Reduce-complexity fuzzy-inference-based iterative multiuser detection for wireless communication systems

In recent years, combining multiuser detection and intelligence computer scheme have received considerable attention. In this paper, adaptive fuzzy-inference multistage matrix wiener filtering (FI-MMWF) techniques, based on the minimum mean-square error criterion, are proposed for ultra-wideband (UWB) impulse radio communication systems. These FI-MMWF-based algorithms employ a time-varying fuzzyinference-controlled filter stage. Consequently, the proposed approaches accomplish a substantial saving in complexity without trading off the system performance and dynamic-tracking characteristic. In addition, the fuzzy-logic-controlled matrix conjugate gradient algorithm is adopted to reduce the system complexity without trading off the bit-error-rate (BER). Simulations are conducted to evaluate the convergence and tracking behavior of the proposed MMWF algorithm, and the BER of the time-hopping-UWB system in a realistic UWB channel is investigated. Copyright 2011 John Wiley & Sons, Ltd.