CN116232394A - A method for bottom layer cognitive user power allocation based on cell-free massive MIMO system - Google Patents

A method for bottom layer cognitive user power allocation based on cell-free massive MIMO system Download PDF

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CN116232394A
CN116232394A CN202310094784.8A CN202310094784A CN116232394A CN 116232394 A CN116232394 A CN 116232394A CN 202310094784 A CN202310094784 A CN 202310094784A CN 116232394 A CN116232394 A CN 116232394A
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power allocation
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戴予成
解志斌
王亚军
苏胤杰
练柱先
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Jiangsu University of Science and Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0426—Power distribution
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. Transmission Power Control [TPC] or power classes
    • H04W52/04—Transmission power control [TPC]
    • H04W52/18—TPC being performed according to specific parameters
    • H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
    • H04W52/241—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters taking into account channel quality metrics, e.g. SIR, SNR, CIR or Eb/lo
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. Transmission Power Control [TPC] or power classes
    • H04W52/04—Transmission power control [TPC]
    • H04W52/30—Transmission power control [TPC] using constraints in the total amount of available transmission power
    • H04W52/32—TPC of broadcast or control channels
    • H04W52/325—Power control of control or pilot channels
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

The invention discloses a bottom layer cognitive user power distribution method based on a cell-free large-scale MIMO system, which comprises the following steps: PU (polyurethane) k And SU respectively to AP l And AP (Access Point) m Transmitting pilot signals to the AP through a channel; AP (access point) l And AP (Access Point) m Projection of the received signal onto
Figure DDA0004071340750000012
And
Figure DDA0004071340750000013
performing minimum mean square error estimation; AP (Access Point) l And AP (Access Point) m Co-transmitting signalsPrecoding the yoke; obtaining PU according to the structure of the received signal k Establishing a power distribution function and environment correlation function relation, and calculating the minimum AP connection number M required by the SU according to the relation; calculating an SU optimal power allocation scheme; after obtaining the minimum AP connection number M needed by SU, the method is to set
Figure DDA0004071340750000011
How much power should be allocated to the SU by each AP in the system. The invention divides the users into the main users and the secondary users, can reduce the resources occupied by the secondary users and the interference to the main users, and effectively improves the receiving rate of the secondary users.

Description

一种基于无小区大规模MIMO系统的底层认知用户功率分配 方法A method for low-level cognitive user power allocation based on cell-free massive MIMO system

技术领域Technical Field

本发明属于无线通信技术领域，涉及一种基于无小区大规模MIMO系统的底层认知用户功率分配方法。The invention belongs to the technical field of wireless communications and relates to a bottom layer cognitive user power allocation method based on a cell-free large-scale MIMO system.

背景技术Background Art

随着通信用户数量历年来的激增，传统蜂窝系统中小区边缘用户受多个基站的影响，小区间干扰日益严重，为了解决这一问题，无小区大规模MIMO系统应运而生。在无小区大规模MIMO中，一个区域内分布大量接入点(AP)，用户在此区域内随机分布，但数量远少于接入点数，AP通过回程网络与中央处理器(CPU)进行信道统计信息和功率控制系数的交换。无小区大规模MIMO和认知无线电技术作为新一代移动通信中的关键技术，两者的结合是通信研究热点之一，无小区大规模MIMO天线分布众多，覆盖率高，用户与AP距离近，抗阴影衰弱的能力比较强，但频谱利用率仍然没有大幅提升，而认知无线电能通过区分主次用户充分利用频谱，在兼容更多用户的同时仍能提升频谱利用率。With the rapid increase in the number of communication users over the years, the cell edge users in the traditional cellular system are affected by multiple base stations, and the interference between cells is becoming increasingly serious. In order to solve this problem, the cell-free massive MIMO system came into being. In cell-free massive MIMO, a large number of access points (APs) are distributed in an area. Users are randomly distributed in this area, but the number is far less than the number of access points. APs exchange channel statistics and power control coefficients with the central processing unit (CPU) through the backhaul network. Cell-free massive MIMO and cognitive radio technology are key technologies in the new generation of mobile communications. The combination of the two is one of the hot topics in communication research. Cell-free massive MIMO antennas are distributed in large numbers, with high coverage, and users are close to APs. The ability to resist shadow fading is relatively strong, but the spectrum utilization rate has not been greatly improved. Cognitive radio can make full use of the spectrum by distinguishing primary and secondary users, and can improve the spectrum utilization rate while being compatible with more users.

目前在无小区大规模MIMO系统中，大多数考虑的都是对未分类的用户进行功率分配或者AP选择提升信道速率，没有考虑将用户分为主用户和次用户后再进行功率分配和AP选择。Currently, in non-cell massive MIMO systems, most of the considerations are to allocate power to unclassified users or select APs to improve channel rates, without considering classifying users into primary users and secondary users before performing power allocation and AP selection.

中国专利申请CN113365334A公开了一种无小区大规模MIMO系统中的导频分配和功率控制方法，该方法采用迫零预编码提前对发送信号进行处理，并在发送过程中通过max-min功率控制算法，优化了下行链路速率；中国专利CN110166088A公开了以用户为中心的无小区大规模MIMO系统的功率控制算法，该方法通过搜索最佳的功率控制系数实现最小用户速率的最大化；国际会议《ICC 2019-2019IEEE International Conference onCommunications(ICC)》中《Cell-Free Massive MIMO with Underlay Spectrum-Sharing》(Diluka Loku Galappaththige and Gayan Amarasuriya)将无小区大规模MIMO系统与认知无线系统相结合，研究了基于时分双工的无小区大规模MIMO和底层频谱共享共存的可行性。然而，以上技术存在以下缺陷：1.没有清晰划分主次用户，频谱利用率不高；2.用户和AP都是单天线，没有考虑多天线情况；3.将AP划分为主AP和辅助AP，在主用户过多次用户偏少的情况下造成了AP资源的浪费。Chinese patent application CN113365334A discloses a pilot allocation and power control method in a cell-free massive MIMO system. The method uses zero-forcing precoding to process the transmitted signal in advance, and optimizes the downlink rate through the max-min power control algorithm during the transmission process; Chinese patent CN110166088A discloses a user-centric power control algorithm for a cell-free massive MIMO system. The method maximizes the minimum user rate by searching for the optimal power control coefficient; "Cell-Free Massive MIMO with Underlay Spectrum-Sharing" (Diluka Loku Galappaththige and Gayan Amarasuriya) in the international conference "ICC 2019-2019IEEE International Conference on Communications (ICC)" combines the cell-free massive MIMO system with the cognitive wireless system, and studies the feasibility of coexistence of cell-free massive MIMO and underlying spectrum sharing based on time division duplexing. However, the above technologies have the following defects: 1. There is no clear division between primary and secondary users, and the spectrum utilization rate is low; 2. Both users and APs have single antennas, and multi-antenna situations are not considered; 3. APs are divided into primary APs and auxiliary APs, which causes a waste of AP resources when there are too many primary users and too few users.

发明内容Summary of the invention

本发明的目的在于克服现有技术的缺陷，提供一种基于无小区大规模MIMO系统的底层认知用户功率分配方法，将用户分为主用户和次用户后，在尽可能减少占用主用户资源和降低对主用户干扰的前提下。通过综合考虑信道大尺度衰落系数、AP功率权重系数，选择最少的AP数目得到最优功率分配方案，最大化次用户接收速率，提升次用户通信质量，从而有效解决频谱利用率不足和多天线AP的分布式传输问题。The purpose of the present invention is to overcome the defects of the prior art and provide a method for power allocation of bottom-layer cognitive users based on a cell-free large-scale MIMO system. After dividing users into primary users and secondary users, the method minimizes the occupation of primary user resources and reduces interference to primary users. By comprehensively considering the large-scale fading coefficient of the channel and the AP power weight coefficient, the minimum number of APs is selected to obtain the optimal power allocation scheme, maximize the secondary user receiving rate, and improve the communication quality of the secondary user, thereby effectively solving the problem of insufficient spectrum utilization and distributed transmission of multi-antenna APs.

为实现上述目的，本发明采用以下技术方案。To achieve the above objectives, the present invention adopts the following technical solutions.

一种基于无小区大规模MIMO系统的底层认知用户功率分配方法，在无小区大规模MIMO系统区域内随机分布L个带有N根天线的AP，K个主用户PU，一个次用户SU，主用户和次用户均为单天线用户，L＞＞K；所述的L>0、N>0、K>0；用

Figure BDA0004071340730000021
和
Figure BDA0004071340730000022
分别表示AP集合和PU集合，用APl表示集合中第l个AP，PUk表示集合中第K个PU；SU作为短暂出现在该区域中的单天线用户，进入区域后尽可能选取最少数量AP进行连接，用动态集合
Figure BDA0004071340730000029
表示选取的AP集合，其中某个元素用APm来表示；A method for allocating power of underlying cognitive users based on a cell-free massive MIMO system, wherein L APs with N antennas, K primary users PUs, and a secondary user SU are randomly distributed in a cell-free massive MIMO system area, wherein both the primary user and the secondary user are single-antenna users, L>>K; wherein L>0, N>0, K>0; and
Figure BDA0004071340730000021
and
Figure BDA0004071340730000022
They represent the AP set and PU set respectively, AP l represents the lth AP in the set, and PU k represents the Kth PU in the set; SU is a single-antenna user that appears in the area briefly. After entering the area, it selects the minimum number of APs to connect to, using the dynamic set
Figure BDA0004071340730000029
represents the selected AP set, where an element is represented by AP m ;

所述方法，包括以下步骤：The method comprises the following steps:

步骤一、PUk和SU分别向APl和APm发送导频信号，导频信号在经过信道传输后到达AP；Step 1: PU k and SU send pilot signals to AP l and AP m respectively. The pilot signals reach AP after being transmitted through the channel.

步骤二、先将APl和APm接收到的信号投影到

Figure BDA0004071340730000023
和
Figure BDA0004071340730000024
上，再进行最小均方误差估计；Step 2: Project the signals received by AP l and AP m onto
Figure BDA0004071340730000023
and
Figure BDA0004071340730000024
Then, the minimum mean square error estimation is performed;

步骤三、APl和APm对发送信号进行共轭预编码处理；Step 3: AP 1 and AP m perform conjugate precoding processing on the transmitted signal;

步骤四、先根据接收信号的结构得到PUk、SU的接收速率表达式，然后建立功率分配函数和环境相关函数的关系式，之后通过关系式计算SU所需的最小AP连接数M；Step 4: First, the receiving rate expressions of PU k and SU are obtained according to the structure of the received signal, and then the relationship between the power allocation function and the environment-related function is established, and then the minimum number of AP connections M required by the SU is calculated through the relationship;

步骤五、计算SU最优功率分配方案；Step 5: Calculate the optimal power allocation scheme for SU;

在得到SU所需的最小AP连接数M后，需要对集合

Figure BDA0004071340730000025
中每个AP应该分配多少功率给SU进行计算。After obtaining the minimum number of AP connections M required by SU, the set
Figure BDA0004071340730000025
How much power should each AP allocate to SU for calculation.

具体地，在步骤一中，所述的PUk和SU分别向APl和APm发送导频信号，导频信号在经过信道传输后到达AP，具体过程包括：Specifically, in step 1, the PU k and SU send pilot signals to AP l and AP m respectively, and the pilot signals reach the AP after being transmitted through the channel. The specific process includes:

S1.1.PUk和SU分别向APl和APm发送导频信号：S1.1.PU k and SU send pilot signals to AP l and AP m respectively:

利用时分复用，将每个相干间隔分为三个部分：上行链路训练、上行链路数据传输、下行链路数据传输，不考虑上行链路数据传输；设τc＝196为相干间隔长度，τu为上行链路训练相干间隔长度，τd＝τc-τu为下行链路数据传输相干间隔长度，τc＜τd；PUk和SU分别向APl和APm发送长度为τu的导频序列

Figure BDA0004071340730000026
其中
Figure BDA0004071340730000027
Figure BDA0004071340730000028
By using time division multiplexing, each coherence interval is divided into three parts: uplink training, uplink data transmission, and downlink data transmission. Uplink data transmission is not considered. Let τ c = 196 be the coherence interval length, τ u be the uplink training coherence interval length, τ d = τ c -τ u be the downlink data transmission coherence interval length, τ c <τ d . PU k and SU send pilot sequences of length τ u to AP l and AP m respectively.
Figure BDA0004071340730000026
in
Figure BDA0004071340730000027
Figure BDA0004071340730000028

S1.2.导频信号在经过信道传输后到达AP：S1.2. The pilot signal reaches the AP after being transmitted through the channel:

信道模型为：The channel model is:

Figure BDA0004071340730000031
Figure BDA0004071340730000031

式中，gab表示第a个AP与第b个用户之间的信道向量，

Figure BDA0004071340730000032
表示第a个AP与第b个用户之间的大尺度衰落系数，dab表示第a个AP与第b个用户之间的距离，η表示路径衰落影响因子，取τ＝0.5，hab表示第a个AP与第b个用户之间的小尺度衰落向量，为N×1的向量，并且假设hab服从瑞利衰落，其中各元素为服从
Figure BDA0004071340730000033
的随机变量，
Figure BDA0004071340730000034
表示均值为0，方差为1的圆对称复高斯分布；Where gab represents the channel vector between the a-th AP and the b-th user,
Figure BDA0004071340730000032
represents the large-scale fading coefficient between the a-th AP and the b-th user, d ab represents the distance between the a-th AP and the b-th user, η represents the path fading influence factor, and takes τ = 0.5, h ab represents the small-scale fading vector between the a-th AP and the b-th user, which is a vector of N × 1, and it is assumed that h ab obeys Rayleigh fading, where each element obeys
Figure BDA0004071340730000033
A random variable,
Figure BDA0004071340730000034
represents a circularly symmetric complex Gaussian distribution with mean 0 and variance 1;

APl和APm端接收到的信号分别为：The signals received by AP l and AP m are:

Figure BDA0004071340730000035
Figure BDA0004071340730000035

Figure BDA0004071340730000036
Figure BDA0004071340730000036

(2)(3)式中，pp为每个导频符号的归一化发射信噪比，Wpl、Wpm为对应接收信号中N×τu的噪声矩阵，其中各元素为服从

Figure BDA0004071340730000037
的随机变量；glk、gmSU分别表示APl到PUk信道和APm到SU的信道；
Figure BDA0004071340730000038
分别表示PUk和SU发送的导频序列的共轭转置。(2) (3) In formula, p p is the normalized transmit signal-to-noise ratio of each pilot symbol, W pl and W pm are the noise matrices of N × τ u in the corresponding received signal, and each element is subject to
Figure BDA0004071340730000037
random variables; g lk , g mSU represent the channel from AP l to PU k and the channel from AP m to SU respectively;
Figure BDA0004071340730000038
denote the conjugate transpose of the pilot sequences sent by PU k and SU respectively.

具体地，在步骤二中，所述的先将APl和APm接收到的信号投影到

Figure BDA0004071340730000039
和
Figure BDA00040713407300000310
上，再进行最小均方误差估计，其过程包括：Specifically, in step 2, the signals received by AP 1 and AP m are first projected onto
Figure BDA0004071340730000039
and
Figure BDA00040713407300000310
Then, the minimum mean square error estimation is performed, and the process includes:

S2.1.将Ypl和Ypm分别投影到

Figure BDA00040713407300000311
和
Figure BDA00040713407300000312
上：S2.1. Project Y pl and Y pm to
Figure BDA00040713407300000311
and
Figure BDA00040713407300000312
superior:

投影结果

Figure BDA00040713407300000313
分别表示为Projection results
Figure BDA00040713407300000313
Respectively expressed as

Figure BDA00040713407300000314
Figure BDA00040713407300000314

Figure BDA00040713407300000315
Figure BDA00040713407300000315

S2.2.进行最小均方误差估计：S2.2. Perform minimum mean square error estimation:

对信道glk和gmSU进行最小均方误差MMSE估计，计算得到的估计值

Figure BDA00040713407300000316
和
Figure BDA00040713407300000317
分别为：Perform minimum mean square error (MMSE) estimation on channels g lk and g mSU and calculate the estimated value
Figure BDA00040713407300000316
and
Figure BDA00040713407300000317
They are:

Figure BDA00040713407300000318
Figure BDA00040713407300000318

Figure BDA00040713407300000319
Figure BDA00040713407300000319

(6)(7)式中，

Figure BDA00040713407300000414
表示期望运算，
Figure BDA0004071340730000041
和
Figure BDA0004071340730000042
有N个独立相同的高斯分量；第n个分量的均方和可由υlk和υmSU表示：In formula (6) and (7),
Figure BDA00040713407300000414
represents the expectation operation,
Figure BDA0004071340730000041
and
Figure BDA0004071340730000042
There are N independent and identical Gaussian components; the mean square sum of the nth component can be expressed by υ lk and υ mSU :

Figure BDA0004071340730000043
Figure BDA0004071340730000043

Figure BDA0004071340730000044
Figure BDA0004071340730000044

具体地，在步骤三中，所述的APl和APm对发送信号进行共轭预编码处理，其过程包括：Specifically, in step 3, the AP 1 and the AP m perform conjugate precoding processing on the transmission signal, and the process includes:

APl向PUk发送的信号和APm向SU发送的信号，分别为The signal sent by AP l to PU k and the signal sent by AP m to SU are

Figure BDA0004071340730000045
Figure BDA0004071340730000045

Figure BDA0004071340730000046
Figure BDA0004071340730000046

(10)(11)式中，plk表示APl分配给PUk的功率权重，pm表示APm分配给SU的功率权重，P表示AP的最大归一化发射功率，

Figure BDA0004071340730000047
为
Figure BDA0004071340730000048
信道估计的共轭，sk、sSU表示APl、APm发送给PUk、SU的符号，
Figure BDA0004071340730000049
(10)(11) In formulas, p lk represents the power weight assigned by AP 1 to PU k , p m represents the power weight assigned by AP m to SU, and P represents the maximum normalized transmit power of AP.
Figure BDA0004071340730000047
for
Figure BDA0004071340730000048
The conjugate of the channel estimate, s k , s SU represents the symbol sent by AP l , AP m to PU k , SU,
Figure BDA0004071340730000049

具体地，所述的步骤四的具体过程包括：Specifically, the specific process of step 4 includes:

S4.1.根据接收信号的结构得到PUk、SU的接收速率表达式：S4.1. According to the structure of the received signal, the receiving rate expression of PU k and SU is obtained:

APk接收到的信号和SU接收到的信号分别为The signals received by AP k and SU are respectively

Figure BDA00040713407300000410
Figure BDA00040713407300000410

Figure BDA00040713407300000411
Figure BDA00040713407300000411

(12)(13)式中，

Figure BDA00040713407300000412
表示对应信道的转置，ωk、ωSU为对应接收信号中的加性噪声，其中各元素为服从
Figure BDA00040713407300000413
的随机变量；(12)(13) In formula,
Figure BDA00040713407300000412
represents the transpose of the corresponding channel, ω k and ω SU are the additive noise in the corresponding received signal, and each element is subject to
Figure BDA00040713407300000413
A random variable of

(12)(13)式可根据信号的构成展开写为：Equations (12) and (13) can be expanded according to the signal composition as follows:

Figure BDA0004071340730000051
Figure BDA0004071340730000051

Figure BDA0004071340730000052
Figure BDA0004071340730000052

PUk、SU端的接收速率可由下式给出：The receiving rate of PU k and SU can be given by the following formula:

Figure BDA0004071340730000053
Figure BDA0004071340730000053

(16)式中，SINR为信干噪比，PUk、SU端的信干噪比分别为：(16) In the formula, SINR is the signal to interference plus noise ratio. The signal to interference plus noise ratios of PU k and SU are:

Figure BDA0004071340730000054
Figure BDA0004071340730000054

Figure BDA0004071340730000055
Figure BDA0004071340730000055

(17)(18)式中，T1、T2、T3、T4分别对应(14)式中的PUk期望信号、信道估计误差、多用户干扰和SU干扰，T1 SU、T2 SU、T3 SU分别对应(15)式中的SU期望信号、信道估计误差和PU干扰；(17)(18) In formulas, T 1 , T 2 , T 3 , and T 4 correspond to the PU k desired signal, channel estimation error, multi-user interference, and SU interference in formula (14), respectively; T 1 SU , T 2 SU , and T 3 SU correspond to the SU desired signal, channel estimation error, and PU interference in formula (15), respectively;

S4.2.建立功率分配函数和环境相关函数的关系式：S4.2. Establish the relationship between power allocation function and environment related function:

由于SU作为次用户接入网络，对PUk造成的干扰必须小于一定阈值，即PUk的接收速率需要满足Rk≥R0，R0为预定义PUk接收速率阈值，此时将(16)代入Rk≥R0并用信道统计量作为信道真实值计算可得：Since SU accesses the network as a secondary user, the interference caused to PU k must be less than a certain threshold, that is, the receiving rate of PU k needs to satisfy R k ≥ R 0 , where R 0 is the predefined PU k receiving rate threshold. At this time, substituting (16) into R k ≥ R 0 and using the channel statistics as the true value of the channel, we can obtain:

Figure BDA0004071340730000056
Figure BDA0004071340730000056

将(19)式中的部分变量合并分类，改写为与PUk相关的环境相关函数

Figure BDA0004071340730000057
和与pm相关的功率分配函数f(G,pm)的关系式：Some variables in (19) are combined and classified, and rewritten as the environment-related function related to PU k
Figure BDA0004071340730000057
The relationship between the power allocation function f(G, pm ) and pm is:

Figure BDA0004071340730000061
Figure BDA0004071340730000061

(20)式中，

Figure BDA0004071340730000062
和f(G,pm)分别为：(20) In the formula,
Figure BDA0004071340730000062
and f(G, pm ) are:

Figure BDA0004071340730000063
Figure BDA0004071340730000063

S4.3.计算SU所需的最小AP连接数M。S4.3. Calculate the minimum number of AP connections M required by SU.

具体地，所述的最小AP连接数M的计算过程包括：Specifically, the calculation process of the minimum number of AP connections M includes:

S4.3.1.将AP集合

Figure BDA0004071340730000064
中每个AP对应的的剩余功率权重与其大尺度衰落系数相乘，然后将所得结果从大到小排序形成一个原始集合
Figure BDA0004071340730000065
S4.3.1. AP Group
Figure BDA0004071340730000064
The residual power weight corresponding to each AP in is multiplied by its large-scale fading coefficient, and then the results are sorted from large to small to form an original set
Figure BDA0004071340730000065

Figure BDA0004071340730000066
Figure BDA0004071340730000066

S4.3.2.按照

Figure BDA0004071340730000067
中AP的排列顺序对原AP集合
Figure BDA0004071340730000068
中的AP进行重新排列，得到AP集合
Figure BDA0004071340730000069
S4.3.2. According to
Figure BDA0004071340730000067
The order of APs in the original AP set
Figure BDA0004071340730000068
Rearrange the APs in to get the AP set
Figure BDA0004071340730000069

S4.3.3.从集合

Figure BDA00040713407300000610
中按照顺序取前M个AP构成集合
Figure BDA00040713407300000611
M从1开始取；S4.3.3. From the collection
Figure BDA00040713407300000610
Take the first M APs in order to form a set
Figure BDA00040713407300000611
M starts from 1;

S4.3.4.将集合

Figure BDA00040713407300000612
中AP的相关参数代入式(22)中，得到：S4.3.4. Collect
Figure BDA00040713407300000612
Substituting the relevant parameters of AP into equation (22), we get:

Figure BDA00040713407300000613
Figure BDA00040713407300000613

S4.3.5.判断式(24)是否满足式(20)，若满足式(20)，则M+1并返回S4.3.3；若不满足式(20)，则取得的M值为SU所需的最小AP连接数，输出M。S4.3.5. Determine whether formula (24) satisfies formula (20). If it satisfies formula (20), then M+1 is calculated and the return is made to S4.3.3. If it does not satisfy formula (20), then the obtained M value is the minimum number of AP connections required by SU, and M is output.

具体地，在步骤五中，所述的SU最优功率分配方案的计算过程包括：Specifically, in step 5, the calculation process of the SU optimal power allocation solution includes:

S5.1.对于第M个AP之前的M-1个AP，将每个AP的全部剩余功率分配给SU；S5.1. For the M-1 APs before the Mth AP, allocate all remaining power of each AP to the SU;

S5.2.对于第M个AP，采用基于二分法的凸优化方法进行最优功率分配的步骤如下：S5.2. For the Mth AP, the steps of using the convex optimization method based on bisection to perform optimal power allocation are as follows:

S5.2.1.用f(G,pm)M来表示取M时式(24)的结果，设定下列初始条件，从n＝1开始计算：S5.2.1. Use f(G, pm ) M to represent the result of equation (24) when M is taken, set the following initial conditions, and start the calculation from n = 1:

Figure BDA00040713407300000614
Figure BDA00040713407300000614

s0＝f(G,pm)M(26)s 0 ＝f(G,p m ) M (26)

S5.2.2.判断计算是否要继续进行，引入预定义公差ε，ε＝0.01，并将ε与

Figure BDA0004071340730000071
进行比较，判断条件如下：S5.2.2. Determine whether to continue the calculation, introduce a predefined tolerance ε, ε = 0.01, and compare ε with
Figure BDA0004071340730000071
For comparison, the judgment conditions are as follows:

Figure BDA0004071340730000072
Figure BDA0004071340730000072

若满足式(27)，则说明计算结果已达到最优功率分配，跳转至S5.2.4，若不满足式(27)，则还未达到最优功率分配，继续进行S5.2.3；If the formula (27) is satisfied, it means that the calculation result has reached the optimal power allocation, and jump to S5.2.4. If the formula (27) is not satisfied, the optimal power allocation has not been reached, and continue to S5.2.3;

S5.2.3.为了减小此时计算结果与最优功率分配之间的差距，将sn与式(21)进行以下比较：S5.2.3. In order to reduce the gap between the calculated result and the optimal power allocation, compare sn with equation (21) as follows:

Figure BDA0004071340730000078
Figure BDA0004071340730000078

若满足式(28)，则说明此时计算结果小于最优功率分配，需要进行增加计算，令n＝n+1且

Figure BDA0004071340730000073
跳转至S5.2.2；若不满足式(28)，说明此时计算结果大于最优功率分配，需要进行减小计算，令n＝n+1且
Figure BDA0004071340730000074
跳转至S5.2.2；If equation (28) is satisfied, it means that the calculated result is less than the optimal power allocation and additional calculation is required. Let n = n + 1 and
Figure BDA0004071340730000073
Jump to S5.2.2; if equation (28) is not satisfied, it means that the calculation result is greater than the optimal power allocation and needs to be reduced. Set n = n + 1 and
Figure BDA0004071340730000074
Jump to S5.2.2;

S5.2.4.得到第M个AP的最优功率分配计算结果(pm)M，计算方式：S5.2.4. Obtain the optimal power allocation calculation result (p m ) M of the Mth AP, calculated as follows:

Figure BDA0004071340730000075
Figure BDA0004071340730000075

S5.3.经过上述步骤，可以得到最终SU最优功率分配方案

Figure BDA0004071340730000076
S5.3. After the above steps, the final SU optimal power allocation solution can be obtained
Figure BDA0004071340730000076

Figure BDA0004071340730000077
Figure BDA0004071340730000077

优选地，所述的无小区大规模MIMO系统，设定区域为800×800m2正方形区域，随机分布的AP数量L为128，拥有的天线数量N为10，主用户数量K为12，次用户数量为1。Preferably, the cell-free massive MIMO system sets the area to be a 800×800m 2 square area, the number of randomly distributed APs L is 128, the number of antennas N is 10, the number of primary users K is 12, and the number of secondary users is 1.

与现有技术相比，本发明的优点和有益效果有：Compared with the prior art, the advantages and beneficial effects of the present invention are:

1.本发明将用户分为主用户和次用户，并且不再设置辅助AP专门服务次用户，而是让主次用户共用范围内的所有AP，在主用户通信网络保持稳定的前提下接入次用户，既增加了整个系统的用户容量，又提升了系统的频谱利用率。1. The present invention divides users into primary users and secondary users, and no longer sets up auxiliary APs to serve secondary users. Instead, all APs within the common range of primary and secondary users are allowed to access secondary users under the premise that the communication network of the primary user remains stable, which not only increases the user capacity of the entire system, but also improves the spectrum utilization of the system.

2.本发明利用主用户的通信环境数据建立功率分配函数和环境相关函数，并在S4.3中设计如何得到最小AP连接数M的流程，继而让次用户连接最少的AP，实现AP资源的节约。2. The present invention uses the communication environment data of the primary user to establish a power allocation function and an environment-related function, and designs a process for obtaining the minimum number of AP connections M in S4.3, and then allows the secondary user to connect to the least AP to achieve AP resource saving.

3.本发明在步骤五中计算每个与次用户连接的AP的最优功率，并且在第M个AP处使用了基于二分法的凸优化方法来进行最优功率计算，成功减小了次用户对主用户接收速率的影响，实现了对次用户的最优功率分配，在尽可能节约AP资源的前提下提升了次用户的接收速率。3. In step five, the present invention calculates the optimal power of each AP connected to the secondary user, and uses a convex optimization method based on bisection to perform optimal power calculation at the Mth AP, successfully reducing the impact of the secondary user on the primary user's receiving rate, achieving optimal power allocation for the secondary user, and improving the secondary user's receiving rate while saving AP resources as much as possible.

附图说明BRIEF DESCRIPTION OF THE DRAWINGS

图1是本发明的一种实施例的系统模型图。FIG. 1 is a system model diagram of an embodiment of the present invention.

图2是本发明的一种实施例的方法流程图；FIG2 is a method flow chart of an embodiment of the present invention;

图3是本发明方法的一种实施例的最小AP连接数M计算流程图。FIG3 is a flow chart of calculating the minimum number of AP connections M according to an embodiment of the method of the present invention.

图4是本发明方法的一种实施例的最优功率分配方案计算流程图。FIG4 is a flow chart of calculating an optimal power allocation scheme according to an embodiment of the method of the present invention.

具体实施方式DETAILED DESCRIPTION

本发明提供一种基于无小区大规模MIMO系统的底层认知用户功率分配方法，适用于次用户以底层频谱共享的方式接入无小区网络的情况，通过综合考虑信道大尺度衰落系数、AP功率分配权重，提出一种新的基于无小区大规模MIMO系统的底层认知用户功率分配方法，达到最大化认知用户的信道速率的目的。通过将用户分为主用户和次用户，尽可能地减少占用主用户的资源和降低主用户的干扰，提升次用户的信道速率。The present invention provides a method for allocating power of underlying cognitive users based on a cell-free massive MIMO system, which is applicable to the case where secondary users access a cell-free network in a manner of underlying spectrum sharing. By comprehensively considering the large-scale fading coefficient of the channel and the AP power allocation weight, a new method for allocating power of underlying cognitive users based on a cell-free massive MIMO system is proposed to maximize the channel rate of cognitive users. By dividing users into primary users and secondary users, the resources occupied by primary users and the interference of primary users are reduced as much as possible, thereby improving the channel rate of secondary users.

下面结合附图，对本发明做进一步详细说明。The present invention will be further described in detail below in conjunction with the accompanying drawings.

如图1所示，是本发明的一种基于无小区大规模MIMO系统的底层认知用户功率分配方法的系统模型，在无小区大规模MIMO系统区域内随机分布L(L>0)个带有N(N>0)根天线的AP，K(K>0)个主用户(PU)，一个次用户(SU)，并且主用户和次用户均为单天线用户，L＞＞K。用

Figure BDA0004071340730000083
和
Figure BDA0004071340730000082
分别表示AP集合和PU集合，用APl表示集合中第l个AP，PUk表示集合中第K个PU。SU作为短暂出现在该区域中的单天线用户，进入区域后尽可能选取最少数量AP进行连接，用动态集合
Figure BDA0004071340730000081
表示选取的AP集合，其中某个元素用APm来表示。As shown in FIG1 , this is a system model of a method for low-level cognitive user power allocation based on a cell-free massive MIMO system of the present invention. L (L>0) APs with N (N>0) antennas, K (K>0) primary users (PUs), and one secondary user (SU) are randomly distributed in the cell-free massive MIMO system area. Both the primary user and the secondary user are single-antenna users, and L>>K.
Figure BDA0004071340730000083
and
Figure BDA0004071340730000082
Denote the AP set and PU set respectively, AP l denotes the lth AP in the set, and PU k denotes the Kth PU in the set. SU is a single-antenna user that appears briefly in the area. After entering the area, it selects the minimum number of APs to connect to, using the dynamic set.
Figure BDA0004071340730000081
Represents the selected AP set, where an element is represented by AP m .

本发明实例设定无小区大规模MIMO系统区域为800×800m2正方形区域，随机分布的AP数量L为128，拥有的天线数量N为10，主用户数量K为12，次用户数量为1。The example of the present invention sets the cell-free massive MIMO system area to be a 800× 800m2 square area, the number of randomly distributed APs L is 128, the number of antennas N is 10, the number of primary users K is 12, and the number of secondary users is 1.

如图2所示，是本发明的一种基于无小区大规模MIMO系统的底层认知用户功率分配方法，包括以下步骤：As shown in FIG2 , a method for allocating power of underlying cognitive users based on a cell-free massive MIMO system of the present invention includes the following steps:

步骤一：PUk和SU分别向APl和APm发送导频信号，导频信号在经过信道传输后到达AP。Step 1: PU k and SU send pilot signals to AP l and AP m respectively. The pilot signals reach AP after being transmitted through the channel.

S1.1：PUk和SU分别向APl和APm发送导频信号。S1.1: PU k and SU send pilot signals to AP 1 and AP m respectively.

利用时分复用，将每个相干间隔分为三个部分：上行链路训练、上行链路数据传输、下行链路数据传输，不考虑上行链路数据传输。设τc＝196为相干间隔长度，τu为上行链路训练相干间隔长度，τd＝τc-τu为下行链路数据传输相干间隔长度，τc＜τd。PUk和SU分别向APl和APm发送长度为τu的导频序列

Figure BDA0004071340730000091
其中
Figure BDA0004071340730000092
Figure BDA0004071340730000093
Using time division multiplexing, each coherence interval is divided into three parts: uplink training, uplink data transmission, and downlink data transmission. Uplink data transmission is not considered. Let τ c = 196 be the coherence interval length, τ u be the uplink training coherence interval length, τ d = τ c -τ u be the downlink data transmission coherence interval length, τ c <τ d . PU k and SU send pilot sequences of length τ u to AP l and AP m respectively.
Figure BDA0004071340730000091
in
Figure BDA0004071340730000092
Figure BDA0004071340730000093

S1.2：导频信号在经过信道传输后到达AP。S1.2: The pilot signal reaches the AP after being transmitted through the channel.

信道模型为：The channel model is:

Figure BDA0004071340730000094
Figure BDA0004071340730000094

(1)式中，gab表示第a个AP与第b个用户之间的信道向量，

Figure BDA0004071340730000095
表示第a个AP与第b个用户之间的大尺度衰落系数，dab表示第a个AP与第b个用户之间的距离，η表示路径衰落影响因子，取η＝0.5，hab表示第a个AP与第b个用户之间的小尺度衰落向量，为N×1的向量，并且假设hab服从瑞利衰落，其中各元素为服从
Figure BDA0004071340730000096
的随机变量，
Figure BDA0004071340730000097
表示均值为0，方差为1的圆对称复高斯分布。(1) where gab represents the channel vector between the a-th AP and the b-th user,
Figure BDA0004071340730000095
represents the large-scale fading coefficient between the a-th AP and the b-th user, d ab represents the distance between the a-th AP and the b-th user, η represents the path fading influence factor, and η=0.5, h ab represents the small-scale fading vector between the a-th AP and the b-th user, which is a vector of N×1, and it is assumed that h ab obeys Rayleigh fading, where each element obeys
Figure BDA0004071340730000096
A random variable,
Figure BDA0004071340730000097
represents a circularly symmetric complex Gaussian distribution with mean 0 and variance 1.

APl和APm端接收到的信号分别为：The signals received by AP l and AP m are:

Figure BDA0004071340730000098
Figure BDA0004071340730000098

Figure BDA0004071340730000099
Figure BDA0004071340730000099

(2)(3)式中，pp为每个导频符号的归一化发射信噪比。Wpl、Wpm为对应接收信号中N×τu的噪声矩阵，其中各元素为服从

Figure BDA00040713407300000910
的随机变量。glk、gmSU分别表示APl到PUk信道和APm到SU的信道。
Figure BDA00040713407300000911
分别表示PUk和SU发送的导频序列的共轭转置。(2) (3) In formula, p p is the normalized transmit signal-to-noise ratio of each pilot symbol. W pl and W pm are the noise matrices of N × τ u in the corresponding received signal, where each element is subject to
Figure BDA00040713407300000910
glk and gmSU represent the channel from AP l to PU k and the channel from AP m to SU respectively.
Figure BDA00040713407300000911
denote the conjugate transpose of the pilot sequences sent by PU k and SU respectively.

步骤二：先将APl和APm接收到的信号投影到

Figure BDA00040713407300000912
和
Figure BDA00040713407300000913
上，再进行最小均方误差估计。Step 2: Project the signals received by AP l and AP m onto
Figure BDA00040713407300000912
and
Figure BDA00040713407300000913
Then, the minimum mean square error estimation is performed.

S2.1：将Ypl和Ypm分别投影到

Figure BDA00040713407300000914
和
Figure BDA00040713407300000915
上。S2.1: Project Y pl and Y pm onto
Figure BDA00040713407300000914
and
Figure BDA00040713407300000915
superior.

投影结果

Figure BDA00040713407300000916
分别表示为：Projection results
Figure BDA00040713407300000916
Respectively expressed as:

Figure BDA00040713407300000917
Figure BDA00040713407300000917

Figure BDA00040713407300000918
Figure BDA00040713407300000918

S2.2：进行最小均方误差估计。S2.2: Perform minimum mean square error estimation.

对信道glk和gmSU进行最小均方误差MMSE估计，计算得到的估计值

Figure BDA0004071340730000101
和
Figure BDA0004071340730000102
分别为：Perform minimum mean square error (MMSE) estimation on channels g lk and g mSU and calculate the estimated value
Figure BDA0004071340730000101
and
Figure BDA0004071340730000102
They are:

Figure BDA0004071340730000103
Figure BDA0004071340730000103

Figure BDA0004071340730000104
Figure BDA0004071340730000104

(6)(7)式中，

Figure BDA00040713407300001015
表示期望运算，
Figure BDA0004071340730000105
和
Figure BDA0004071340730000106
有N个独立相同的高斯分量，第n个分量的均方和可由υlk和υmSU表示：In formula (6) and (7),
Figure BDA00040713407300001015
represents the expectation operation,
Figure BDA0004071340730000105
and
Figure BDA0004071340730000106
There are N independent and identical Gaussian components, and the mean square sum of the nth component can be expressed by υ lk and υ mSU :

Figure BDA0004071340730000107
Figure BDA0004071340730000107

Figure BDA0004071340730000108
Figure BDA0004071340730000108

步骤三：APl和APm对发送信号进行共轭预编码处理。Step 3: AP 1 and AP m perform conjugate precoding processing on the transmission signal.

APl向PUk发送的信号和APm向SU发送的信号分别为：The signal sent by AP l to PU k and the signal sent by AP m to SU are:

Figure BDA0004071340730000109
Figure BDA0004071340730000109

Figure BDA00040713407300001010
Figure BDA00040713407300001010

(10)(11)式中，plk表示APl分配给PUk的功率权重，pm表示APm分配给SU的功率权重，P表示AP的最大归一化发射功率，

Figure BDA00040713407300001011
为
Figure BDA00040713407300001012
信道估计的共轭，sk、sSU表示APl、APm发送给PUk、SU的符号，
Figure BDA00040713407300001013
(10)(11) In formulas, p lk represents the power weight assigned by AP 1 to PU k , p m represents the power weight assigned by AP m to SU, and P represents the maximum normalized transmit power of AP.
Figure BDA00040713407300001011
for
Figure BDA00040713407300001012
The conjugate of the channel estimate, s k , s SU represents the symbol sent by AP l , AP m to PU k , SU,
Figure BDA00040713407300001013

步骤四：先根据接收信号的结构得到PUk、SU的接收速率表达式，然后建立功率分配函数和环境相关函数的关系式，之后通过关系式计算SU所需的最小AP连接数M。Step 4: First, the receiving rate expressions of PU k and SU are obtained according to the structure of the received signal, and then the relationship between the power allocation function and the environment-related function is established. Then, the minimum number of AP connections M required by the SU is calculated through the relationship.

S4.1：根据接收信号的结构得到PUk、SU的接收速率表达式。S4.1: Obtain the receiving rate expressions of PU k and SU according to the structure of the received signal.

APk接收到的信号和SU接收到的信号分别为：The signals received by AP k and SU are:

Figure BDA00040713407300001014
Figure BDA00040713407300001014

Figure BDA00040713407300001016
Figure BDA00040713407300001016

(12)(13)式中，

Figure BDA0004071340730000111
表示对应信道的转置，ωk、ωSU为对应接收信号中的加性噪声，其中各元素为服从
Figure BDA0004071340730000112
的随机变量。(12)(13) In formula,
Figure BDA0004071340730000111
represents the transpose of the corresponding channel, ω k and ω SU are the additive noise in the corresponding received signal, and each element is subject to
Figure BDA0004071340730000112
A random variable.

(12)(13)式可以根据信号的构成展开写为：Equations (12) and (13) can be expanded according to the signal composition as follows:

Figure BDA0004071340730000113
Figure BDA0004071340730000113

Figure BDA0004071340730000114
Figure BDA0004071340730000114

PUk、SU端的接收速率可由下式给出：The receiving rate of PU k and SU can be given by the following formula:

Figure BDA0004071340730000115
Figure BDA0004071340730000115

(16)式中，SINR为信干噪比，PUk、SU端的信干噪比分别为：(16) In the formula, SINR is the signal to interference plus noise ratio. The signal to interference plus noise ratios of PU k and SU are:

Figure BDA0004071340730000116
Figure BDA0004071340730000116

Figure BDA0004071340730000117
Figure BDA0004071340730000117

(17)(18)式中，T1、T2、T3、T4分别对应(14)式中的PUk期望信号、信道估计误差、多用户干扰和SU干扰，T1 SU、T2 SU、T3 SU分别对应(15)式中的SU期望信号、信道估计误差和PU干扰。In formula (17)(18), T 1 , T 2 , T 3 , and T 4 correspond to the PU k desired signal, channel estimation error, multi-user interference, and SU interference in formula (14), respectively; T 1 SU , T 2 SU , and T 3 SU correspond to the SU desired signal, channel estimation error, and PU interference in formula (15), respectively.

S4.2：建立功率分配函数和环境相关函数的关系式。S4.2: Establish the relationship between the power allocation function and the environmental correlation function.

由于SU作为次用户接入网络，对PUk造成的干扰必须小于一定阈值，即PUk的接收速率需要满足Rk≥R0，R0为预定义PUk接收速率阈值，此时将(16)代入Rk≥R0并用信道统计量作为信道真实值计算可得：Since SU accesses the network as a secondary user, the interference caused to PU k must be less than a certain threshold, that is, the receiving rate of PU k needs to satisfy R k ≥ R 0 , where R 0 is the predefined PU k receiving rate threshold. At this time, substituting (16) into R k ≥ R 0 and using the channel statistics as the true value of the channel, we can obtain:

Figure BDA0004071340730000121
Figure BDA0004071340730000121

将(19)式中的部分变量合并分类，改写为与PUk相关的环境相关函数

Figure BDA0004071340730000122
和与pm相关的功率分配函数f(G,pm)的关系式：Some variables in (19) are combined and classified, and rewritten as the environment-related function related to PU k
Figure BDA0004071340730000122
The relationship between the power allocation function f(G, pm ) and pm is:

Figure BDA0004071340730000123
Figure BDA0004071340730000123

(20)式中，

Figure BDA0004071340730000124
和f(G,pm)分别为：(20) In the formula,
Figure BDA0004071340730000124
and f(G, pm ) are:

Figure BDA0004071340730000125
Figure BDA0004071340730000125

S4.3：计算SU所需的最小AP连接数M。S4.3: Calculate the minimum number of AP connections M required by SU.

如图3所示，是本发明方法的一种实施例的最小AP连接数M计算流程图，计算方法如下：As shown in FIG. 3 , it is a flow chart of calculating the minimum number of AP connections M according to an embodiment of the method of the present invention. The calculation method is as follows:

S4.3.1：将AP集合

Figure BDA0004071340730000126
中每个AP对应的的剩余功率权重与其大尺度衰落系数相乘，然后将所得结果从大到小排序形成一个原始集合
Figure BDA0004071340730000127
S4.3.1: AP Grouping
Figure BDA0004071340730000126
The residual power weight corresponding to each AP in is multiplied by its large-scale fading coefficient, and then the results are sorted from large to small to form an original set
Figure BDA0004071340730000127

Figure BDA0004071340730000128
Figure BDA0004071340730000128

S4.3.2：按照

Figure BDA0004071340730000129
中AP的排列顺序对原AP集合
Figure BDA00040713407300001210
中的AP进行重新排列，得到AP集合
Figure BDA00040713407300001211
S4.3.2: Follow
Figure BDA0004071340730000129
The order of APs in the original AP set
Figure BDA00040713407300001210
Rearrange the APs in to get the AP set
Figure BDA00040713407300001211

S4.3.3：从集合

Figure BDA00040713407300001212
中按照顺序取前M个AP构成集合
Figure BDA00040713407300001213
M从1开始取。S4.3.3: From the collection
Figure BDA00040713407300001212
Take the first M APs in order to form a set
Figure BDA00040713407300001213
M starts from 1.

S4.3.4：将集合

Figure BDA00040713407300001214
中AP的相关参数代入式(22)中，得到：S4.3.4: Assemble
Figure BDA00040713407300001214
Substituting the relevant parameters of AP into equation (22), we get:

Figure BDA00040713407300001215
Figure BDA00040713407300001215

S4.3.5：判断式(24)是否满足式(20)，若满足式(20)，则M+1并返回S4.3.3，若不满足式(20)，则取得的M值为SU所需的最小AP连接数，输出M。S4.3.5: Determine whether equation (24) satisfies equation (20). If it satisfies equation (20), then M+1 is calculated and the return is made to S4.3.3. If it does not satisfy equation (20), then the obtained M value is the minimum number of AP connections required by the SU, and M is output.

步骤五：计算SU最优功率分配方案。Step 5: Calculate the optimal power allocation scheme for SU.

在得到SU所需的最小AP连接数M后，需要对集合

Figure BDA00040713407300001216
中每个AP应该分配多少功率给SU进行计算。After obtaining the minimum number of AP connections M required by SU, the set
Figure BDA00040713407300001216
How much power should each AP allocate to SU for calculation.

如图4所示，下面是本发明方法的一种实施例的SU最优功率分配方案计算步骤：As shown in FIG4 , the following are the steps for calculating the SU optimal power allocation solution in an embodiment of the method of the present invention:

S5.1：对于第M个AP之前的M-1个AP，将每个AP的全部剩余功率分配给SU。S5.1: For the M-1 APs before the Mth AP, all remaining power of each AP is allocated to the SU.

S5.2：对于第M个AP，采用基于二分法的凸优化方法进行最优功率分配，步骤如下：S5.2: For the Mth AP, a convex optimization method based on bisection is used to perform optimal power allocation. The steps are as follows:

S5.2.1：用f(G,pm)M来表示取M时式(24)的结果，设定下列初始条件，从n＝1开始计算：S5.2.1: Use f(G, pm ) M to represent the result of equation (24) when M is taken. Set the following initial conditions and start the calculation from n = 1:

Figure BDA0004071340730000131
Figure BDA0004071340730000131

s0＝f(G,pm)M (26)s 0 ＝f(G,p m ) M (26)

S5.2.2：判断计算是否要继续进行，引入预定义公差ε，ε＝0.01，并将ε与

Figure BDA0004071340730000132
进行比较，判断条件如下：S5.2.2: Determine whether to continue the calculation, introduce a predefined tolerance ε, ε = 0.01, and compare ε with
Figure BDA0004071340730000132
For comparison, the judgment conditions are as follows:

Figure BDA0004071340730000133
Figure BDA0004071340730000133

若满足式(27)，则说明计算结果已达到最优功率分配，跳转至S5.2.4，若不满足式(27)，则还未达到最优功率分配，继续进行S5.2.3。If equation (27) is satisfied, it means that the calculation result has achieved the optimal power allocation, and jump to S5.2.4. If equation (27) is not satisfied, the optimal power allocation has not been achieved, and continue to S5.2.3.

S5.2.3：为了减小此时计算结果与最优功率分配之间的差距，将sn与式(21)进行以下比较：S5.2.3: In order to reduce the gap between the calculated result and the optimal power allocation, compare sn with equation (21) as follows:

Figure BDA0004071340730000134
Figure BDA0004071340730000134

若满足式(28)，则说明此时计算结果小于最优功率分配，需要进行增加计算，令n＝n+1且

Figure BDA0004071340730000135
跳转至S5.2.2；若不满足式(28)，说明此时计算结果大于最优功率分配，需要进行减小计算，令n＝n+1且
Figure BDA0004071340730000136
跳转至S5.2.2。If equation (28) is satisfied, it means that the calculated result is less than the optimal power allocation and additional calculation is required. Let n = n + 1 and
Figure BDA0004071340730000135
Jump to S5.2.2; if equation (28) is not satisfied, it means that the calculation result is greater than the optimal power allocation and needs to be reduced. Set n = n + 1 and
Figure BDA0004071340730000136
Jump to S5.2.2.

S5.2.4：得到第M个AP的最优功率分配计算结果(pm)M，计算方式如下：S5.2.4: Obtain the optimal power allocation calculation result (p m ) M of the Mth AP, which is calculated as follows:

Figure BDA0004071340730000137
Figure BDA0004071340730000137

S5.3：经过上述步骤，可以得到最终SU最优功率分配方案

Figure BDA0004071340730000138
S5.3: After the above steps, the final SU optimal power allocation solution can be obtained
Figure BDA0004071340730000138

Figure BDA0004071340730000139
Figure BDA0004071340730000139

Claims (8)

1.一种基于无小区大规模MIMO系统的底层认知用户功率分配方法，其特征在于，在无小区大规模MIMO系统区域内随机分布L个带有N根天线的AP，K个主用户PU，一个次用户SU，主用户和次用户均为单天线用户，L＞＞K；所述的L>0、N>0、K>0；用
Figure FDA0004071340720000011
和
Figure FDA0004071340720000012
分别表示AP集合和PU集合，用APl表示集合中第l个AP，PUk表示集合中第K个PU；SU作为短暂出现在该区域中的单天线用户，进入区域后尽可能选取最少数量AP进行连接，用动态集合
Figure FDA0004071340720000013
表示选取的AP集合，其中某个元素用APm来表示；1. A method for allocating power of low-level cognitive users based on a cell-free massive MIMO system, characterized in that L APs with N antennas, K primary users PUs, and one secondary user SU are randomly distributed in a cell-free massive MIMO system area, where both the primary user and the secondary user are single-antenna users, L>>K;L>0,N>0,K>0;
Figure FDA0004071340720000011
and
Figure FDA0004071340720000012
They represent the AP set and PU set respectively, AP l represents the lth AP in the set, and PU k represents the Kth PU in the set; SU is a single-antenna user that appears in the area briefly. After entering the area, it selects the minimum number of APs to connect to, using the dynamic set
Figure FDA0004071340720000013
represents the selected AP set, where an element is represented by AP m ; 所述方法，包括以下步骤：The method comprises the following steps: 步骤一、PUk和SU分别向APl和APm发送导频信号，导频信号在经过信道传输后到达AP；Step 1: PU k and SU send pilot signals to AP l and AP m respectively. The pilot signals reach AP after being transmitted through the channel. 步骤二、先将APl和APm接收到的信号投影到
Figure FDA0004071340720000014
和
Figure FDA0004071340720000015
上，再进行最小均方误差估计；Step 2: Project the signals received by AP l and AP m onto
Figure FDA0004071340720000014
and
Figure FDA0004071340720000015
Then, the minimum mean square error estimation is performed; 步骤三、APl和APm对发送信号进行共轭预编码处理；Step 3: AP 1 and AP m perform conjugate precoding processing on the transmitted signal; 步骤四、先根据接收信号的结构得到PUk、SU的接收速率表达式，然后建立功率分配函数和环境相关函数的关系式，之后通过关系式计算SU所需的最小AP连接数M；Step 4: First, the receiving rate expressions of PU k and SU are obtained according to the structure of the received signal, and then the relationship between the power allocation function and the environment-related function is established, and then the minimum number of AP connections M required by the SU is calculated through the relationship; 步骤五、计算SU最优功率分配方案；Step 5: Calculate the optimal power allocation scheme for SU; 在得到SU所需的最小AP连接数M后，需要对集合
Figure FDA0004071340720000016
中每个AP应该分配多少功率给SU进行计算。After obtaining the minimum number of AP connections M required by SU, the set
Figure FDA0004071340720000016
How much power should each AP allocate to SU for calculation. 2.根据权利要求1所述的一种基于无小区大规模MIMO系统的底层认知用户功率分配方法，其特征在于，在步骤一中，所述的PUk和SU分别向APl和APm发送导频信号，导频信号在经过信道传输后到达AP，具体过程包括：2. According to claim 1, a method for bottom-layer cognitive user power allocation based on a cell-free massive MIMO system is characterized in that, in step 1, the PU k and SU send pilot signals to AP l and AP m respectively, and the pilot signals reach the AP after being transmitted through the channel. The specific process includes: S1.1.PUk和SU分别向APl和APm发送导频信号：S1.1.PU k and SU send pilot signals to AP l and AP m respectively: 利用时分复用，将每个相干间隔分为三个部分：上行链路训练、上行链路数据传输、下行链路数据传输，不考虑上行链路数据传输；设τc＝196为相干间隔长度，τu为上行链路训练相干间隔长度，τd＝τc-τu为下行链路数据传输相干间隔长度，τc＜τd；PUk和SU分别向APl和APm发送长度为τu的导频序列
Figure FDA0004071340720000017
其中
Figure FDA0004071340720000018
Figure FDA0004071340720000019
By using time division multiplexing, each coherence interval is divided into three parts: uplink training, uplink data transmission, and downlink data transmission. Uplink data transmission is not considered. Let τ c = 196 be the coherence interval length, τ u be the uplink training coherence interval length, τ d = τ c -τ u be the downlink data transmission coherence interval length, τ c <τ d . PU k and SU send pilot sequences of length τ u to AP l and AP m respectively.
Figure FDA0004071340720000017
in
Figure FDA0004071340720000018
Figure FDA0004071340720000019
 S1.2.导频信号在经过信道传输后到达AP：S1.2. The pilot signal reaches the AP after being transmitted through the channel: 信道模型为：The channel model is:
Figure FDA00040713407200000110
Figure FDA00040713407200000110
 式中，gab表示第a个AP与第b个用户之间的信道向量，
Figure FDA00040713407200000111
表示第a个AP与第b个用户之间的大尺度衰落系数，dab表示第a个AP与第b个用户之间的距离，η表示路径衰落影响因子，取η＝0.5，hab表示第a个AP与第b个用户之间的小尺度衰落向量，为N×1的向量，并且假设hab服从瑞利衰落，其中各元素为服从
Figure FDA0004071340720000021
的随机变量，
Figure FDA0004071340720000022
表示均值为0，方差为1的圆对称复高斯分布；Where gab represents the channel vector between the a-th AP and the b-th user,
Figure FDA00040713407200000111
represents the large-scale fading coefficient between the a-th AP and the b-th user, d ab represents the distance between the a-th AP and the b-th user, η represents the path fading influence factor, and η=0.5 is taken, h ab represents the small-scale fading vector between the a-th AP and the b-th user, which is a vector of N×1, and it is assumed that h ab obeys Rayleigh fading, where each element obeys
Figure FDA0004071340720000021
A random variable,
Figure FDA0004071340720000022
represents a circularly symmetric complex Gaussian distribution with mean 0 and variance 1; APl和APm端接收到的信号分别为：The signals received by AP l and AP m are:
Figure FDA0004071340720000023
Figure FDA0004071340720000023
Figure FDA0004071340720000024
Figure FDA0004071340720000024
 (2)(3)式中，pp为每个导频符号的归一化发射信噪比，Wpl、Wpm为对应接收信号中N×τu的噪声矩阵，其中各元素为服从
Figure FDA0004071340720000025
的随机变量；glk、gmSU分别表示APl到PUk信道和APm到SU的信道；
Figure FDA0004071340720000026
分别表示PUk和SU发送的导频序列的共轭转置。(2) (3) In formula, p p is the normalized transmit signal-to-noise ratio of each pilot symbol, W pl and W pm are the noise matrices of N × τ u in the corresponding received signal, and each element is subject to
Figure FDA0004071340720000025
random variables; g lk , g mSU represent the channel from AP l to PU k and the channel from AP m to SU respectively;
Figure FDA0004071340720000026
denote the conjugate transpose of the pilot sequences sent by PU k and SU respectively. 3.根据权利要求1所述的一种基于无小区大规模MIMO系统的底层认知用户功率分配方法，其特征在于，在步骤二中，所述的先将APl和APm接收到的信号投影到
Figure FDA0004071340720000027
和
Figure FDA0004071340720000028
上，再进行最小均方误差估计，其过程包括：3. The method for allocating power of underlying cognitive users based on a cell-free massive MIMO system according to claim 1, wherein in step 2, the signals received by AP 1 and AP m are first projected onto
Figure FDA0004071340720000027
and
Figure FDA0004071340720000028
Then, the minimum mean square error estimation is performed, and the process includes: S2.1.将Ypl和Ypm分别投影到
Figure FDA0004071340720000029
和
Figure FDA00040713407200000210
上：S2.1. Project Y pl and Y pm to
Figure FDA0004071340720000029
and
Figure FDA00040713407200000210
superior: 投影结果
Figure FDA00040713407200000211
分别表示为Projection results
Figure FDA00040713407200000211
Respectively expressed as
Figure FDA00040713407200000212
Figure FDA00040713407200000212
Figure FDA00040713407200000213
Figure FDA00040713407200000213
 S2.2.进行最小均方误差估计：S2.2. Perform minimum mean square error estimation: 对信道glk和gmSU进行最小均方误差MMSE估计，计算得到的估计值
Figure FDA00040713407200000214
和
Figure FDA00040713407200000215
分别为：Perform minimum mean square error (MMSE) estimation on channels g lk and g mSU and calculate the estimated value
Figure FDA00040713407200000214
and
Figure FDA00040713407200000215
They are:
Figure FDA00040713407200000216
Figure FDA00040713407200000216
Figure FDA00040713407200000217
Figure FDA00040713407200000217
 (6)(7)式中，
Figure FDA00040713407200000218
表示期望运算，
Figure FDA00040713407200000219
和
Figure FDA00040713407200000220
有N个独立相同的高斯分量；第n个分量的均方和可由υlk和υmSU表示：In formula (6) and (7),
Figure FDA00040713407200000218
represents the expectation operation,
Figure FDA00040713407200000219
and
Figure FDA00040713407200000220
There are N independent and identical Gaussian components; the mean square sum of the nth component can be expressed by υ lk and υ mSU :
Figure FDA0004071340720000031
Figure FDA0004071340720000031
Figure FDA0004071340720000032
Figure FDA0004071340720000032
 4.根据权利要求1所述的一种基于无小区大规模MIMO系统的底层认知用户功率分配方法，其特征在于，在步骤三中，所述的APl和APm对发送信号进行共轭预编码处理，其过程包括：4. The method for allocating power of underlying cognitive users based on a cell-free massive MIMO system according to claim 1, characterized in that in step 3, the AP 1 and the AP m perform conjugate precoding processing on the transmitted signal, and the process includes: APl向PUk发送的信号和APm向SU发送的信号，分别为The signal sent by AP l to PU k and the signal sent by AP m to SU are
Figure FDA0004071340720000033
Figure FDA0004071340720000033
Figure FDA0004071340720000034
Figure FDA0004071340720000034
 (10)(11)式中，plk表示APl分配给PUk的功率权重，pm表示APm分配给SU的功率权重，P表示AP的最大归一化发射功率，
Figure FDA0004071340720000035
为
Figure FDA0004071340720000036
信道估计的共轭，sk、sSU表示APl、APm发送给PUk、SU的符号，
Figure FDA0004071340720000037
(10)(11) In formulas, p lk represents the power weight assigned by AP 1 to PU k , p m represents the power weight assigned by AP m to SU, and P represents the maximum normalized transmit power of AP.
Figure FDA0004071340720000035
for
Figure FDA0004071340720000036
The conjugate of the channel estimate, s k , s SU represents the symbol sent by AP l , AP m to PU k , SU,
Figure FDA0004071340720000037
 5.根据权利要求1所述的一种基于无小区大规模MIMO系统的底层认知用户功率分配方法，其特征在于，所述的步骤四的具体过程包括：5. The method for low-level cognitive user power allocation based on a cell-free massive MIMO system according to claim 1, wherein the specific process of step 4 comprises: S4.1.根据接收信号的结构得到PUk、SU的接收速率表达式：S4.1. According to the structure of the received signal, the receiving rate expression of PU k and SU is obtained: APk接收到的信号和SU接收到的信号分别为The signals received by AP k and SU are respectively
Figure FDA0004071340720000038
Figure FDA0004071340720000038
Figure FDA0004071340720000039
Figure FDA0004071340720000039
 (12)(13)式中，
Figure FDA00040713407200000310
表示对应信道的转置，ωk、ωSU为对应接收信号中的加性噪声，其中各元素为服从
Figure FDA00040713407200000311
的随机变量；(12)(13) In formula,
Figure FDA00040713407200000310
represents the transpose of the corresponding channel, ω k and ω SU are the additive noise in the corresponding received signal, and each element is subject to
Figure FDA00040713407200000311
A random variable of (12)(13)式可根据信号的构成展开写为：Equations (12) and (13) can be expanded according to the signal composition as follows:
Figure FDA0004071340720000041
Figure FDA0004071340720000041
Figure FDA0004071340720000042
Figure FDA0004071340720000042
 PUk、SU端的接收速率可由下式给出：The receiving rate of PU k and SU can be given by the following formula:
Figure FDA0004071340720000043
Figure FDA0004071340720000043
 (16)式中，SINR为信干噪比，PUk、SU端的信干噪比分别为：(16) In the formula, SINR is the signal to interference plus noise ratio. The signal to interference plus noise ratios of PU k and SU are:
Figure FDA0004071340720000044
Figure FDA0004071340720000044
Figure FDA0004071340720000045
Figure FDA0004071340720000045
 (17)(18)式中，T1、T2、T3、T4分别对应(14)式中的PUk期望信号、信道估计误差、多用户干扰和SU干扰，T1 SU、T2 SU、T3 SU分别对应(15)式中的SU期望信号、信道估计误差和PU干扰；(17)(18) In formulas, T 1 , T 2 , T 3 , and T 4 correspond to the PU k desired signal, channel estimation error, multi-user interference, and SU interference in formula (14), respectively; T 1 SU , T 2 SU , and T 3 SU correspond to the SU desired signal, channel estimation error, and PU interference in formula (15), respectively; S4.2.建立功率分配函数和环境相关函数的关系式：S4.2. Establish the relationship between power allocation function and environment related function: 由于SU作为次用户接入网络，对PUk造成的干扰必须小于一定阈值，即PUk的接收速率需要满足Rk≥R0，R0为预定义PUk接收速率阈值，此时将(16)代入Rk≥R0并用信道统计量作为信道真实值计算可得：Since SU accesses the network as a secondary user, the interference caused to PU k must be less than a certain threshold, that is, the receiving rate of PU k needs to satisfy R k ≥ R 0 , where R 0 is the predefined PU k receiving rate threshold. At this time, substituting (16) into R k ≥ R 0 and using the channel statistics as the true value of the channel, we can obtain:
Figure FDA0004071340720000046
Figure FDA0004071340720000046
 将(19)式中的部分变量合并分类，改写为与PUk相关的环境相关函数
Figure FDA0004071340720000047
和与pm相关的功率分配函数f(G,pm)的关系式：Some variables in (19) are combined and classified, and rewritten as the environment-related function related to PU k
Figure FDA0004071340720000047
The relationship between the power allocation function f(G, pm ) and pm is:
Figure FDA0004071340720000051
Figure FDA0004071340720000051
 (20)式中，
Figure FDA0004071340720000052
和f(G,pm)分别为：(20) In the formula,
Figure FDA0004071340720000052
and f(G, pm ) are:
Figure FDA0004071340720000053
Figure FDA0004071340720000053
Figure FDA0004071340720000054
Figure FDA0004071340720000054
 S4.3.计算SU所需的最小AP连接数M。S4.3. Calculate the minimum number of AP connections M required by SU. 6.根据权利要求1或5所述的一种基于无小区大规模MIMO系统的底层认知用户功率分配方法，其特征在于，所述的最小AP连接数M的计算过程包括：6. The method for allocating power of underlying cognitive users based on a cell-free massive MIMO system according to claim 1 or 5, wherein the calculation process of the minimum number of AP connections M comprises: S4.3.1.将AP集合
Figure FDA0004071340720000055
中每个AP对应的的剩余功率权重与其大尺度衰落系数相乘，然后将所得结果从大到小排序形成一个原始集合
Figure FDA0004071340720000056
S4.3.1. AP Group
Figure FDA0004071340720000055
The residual power weight corresponding to each AP in is multiplied by its large-scale fading coefficient, and then the results are sorted from large to small to form an original set
Figure FDA0004071340720000056
Figure FDA0004071340720000057
Figure FDA0004071340720000057
 S4.3.2.按照
Figure FDA0004071340720000058
中AP的排列顺序对原AP集合
Figure FDA0004071340720000059
中的AP进行重新排列，得到AP集合
Figure FDA00040713407200000510
S4.3.2. According to
Figure FDA0004071340720000058
The order of APs in the original AP set
Figure FDA0004071340720000059
Rearrange the APs in to get the AP set
Figure FDA00040713407200000510
 S4.3.3.从集合
Figure FDA00040713407200000511
中按照顺序取前M个AP构成集合
Figure FDA00040713407200000512
M从1开始取；S4.3.3. From the collection
Figure FDA00040713407200000511
Take the first M APs in order to form a set
Figure FDA00040713407200000512
M starts from 1; S4.3.4.将集合
Figure FDA00040713407200000513
中AP的相关参数代入式(22)中，得到：S4.3.4. Collect
Figure FDA00040713407200000513
Substituting the relevant parameters of AP into equation (22), we get:
Figure FDA00040713407200000514
Figure FDA00040713407200000514
 S4.3.5.判断式(24)是否满足式(20)，若满足式(20)，则M+1并返回S4.3.3；若不满足式(20)，则取得的M值为SU所需的最小AP连接数，输出M。S4.3.5. Determine whether formula (24) satisfies formula (20). If it satisfies formula (20), then M+1 is calculated and the return is made to S4.3.3. If it does not satisfy formula (20), then the obtained M value is the minimum number of AP connections required by SU, and M is output. 7.根据权利要求1所述的一种基于无小区大规模MIMO系统的底层认知用户功率分配方法，其特征在于，在步骤五中，所述的SU最优功率分配方案的计算过程包括：7. The method for bottom-layer cognitive user power allocation based on a cell-free massive MIMO system according to claim 1, wherein in step 5, the calculation process of the SU optimal power allocation scheme comprises: S5.1.对于第M个AP之前的M-1个AP，将每个AP的全部剩余功率分配给SU；S5.1. For the M-1 APs before the Mth AP, allocate all remaining power of each AP to the SU; S5.2.对于第M个AP，采用基于二分法的凸优化方法进行最优功率分配的步骤如下：S5.2. For the Mth AP, the steps of using the convex optimization method based on bisection to perform optimal power allocation are as follows: S5.2.1.用f(G,pm)M来表示取M时式(24)的结果，设定下列初始条件，从n＝1开始计算：S5.2.1. Use f(G, pm ) M to represent the result of equation (24) when M is taken, set the following initial conditions, and start the calculation from n = 1:
Figure FDA00040713407200000515
Figure FDA00040713407200000515
 s0＝f(G,pm)M (26)s 0 ＝f(G,p m ) M (26) S5.2.2.判断计算是否要继续进行，引入预定义公差ε，ε＝0.01，并将ε与
Figure FDA0004071340720000061
进行比较，判断条件如下：S5.2.2. Determine whether to continue the calculation, introduce a predefined tolerance ε, ε = 0.01, and compare ε with
Figure FDA0004071340720000061
For comparison, the judgment conditions are as follows:
Figure FDA0004071340720000062
Figure FDA0004071340720000062
 若满足式(27)，则说明计算结果已达到最优功率分配，跳转至S5.2.4，若不满足式(27)，则还未达到最优功率分配，继续进行S5.2.3；If the formula (27) is satisfied, it means that the calculation result has reached the optimal power allocation, and jump to S5.2.4. If the formula (27) is not satisfied, the optimal power allocation has not been reached, and continue to S5.2.3; S5.2.3.为了减小此时计算结果与最优功率分配之间的差距，将sn与式(21)进行以下比较：S5.2.3. In order to reduce the gap between the calculated result and the optimal power allocation, compare sn with equation (21) as follows:
Figure FDA0004071340720000063
Figure FDA0004071340720000063
 若满足式(28)，则说明此时计算结果小于最优功率分配，需要进行增加计算，令n＝n+1且
Figure FDA0004071340720000064
跳转至S5.2.2；若不满足式(28)，说明此时计算结果大于最优功率分配，需要进行减小计算，令n＝n+1且
Figure FDA0004071340720000065
跳转至S5.2.2；If equation (28) is satisfied, it means that the calculated result is less than the optimal power allocation and additional calculation is required. Let n = n + 1 and
Figure FDA0004071340720000064
Jump to S5.2.2; if equation (28) is not satisfied, it means that the calculation result is greater than the optimal power allocation and needs to be reduced. Set n = n + 1 and
Figure FDA0004071340720000065
Jump to S5.2.2; S5.2.4.得到第M个AP的最优功率分配计算结果(pm)M，计算方式：S5.2.4. Obtain the optimal power allocation calculation result (p m ) M of the Mth AP, calculated as follows:
Figure FDA0004071340720000066
Figure FDA0004071340720000066
 S5.3.经过上述步骤，可以得到最终SU最优功率分配方案
Figure FDA0004071340720000068
S5.3. After the above steps, the final SU optimal power allocation solution can be obtained
Figure FDA0004071340720000068
Figure FDA0004071340720000067
Figure FDA0004071340720000067
 8.根据权利要求1所述的一种基于无小区大规模MIMO系统的底层认知用户功率分配方法，其特征在于，所述的无小区大规模MIMO系统，设定区域为800×800m2正方形区域，随机分布的AP数量L为128，拥有的天线数量N为10，主用户数量K为12，次用户数量为1。8. According to claim 1, a bottom-layer cognitive user power allocation method based on a cell-free massive MIMO system is characterized in that, for the cell-free massive MIMO system, a set area is a 800×800m2 square area, the number of randomly distributed APs L is 128, the number of antennas N is 10, the number of primary users K is 12, and the number of secondary users is 1.
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