Block-Shanno Minimum Bit Error Rate Beamforming

Abstract

Beamforming is a key technology in smart antenna systems that can increase capacity and coverage and mitigate multipath propagation in mobile radio communication systems. The most popular criterion for linear beamforming is the minimum mean square error (MMSE). However, the mean square error (MSE) cost function is not optimal in terms of the bit error probability performance of the system. A class of adaptive beamforming algorithms has been proposed based on minimizing the bit error rate (BER) cost function directly. Unfortunately, the popular least minimum BER (LMBER) stochastic beamforming algorithm suffers from low convergence speed. Gradient Newton algorithms have been proposed to speed up the convergence rate and enhance performance but at the expense of complexity. In this paper, a block processing objective function for the minimum BER (MBER) is formulated, and a nonlinear optimization strategy, which produces the so-called block-Shanno MBER (BSMBER), is developed. A complete discussion for the complexity calculations of the proposed algorithm is demonstrated. Simulation scenarios are carried out in a multipath Rayleigh-fading direct-sequence code-division multiple access (DS-CDMA) system to explore the performance of the proposed algorithm. Simulation results show that the proposed algorithm offers good performance in terms of convergence speed, steady-state performance, and even system capacity compared to other MBER- and MSE-based algorithms.