
AbstractThe capability of adaptive antenna array lies in forming higher gain in the user directions and lower gain in the interferer directions. The technique used to produce such radiation pattern by calculating the excitation weights are called the adaptive beamforming (ABF) techniques. It tries to minimize the error 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), blind constant modulus algorithm (CMA) and evolutionary Particle Swarm Optimization (PSO). The performance and validation of beamforming algorithms are studied through MATLAB simulation by varying SIR parameters for different 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 different angles of user and interferer. The mean SLL and directivity are also studied.
Adaptive antenna, Beamforming, Particle swarm optimization, Signal to interference ratio, Least mean square, TA1-2040, Constant modulus algorithm, Engineering (General). Civil engineering (General), Engineering(all)
Adaptive antenna, Beamforming, Particle swarm optimization, Signal to interference ratio, Least mean square, TA1-2040, Constant modulus algorithm, Engineering (General). Civil engineering (General), Engineering(all)
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