Efficient beamforming and spectral efficiency maximization in a joint transmission LTE-A system

Next-generation cellular networks and beyond are expected to adopt a frequency reuse factor of one to support high spectral eficiency. Consequently, Inter-Cell Interference (ICI) represents a serious issue among neighboring cells, especially for cell-edge users. In addressing this, Joint Transmission (JT) represents one of the most sophisticated techniques for mitigating ICI stemming from implementing a frequency reuse factor of one. Moreover, JT also converts the interfering signals into useful signals to improve the spectral eficiency of the system. However, JT produces enormous overhead on both the feedback and backhaul interfaces; thus, partial JT was proposed as a trade of between signaling demand and increased spectral eficiency. Maintaining an equivalent Beamforming (BF) matrix based on a sparse aggregated channel matrix is a challenging issue with regard to linear BF schemes such as Zero-Forcing (ZF). This is mainly because ZF can only invert a well-conditioned matrix. Therefore, a Multi-Start Particle Swarm Optimization Algorithm (MSPSOA) is included in this thesis and used to present an eficient beamformer that achieves equivalent backhaul reduction and high spectral eficiency. Moreover, addressing the lack-of-diversity issue in Basic Particle Swarm Optimization Algorithm (BPSOA) is a primary concern of this work. As a contribution of this thesis, diversity loss can be solved by replacing the inactive particles adaptively based on the difference between local best and global best optimization criterion. In this study, the performance of ZF, BPSOA and the proposed MSPSOA BF are evaluated by using different metrics like acquired sum rate, level of actual interference and transmitting power along with total utility of three different internet applications. The beamformer obtained with the objective function of sum rate maximization achieves a spectral eficiency of 15.3% compared to BPSO BF in some of the conducted scenarios.

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