Research On Resource Allocation In Wireless Millimeter Wave Communication

The rapid growth of smart devices and high-data-rate applications such as online gaming and high-definition video have imposed ever-increasing high rate traffic demands on the future wireless communications.To cope with this challenge,MIMO,beamforming,mobile edge computing(MEC)and other technologies have been proposed to address user needs.There has also been a great interest in millimeter wave(mm Wave)frequency band where a wide range of bandwidth is available.Meanwhlie,how to design a reliable and effective resource allocation algorithm to maximize the system capacity,or minimize the total system energy consumption will become a more worthy issue.The main contents of this article are summarized as follows:1.This section focuses on the joint beam,subcarrier and power allocation in switched-beam based massive multipleinput-multiple-output(MIMO)orthogonal frequency division multiple access(OFDMA)system working at the millimeter wave(mm Wave)frequency band,with the target of maximizing the weighted sum rate.To solve the optimization problem,we divide it into two subproblems: 1)beam allocation for fixed subcarrier and power allocation;2)subcarrier and power allocation for fixed beam allocation.For the first subproblem,a heuristic beam allocation algorithm is proposed.For the second subproblem,we transform it into a convex problem and solve it by using the proposed optimization algorithm based on the difference of two convex functions approximation(DCA)method.A low-complexity algorithm is also proposed to further reduce the complexity.Simulation results demonstrate that the proposed algorithms can enhance the weighted sum rate of the wireless transmission system significantly.2.This section studies the problem of joint user grouping,beams,subcarriers,and power allocation in a switched beam multiple input multiple output orthogonal frequency division multiple access system working at the millimeter wave band.The goal of the optimization is to maximize downlink multiple time slots average system sum rate.A user grouping method is proposed,and the beam,subcarrier,power joint optimization method and low complexity algorithm are used to propose the user group joint optimization algorithm and the user group low complexity algorithm to solve this problem.The simulation results show the relationship between the system sum rate and the number of user groups and beams.3.The problem of user computing offloading in a multi-base station multiuser OFDMA system is studied.The user computing offloading decision,subcarrier and power allocation are jointly optimized to minimize the energy consumption of the system.Decompose the original optimization problem into multiple sub-problems and solve them separately.The user computing offloading decision and subcarrier allocation are given at first,and the alternate iteration method is used to obtain the optimal power allocation result.Both subcarrier allocation and user computing offloading decision problems are modeled as weighted optimal matching problems.After calculating the weight matrix of the bipartite graph,it can be solved by using Kuhn-Munkers algorithm.Low complexity algorithms have also been proposed to reduce computational complexity.The simulation results are given to prove the effectiveness of the joint optimization algorithm.