CN114025368A - Distributed intelligent reflection surface assisted D2D communication method and system - Google Patents

Distributed intelligent reflection surface assisted D2D communication method and system Download PDF

Info

Publication number
CN114025368A
CN114025368A CN202111258467.2A CN202111258467A CN114025368A CN 114025368 A CN114025368 A CN 114025368A CN 202111258467 A CN202111258467 A CN 202111258467A CN 114025368 A CN114025368 A CN 114025368A
Authority
CN
China
Prior art keywords
cell
model
data transmission
uplink data
communication
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202111258467.2A
Other languages
Chinese (zh)
Other versions
CN114025368B (en
Inventor
徐齐钱
陈海军
何春龙
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Chengdu Sanyuan Optical Communication Technology Co ltd
Original Assignee
Zhejiang Yizheng Communication Technology Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Zhejiang Yizheng Communication Technology Co ltd filed Critical Zhejiang Yizheng Communication Technology Co ltd
Priority to CN202111258467.2A priority Critical patent/CN114025368B/en
Publication of CN114025368A publication Critical patent/CN114025368A/en
Application granted granted Critical
Publication of CN114025368B publication Critical patent/CN114025368B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W28/00—Network traffic management; Network resource management
    • H04W28/02—Traffic management, e.g. flow control or congestion control
    • H04W28/0215—Traffic management, e.g. flow control or congestion control based on user or device properties, e.g. MTC-capable devices
    • 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
    • H04B7/04013—Intelligent reflective surfaces
    • 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
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/06—Testing, supervising or monitoring using simulated traffic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W28/00—Network traffic management; Network resource management
    • H04W28/16—Central resource management; Negotiation of resources or communication parameters, e.g. negotiating bandwidth or QoS [Quality of Service]
    • H04W28/18—Negotiating wireless communication parameters
    • H04W28/22—Negotiating communication rate
    • 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

Abstract

The application discloses a distributed intelligent reflection surface assisted D2D communication method and a system, wherein the method comprises the steps of distributing at least one intelligent reflection surface IRS in a cell, constructing to obtain at least one D2D pair, wherein each D2D pair comprises two cell users; establishing an uplink data transmission rate model of all D2D in the cell to users in the cell; establishing a communication rate model of all D2D pairs in the cell; and optimizing based on the uplink data transmission model and the communication rate model, so that the optimized D2D communication rate and the uplink data transmission rate of the cell user meet preset requirements. By introducing the IRS, the interference of the D2D on the communication of the cell users is reduced in the communication process, and the transmission rate of the communication between the D2D pairs is improved.

Description

Distributed intelligent reflection surface assisted D2D communication method and system
Technical Field
The invention relates to the field of wireless communication, in particular to a distributed intelligent reflective surface assisted D2D communication system.
Background
Currently, in the existing Communication system, Communication between devices is controlled by a base station of a wireless Communication operator, and voice or data Communication between terminals cannot be directly performed between terminals because capabilities of Communication devices and channel resources of wireless Communication are limited, whereas in the next generation of Communication technology, terminal-To-Device Communication D2D (Device-To-Device Communication) attracts more and more commercial interest, and the terminal-To-terminal Communication means that direct Communication between terminal devices is realized by means of technologies such as wireless local area network technology (WI-FI), Bluetooth technology (Bluetooth), and fourth generation Communication technology (LET-D2D).
The D2D technology allows neighboring users to communicate directly without going through the base station, thereby reducing the burden of the base station and enabling the communication system to accommodate more users, generally only users far away from the base station and with low quality of service will communicate by using the D2D communication method, and the D2D communication needs to reuse the spectrum resources of the users in the cell communicating with the base station, and as the demand for higher data transmission rate of the next generation wireless communication system increases, the spectrum efficiency of the system can be improved.
However, since the multiplexing D2D communication causes interference to the cell users and the base station, and the interference range includes interference from the uplink frequency band to the base station, interference from the downlink frequency band to the D2D receiving end, interference from the D2D transmitting end to the cellular network, and the like, the D2D technology needs to control the interference within a certain range.
Disclosure of Invention
To ameliorate interference and reduce the impact of interference during use of D2D technology, the present application provides a distributed smart reflective surface assisted D2D communication system.
The distributed intelligent reflection surface assisted D2D communication system provided by the application adopts the following technical scheme:
the distributed intelligent reflection surface assisted D2D communication system comprises at least one intelligent reflection surface IRS arranged in a cell, at least one D2D pair is constructed, and each D2D pair comprises two cell users;
establishing an uplink data transmission rate model of all D2D in the cell to users in the cell;
establishing a communication rate model of all D2D pairs in the cell;
and optimizing based on the uplink data transmission model and the communication rate model, so that the optimized D2D communication rate and the uplink data transmission rate of the cell user meet preset requirements.
By adopting the technical scheme, at least one intelligent reflection surface IRS is arranged in the cell; the IRS remodels the wireless signal propagation environment; at least one D2D pair is constructed, each D2D pair comprises two cell users, and two user terminals form a D2D pair, so that the communication between the two cell users can be realized, an uplink data transmission rate model of all the D2D pairs of the cell users in a corresponding cell is established, communication rate models of all the D2D pairs in the cell are established, the transmission rate of the cell users and the communication rate of the D2D pair can be adjusted and optimized, the optimized IRS of the phase shift angle matrix of the IRS can realize passive beam forming, signals of a D2D transmitting end are reflected to a D2D receiving end in an IRS concentration mode, a shorter reflection path is provided for the cell users, the communication rate between the D2D pairs is improved, and meanwhile the interference to the cell users in the D2D communication process can be reduced.
In summary, the present application includes at least one of the following beneficial technical effects:
1. at least one intelligent reflection surface IRS is arranged in a cell, the IRS carries out remodeling on a wireless signal propagation environment, corresponding D2D pairs are respectively constructed, each D2D pair comprises two cell users, and an uplink data transmission rate model of all the cell users in the cell by all the D2D pairs and a communication rate model of all the D2D pairs in the cell are respectively established, so that the transmission rate of the cell users and the communication rate of the D2D pairs can be adjusted and optimized;
and 2, the IRS after the phase shift angle matrix of the IRS is optimized can realize passive beam forming, so that signals at a D2D sending end are reflected to a D2D receiving end in a centralized manner through the IRS, a shorter reflection path is provided for cell users, the communication speed between D2D pairs is improved, and meanwhile, the interference to the cell users in the D2D communication process can be reduced.
Drawings
FIG. 1 is a schematic flow chart of a distributed intelligent reflective surface assisted D2D communication method according to an embodiment of the present application;
FIG. 1-1 is a block diagram of an embodiment of a distributed intelligent reflective surface assisted D2D communication method according to the present application;
fig. 2 is a schematic flowchart of an embodiment of the present application, which is optimized based on an uplink data transmission model and a communication rate model, so that an optimized D2D communication rate and an uplink data transmission rate of a cell user satisfy a preset requirement;
fig. 3 is a schematic flow chart of multiplexing factors of a D2D pair in an uplink data transmission model and a communication rate model with preset requirements as optimization targets according to an embodiment of the present application;
fig. 3-1 is a weighted bipartite graph of multiplexing factors for a D2D pair in an uplink data transmission model and a communication rate model, with preset requirements as optimization objectives according to an embodiment of the present application;
fig. 4 is a schematic flowchart illustrating a process of optimizing a beamforming vector of a cell user by a base station in an uplink data transmission model according to an embodiment of the present application;
fig. 5 is a schematic flowchart illustrating optimization of the transmission power of the cell users in the uplink data transmission model and the communication rate model and the transmission power of the D2D pair with preset requirements as an optimization target according to an embodiment of the present application;
fig. 5-1 is a schematic diagram of a power allocation feasible solution for optimizing the transmit power of the cell users and the transmit power of the D2D pair in the uplink data transmission model and the communication rate model with preset requirements as an optimization target according to an embodiment of the present application;
fig. 6 is a schematic flowchart illustrating a result of power allocation obtained for the maximum value and the minimum value of the transmission power value range of the cell user according to an embodiment of the present application;
fig. 7 is a schematic flowchart illustrating a process of optimizing a phase shift angle matrix of an IRS in an uplink data transmission model and a communication rate model according to an embodiment of the present application, with a preset requirement as an optimization target;
FIG. 8-1 is a coordinate diagram of the BCD algorithm in one embodiment of the present application comparing the number of iterations with the communication transmission rate achieved by D2D communication after each iteration;
fig. 8-2 is a diagram illustrating the coordinates of the communication transmission rate achievable by D2D communication under different IRS numbers in one embodiment of the present application;
fig. 8-3 is a diagram illustrating data transmission rates achievable by D2D communications under different maximum transmit powers of D2D in an embodiment of the present application;
fig. 8-4 are graphs comparing data transmission rates for D2D communications with minimum rates required by users in different cells in one embodiment of the present application;
8-5 are graphs comparing data transmission rates of D2D communications for different path loss coefficients of D2D links in one embodiment of the present application;
fig. 9 is a block diagram of a distributed intelligent reflective surface assisted D2D communication system according to an embodiment of the present application.
Detailed Description
The present application is described in further detail below with reference to the attached drawings.
Referring to fig. 1 and 1-1, a distributed intelligent reflective surface assisted D2D communication method includes the steps of:
s110, arranging at least one intelligent reflection surface IRS in the cell, and constructing to obtain at least one D2D pair, wherein each D2D pair comprises two cell users.
The intelligent reflection surface IRS (intelligent reflection surface) reconfigures the wireless propagation environment by integrating a large number of low-cost passive reflection elements on a plane, thereby improving the performance of the wireless communication network, that is, the IRS independently reflects an incident signal by controlling a phase shift angle matrix to obtain a beamforming vector, a cell is also called a cellular cell and refers to an area covered by one or a part of the base station (sector antenna) in the cellular mobile communication system, a cell user can communicate with the base station through a wireless channel in the area, at least one IRS is distributed in the cell, and reconfigures the wireless propagation environment in the cell; the cell comprises a plurality of cell users, two D2D pairs which are based on direct communication between the cell users are constructed, and auxiliary communication is carried out through the IRS, so that the two cell users can directly access without forwarding through a base station.
And S120, establishing an uplink data transmission rate model of all D2D in the cell to users in the cell.
The uplink refers to a physical channel from a cell user to a base station, and the uplink data transmission process of the cell user in the cell can be controlled and optimized by establishing an uplink data transmission rate model of all D2D pairs of the cell user in the cell, wherein the uplink transmission model of the cell user is as follows:
Figure RE-DEST_PATH_IMAGE001
（1）
the model comprises a base station, represented by BS, and l IRS, K cell users and j (j is less than or equal to K) pairs of D2D, wherein the spectrum resource of one cell user can only be multiplexed by one pair of D2D pairs; the l-th IRS is represented by IRS l, each IRS comprises M reflection units, the K-th cell is represented by CU K, the transmitting end of the j-th pair D2D is represented by DT j, and the receiving end is represented by DR j; assuming that the base station is equipped with N antennas, and the cell user equipment and the D2D equipment are both single-antenna equipment, the base station receives the beamforming vector of CU k
Figure RE-DEST_PATH_IMAGE002
It is shown that,
Figure RE-DEST_PATH_IMAGE003
，
Figure RE-DEST_PATH_IMAGE004
to represent
Figure RE-DEST_PATH_IMAGE005
The matrix is a matrix of a plurality of matrices,
Figure RE-DEST_PATH_IMAGE006
represents the conjugate transpose of the matrix and,
Figure RE-DEST_PATH_IMAGE007
and
Figure RE-DEST_PATH_IMAGE008
respectively representing the transmission power of CU k and DT j;
wherein the content of the first and second substances,
Figure RE-DEST_PATH_IMAGE009
for multiplexing factor, when DT j multiplexes the frequency band of the uplink from CU k to the base station
Figure RE-DEST_PATH_IMAGE010
I.e., interference, on CU k, otherwise,
Figure RE-DEST_PATH_IMAGE011
；
Figure RE-DEST_PATH_IMAGE012
indicating a direct channel connecting CU k to the base station,
Figure RE-DEST_PATH_IMAGE013
interference channel to the base station for DT j;
Figure RE-DEST_PATH_IMAGE014
is a phase shift angle matrix of the IRS,
Figure RE-DEST_PATH_IMAGE015
represents a diagonal matrix made up of elements in parentheses;
Figure RE-DEST_PATH_IMAGE016
represents the channels of CU k to IRS l, and
Figure RE-DEST_PATH_IMAGE017
and
Figure RE-DEST_PATH_IMAGE018
the reflection channels IRS l to BS and DT j to IRS l, respectively, B denotes the bandwidth,
Figure RE-DEST_PATH_IMAGE019
representing gaussian white noise.
And S130, establishing a communication rate model of all D2D pairs in the cell.
Wherein, the communication rate model of all D2D communication in the cell is:
Figure RE-DEST_PATH_IMAGE020
（2）
wherein the content of the first and second substances,
Figure RE-DEST_PATH_IMAGE021
for the direct channels DT j to DR j,
Figure RE-DEST_PATH_IMAGE022
the direct interference channels for CU k to DR j,
Figure RE-DEST_PATH_IMAGE023
for the reflected channels of RS l to DT j, the communication rate of the communication process of the D2D pair is controlled and optimized conveniently by establishing a communication rate model of all D2D pairs in the cell.
And S140, optimizing based on the uplink data transmission model and the communication rate model, so that the optimized D2D communication rate and the uplink data transmission rate of the cell user meet preset requirements.
The uplink data transmission model comprises maximum transmission power between D2D pairs and maximum transmission power of cell users, the preset requirement is that the maximum communication rate of D2D is maximized while the minimum uplink transmission rate of the cell users is met, and the maximum transmission power between D2D pairs and the maximum transmission power of the cell users are met by optimizing the uplink data transmission model and the communication rate model, so that the D2D communication rate, the minimum transmission rate of the cell users, the maximum uplink transmission power of the cell users and the maximum transmission power of D2D are optimized simultaneously.
The implementation principle of the distributed intelligent reflection surface assisted D2D communication method in the embodiment of the application is as follows: the method comprises the steps of arranging at least one intelligent reflection surface IRS in a cell, constructing to obtain at least one D2D pair, wherein each D2D pair comprises two cell users, establishing uplink data transmission rate models of all the D2D pairs of the cell users in the cell, establishing communication rate models of all the D2D pairs in the cell, and optimizing based on the uplink data transmission models and the communication rate models, so that the optimized D2D communication rate and the uplink data transmission rate of the cell users meet preset requirements.
The preset requirement is that the communication rate of the D2D is maximized and the uplink transmission rate of the cell user is minimized, and the value ranges and limits of a plurality of different parameters are obtained by the preset requirement:
Figure RE-DEST_PATH_IMAGE024
wherein (3 a) and (3 b) are maximum power limits,
Figure RE-DEST_PATH_IMAGE025
and
Figure RE-DEST_PATH_IMAGE026
maximum signal transmission power of CU k and DT j, respectively; (3c) for the minimum transmission rate limit of the CU,
Figure RE-DEST_PATH_IMAGE027
a minimum signal transmission rate required for communication for cell users; (3d) and (3 e) indicates that the spectrum resources of one cell user can only be multiplexed by one pair of D2D, i.e., (3D) for j, (3 e) for k, (3D) together with (3 e) indicates that one cell user CU k can only be multiplexed by one pair of D2D for j; (3f) normalizing and limiting the beamforming vector; (3g) is the limit of the mode of the phase shift angle matrix of the reflective element.
Because the optimization problem (P1) contains multiple variables, the multiple variables affect each other, and the optimal value of each variable cannot be directly obtained, the original optimization problem is decomposed into multiple sub-problems by using a block Coordinate descent (bcd) based (block Coordinate determination) algorithm, and the optimal solution for maximizing the D2D communication transmission rate is obtained by optimizing and continuously iterating the multiplexing factor, the beamforming vector, the power distribution, and the phase shift angle matrix, respectively:
referring to fig. 2, the optimization based on the uplink data transmission model and the communication rate model so that the optimized D2D communication rate and the uplink data transmission rate of the cell user satisfy the preset requirements includes the following steps:
and S210, optimizing the multiplexing factor of the D2D pair in the uplink data transmission model and the communication rate model by taking the preset requirement as an optimization target.
Among them, D2D communication needs to reuse the spectrum resources of the cell users in the cell communicating with the base station, which can greatly improve the spectrum efficiency of the system.
And S220, optimizing the beam forming vector of the cell user by the base station in the uplink data transmission model by taking the preset requirement as an optimization target.
The passive beamforming is generated by optimizing the beamforming vector, the wireless signal propagation environment is reshaped, the interference of D2D to cell users in the communication process is reduced, and the data transmission rate of D2D communication is improved.
And S230, optimizing the transmission power of the cell users and the transmission power of the D2D pair in the uplink data transmission model and the communication rate model by taking the preset requirement as an optimization target.
The preset requirement is taken as an optimization target, the transmission power of the cell users in the uplink data transmission model and the communication rate model and the transmission power of the D2D pair are optimized respectively, the communication rate of the D2D is maximized, and meanwhile the communication quality of the cell users is guaranteed.
And S240, with a preset requirement as an optimization target, optimizing the phase shift angle matrix of the IRS in the uplink data transmission model and the communication rate model, so that the optimized D2D communication rate is maximized and the uplink data transmission rate of the cell user is minimized.
After the phase shift angle matrix of the IRS is optimized, the intelligent reflection surface can realize passive beam forming, so that signals of a sending end are intensively reflected to a D2D receiving end by the D2D through the IRS, and uplink interference signals from cell users are reflected to a base station end.
The implementation principle that the preset requirement is that the uplink transmission rate of the cell user is minimum while the communication rate of the D2D is maximized is that the optimization is performed based on an uplink data transmission model and a communication rate model, so that the optimized communication rate of the D2D and the uplink transmission rate of the cell user meet the preset requirement: with preset requirements as optimization targets, multiplexing factors of the D2D pair, beamforming vectors of cell users by the base station, transmission power of the cell users and transmission power of the D2D pair, transmission power of the cell users and transmission power of the D2D pair, and phase shift angle matrixes of IRSs are optimized respectively, so that interference on the cell users is reduced while the data transmission rate of D2D communication is increased.
Referring to fig. 3 and 3-1, the multiplexing factor for the pair D2D in the uplink data transmission model and the communication rate model with the preset requirement as the optimization target includes the following steps:
and S310, acquiring the initial multiplexing factor of the D2D pair in the uplink data transmission model and the communication rate model.
Wherein, for the cell user CU k, if its uplink spectrum resource is multiplexed by D2D for j, it must satisfy the requirement after multiplexing
Figure RE-DEST_PATH_IMAGE028
Let the CU who satisfies this condition be a multiplexing set
Figure RE-DEST_PATH_IMAGE029
Then for D2D pair j, the initial multiplex object is:
Figure RE-DEST_PATH_IMAGE030
（4）
however, if the system includes multiple pairs of D2D pairs, the same cell user may become the best multiplexing target for the multiple pairs of D2D pairs, but when the D2D pair j does not need to multiplex the spectrum resources of the cell user, its transmission rate can be expressed as:
Figure RE-DEST_PATH_IMAGE031
（5）
and S320, when the D2D pair does not need to multiplex the frequency spectrum resources of the cell users, obtaining the maximum transmission rate based on the uplink data transmission model, and subtracting the maximum transmission rate of the D2D pair to obtain the multiplexing gain.
Wherein, the multiplexing gain is a combination of equations (2) and (5), that is:
Figure RE-DEST_PATH_IMAGE032
（6）
and S330, calculating to obtain the optimized multiplexing factor of the D2D pair based on the multiplexing gain of the D2D pair.
Wherein, the optimal multiplexing factor of D2D to j is:
Figure RE-DEST_PATH_IMAGE033
（7）
let D2D pair set and cell user set be two vertex sets of weighted bipartite graph respectively, but CU k can adopt a connection jk when D2D pair j is multiplexed, and the weight of the connection is multiplexing gain
Figure RE-DEST_PATH_IMAGE034
(ii) a The problem is converted into a weighted bipartite graph maximum matching problem in graph theory, and can be solved by using a KM algorithm based on Hungary algorithm, wherein the complexity is
Figure RE-DEST_PATH_IMAGE035
(ii) a During execution, whether the graph 3-1 is connected or not is checked, if yes, the KM algorithm is executed on the whole graph, and if not, the KM algorithm is executed on each connected branch;
the Hungarian algorithm is used for finding the maximum matching of the bipartite graph, namely any two edges in the bipartite graph do not have the same vertex, the weighted bipartite graph is referred to, the upper k represents a cell user CU, the lower j is a D2D pair, and the Hungarian algorithm can be used for realizing that each CU is only connected by one D2D pair, namely multiplexing; the weight of each edge is defaulted to be 1 in the Hungarian algorithm, and the KM algorithm realizes maximum matching on the basis of the weighting of each edge of the bipartite graph; the core of the KM algorithm is to find an augmentation path, when two j have an optimal k, the j with small weight is connected with another k if the k with small weight is suitable, the connection line is the augmentation path, if collision occurs, the operation is repeated to disconnect and reconnect until each j with the maximum matching matches one k.
And S340, replacing the optimized multiplexing factor with an initial multiplexing factor in the uplink data transmission model and the communication rate model.
In the embodiment of the present application, with a preset requirement as an optimization target, the implementation principle of the multiplexing factor of the D2D pair in the uplink data transmission model and the communication rate model is as follows: the method comprises the steps of obtaining initial multiplexing factors of a D2D pair in an uplink data transmission model and a communication rate model, obtaining a maximum transmission rate based on the uplink data transmission model when spectrum resources of cell users do not need to be multiplexed by the D2D pair, subtracting the maximum transmission rate of the D2D pair to obtain multiplexing gains, calculating and obtaining optimized multiplexing factors of the D2D pair based on the multiplexing gains of the D2D pair, and replacing the optimized multiplexing factors with the initial multiplexing factors in the uplink data transmission model and the communication rate model.
Referring to fig. 4, the method for optimizing the beamforming vector of the cell user by the base station in the uplink data transmission model includes the following steps:
and S410, respectively setting the transmitting power of cell users, and a phase shift angle matrix of the signal transmitting power of the D2D pair and the IRS.
After the multiplexing factor is optimized, the signal transmission power of the CU k and the phase shift angle matrix of the signal transmission power of the DT j and the IRS are fixed, and the interference of extra variables is reduced.
And S420, when the D2D is not multiplexed with the multiplexing factor, acquiring the uplink transmission rate of the cell user.
Wherein when uplink resources of CU k are not multiplexed, that is
Figure RE-DEST_PATH_IMAGE036
When, the uplink transmission rate of CU k is:
Figure RE-DEST_PATH_IMAGE037
（8）
s430, acquiring a beam forming vector based on the maximum ratio sending criterion and the uplink data transmission rate model of the cell users.
Since CU k is not multiplexed by D2D pairs, the transmission power of CU k is known by the maximum ratio transmission criterion
Figure RE-DEST_PATH_IMAGE038
And the beamforming vector is:
Figure RE-DEST_PATH_IMAGE039
and S440, when the multiplexing factors are multiplexed by the D2D, acquiring the beamforming vector according to the threshold requirement.
Wherein when the uplink frequency band of CU k is multiplexed
Figure RE-DEST_PATH_IMAGE040
Considering that only (3 d) and (3 g) contain beamforming vectors, the original optimization problem is converted into a feasible solution problem:
Figure RE-DEST_PATH_IMAGE041
wherein the content of the first and second substances,
Figure RE-DEST_PATH_IMAGE042
，
Figure RE-DEST_PATH_IMAGE043
and l is a unit matrix,
Figure RE-DEST_PATH_IMAGE044
(9 a) the left expression of the inequality is in the form of a Rayleigh quotient,for Rayleigh quotient expression, making its value maximum
Figure RE-DEST_PATH_IMAGE045
Is a matrix
Figure RE-DEST_PATH_IMAGE046
The feature vector corresponding to the maximum feature value of (1).
S450, replacing the beamforming vector with the beamforming vector in the uplink data transmission model.
The implementation principle of optimizing the cell user beam forming vector by the base station in the uplink data transmission model in the embodiment of the application is as follows: respectively setting a transmitting power of a cell user, a signal transmitting power of a D2D pair and a phase shift angle matrix of an IRS, when a multiplexing factor of a D2D pair is not multiplexed, acquiring a transmission rate of an uplink of the cell user, acquiring a beamforming vector based on a maximum ratio transmission criterion and an uplink data transmission rate model of the cell user, when the multiplexing factor of the D2D pair is multiplexed, acquiring the beamforming vector through a threshold requirement, replacing the beamforming vector with the beamforming vector in the uplink data transmission model, and enabling the base station to reduce the interference of communication between the D2D pair as much as possible.
Referring to fig. 5 and 5-1, optimizing the transmit power of the cell users and the transmit power of the D2D pair in the uplink data transmission model and the communication rate model with the preset requirement as an optimization target includes the following steps:
and S510, fixing the phase shift angle matrix of the IRS and acquiring the value range of the transmission power of the cell user based on the preset requirement.
Wherein, the phase shift angle matrix of the IRS is fixed, and the power distribution subproblems can be obtained based on (3 a), (3 b) and (3 c) in the preset requirements, and inequalities (3 a) and (3 c) are combined to obtain the power distribution subproblems
Figure RE-DEST_PATH_IMAGE047
The value range is as follows:
Figure RE-DEST_PATH_IMAGE048
（10）
wherein the content of the first and second substances,
Figure RE-DEST_PATH_IMAGE049
in fig. 5-1, the feasible solution area of power allocation is shown with reference to the shaded area in fig. 5-1,
Figure RE-DEST_PATH_IMAGE050
is dependent on
Figure RE-DEST_PATH_IMAGE051
Increase and increase with
Figure RE-DEST_PATH_IMAGE052
The reduction is reduced, i.e. the shaded area in 5-1 can be regarded as a bounded convex set, the optimal value of which lies on the boundary of the area.
S520, respectively obtaining the power distribution result according to the maximum value and the minimum value of the value range of the sending power of the cell user.
Wherein when
Figure RE-DEST_PATH_IMAGE053
When, as shown in fig. 5-1, the optimal power allocation is:
Figure RE-DEST_PATH_IMAGE054
（11）
when in use
Figure RE-DEST_PATH_IMAGE055
When, as shown in fig. 5-1, the optimal power allocation is:
Figure RE-DEST_PATH_IMAGE056
（12）
s530, the transmission power of the allocated cell user and the transmission power of the D2D pair are replaced with the transmission power of the cell user and the transmission power of the D2D pair in the uplink data transmission model and the communication rate model, respectively.
In the embodiment of the present application, with a preset requirement as an optimization target, the implementation principle of optimizing the transmit power of the cell user and the transmit power of the D2D pair in the uplink data transmission model and the communication rate model is as follows: fixing the phase shift angle matrix of the IRS, acquiring the value range of the transmission power of the cell user based on a preset requirement, acquiring the result of power distribution respectively according to the maximum value and the minimum value of the value range of the transmission power of the cell user, replacing the transmission power of the distributed cell user and the transmission power of the D2D pair with the transmission power of the cell user and the transmission power of the D2D pair in an uplink data transmission model and a communication rate model respectively, and further reducing the interference of the D2D to the cell user in the communication process by distributing the transmission power of the cell user and the transmission power of the D2D pair.
Referring to fig. 6, the method for obtaining the power distribution result for the maximum value and the minimum value of the transmission power value range of the cell user respectively includes the following steps:
s610, establishing a coordinate system by taking the maximum transmission power of the cell users as an ordinate and the maximum transmission power of the D2D to the transmitting end as an abscissa.
And S620, acquiring a power distribution result in the coordinate system according to a preset requirement.
The implementation principle of obtaining the power distribution result respectively for the maximum value and the minimum value of the value range of the transmission power of the cell user in the embodiment of the application is as follows: corresponding to fig. 5-1, a form of establishing a coordinate system is adopted, so that the optimal value of power distribution is located on the boundary corresponding to the bounded convex set.
Referring to fig. 7, with a preset requirement as an optimization target, a phase shift angle matrix of an IRS in an uplink data transmission model and a communication rate model is optimized, including the following steps:
and S710, acquiring the signal to interference plus noise ratio (SINR) of the cell users.
Wherein, the signal to Interference plus Noise ratio sinr (signal to Interference plus Noise ratio) is a signal to Interference plus Noise ratio, which is a ratio of the strength of the received useful signal to the strength of the received Interference signal (Noise and Interference), and the signal to Interference plus Noise ratio of the cell user CU k is:
Figure RE-DEST_PATH_IMAGE057
in order to facilitate calculation and simplification in the aspect of mathematics, the following steps are respectively ordered:
Figure RE-DEST_PATH_IMAGE058
，
Figure RE-DEST_PATH_IMAGE059
，
Figure RE-DEST_PATH_IMAGE060
，
Figure RE-DEST_PATH_IMAGE061
，
Figure RE-DEST_PATH_IMAGE062
，
Figure RE-DEST_PATH_IMAGE063
。
s720, acquiring the SINR of the D2D to the transmitting end.
Wherein, the SINR of D2D to j is:
Figure RE-DEST_PATH_IMAGE064
in order to facilitate calculation and simplification in the aspect of mathematics, the following steps are respectively ordered:
Figure RE-DEST_PATH_IMAGE065
，
Figure RE-DEST_PATH_IMAGE066
，
Figure RE-DEST_PATH_IMAGE067
，
Figure RE-DEST_PATH_IMAGE068
。
and S730, rewriting the part of the phase shift angle matrix containing the IRS in the preset target based on the signal to interference plus noise ratio (SINR) of the cell users and the signal to interference plus noise ratio (D2D) of the transmitting end.
Wherein, the rewriting process is optimized and rewritten in mathematical sense, and the (3 d) in the preset target can be rewritten as follows:
Figure RE-DEST_PATH_IMAGE069
(15)
and S740, respectively fixing the transmission power of the D2D pair, the transmission power of the cell users, the beamforming vector and the multiplexing factor of the base station to the cell users, and acquiring the phase shift angle matrix of the IRS by taking the preset requirement as an optimization target.
When the transmit power of D2D pair, the transmit power of cell users, the appropriate amount of beamforming of base station to cell users, and the multiplexing factor are fixed, the optimization problem of the phase shift angle matrix of IRS in the preset requirement can be written as:
Figure RE-DEST_PATH_IMAGE070
and S750, optimizing a phase shift angle matrix of the IRS.
Wherein, the optimization problem of the phase shift angle matrix is rewritten in the mathematical sense:
Figure RE-DEST_PATH_IMAGE071
(17)
wherein
Figure RE-DEST_PATH_IMAGE072
As an auxiliary variable, the number of variables,
Figure RE-DEST_PATH_IMAGE073
to pair
Figure RE-DEST_PATH_IMAGE074
And
Figure RE-DEST_PATH_IMAGE075
all are concave functions, pass pair
Figure RE-DEST_PATH_IMAGE076
The first partial derivative is calculated and made to be zero to obtain the optimal solution
Figure RE-DEST_PATH_IMAGE077
Will be
Figure RE-712368DEST_PATH_IMAGE077
Substituted into (17) to obtain
Figure RE-DEST_PATH_IMAGE078
Thus, the optimization problem (P3) can be equated to the optimization problem (P4):
Figure RE-DEST_PATH_IMAGE079
the fraction of the objective function of the (P4) optimization problem is transformed into the following form using a quadratic transformation:
Figure RE-DEST_PATH_IMAGE080
（19）
unfolding the quadratic term in (19) yields:
Figure RE-DEST_PATH_IMAGE081
(21)
wherein the content of the first and second substances,
Figure RE-DEST_PATH_IMAGE082
，
Figure RE-DEST_PATH_IMAGE083
，
Figure RE-DEST_PATH_IMAGE084
。
similarly, the constraint (15) can be rewritten as:
Figure RE-DEST_PATH_IMAGE085
(22)
wherein the content of the first and second substances,
Figure RE-DEST_PATH_IMAGE086
the optimization problem (P4) can therefore be transformed into the following optimization problem:
Figure RE-DEST_PATH_IMAGE087
due to the fact that
Figure RE-DEST_PATH_IMAGE088
Is about
Figure RE-DEST_PATH_IMAGE089
The convex function of (a), we can obtain its lower bound by successive convex approximation sca (less progressive context approximation), as follows:
Figure RE-DEST_PATH_IMAGE090
(24)
wherein the content of the first and second substances,
Figure RE-DEST_PATH_IMAGE091
obtained in the nth iteration, the constraint (24) may be converted into:
Figure RE-DEST_PATH_IMAGE092
(25)
this constraint is a linear constraint, so (P5) can be converted into:
Figure RE-DEST_PATH_IMAGE093
solving optimization problem (P6) by MM algorithm, core idea of MM algorithmThe original problem is decomposed into a series of subproblems of replacing the objective function of the original problem by a substitute function, and the objective function of the original problem is assumed to be
Figure RE-DEST_PATH_IMAGE094
At the n +1 th iteration, we find its lower bound
Figure RE-DEST_PATH_IMAGE095
But which satisfies:
（1）
Figure RE-DEST_PATH_IMAGE096
；（2）
Figure RE-DEST_PATH_IMAGE097
；（3）
Figure RE-DEST_PATH_IMAGE098
under the three conditions, the temperature of the mixture is controlled,
Figure RE-DEST_PATH_IMAGE099
can be used as
Figure RE-DEST_PATH_IMAGE100
And the optimal solution can be obtained by continuously iterating to converge:
suppose that the nth iteration is at
Figure RE-DEST_PATH_IMAGE101
Where the following inequality holds true:
Figure RE-DEST_PATH_IMAGE102
(28)
wherein the content of the first and second substances,
Figure RE-DEST_PATH_IMAGE103
is a matrix
Figure RE-DEST_PATH_IMAGE104
Maximum eigenvalue, surrogate function
Figure RE-DEST_PATH_IMAGE105
The sub-problem for the nth iteration is:
Figure RE-DEST_PATH_IMAGE106
due to the fact that
Figure RE-DEST_PATH_IMAGE107
And (3) abandoning the constant term in the step (29), and simplifying the original problem into that:
Figure RE-DEST_PATH_IMAGE108
wherein the content of the first and second substances,
Figure RE-DEST_PATH_IMAGE109
since the condition of the mode of the phase shift angle matrix of the reflection unit in (3 g) is non-convex, (P8) is still a non-convex optimization problem, by introducing a non-negative variable P, the original optimization problem is converted into:
Figure RE-DEST_PATH_IMAGE110
given the value of P, (P8) the optimal solution is
Figure RE-DEST_PATH_IMAGE111
To ensure that the optimal solution is both the optimal solution for the original problem and the dual problem, p must satisfy the complementary relaxation condition of (25)
Figure RE-DEST_PATH_IMAGE112
Wherein
Figure RE-DEST_PATH_IMAGE113
(ii) a When p =0, the ratio of p =0,
Figure RE-DEST_PATH_IMAGE114
need to satisfy (25), otherwise p>0; when p is>At 0 time, due to
Figure RE-DEST_PATH_IMAGE115
Is a monotonic function with respect to p, and thus can be satisfied by a dichotomy
Figure RE-DEST_PATH_IMAGE116
P of (1).
The solution of the dichotomy pair (P9) is as follows:
1, calculating J (0), if J (0) < Q, terminating the operation, otherwise, performing the step 2;
2: definition accuracy
Figure RE-DEST_PATH_IMAGE117
And upper bound
Figure RE-DEST_PATH_IMAGE118
And lower bound
Figure RE-DEST_PATH_IMAGE119
；
3 calculation of
Figure RE-DEST_PATH_IMAGE120
；
4: according to
Figure RE-DEST_PATH_IMAGE121
Updating
Figure RE-DEST_PATH_IMAGE122
；
5: if J (p) is not less than Q, let
Figure RE-DEST_PATH_IMAGE123
Otherwise, to
Figure RE-DEST_PATH_IMAGE124
；
6: if it is
Figure RE-DEST_PATH_IMAGE125
And terminating the operation, otherwise, repeating the step 3.
The solution of the BCD algorithm pair (P1) is as follows:
1: initialization
Figure RE-DEST_PATH_IMAGE126
And
Figure RE-DEST_PATH_IMAGE127
let us order
Figure RE-DEST_PATH_IMAGE128
2: repeating:
3: finding optimal multiplexing mode through KM algorithm
Figure RE-DEST_PATH_IMAGE129
,
4: fixing
Figure RE-DEST_PATH_IMAGE130
And
Figure RE-DEST_PATH_IMAGE131
finding a suitable beamforming vector by solving (P2)
Figure RE-DEST_PATH_IMAGE132
；
5: fixing
Figure RE-DEST_PATH_IMAGE133
Figure RE-DEST_PATH_IMAGE134
And
Figure RE-610267DEST_PATH_IMAGE131
obtaining the optimal power distribution by (11) and (12)
Figure RE-DEST_PATH_IMAGE135
；
6: fixing
Figure RE-858846DEST_PATH_IMAGE133
Figure RE-972164DEST_PATH_IMAGE134
And
Figure RE-DEST_PATH_IMAGE136
the optimal phase shift angle matrix is obtained by solving (P9)
Figure RE-DEST_PATH_IMAGE137
；
7: order to
Figure RE-DEST_PATH_IMAGE138
；
8: until convergence;
9: return to
Figure RE-DEST_PATH_IMAGE139
And
Figure RE-DEST_PATH_IMAGE140
the value of (c).
And (3) simulation result analysis:
the simulation scene is assumed to be located in a cell with the radius of 200 m, a base station is located at the center of the cell, 6 cell users are randomly distributed in the cell, and the IRS is distributed in two ways, wherein one way is that the base station is uniformly distributed at the edge of the cell, the other way is that the base station is randomly distributed in the cell, and 3 pairs of D2D users are randomly generated near the IRS; the phase shift angle matrix of the IRS also has two settings, one is optimized by an MM algorithm, and the other is randomly distributed from 0 to 2 pi; the bandwidth is set to be 1Mbps, and the noise density is-114 dBm/MHz; unless otherwise noted, the maximum transmit power of the cell user and the D2D sender are both 25 dBm, the minimum uplink transmission rate of the cell user is 5 Mbps, and the path loss model is as follows:
Figure RE-DEST_PATH_IMAGE141
（32）
wherein the content of the first and second substances,
Figure RE-DEST_PATH_IMAGE142
is a reference distance
Figure RE-DEST_PATH_IMAGE143
Path loss in meters, λ is the wavelength, d is the link length,
Figure RE-DEST_PATH_IMAGE144
for the path loss coefficient, the path loss coefficient of the D2D link is set to 2, and the path loss coefficients of the remaining links are set to 3.75; the channel model of the small-scale fading adopts a Rice channel model, and the expression is as follows:
Figure RE-DEST_PATH_IMAGE145
（32）
wherein the content of the first and second substances,βis a rice coefficient, is set to 3,
Figure RE-DEST_PATH_IMAGE146
as a component of the line-of-sight,
Figure RE-DEST_PATH_IMAGE147
，
Figure RE-DEST_PATH_IMAGE148
and
Figure RE-DEST_PATH_IMAGE149
are respectively defined as:
Figure RE-DEST_PATH_IMAGE150
（33）
Figure RE-DEST_PATH_IMAGE151
（34）
wherein Dt and Dr are the number of antennas at the transmitting end and the receiving end respectively, d is the antenna spacing, d/λ =1/2 is set for the convenience of people,
Figure RE-DEST_PATH_IMAGE152
and
Figure RE-DEST_PATH_IMAGE153
the arrival angle and departure angle of the signal, respectively, we make it randomly generated at [0,2 π]In the above-mentioned manner,
Figure RE-DEST_PATH_IMAGE154
the non-line-of-sight component is rayleigh fading.
Fig. 8-1 compares the number of iterations with the communication transmission rate achieved by D2D communication after each iteration, which is the case of 6 IRS, 6 IRS and 4 IRS respectively from top to bottom, and it can be seen from the figure that the BCD algorithm has basically converged after nearly 30 iterations, which effectively proves the convergence of the BCD algorithm.
8-2 compare the achievable communication transmission rate of D2D communication for different IRS numbers, from top to bottom for the case of IRS edge distribution with optimized IRS phase shift angle, IRS random distribution with optimized IRS phase shift angle, single IRS with the number of reflection units as the sum of distributed IRS numbers, IRS edge distribution with unoptimized IRS phase shift angle, IRS random distribution with unoptimized IRS phase shift angle, and no IRS in the system; when the number of IRS is more than 10, the rate of D2D communication is lower when the non-optimized IRS is randomly distributed in the system than when no IRS is contained in the system, because a large number of interference links are generated when a large number of non-optimized IRS is distributed in the system, so that the interference of D2D users to cell users is increased.
Fig. 8-3 compare the data transmission rates achievable with D2D communications at different maximum transmit powers at the D2D transmitter, and it can be seen that the data transmission rate for D2D communications monotonically increases with increasing maximum transmit power, as compared to the case when different IRS numbers are compared, the rate for D2D communications is higher when the optimized IRS is located at the cell edge, and a multiple IRS distributed arrangement is better than a single large IRS arrangement, since an IRS located at the cell edge can better serve D2D users located at the cell edge, and multiple IRS can provide shorter reflection paths so that the path loss is reduced.
Fig. 8-4 compares the data transmission rate of D2D communication under the condition of minimum rate required by different cell users, and it can be seen from the figure that the data transmission rate achievable by D2D communication is monotonically decreased with the increase of the minimum transmission rate required by the cell users to communicate with the base station, and when the rate required by the cell users is greater than 10 Mbps, the transmission rate of the system D2D in which the un-optimized IRS and the system without IRS are arranged is extremely low, which can be regarded as communication interruption, while the transmission rate of the system D2D adopting the optimized distributed IRS scheme is still greater than 5 Mbps, which can ensure the normal operation of the system to some extent.
8-5 compare the data transmission rates of D2D communications for different path loss coefficients of the D2D link, and it can be seen that as the path loss coefficient of the D2D link increases, the data transmission rate achievable by the D2D communications decreases monotonically, but the magnitude of the decrease is large without increasing the rate required by the cell user; when the path loss factor of the D2D link is greater than 3.6, the communication rate of the D2D system with non-optimized IRS and the system without IRS is very low, while the transmission rate of the D2D system with distributed IRS exceeds 20 Mbps, because the distributed IRS provides a shorter reflection path for the D2D pair, the path loss is greatly reduced, and the transmission rate can be ensured.
Referring to fig. 9, a distributed intelligent reflective surface assisted D2D communication system, comprising:
the intelligent reflection surface IRS setting module is used for arranging at least one IRS in a cell to construct at least one D2D pair, and each D2D pair comprises two cell users;
the first model establishing module is used for establishing uplink data transmission rate models of all D2D in the cell to users in the cell;
the second model establishing module is used for establishing communication rate models of all D2D pairs in the cell;
and the optimization module is used for optimizing based on the uplink data transmission model and the communication rate model, so that the optimized D2D communication rate and the uplink data transmission rate of the cell user meet preset requirements.
The above embodiments are preferred embodiments of the present application, and the protection scope of the present application is not limited by the above embodiments, so: all equivalent changes made according to the structure, shape and principle of the present application shall be covered by the protection scope of the present application.

Claims (8)

1. A distributed smart reflective surface assisted D2D communication method, comprising:
at least one intelligent reflection surface IRS is distributed in a cell, at least one D2D pair is constructed, and each D2D pair comprises two cell users;
establishing an uplink data transmission rate model of all D2D in the cell to users in the cell;
establishing a communication rate model of all D2D pairs in the cell;
and optimizing based on the uplink data transmission model and the communication rate model, so that the optimized D2D communication rate and the uplink data transmission rate of the cell user meet preset requirements.
2. The distributed smart reflective surface assisted D2D communication method of claim 1, wherein the preset requirement is that uplink transmission rates of cell users are minimized while D2D communication rates are maximized, the optimizing based on the uplink data transmission model and the communication rate model such that the optimized D2D communication rates and the uplink data transmission rates of the cell users meet preset requirements comprises:
optimizing the multiplexing factor of the D2D pair in the uplink data transmission model and the communication rate model with the preset requirement as an optimization target;
optimizing a cell user beam forming vector by a base station in the uplink data transmission model by taking the preset requirement as an optimization target;
optimizing the transmission power of the cell users and the transmission power of the D2D pair in the uplink data transmission model and the communication rate model with the preset requirement as an optimization target;
and optimizing the phase shift angle matrix of the IRS in the uplink data transmission model and the communication rate model by taking the preset requirement as an optimization target, so that the optimized D2D communication rate is maximized and the uplink data transmission rate of the cell user is minimized.
3. The distributed smart reflective surface assisted D2D communication method according to claim 2, wherein the multiplexing factor for the D2D pair in the uplink data transmission model and the communication rate model with the preset requirement as an optimization target includes:
obtaining initial multiplexing factors of the D2D pairs in the uplink data transmission model and the communication rate model;
when the spectrum resources of the D2D pairs do not need to be multiplexed, obtaining the maximum transmission rate based on the uplink data transmission model, and subtracting the maximum transmission rate of the D2D pair to obtain multiplexing gain;
obtaining an optimized multiplexing factor for the D2D pair based on the multiplexing gain calculation for the D2D pair;
replacing the optimized multiplexing factor with the initial multiplexing factor in the uplink data transmission model and the communication rate model.
4. The distributed intelligent reflective surface assisted D2D communication method according to claim 2, wherein the optimizing base station-to-cell user beamforming vectors in the uplink data transmission model comprises:
respectively setting a phase shift angle matrix of the transmission power of the cell user, the signal transmission power of the D2D pair and the IRS;
when the D2D pair multiplexing factor is not multiplexed, acquiring the transmission rate of the uplink of the cell user;
obtaining the beamforming vector based on a maximum ratio transmission criterion and an uplink data transmission rate model of the cell user;
when the D2D pair multiplexing factor is multiplexed, acquiring the beamforming vector through the threshold requirement;
replacing the beamforming vector with the beamforming vector in the uplink data transmission model.
5. The distributed smart reflective surface assisted D2D communication method according to claim 2, wherein the optimizing the transmit power of the cell users and the transmit power of the D2D pair in the uplink data transmission model and the communication rate model with the preset requirement as an optimization target comprises:
fixing the phase shift angle matrix of the IRS and acquiring the value range of the transmission power of the cell user based on the preset requirement;
respectively obtaining the power distribution result according to the maximum value and the minimum value of the value range of the sending power of the cell user;
replacing the allocated transmission power of the cell user and the transmission power of the D2D pair with the transmission power of the cell user and the transmission power of the D2D pair in the uplink data transmission model and the communication rate model, respectively.
6. The distributed intelligent reflective surface assisted D2D communication method of claim 5, wherein the obtaining the results of power allocation for the maximum and minimum values, respectively, of the transmit power span of the cell users comprises:
establishing a coordinate system by taking the maximum transmitting power of cell users as a vertical coordinate and the maximum transmitting power of D2D to a transmitting end as a horizontal coordinate;
and acquiring the result of power distribution in the coordinate system according to preset requirements.
7. The distributed intelligent reflective surface assisted D2D communication method of claim 2, wherein the optimizing the IRS phase shift angle matrices in the uplink data transmission model and the communication rate model with the preset requirement as an optimization objective comprises:
acquiring the signal to interference plus noise ratio (SINR) of cell users;
acquiring SINR of D2D to a transmitting end;
rewriting the part of the preset target containing the phase shift angle matrix of the IRS based on the SINR of the cell user and the SINR of the D2D to the transmitting end;
respectively fixing the transmitting power of the D2D pair, the transmitting power of the cell user, the beamforming vector of the base station to the cell user and the multiplexing factor, and acquiring a phase shift angle matrix of the IRS by taking the preset requirement as an optimization target;
optimizing a phase shift angle matrix of the IRS.
8. A distributed smart reflective surface assisted D2D communication system, comprising:
the intelligent reflection surface IRS setting module is used for arranging at least one IRS in a cell to construct at least one D2D pair, and each D2D pair comprises two cell users;
a first model establishing module, configured to establish uplink data transmission rate models of all D2D in the cell for users in the cell;
a second model establishing module, configured to establish communication rate models of all D2D pairs in the cell;
and the optimization module is used for optimizing based on the uplink data transmission model and the communication rate model, so that the optimized D2D communication rate and the uplink data transmission rate of the cell user meet preset requirements.
CN202111258467.2A 2021-10-27 2021-10-27 Distributed intelligent reflection surface assisted D2D communication method and system Active CN114025368B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111258467.2A CN114025368B (en) 2021-10-27 2021-10-27 Distributed intelligent reflection surface assisted D2D communication method and system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111258467.2A CN114025368B (en) 2021-10-27 2021-10-27 Distributed intelligent reflection surface assisted D2D communication method and system

Publications (2)

Publication Number Publication Date
CN114025368A true CN114025368A (en) 2022-02-08
CN114025368B CN114025368B (en) 2023-04-07

Family

ID=80058005

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111258467.2A Active CN114025368B (en) 2021-10-27 2021-10-27 Distributed intelligent reflection surface assisted D2D communication method and system

Country Status (1)

Country Link
CN (1) CN114025368B (en)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20200186226A1 (en) * 2018-01-02 2020-06-11 Apple Inc. Phase Tracking Reference Signal (PT-RS) Power Boosting
CN111314893A (en) * 2020-02-17 2020-06-19 电子科技大学 Reflector assisted device-to-device communication system design method
CN112272418A (en) * 2020-09-29 2021-01-26 南京邮电大学 RIS-assisted D2D communication transmission mode selection method
CN113315547A (en) * 2021-05-28 2021-08-27 北京邮电大学 Robust joint transmission beam optimization method for intelligent reflecting surface assisted multiple cells

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20200186226A1 (en) * 2018-01-02 2020-06-11 Apple Inc. Phase Tracking Reference Signal (PT-RS) Power Boosting
CN111314893A (en) * 2020-02-17 2020-06-19 电子科技大学 Reflector assisted device-to-device communication system design method
CN112272418A (en) * 2020-09-29 2021-01-26 南京邮电大学 RIS-assisted D2D communication transmission mode selection method
CN113315547A (en) * 2021-05-28 2021-08-27 北京邮电大学 Robust joint transmission beam optimization method for intelligent reflecting surface assisted multiple cells

Also Published As

Publication number Publication date
CN114025368B (en) 2023-04-07

Similar Documents

Publication Publication Date Title
CN111181615B (en) Multi-cell wireless communication method based on intelligent reflector
US8369791B2 (en) Multi-user beamforming with inter-cell interference suppression
CN102457951B (en) Method for forming link combined wave beam in multi-cell collaborative communication, and base station
US9345032B2 (en) Method and apparatus for determining network clusters for wireless backhaul networks
CN106604300B (en) Small cell base station self-energy supply and self-return method based on full duplex and large-scale antenna technology
CN108449150B (en) Satellite-ground interference coordination method, device and equipment based on radio map information
CN111866901B (en) Relay selection and resource information optimization method, system, computer equipment and application
CN102917442B (en) Comprehensive relay node selection method based on multiple factors in two-hop system with multiple relays
CN111586646B (en) Resource allocation method for D2D communication combining uplink and downlink channels in cellular network
CN114286312A (en) Method for enhancing unmanned aerial vehicle communication based on reconfigurable intelligent surface
CN114070365B (en) Intelligent reflection surface assisted low-radio-frequency-complexity multi-user MIMO uplink spectrum efficiency optimization method
CN102647728B (en) Method for beam forming of down link, transmitting terminal and multi-cell cooperative system
CN111555795A (en) Network resource allocation method and device based on user grouping scheduling
CN113938179A (en) Joint beam forming and power control method for interference of 5G base station to satellite user
Hao et al. Beam alignment for MIMO-NOMA millimeter wave communication systems
Nangir et al. Comparison of the MRT and ZF precoding in Massive MIMO systems from Energy Efficiency viewpoint
CN114025368B (en) Distributed intelligent reflection surface assisted D2D communication method and system
CN114095944B (en) Combined air base station deployment and air-ground information-energy simultaneous transmission method
CN113595599B (en) 5G-oriented cluster cooperative communication heterogeneous system and interference suppression method
Fazliu et al. Graph-based model for beam management in mmwave vehicular networks
CN115865160A (en) Beam forming method and system of large-scale MIMO-NOMA system in low-orbit satellite communication scene
CN114665925A (en) Intelligent reflecting surface backscattering energizing coordinated multipoint transmission method and system
CN115696437A (en) IRS-based user total rate maximization method of wireless energy transmission network
Xia et al. Delay-based user association in heterogeneous networks with Backhaul
Alghamdi et al. Equitable 6G Access Service via Cloud-Enabled HAPS for Optimizing Hybrid Air-Ground Networks

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
TA01 Transfer of patent application right
TA01 Transfer of patent application right

Effective date of registration: 20230320

Address after: No. 2, Section 2, Changcheng Road, Southwest Airport Economic Development Zone, Shuangliu District, Chengdu City, Sichuan Province, 610200

Applicant after: Chengdu Sanyuan Optical Communication Technology Co.,Ltd.

Address before: 311100 No. 318, building 2, No. 1812, Wenyi West Road, Wuchang Street, Yuhang District, Hangzhou City, Zhejiang Province

Applicant before: Zhejiang Yizheng Communication Technology Co.,Ltd.

GR01 Patent grant
GR01 Patent grant