Interference Mitigation in Multiuser Multiple Input Multiple Output Long Term Evolution-Advanced Systems

Abstract

Wireless data usage is increasing at a phenomenal rate and driving the need for continued innovations in wireless data technologies to provide more capacity and higher quality of service. 3GPP LTE advanced is an evolving standard targeting 4G wireless system, LTE-Advanced introduces new functionalities such as Carrier aggregation, enhanced use of multi-antenna techniques Multiple-Input Multiple-Output (MIMO) antenna technology can have a multiplicative effect on LTE’s data capacity and better spectral efficiency. The predicted enormous capacity gain of MIMO is nonetheless significantly limited by interference, it consider as a problem which will degrade the system performance arises in transmission quality and the system capacity. This research studies the interference problem in LTE Advanced MIMO as one of the challenges facing 4G systems, Smart antenna technology offer significantly improved solution to reduce this interference level and improve system capacity. With this technology, each user’s signal is transmitted and received only in the direction of that particular user. Smart antenna technology attempts to address this problem via advanced signal processing technology called beam-forming ,which uses adaptive algorithms to cancel the interference signals by increasing the gain in a chosen direction. Therefore, it would improve the system performance. In this thesis least mean square (LMS) and recursive least square (RLS) Adaptive Beamforming algorithms methods are studied and analyzed to update weights of the smart antenna to form narrower beams towards the desired user and nulls towards interfering users, considerably improving the signal-to-interference-plus-noise ratio. The system performance of MU-MIMO case was evaluated in different scenarios, with and without beamforming techniques in terms of Bit-Error-Rate (BER) and signal-to-interference-plus-noise ratio (SINR). For the simulation purpose we use MATLAB software package. The achieved results shows that both the two algorithms offers a significantly improved solution to reduce interference levels and improve the system capacity but the RLS algorithm has faster convergence rate and much better performance than LMS algorithm.