Reduced complexity M-ary hypotheses testing in wireless communications

We present a progressive refinement approach to M-ary detection problems. The approach leads on average to a logarithmic reduction in the complexity of the detector. It relies on designing binary decision trees that trade complexity with probability of error. We also discuss simplified solutions that can be used in several cases of interest in wireless communications such as CDMA multiuser detection and blind equalization.

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