Markov Chain Monte Carlo Based Detection for Two-Dimensional Intersymbol Interference Channels

Recent advances in ultra-high-density data storage technologies have led to two-dimensional (2-D) intersymbol interference (ISI) in the system. The optimum detection method for 2-D ISI channels has prohibitive computational complexity which makes it impractical. In this paper, we propose a Markov chain Monte Carlo (MCMC) based 2-D detection algorithm whose complexity grows polynomially with the ISI size. When turbo decoded in conjunction with a low-density parity check (LDPC) channel code, the performance of the proposed detection method is evaluated for ultra-high-density bit-patterned magnetic recording (BPMR) systems. Its computational complexity is also analyzed. Our study shows that the proposed detection method significantly reduces the computational burden, while achieving performance better than the BCJR based detection method.