Symbol-by-symbol MAP detection of differential frequency hopping signals for PLC applications

Abstract

In this paper, a symbol-by-symbol maximum a posteriori probability (SBS-MAP) detection of differential frequency hopping (DFH) signals is proposed. Because the frequency sequence of DFH signals can be interpreted as a Markov chain, the algorithm is derived based on a trellis diagram describing the state transitions of a Markov source. The signals are assumed to be transmitted over AWGN channels. Simulation results demonstrate that the SBS-MAP detection outperforms others such as fast Fourier transform (FFT) detection and maximum likelihood sequence estimation (MLSE) detection, which makes it a potentially powerful detection scheme for the design of the receiver of reliable high data rate power line communications (PLC).