The full-complexity soft-input/soft-output (SISO) detector based on the BCJR algorithm for coded partial-response channels has a computational complexity growing exponentially with channel memory length. In this letter, we propose a low complexity soft-output channel detector based on the Chase decoding algorithm, which was previously applied to decode turbo product codes. At each iteration, the proposed detector forms a candidate list using all possible combinations of bit patterns in the weakest indices based on tentative hard estimates and a priori information fed back from the outer decoder. To demonstrate the performance/complexity tradeoff of the proposed detector, simulation results over rate-8/9 turbo-coded EPR4 and ME/sup 2/PR4 channels are presented, respectively. It is shown that the proposed detector can significantly reduce the computational complexity with only a small performance loss compared to the BCJR algorithm.

The full-complexity soft-input/soft-output (SISO) multiuser detector based on the a posteriori probability (APP) algorithm has a computational complexity growing exponentially with the number of users. In this paper, we consider the multiuser detection problem from a combinatorial optimization viewpoint and develop a novel class of SISO multiuser detectors based on local search (LS) heuristics. By restricting the search to a small subset of the solution space and producing the APP based on a candidate list of potential solutions, the proposed detector can achieve bit-error-rate (BER) performance close to that of the APP algorithm with a significantly lower computational complexity.

This paper describes a robust speech detection algorithm that can operate reliably in a microphone array teleconferencing system. High performance in a nonstationary noisy environment is achieved by combining the following techniques: (1) noise suppression by spectral subtraction, (2) silence detection by adaptive noise threshold and (3) non-stationary noise detection based on the availability of pitch signal. This algorithm can prevent the microphone-array-based speaker tracking system from being misguided by noises commonly present in a conference room. Real world experiments show that this algorithm performs very well and has the potential for practical applications.