Adaptive Beamforming Algorithms for Cancellation of Multiple Interference Signals

Abstract

Abstract-This paper proposes a fast Minimum-Variance-Distortionless-Response (MVDR) beamforming algorithm for an antenna array for cancellation of multiple interference signals. The proposed algorithm uses Sample-Average Estimate (SAE) of the data covariance matrix and reduces its computational effort by applying the Matrix-Inversion-Lemma (MIL) to its covariance Matrix Inversion (MI) operation. The proposed algorithm is compared to two SAE-based algorithms: the Sample Matrix Inversion (SMI) algorithm that requires an MI operation and the Auxiliary Vector (AV) algorithm that does not need an MI operation. A non-SAE based algorithm using the Least Mean Square (LMS) method is also included for comparison. Simulation results show that the proposed algorithm converges slower than the SMI scheme but outperforms the AV and LMS schemes during the transient phase. Once convergence is achieved, the proposed algorithm converges to a better Mean Square Error than the rest of the algorithms evaluated.

Features and Futures of Smart Antennas for Wireless Communications: A Technical Review

“…Directional beams of smart antenna systems are normally used for steering in order to reduce the interference to the barest minimum. In wireless communication systems, one can experience interference to co-channel, provided that it is in the purview of narrow beamwidth of the smart antennas [31,44,45]. There is reduction of interference using smart antenna systems by nulls formation and by placing it in the interfering co-channel user's direction.…”

“…The switched beam system comprises a RF switch between discrete directional antennas pattern of an array which can be formed by beamforming network, while aiding high gain and controlled beamwidth [45][46][47][48][77][78][79][80]. This approach can be considered as an extension of cellular sectrorization scheme [49,50].…”

“…Hence, the journey of smart antenna techniques began and a large amount of scientific contributions have been published on numerous conferences and in peer reviewed scientific journals and books. Many researchers have investigated various techniques for improving the performance of the smart antenna arrays in mobile communication systems [15,29,40,45,57,60,61,101]. There are various signal processing algorithms such as Least Mean Square (LMS), Recursive Least Square (RLS), Normalized Least Mean Square (NLMS), Fractional least Mean Square (FLMS) and Constant Modulus Algorithm (CMA), etc.…”

“…LMS algorithm, and RLS algorithm. Its principle for decisive the weight is centered on reducing the least square error (LSE) [45,[69][70][71].…”

“…In digital communication the synchronization signals can be used for the same purpose. The RLS is the paramount algorithm appropriate for antijamming uses and it frequently joins with instruction of enormousness more rapidly than LMS algorithm alternatively the disadvantage is the added complexity [45,[69][70][71]. Quite a lot of modifications of RLS algorithm are correspondingly recommended, one of which is Gradient based Variable Forgetting Factor (GVFF) RLS.…”