Adaptive filter theory (3rd ed.)
Adaptive filter theory (3rd ed.)
Matrix computations (3rd ed.)
Multiuser Detection
Efficient signal processing techniques for exploiting transmitantenna diversity on fading channels
IEEE Transactions on Signal Processing
Iterative multiuser joint decoding: unified framework and asymptotic analysis
IEEE Transactions on Information Theory
On the asymptotic performance of the decorrelator
IEEE Transactions on Information Theory
Journal of Control Science and Engineering - Special issue on Hardware Implementation of Digital Signal Processing Algorithms
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A new and efficient class of nonlinear receivers is introduced for digital communication systems. These “iterated-decision” receivers use optimized multipass algorithms to successively cancel interference from a block of received data and generate symbol decisions whose reliability increases monotonically with each iteration. Two variants of such receivers are discussed: the iterated-decision equalizer and the iterated-decision multiuser detector. Iterated-decision equalizers, designed to equalize intersymbol interference (ISI) channels, asymptotically achieve the performance of maximum-likelihood sequence detection (MLSD), but only have a computational complexity on the order of a linear equalizer (LE). Even more importantly, unlike the decision-feedback equalizer (DFE), iterated-decision equalizers can be readily used in conjunction with error-control coding. Similarly, iterated-decision multiuser detectors, designed to cancel multiple-access interference (MAI) in typical wireless environments, approach the performance of the optimum multiuser detector in uncoded systems with a computational complexity comparable to a decorrelating detector or a linear minimum mean-square error (MMSE) multiuser detector.