Research On Resource Allocation Technologies Of Integrated Communication And Positioning Based On Millimeter Wave

With the deployment of 5G wireless systems,various emerging applications such as augmented and virtual reality,short videos,webcasting and online games have emerged,leading to explosive growth in wireless data traffic.The traditional microwave spectrum below 6GHz is congested,and it is difficult to meet the huge traffic demand of 5G system.As one of the key technologies of 5G system,mmWave has a spectrum range of 30GHz-300 GHz,which can provide unprecedented spectrum and data rates of several megabits per second.Although the mmWave has great potential in communications,in the NLOS scenario,the mmWave signal has a large blocking loss.However,due to the short wavelength,a large number of antenna arrays can be packaged into small size to form a MIMO system,which uses highly directional transmitting and receiving beams and large-scale MIMO to compensate for the link losses.At the same time,wireless location service is one of the important functions of 5G network.The combination of mmWave and massive MIMO technology is considered to be the key technology of 5G wireless location system.These technologies are not only the key factors for achieving high data rate and high spectral efficiency,but also due to With high resolution and high directivity,they are also promising precision positioning tools.Therefore,it is of great practical significance to integrate mmWave technology,MIMO technology and beamforming technology into the research of communication location integration.In this paper,under the background of integration of communication and location,we design the method of networking based on mmWave characteristics and study the resource allocation technology of integration of communication and location.The main contributions of the paper are as follows:First,under the structure of the mmWave scheduling frame,a time-sharing framework is proposed.In the initial access stage of the framework,the mmWave LOS transmission probability between user pairs is used as the clustering similarity measure,based on K-AP Clustering Algorithm,and the LOS-K-AP clustering algorithm is designed suitable for mmWave systems.Users within a cluster can transmit information through a one-hop link,while communication between users in different clusters requires gateway forwarding.In order to enhance the connectivity between clusters,two adjacent non-overlapping clusters are taken as the research object,path loss is taken as the network cost,and the gateway selection algorithm is designed for the purpose of minimizing the network cost,which provides the integrated communication and positioning system.The basic network topology is analyzed,and the simulation results prove the effectiveness of the clustering calculation and transmission gateway selection algorithm.Then,in the service phase of mmWave scheduling frames,the service phase is divided into positioning phases and communication phases using TDMA technology.In the positioning stage,using single-anchor node positioning technology and Fischer and Cramereau bound theory,derives the positioning error measurement indicators PEB and OEB under the multicarrier condition of the OFDM system,and combines PEB and OEB to obtain the TDMAOFDM system Single user equivalent positioning error.In the communication stage,starting from the signal-to-noise ratio of a single user,the average data rate of multiple users is obtained,and it is extended to the TDMA-OFDM system,and the average data rate of the multi-user under the TDMA-OFDM system is used as an indicator to measure the communication performance.Finally,the positioning performance and communication performance indicators are jointly considered.During the service phase of the mmWave scheduling frame,under the constraints of power and minimum communication rate,a resource allocation optimization problem model is established.By analyzing the characteristics of the optimization problem model,introducing the generalized Benders decomposition algorithm and coloring theory,the optimization problem is decomposed into two sub-problems,and the optimal resource allocation results are obtained by iterative solution between the sub-problems.Simulations verify the impact of resource allocation on positioning and communication performance,as well as the effectiveness and convergence speed of the algorithm.