Interference mitigation using coordinated beamforming techniques in 4G multi-cell multi-user MIMO

Abstract

Interference mitigation in current and next-generation wireless cellular networks has always been a central focus of research. With increasingly aggressive frequency reuse being implemented, and the interest in heterogeneous network structures; cell boundaries are expected to heavily overlap in the near future. This generates inter-cell interference towards users located near cell edges, significantly degrading their overall performance and spectral efficiency. Therefore, newer interference mitigation schemes to support the exponential growth in mobile data requirements are needed. · This dissertation explores the benefit of coordination amcing multiple cells using multiple antenna techniques to reduce the level of interference generated by the network. Based on the specifications listed in the LTE-Advanced (LTE-A) standard, which is expected to deliver next generation wireless speeds ( 4G), a taxonomy of possible interference mitigation techniques is presented. The focus of this study is narrowed down to coordinated beamforming solutions, where multiple base stations (BS) coordinate efficiently by sharing scheduling and resource information. This extra information is then used by the transmit strategy in order to balance overall network performance. The proposed algorithm is based on coordinated zero-forcing beamforming (C-ZFBF) with time division multiplexing (TDM). It uses antennas at the BS in order to cancel interference directed towards out-of-cell users so as not to degrade their performance. The strategy proposed is scalable and easily implemented in LTE-A networks where existing backhaul infrastructures can support the limited coordination being used. The algorithm is then tested in a software simulation environment built in MATLAB, which replicates a testing environment already used in the literature. Compared to uncoordinated beamforming algorithms, the proposed solution is found to improve spectral efficiency by around 90%. Furthermore, it achieves an improvement of 36% over the uplink-downlink duality-based coordinated beamforming (CBF) algorithms proposed in the literature.