Low-Complexity Factor Graph-Based Iterative Detection for RRC-SEFDM Signals

Abstract

Spectrally efficient frequency division multiplexing (SEFDM) is a promising technique for the next generation wireless communication due to its high spectral efficiency. Conventional SEFDM detectors suffer from the challenging tradeoff between computational complexity and bit error rate (BER) performance. In this paper, we propose a low-complexity iterative detector using Gaussian message passing (GMP) on factor graph for coded root raised cosine (RRC) shaped SEFDM signals. By ignoring the weak intersymbol interference (ISI) imposed by packing sub-carrier interval, the detection of SEFDM signals is reformulated into a linear state-space model and a corresponding Forney-style factor graph (FFG) is constructed. Then, we derive messages updating expressions based on GMP rules, which enable low-complexity parametric message passing. Since the Gaussian approximation employed on the cycle-free factor graph, the computational complexity of the proposed algorithm increases linearly with the number of sub-carriers. Simulation results show that the coded RRC-SEFDM system with the proposed factor graph-based iterative detection can improve the transmission rate up to 40% with about 0.5 dB $E_{b}/N_{0}$ loss.