Abstract
Adaptive beamforming (ABF) techniques are used to produce higher gain in the user directions and lower gain in the interferer directions by calculating the excitation weights. It tries to reduce the difference between the desired and actual signal and maximize the signal-to-interference ratio (SIR). But in severe interference environment when the actual signal is weak, the effect of SIR on the radiation pattern needs to be considered. This paper describes the effect of signal-to-interference ratio on different adaptive beamforming techniques such as non-blind least mean square (LMS) and evolutionary particle swarm optimization (PSO). The performance and validation of beamforming algorithms are studied through MATLAB simulation by varying SIR parameter for desired and interference direction. Different weights are obtained using this beamforming algorithm to optimize the radiation pattern. The parameters for comparison are the main beam and null placement keeping signal-to-noise (SNR) constant for specified user and interferer.
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