application requirements of pleasure boats, business boats, fishing boats, sea prisoners and the like, guarantee the navigation safety of offshore sea areas, promote the quality of life of sea-related personnel, and promote the further development of marine economy, the development of sea area broadband communication technology is urgently needed. The existing LTE network body is covered on land, emphasizes on solving the communication problem of urban areas and suburban areas, and technically depends on large-range dense station arrangement. Base stations are difficult to build on the sea surface, so that the base stations of the sea area broadband communication network can only be built along the shore, and thus, the network topology is severely limited and the system performance is difficult to guarantee.
The development of sea area broadband communication cannot be started from scratch, and one feasible technical approach is to modify the current ground communication LTE technology. In order to adapt to channel characteristics and User distribution in offshore sea areas, a Multi-User Multi-antenna (Multi-User MIMO) system can be formed with offshore users by deploying an overhead base station (shore base station) with a large-scale antenna array on the coast, so that the communication rate and the service quality are improved. However, under the constraint of the base station site, the coverage of the LTE network is limited, and since the site selection of the elevated base station is limited by geographical conditions, the classical LTE network is difficult to realize continuous broadband coverage along the coastline, and under the narrow-band global coverage, each shore base station covers a sea area, so that a broadband information port is formed. The navigation ship enters an information port, accesses a network in the coverage range of a shore base station and enjoys broadband service; at other times, the user can enjoy narrow-band communication service, and the basic safe navigation requirement is met.
The above-mentioned communication systems in the harbor area are very different from the terrestrial communication systems in channel estimation. In the communication system of this form, some users are far away from the shore base station, and it is difficult to estimate the small-scale effect of the channel of these users, and the communication quality cannot be guaranteed.
Disclosure of Invention
In view of the above problems, the present invention proposes a method and apparatus for sea area downlink multi-user hybrid precoding that overcomes or at least partially solves the above problems.
To this end, in a first aspect, the present invention provides a method for sea area downlink multi-user hybrid precoding, which is characterized by comprising the steps of:
calculate one by one
Figure BDA0001349914440000021
Obtaining a digital precoding matrix of
Figure BDA0001349914440000022
Wherein the content of the first and second substances,
Figure BDA0001349914440000023
is the downlink power vector and is the downlink power vector,
Figure BDA0001349914440000024
is a complex unit vector;
Figure BDA0001349914440000025
calculated by the following way:
Figure BDA0001349914440000026
for simulating a precoding matrix, K is the number of users, and the channel vector expression corresponding to the kth user is
Figure BDA0001349914440000027
Wherein
Figure BDA0001349914440000028
A phase deviation vector of the originating antenna is represented,
Figure BDA0001349914440000029
is part of the channel large scale effect; dkIndicating the distance from the kth user to the base station, β being the energy attenuation coefficient, αl,kRepresents the small scale effect of the channel due to channel fading α in a sea communication systeml,kIs difficult to estimate, but it can be assumed that it is subject to the standardα of quasi-complex Gaussian distributed random variables with different indicesl,kAre independent of each other. Defining an equivalent channel matrix A for the kth userkIs composed of
Figure BDA00013499144400000210
Is provided with
Figure BDA0001349914440000031
Order to
Figure BDA0001349914440000032
Constructing two matrixes D and omega;
Figure BDA0001349914440000033
Figure BDA0001349914440000034
Figure BDA0001349914440000035
construction vector
Figure BDA0001349914440000036
In order to be a vector of the noise,
Figure BDA0001349914440000037
is a K-dimensional all-1 vector,
Figure BDA0001349914440000038
is the user power of the equivalent uplink channel; h denotes a conjugate transposed symbol.
Solving the digital precoding matrix F using the following iterative methodBBWhere the variable x in the iteration of step n is represented by x(n)Denotes epsilon1、ε2To cut-off threshold, pt、qtAs temporary variables:
when in use
Figure BDA0001349914440000039
Or
Figure BDA00013499144400000310
Time of flight
Computing
Figure BDA00013499144400000311
Updating downlink power, and normalizing:
Figure BDA00013499144400000312
computing
Figure BDA00013499144400000313
Updating uplink power, and normalizing:
Figure BDA00013499144400000314
for i ═ 1: K
Construction matrix
Figure BDA00013499144400000315
Figure BDA00013499144400000316
Then the nth step is the best beamforming vector for the ith user
Figure BDA00013499144400000317
Is that
Figure BDA00013499144400000318
And
Figure BDA00013499144400000319
generalized eigenvector corresponding to maximum generalized eigenvalue
Figure BDA00013499144400000320
Ending the circulation;
updating D according to definition(n)、Ω(n)；
The loop is exited.
I assume all
Figure BDA0001349914440000041
Are all equal and the specific value is actually the power level of the noise. For example in a simulated embodiment of the present application,
Figure BDA0001349914440000042
the value is-106 dBm.
Optionally, calculating the analog precoding matrix FRFComprises the following steps:
let FtIs formed by all possible phase deviation vectors
Figure BDA0001349914440000043
A matrix of compositions then having
Figure BDA0001349914440000044
FRFEach column of (1) is from FtGet in the matrix, and FRFIs F in the kth columntMiddle school messenger
Figure BDA0001349914440000045
Largest size
Figure BDA0001349914440000046
Namely, it is
For K to 1: K
Let i ═ argmaxdiag (F)t HAkFt)
Get
Figure BDA0001349914440000047
The loop is ended.
In a second aspect, the invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method as set forth in any one of the above.
In a third aspect, the present invention provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of any of the methods described above when executing the program.
The technical scheme can be seen that the invention provides a downlink multi-user hybrid precoding scheme based on the maximum and minimum criterion, which is suitable for application scenarios of a multi-user multi-antenna sea area communication system, and aims to ensure fairness among downlink users by using originating precoding under the premise that channel small-scale information is unknown, so that the rates of all downlink users can be higher than a certain standard line, and downlink multi-user broadband coverage is realized.
The foregoing is a brief summary that provides an understanding of some aspects of the invention. This section is neither exhaustive nor exhaustive of the invention and its various embodiments. It is neither intended to identify key or critical features of the invention nor to delineate the scope of the invention but rather to present selected principles of the invention in a simplified form as a brief introduction to the more detailed description presented below. It is to be understood that other embodiments of the present invention are possible utilizing, alone or in combination, one or more of the features set forth above or described in detail below.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow chart illustrating steps performed in one embodiment of the present invention.
Detailed Description
The present invention will be described in connection with an exemplary communication system.
The invention provides a downlink multi-user hybrid pre-coding scheme based on a maximum and minimum criterion, which is suitable for application scenes of a multi-user multi-antenna sea area communication system and aims to ensure fairness among downlink users by using originating pre-coding under the premise that channel small-scale information is unknown, so that the speed of all downlink users can be higher than a certain standard line, and the broadband coverage of downlink multi-users is realized.
In the sea area communication system according to an embodiment of the present invention, the number of users K is 6, the number of antennas M is 128, the number of paths L of the multipath channel is 3, and it is assumed that noise power of all users is-106 dBm. When comparing the performance, the variable of the abscissa of the curve is the originating power P, changes from 0dBm to 50dBm, and imitates a point every 5dBm on the curve; the variable of the ordinate is the user minimum rate R, and the calculation method is that the SINR newly defined in the present scheme is adopted here. In the simulation process, firstly, 6 user positions are randomly generated within the range of 1km to 100km, and angles are randomly generated in an interval according to uniform distribution of each path of each user, so that a simulation channel is generated.
In the conventional precoding scheme, since the channel information is completely known, the SINR of the kth user is generally written as
Figure BDA0001349914440000061
When the channel information part is known however,
Figure BDA0001349914440000062
is a random vector, so the SINR of the present invention cannot be calculated by the above equation. Then the SINR needs to be measured at the angle of statistical averaging, and then the SINR of user k can be written as
Figure BDA0001349914440000063
The above formula can be expressed as after simplification
Figure BDA0001349914440000064
Wherein A iskIs expressed as
Figure BDA0001349914440000065
In an embodiment of the present invention, a method for sea area downlink multi-user hybrid precoding includes the steps of: calculating an analog precoding matrix FRFAnd calculating a digital precoding matrix FBB。
Calculating an analog precoding matrix FRFComprises the following steps:
let FtIs formed by all possible phase deviation vectors
Figure BDA0001349914440000066
A matrix of compositions then having
Figure BDA0001349914440000067
FRFEach column of (1) is from FtGet in the matrix, and FRFIs F in the kth columntMiddle school messenger
Figure BDA0001349914440000068
Largest size
Figure BDA0001349914440000069
Namely, it is
For K to 1: K
Let i ═ argmaxdiag (F)t HAkFt)
Get
Figure BDA00013499144400000610
The loop is ended.
The step of calculating the digital precoding matrix comprises:
calculate one by one
Figure BDA0001349914440000071
Obtaining a digital precoding matrix of
Figure BDA0001349914440000072
Wherein the content of the first and second substances,
Figure BDA0001349914440000073
is the downlink power vector and is the downlink power vector,
Figure BDA0001349914440000074
is a complex unit vector;
Figure BDA0001349914440000075
calculated by the following way:
Figure BDA0001349914440000076
for simulating the precoding matrix, K is the number of users
Figure BDA0001349914440000077
Order to
Figure BDA0001349914440000078
Constructing two matrixes D and omega;
Figure BDA0001349914440000079
Figure BDA00013499144400000710
Figure BDA00013499144400000711
construction vector
Figure BDA00013499144400000712
In order to be a vector of the noise,
Figure BDA00013499144400000713
is a K-dimensional all-1 vector,
Figure BDA00013499144400000714
is the user power of the equivalent uplink channel;
using the following iterative methodDecoding the digital precoding matrix FBBWhere the variable x in the iteration of step n is represented by x(n)Denotes epsilon1、ε2As a cutoff threshold:
when in use
Figure BDA00013499144400000715
Or
Figure BDA00013499144400000716
Time of flight
Computing
Figure BDA00013499144400000717
Updating downlink power, and normalizing:
Figure BDA00013499144400000718
computing
Figure BDA00013499144400000719
Updating uplink power, and normalizing:
Figure BDA00013499144400000720
for i ═ 1: K
Construction matrix
Figure BDA00013499144400000721
Figure BDA00013499144400000722
Then the nth step is the best beamforming vector for the ith user
Figure BDA00013499144400000723
Is that
Figure BDA00013499144400000724
And
Figure BDA00013499144400000725
maximum breadthGeneralized eigenvector corresponding to semantic eigenvalue
Figure BDA00013499144400000726
Ending the circulation;
updating D according to definition(n)、Ω(n)；
The loop is exited.
The simulation experiment is carried out on the traditional pure digital precoding and hybrid precoding schemes, and the small-scale fading parameters α of the channel are causedl,kUnknown, the channel vector for each user can be expressed as
Figure BDA0001349914440000081
Conventional methods in simulation experiments all generate a conventional precoding matrix based on this channel. Simulation shows that when the channel information part is known, under different transmission power conditions, the scheme of the invention can obtain higher gain compared with the traditional precoding scheme.
The invention considers the characteristics of easy estimation of large-scale fading and difficult estimation of small-scale fading information of sea area channels, defines a new signal-to-interference-and-noise ratio expression, designs a hybrid precoding scheme based on the maximum and minimum criterion, greatly improves the lowest rate of a user compared with the traditional precoding method under the condition that the channel information part is known, and realizes the system broadband coverage.
The invention provides a computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method as set forth in any of the above.
The invention provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of any of the methods described above when executing the program.
As used herein, "monitoring" includes any type of function associated with observing, recording or detecting with an instrument that does not have any effect on the operation or status of the element or group of elements being monitored.
As used herein, "at least one," "one or more," and/or "are open-ended expressions that can be combined and separated when used. For example, "at least one of A, B and C," "at least one of A, B or C," "one or more of A, B and C," and "one or more of A, B or C" mean a alone, B alone, C, A and B together, a and C together, B and C together, or A, B and C together.
The term "a" or "an" entity refers to one or more of that entity. Thus the terms "a", "an", "one or more" and "at least one" are used interchangeably herein. It should also be noted that the terms "comprising," "including," and "having" are also used interchangeably.
The term "automated" and variations thereof as used herein refers to any process or operation that is completed without substantial human input when the process or operation is performed. However, a process or operation may be automated even if substantial or insubstantial human input received prior to performing the process or operation is used in performing the process or operation. An artificial input is considered essential if the input affects how the process or operation will proceed. Human input that does not affect the processing or operation is not considered essential.
The term "computer-readable medium" as used herein refers to any tangible storage device and/or transmission medium that participates in providing instructions to a processor for execution. The computer readable medium may be a serial set of instructions encoded in a network transport (e.g., SOAP) over an IP network. Such a medium may take many forms, including but not limited to, non-volatile media, and transmission media. Non-volatile media includes, for example, NVRAM or magnetic or optical disks. Volatile media include dynamic memory, such as main memory (e.g., RAM). Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, or any other magnetic medium, magneto-optical medium, a CD-ROM, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, a PROM, an EPROM, a FLASH-EPROM, a solid state medium such as a memory card, any other memory chip or cartridge, a carrier wave as described hereinafter, or any other medium from which a computer can read. Digital file attachments to e-mail or other self-contained information archives or sets of archives are considered distribution media equivalent to tangible storage media. When the computer readable medium is configured as a database, it should be understood that the database may be any type of database, such as a relational database, a hierarchical database, an object-oriented database, and the like. Accordingly, the present invention is considered to include a tangible storage or distribution medium and equivalents of the prior art known as well as future developed media in which to store a software implementation of the present invention.
The terms "determine," "calculate," and "compute," and variations thereof, as used herein, are used interchangeably and include any type of methodology, process, mathematical operation or technique. More specifically, such terms may include interpreted rules or rule languages such as BPEL, where logic is not hard coded but represented in a rule file that can be read, interpreted, compiled, and executed.
Although the embodiments have been described, once the basic inventive concept is obtained, other variations and modifications of these embodiments can be made by those skilled in the art, so that the above embodiments are only examples of the present invention, and not intended to limit the scope of the present invention, and all equivalent structures or equivalent processes using the contents of the present specification and drawings, or any other related technical fields, which are directly or indirectly applied thereto, are included in the scope of the present invention.

Claims (3)

1. A sea area downlink multi-user hybrid precoding method is characterized by comprising the following steps:
calculate one by one
Figure FDA0002363176340000011
Obtaining a digital precoding matrix of
Figure FDA0002363176340000012
Wherein the content of the first and second substances,
Figure FDA0002363176340000013
is the downlink power vector and is the downlink power vector,
Figure FDA0002363176340000014
is a complex unit vector;
Figure FDA0002363176340000015
calculated by the following way:
Figure FDA0002363176340000016
for simulating the precoding matrix, K is the number of users
Figure FDA0002363176340000017
Order to
Figure FDA0002363176340000018
Constructing two matrixes D and omega;
Figure FDA0002363176340000019
Figure FDA00023631763400000110
Figure FDA00023631763400000111
construction vector
Figure FDA00023631763400000112
In order to be a vector of the noise,
Figure FDA00023631763400000113
is a K-dimensional all-1 vector,
Figure FDA00023631763400000114
is the user power of the equivalent uplink channel;
solving the digital precoding matrix F using the following iterative methodBBWhere the variable x in the iteration of step n is represented by x(n)Denotes epsilon1、ε2As a cutoff threshold:
when in use
Figure FDA00023631763400000115
Or
Figure FDA00023631763400000116
Time of flight
Computing
Figure FDA00023631763400000117
Updating downlink power, and normalizing:
Figure FDA00023631763400000118
computing
Figure FDA00023631763400000119
Updating uplink power, and normalizing:
Figure FDA00023631763400000120
for i ═ 1: K
Construction matrix
Figure FDA0002363176340000021
Then the nth step is the best beamforming vector for the ith user
Figure FDA0002363176340000022
Is that
Figure FDA0002363176340000023
And
Figure FDA0002363176340000024
generalized eigenvector corresponding to maximum generalized eigenvalue
Figure FDA0002363176340000025
Ending the circulation;
updating D according to definition(n)、Ω(n)；
Exiting the loop;
wherein A iskIs the equivalent channel matrix for the kth user,
Figure FDA0002363176340000026
in the case of a temporary variable,
Figure FDA0002363176340000027
is a temporary variable, P is the power value used for normalization;
wherein an analog precoding matrix F is calculatedRFComprises the following steps:
let FtIs formed by all possible phase deviation vectors
Figure FDA0002363176340000028
A matrix of compositions then having
Figure FDA0002363176340000029
FRFEach column of (1) is from FtGet in the matrix, and FRFIs F in the kth columntMiddle school messenger
Figure FDA00023631763400000210
Largest size
Figure FDA00023631763400000211
Namely:
for K to 1: K
Order to
Figure FDA00023631763400000212
Get
Figure FDA00023631763400000213
The loop is ended.
2. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method as claimed in claim 1.
3. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method as claimed in claim 1 are implemented when the processor executes the program.
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* Cited by examiner, † Cited by third party
Title
Improving the Performance of DL Massive MIMO in the Presence of Composite Fading;Amrita Ruperee 等;《IEEE International Conference on Recent Trends in Electronics Information Communication Technology》;IEEE;20160521;第2107-2111页 *
Max-Min Fair Joint Precoding for Multibeam Satellite Communication Systems;Hongjun LI 等;《6th International Conference on Information Science and Technology》;IEEE;20160508;第437-442页 *
一种海上无线信道小尺度衰落特性的测试及分析方法;詹金晶;《水雷战与舰船防护》;20110831;第19卷(第3期);第52-54页 *
分布式无线通信系统下行功率分配策略;冯伟 等;《清华大学学报》;20090731;第49卷(第7期);第998-1001页 *

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