A Markov Chain Monte Carlo Algorithm for Near-Optimum Detection of MIMO-GFDM Signals

Within the framework of Monte Carlo simulation. this paper derives a Markov chain Monte Carlo (MCMC) algorithm for efficient detection in multiple-input multiple output (MIMO) systems using the non-orthogonal multi-carrier waveform termed generalized frequency division multiplexing (GFDM). The proposed MCMC algorithm performs the detection task in frequency domain. Its adopted proposal distribution and Gibbs sampler are tailored under the consideration of complexity and latency for tackling the three-dimensional interference involved in the received signal, i.e., inter-carrier, inter-symbol and inter-antenna interference. By means of simulation, its decoding performance is compared with that achieved by employing the sphere decoding algorithm in a conventional orthogonal frequency division multiplexing (OFDM) based MIMO system. For multi-path fading channels with strong frequency selectivity, the MCMC algorithm proposed for the MIMO-GFDM system can deliver superior performance.