Resource Allocation And Interference Management Technologies For The Future Wireless Communication Networks

With the rapid development of wireless communication technology, increasingly heterogeneous network and the development of various kinds of wireless business requirements, the future wireless communication network needs to provide a wide range of network services, and supports high rate of real time streaming media business. In order to meet the requirement for network deployment, maintenance, and optimization of future communication systems, a promising solution to improve network performance is self-organizing network (SON) technology. Load balancing of wireless communication networks, energy consumption and interference has attracted widely attention. Future communication networks must improve system performance within the constrains of radio resource and interference. Therefore, it is worthwhile to explore resource allocation and interference management techniques for the future of wireless communication network. In this paper, we will explore the allocation of resource and interference management for load balancing, optimization of energy efficiency and interference cancellation. The main works are as follows:1. This paper investigates the user association for load balancing in Heterogeneous network. For the scenario where the macro cell and micro cell are overlaid in the Heterogeneous network, we propose a QoS-aware user association strategy. Firstly, we jointly consider the load of each BS and user’s achievable rate, and formulate it as a network-wide weighted utility maximization problem. Secondly, we design a low-complexity distributed algorithm for the proposed problem. Each Base Sation updates the optimum load and the Lagrange multiplier and announces the new multiplier to the system. Each user receives the multiplier broadcast by each BS and formulates the optimum number of the BS. Numerical results show that, compared with the user-based association strategy, our strategy has much faster convergence rate, lower call blocking probability and higher load balancing level.2. This paper investigates the problem of energy efficient resource and power allocation in the two-tier Orthogonal Frequency Division Multiplexing (OFDM) Heterogeneous network. We explore a user association strategy which is based on maximizing energy efficient. This paper studies subcarrier allocation and energy-efficient resource allocation scheme subject to user’s maximum transmission power. The single-user single-carrier and multi-user multi-carrier energy efficiency maximization problems are mainly discussed. Using an iterative solution approach, we explore two low-complexity subcarrier allocationing scheme to maximize the energy efficency in the multi-user multi-carrier scene. The impact of user’s maximum transmission power on system’s throughput and energy efficiency is studied through the simulation experiment. Numerical simulation shows that compared with traditional algorithm, the algorithms of maximizing energy efficient based user association and subcarrier allocationing scheme can effectively improve system performance significantly and validate the feasibility of the scheme.3. This paper finally investigates the interference cancellation technology for the SON and proposes a joint zero-forced interference alignment and power allocation scheme. According to the characteristics of self-organizing networks, we propose an interference cancellation scheme which employed at macro base station for the cancellation of cross-tier interference. In this scheme, the mobile stations just need to send their cross-channel information to the macro base station in order to achieve self-optimizing in the small cells. Based on the theoretical analysis, we derive the expressions of the probability density function (PDF) and cumulative distribution function (CDF) of the received SNRs of both macro and small cell users, and provide the closedform expressions of overall outage probability of the system. The numerical results show that the overall performance of the network is improved with interference cancellation and verify the accuracy of theoretical analysis.