Maximum-likelihood synchronization, equalization, and sequence estimation for unknown time-varying frequency-selective Rician channels

This paper develops a receiver structure to perform jointly ML synchronisation, equalisation and detection of a linearly modulated signal transmitted over a time-varying, frequency-selective, Rician faded channel, corrupted by AWGN. The receiver is particularly suited to a fast fading channel, where other receivers that rely on estimating the channel cannot track it quickly enough. The signal mean and autocovariance are needed, and a scheme is proposed for estimating these quantities adaptively. The receiver processes the specular and diffuse components (corresponding to the signal mean and autocovariance) separately. Processing the known specular component is the classical detection problem. The unknown diffuse component is processed by predictors [11]. We show that the predictors can achieve synchronisation in a novel manner, if synchronisation is required. A union bound on the receiver’s BER is derived, and it tightly bounds simulated BERs in fast fading at high SNRs.