CN115499115B - Active user detection method based on orthogonal pilot frequency in CF-mMIMO scene - Google Patents
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- H04L5/00—Arrangements affording multiple use of the transmission path
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- 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
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L5/00—Arrangements affording multiple use of the transmission path
- H04L5/003—Arrangements for allocating sub-channels of the transmission path
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- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The invention provides an active user detection method based on orthogonal pilot frequency in a CF-mMIMO scene. The method comprises the following steps: and (3) information acquisition: before the uplink pilot training stage is carried out, a CPU (Central processing Unit) collects large-scale fading information between each user and an AP (access point); pilot frequency allocation: the CPU performs initial pilot frequency distribution on each user by using a pilot frequency distribution scheme with minimum false detection rate as a target according to the large-scale fading information; active user detection: in the uplink pilot training stage, each active user sends pilot information to an AP, and each AP maps the information received by the active user to each pilot signal in a pilot pool and obtains the energy of each mapping symbol; and judging whether the user near the AP corresponding to each pilot symbol is activated or not by judging whether the energy of each mapping symbol is larger than an energy threshold value, and reporting the activated information to a CPU. The invention proposes that the pilot scheme can minimize the active false detection rate of the user compared with other pilot schemes.
Description
Technical Field
The invention belongs to the technical field of communication, and particularly relates to an active user detection method based on orthogonal pilot frequency in a CF-mMIMO scene.
Background
As communication technology evolves, the number of wireless access devices and the consumption of data traffic will show explosive growth. Massive MIMO is a promising 5G radio access technology, where a base station with multiple antennas can serve many users simultaneously in the same time-frequency resource, which can provide high throughput, reliability and energy efficiency by simple signal processing. In recent years, cell-FREE MASSIVE MIMO has been proposed as a novel distributed massive MIMO network architecture equipped with a large number of distributed Access Points (APs) serving a smaller number of distributed users. For CF-mMIMO, all access points are connected to the central processing unit by means of a forward link and the concept of cell boundaries is no longer present. Compared with the existing centralized Massive MIMO, the CF-mMIMO not only inherits good characteristics of channel hardening to a certain extent, but also has higher energy efficiency and system deployment flexibility. The distributed network topology enables CF-mMIMO to benefit from macroscopic diversity, mitigates the edge impact of centralized Massive MIMO, and ensures better system coverage, user service fairness and network throughput. Clearly, the CF-mMIMO network is expected to become one of the potential architectures in the future.
The development of 5G and future wireless communication networks is intended to support a wide range of high-demand services and applications, including supporting mass machine class communications (mMTC), i.e., mass internet of things (IoT) devices. mMTC are focused on solving the problem that the traditional mobile communication can not well support the application of the Internet of things and the vertical industry. The low-power-consumption large-connection scene is mainly oriented to application scenes of smart cities, environment monitoring, smart home, forest fire prevention and the like which aim at sensing and data acquisition, and has the characteristics of small data package, low power consumption, mass connection and the like. According to sporadic data transmission characteristics of MTC devices, only a small portion of devices connected to the network may be active at the same time. Thus, in order to efficiently support mMTC, active user identification is first required.
Active user identification is largely divided into two categories, authorized and unauthorized. Literature (U.K. ganesan, E.and E.G.Larsson,"Clustering-Based Activity Detection Algorithms for Grant-Free Random Access in Cell-Free Massive MIMO,"in IEEE Transactions on Communications,vol.69,no.11,pp.7520-7530,Nov.2021) And (X.Wang,A.Ashikhmin,Z.Dong and C.Zhai,"Two-Stage Channel Estimation Approach for Cell-Free IoT with Massive Random Access,"in IEEE Journal on Selected Areas in Communications), adopting an unauthorized connection mode, distributing unique non-orthogonal pilot frequency to each user, and carrying out equipment activity detection and channel estimation according to the sparsity of the received signals. The use of non-orthogonal pilots generally considers the pilot symbols to follow a complex gaussian random distribution, that is to say the phase of the default pilot symbols is continuous, whereas the actual modulated signal phase is generally discrete and therefore physically difficult to achieve entirely. Document (VCroisfelt,T.Abro,and J.C.Marinello."User-Centric Perspective in Random Access Cell-Free Aided by Spatial Separability."in IEEE Internet of Things Journal(2022)) considers how such a network solves the random access problem in case of pilot collision in case of orthogonal pilot reuse, he solves this problem by combining the spatial separation criterion with the SUCE criterion. Document (V Croisfelt,T.Abro,and J.C.Marinello."User-Centric Perspective in Random Access Cell-Free Aided by Spatial Separability."in IEEE Internet of Things Journal(2022)) is based on an authorized access scheme, which is very tedious and may cause unnecessary delay for the user. There is no unlicensed active user detection scheme for orthogonal pilots, and no design of pilot allocation scheme is considered in the related literature.
Disclosure of Invention
The invention aims to solve the problems in the prior art and provides an active user detection method based on orthogonal pilot frequency in a CF-mMIMO scene.
The invention is realized by the following technical scheme, and provides an active user detection method based on orthogonal pilot frequency in a CF-mMIMO scene, which specifically comprises the following steps:
And (3) information acquisition: before the uplink pilot training stage is carried out, a CPU (Central processing Unit) collects large-scale fading information between each user and an AP (access point);
pilot frequency allocation: the CPU performs initial pilot frequency distribution on each user by using a pilot frequency distribution scheme with minimum false detection rate as a target according to the large-scale fading information;
Active user detection: in the uplink pilot training stage, each active user sends pilot information to an AP, and each AP maps the information received by the active user to each pilot signal in a pilot pool and obtains the energy of each mapping symbol; and judging whether the user near the AP corresponding to each pilot symbol is activated or not by judging whether the energy of each mapping symbol is larger than an energy threshold value, and reporting the activated information to a CPU.
Further, considering the CF-mMIMO system where a large number of MTC devices exist, it is assumed that M APs equipped with L antennas and K single antenna MTC devices are randomly distributed in a certain area,And/>Respectively representing an AP group and a device group; the maximum power of the MTC device is represented as p u;αk epsilon {0,1} represents the/>Active variable of individual user, and/>
The channel coefficient between the mth AP and the kth user is recorded asThen the first time period of the first time period,
gm,k＝βm,khm,k
Where beta m,k represents a large-scale fading,Representing small scale fading; hypothesis/>Is a complex Gaussian random variable which is independently and uniformly distributed and obeys/>
Further, the method comprises the steps of,
Defining pilot poolComprises tau orthogonal pilots; definition/>Represents the t pilot in the pilot pool, there is/>Definition/>Representing shared pilot/>Wherein f tk =1 represents pilot/>Is assigned to the/>And f tk = 0.
Further, the pilot frequency allocation scheme with the minimum false detection rate as the target specifically comprises the following steps:
Definition s k represents the difference energy between the primary detected amount and the interference when the primary AP detects user k, then s k is expressed as,
Wherein the method comprises the steps ofRepresenting the AP group detecting user k, β c is the large-scale fading threshold; then the pilot allocation scheme f tk can be obtained by solving the following optimization problem:
P1：
Wherein the method comprises the steps of Problem P1 is a 0-1 nonlinear optimization problem; definition/>According to the limiting condition/>Available, f tkfti＝min{ftk,fti }; the problem P1 may be translated into a problem,
P2：
Problem P2 is a mixed integer linear problem that is solved.
Further, the method for solving the problem is to apply a branch-and-bound method for solving, or directly use GUROBI solver for solving.
Further, defineCan be obtained by solving problem P2; at this time/>A set of only one element or an empty set; definition m k represents a master AP that detects whether user k is active,The set of users that APm detects as the primary detecting AP may be expressed as/>
Further, in the uplink training phase, all active users transmit pilot signals to all APs simultaneously, and the pilot signal received by the mth AP can be expressed as:
Further, the mth AP maps the received signals to each pilot signal in the pilot pool, and the pilot is The up-mapped symbols can be expressed as:
Further, the energy of the mapped symbol can be expressed as:
Further, an energy threshold is set
The beneficial effects of the invention are as follows:
The method of the invention provides an active user detection scheme under orthogonal pilot frequency and a corresponding pilot frequency allocation scheme. Compared with the existing active user detection scheme under the orthogonal pilot frequency, the method is an unauthorized active user detection scheme, and detection steps are simpler and easier to realize. Based on the proposed active user detection method, the pilot scheme provided by the invention can minimize the active false detection rate of the user compared with other pilot schemes.
Drawings
Fig. 1 is a diagram of the comparison of different pilot allocation schemes.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Considering the CF-mMIMO system where a large number of MTC devices exist, it is assumed that M APs equipped with L antennas and K single-antenna MTC devices are randomly distributed in a certain area,And/>Respectively representing AP combined equipment groups; the maximum power of the MTC device is represented as p u;αk epsilon {0,1} represents the/>Active variable of individual user, and/>
The channel coefficient between the mth AP and the kth user is recorded asThen the first time period of the first time period,
gm,k＝βm,khm,k
Where beta m,k represents a large-scale fading,Representing small scale fading; hypothesis/>Is a complex Gaussian random variable which is independently and uniformly distributed and obeys/>
In this system, the CPU would first allocate pilots for all users in the system, so the AP/CPU would know the pilot sequences corresponding to each device. In this system, the pilot has two roles. One is that after the active users send pilots to the AP, the AP/CPU can determine which users are active based on the received signals, and the second is that the AP/CPU can perform channel estimation for these active users based on the received signals. Active user identification and channel estimation are accomplished simultaneously during the uplink training phase.
Generally, the number of MTC devices is very large, so even in a static scenario, it is difficult to fully allocate orthogonal pilots to MTC devices, and there is a case where different users use the same pilots. Defining pilot poolComprises tau orthogonal pilots; definition/>Representing the t-th pilot in the pilot pool, withDefinition/>Representing shared pilot/>Wherein f tk =1 represents pilot/>Is assigned to the/>And f tk = 0.
Referring to fig. 1, the invention provides an active user detection method based on orthogonal pilot frequency in a CF-mMIMO scene, which specifically comprises the following steps:
And (3) information acquisition: before the uplink pilot training stage is carried out, a CPU (Central processing Unit) collects large-scale fading information between each user and an AP (access point);
pilot frequency allocation: the CPU performs initial pilot frequency distribution on each user by using a pilot frequency distribution scheme with minimum false detection rate as a target according to the large-scale fading information;
Active user detection: in the uplink pilot training stage, each active user sends pilot information to an AP, and each AP maps the information received by the active user to each pilot signal in a pilot pool and obtains the energy of each mapping symbol; and judging whether the user near the AP corresponding to each pilot symbol is activated or not by judging whether the energy of each mapping symbol is larger than an energy threshold value, and reporting the activated information to a CPU.
The pilot frequency distribution scheme with the minimum false detection rate as the target specifically comprises the following steps:
Definition s k represents the difference energy between the primary detected amount and the interference when the primary AP detects user k, then s k is expressed as,
Wherein the method comprises the steps ofRepresenting the AP group detecting user k, β c is the large-scale fading threshold; then the pilot allocation scheme f tk can be obtained by solving the following optimization problem:
P1：
Wherein the method comprises the steps of Problem P1 is a 0-1 nonlinear optimization problem, although it may be possible to search through an enumeration process exhaustively, and its complexity may be very high. If the problem P1 can be converted into a linear problem, it can be solved by some solver; thus define/>According to the limiting condition/>Available, f tkfti＝min{ftk,fti }; the problem P1 may be translated into a problem,
P2：
The problem P2 is a mixed integer linear problem (MLP) that is solved. The method for solving the problem is to apply a branch-and-bound method for solving, or directly use GUROBI solver for solving.
Definition of the definitionCan be obtained by solving problem P2; at this time/>A set of only one element or an empty set; definition m k represents a master AP that detects whether user k is active,/>The set of users that APm detects as the primary detecting AP may be expressed as/>
In the uplink training phase, all active users transmit pilot signals to all APs simultaneously, and the pilot signal received by the mth AP can be expressed as:
The mth AP maps the received signals to each pilot signal in the pilot pool, and the pilot is The up-mapped symbols can be expressed as:
the energy of the mapped symbol can be expressed as:
Setting an energy threshold
The active user detection scheme is specifically as follows:
with this user activity detection scheme, the user's activity false detection rate can be expressed as,
The method adopts Monte Carlo simulation to verify the effect of different pilot frequency allocation schemes. The range of simulation is a D x D square area, assuming M randomly placed APs and K randomly placed users. A three-segment path loss model is employed to model large scale fading,
Where d m,k denotes the distance between user k and base station n in km, and PL m,k denotes the path loss between user k and base station m. X m,k represents shadow fading, and X m,k～N(0,σsh). The specific parameters are shown in the following table, and the simulation parameters of the system are shown in table 1.
Table 1 simulation parameters
The invention compares the proposed pilot frequency distribution scheme with the pilot frequency distribution scheme in literature (W.Zeng,Y.He,B.Li and S.Wang,"Pilot Assignment for Cell Free Massive MIMO Systems Using a Weighted Graphic Framework,"in IEEE Transactions on Vehicular Technology,vol.70,no.6,pp.6190-6194,June 2021) in the prior art, simulates the false detection rate of the user liveness of different pilot frequency schemes under different pilot frequency lengths, and the simulation result is shown in figure 1. As the pilot length increases, the false detection rate gradually decreases, and it can be seen that the proposed pilot allocation method is superior to the prior art pilot allocation method based on vertex coloring in terms of the performance of the false detection rate. The false detection rate at smaller pilot lengths is also within an acceptable range.
The method for detecting the active user based on the orthogonal pilot frequency in the CF-mMIMO scene provided by the invention is described in detail, and specific examples are applied to the principle and the implementation mode of the invention, and the description of the above examples is only used for helping to understand the method and the core idea of the invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.
Claims (5)
- An active user detection method based on orthogonal pilot frequency in a CF-mMIMO scene is characterized by comprising the following steps:And (3) information acquisition: before the uplink pilot training stage is carried out, a CPU (Central processing Unit) collects large-scale fading information between each user and an AP (access point);pilot frequency allocation: the CPU performs initial pilot frequency distribution on each user by using a pilot frequency distribution scheme with minimum false detection rate as a target according to the large-scale fading information;active user detection: in the uplink pilot training stage, each active user sends pilot information to an AP, and each AP maps the information received by the active user to each pilot signal in a pilot pool and obtains the energy of each mapping symbol; judging whether the user near the AP corresponding to each pilot symbol is activated or not by judging whether the energy of each mapping symbol is larger than an energy threshold value, and reporting the activated information to a CPU (Central processing Unit);Considering the CF-mMIMO system where a large number of MTC devices exist, it is assumed that M APs equipped with L antennas and K single-antenna MTC devices are randomly distributed in a certain area, And/>Respectively representing an AP group and a device group; the maximum power of the MTC device is represented as p u;αk epsilon {0,1} represents the/>Active variable of individual user, and/>The channel coefficient between the mth AP and the kth user is recorded asThen the first time period of the first time period,gm,k＝βm,khm,kWhere beta m,k represents a large-scale fading,Representing small scale fading; hypothesis/>Is a complex Gaussian random variable which is independently and uniformly distributed and obeys/>Defining pilot poolComprises tau orthogonal pilots; definition/>Represents the t pilot in the pilot pool, there is/>Definition/>Represents the set of users sharing pilot phi t, where f tk =1 represents pilot/>Is assigned to the/>Users, whereas f tk =0;the pilot frequency distribution scheme with the minimum false detection rate as the target specifically comprises the following steps:Definition s k represents the difference energy between the primary detected amount and the interference when the primary AP detects user k, then s k is expressed as,Wherein the method comprises the steps ofRepresenting the AP group detecting user k, β c is the large-scale fading threshold; then the pilot allocation scheme f tk is obtained by solving the following optimization problem:Wherein the method comprises the steps of Problem P1 is a 0-1 nonlinear optimization problem; definition/>According to the limiting conditionsObtaining, f tkfti＝min{ftk,fti; the problem P1 is then translated into a problem,Problem P2 is a mixed integer linear problem, which is solved;The method for solving the problem is to solve the problem by applying a branch-and-bound method or directly solve the problem by using GUROBI solver;Definition of the definition Obtaining by solving the problem P2; at this time/>A set of only one element or an empty set; definition m k represents a master AP that detects whether user k is active,Then APm is denoted/>, as the set of users detected by the primary detecting AP
- 2. The method of claim 1, wherein during the uplink training phase, all active users transmit pilot signals to all APs simultaneously, and the pilot signal received by the mth AP is expressed as:
- 3. the method of claim 2 wherein the mth AP maps its received signal to each pilot signal in the pilot pool, at pilot The symbols of the up-map are expressed as:
- 4. a method according to claim 3, characterized in that the energy of the mapped symbols is expressed as:
- 5. the method of claim 4, wherein setting an energy threshold
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