A NLVFF-RLS approach to adaptive beamforming for wireless communication

Adaptive antenna system synthesis is presented for wireless communication with reduced interference with the help of non linear variable forgetting factor Recursive least squares algorithm(NLVFF-RLS). A case of 8 elements of uniform linear array is considered and operated in the WiMAX frequency of (IEEE802.16e) 2.5GHz. The signal is modeled as MSK symbols. This approach models the uniform linear array to track the dynamic changes in the angle of arrival and simultaneously steers number of users with minimum Half Power Beam width (HPBW) and maximum directivity. The novel aspect of the proposed (RLS) algorithm is its convergence speed and ability to track several users in the adaptive signal environment. Simulation results shows that the Recursive Least squares (RLS) algorithm yields 12db interference suppression with appreciable convergence rate in 10 iterations in the scanning sector of -50 to +50. Conventional RLS with constant forgetting factor will not yield the optimal performance in non-stationary environment and the algorithm is simulated in Matlab.