PSK symbol synchronization performance of ML-oriented data-aided algorithms for nonselective fading channels

Two maximum-likelihood (ML)-oriented data-aided (DA) symbol synchronization algorithms are investigated in this paper. They operate on a noisy M-PSK signal (M>2) transmitted over a slowly time-varying nonselective Rician fading channel. The first algorithm is channel-aided (CA): it makes use of an estimate or the instantaneous channel gain. The second algorithm is nonchannel-aided (NCA): timing is acquired independently of the channel gain estimation. Both algorithms operate either with a known training sequence or in a decision-directed mode, and are suitable for fully digital implementation. We find that the CA algorithm yields a smaller tracking error variance than the NCA algorithm, but the difference in performance decreases with increasing carrier-to-multipath (C/M) ratio.<
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