A Study on Interference Alignment with Clustered Base Stations and Scheduled Users

• Main Authors: Chen, Shih-Yang, 陳世揚
• Other Authors: Sang, Tzu-Hsien
• Format: Others
• Language: en_US
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/t4v8fu

碩士 === 國立交通大學 === 電子研究所 === 105 === 5G mobile wireless communication network is future trend. The number of users grow rapidly and the impact of interference cannot be ignored. In order to reduce the impact of interference to communication systems, many interference suppression schemes have been proposed. It is mainly solved by signal processing in the physical layer or by resources allocation in the media access control layer (MAC layer). In the physical layer, interference alignment (IA) is a promising solution of interference suppression scheme. A selection of transmitters will cooperate, and encoders and decoders will be designed accordingly. The signals from interfering transmitters are aligned to the same sub-space at the receiver, and the desired signal can be transmitted in the interference-free signal subspace. Generally speaking, it can be viewed as a beamforming technique. The technique has been proven effective in eliminate interference in theory. Although the performance gain of IA is significant, there are two serious issues. One is that every transmitter needs to know the channel status information (CSI) of each interference channels; it is a big challenge to backhaul networks. The other is limitation of the number of cooperative transmitters. The limited number of antennas can only align limited interferences, so another problem is how to decide which interference should be aligned. The current feasible solution is to divide all transmitters into many isolated and appropriate groups by a clustering algorithm, such as the genetic algorithm and the particle swarm optimization algorithm. Then apply interference alignment to each cluster. As for the excessive number of users, scheduling is deployed to manage the situation. The goal of this thesis is to develop an integrated interference suppression scheme by incorporating the clustering algorithm and scheduling algorithm for IA, and reduce power allocation is conducted to improve performance further more. Theoretical analysis and numerical simulations are provided to illustrate the effectiveness and limitation of this interference management scheme in reducing the multiuser interference in interference networks.