Robust Blind Beam Formers for Smart Antenna System Using Window Techniques

In this paper, we devised three efficient adaptive blind beamformers for smart antenna system based on popular constant modulus algorithm (CMA). Slow convergence rate of classical CMA limits its utilization in wireless communication applications where the channel conditions are rapidly changing. To overcome this problem, we firstly improved the convergence rate of CMA by making a step size adaptive. This makes CMA to converge within 10 iterations. Furthermore, to reduce the side lobe level (SLL), we applied three different windows namely; hanning, hamming and kaiser to the improved CMA and these algorithms are called as H-CMA, HW-CMA and KW-CMA respectively. Simulated results show that, KW-CMA has highest reduction in SLL as compared to H-CMA and HW-CMA. It has -80 dB peak SLL with an improvement of 70.89 dB for ten antenna elements than the conventional CMA for the same conditions. Hence the proposed algorithms exhibit fast convergence rate and reduced SLL. These key features make the smart antenna system robust and efficient and can be used in advanced wireless communication applications like radar, sonar and mobile communications.