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.Index Terms-BCJR algorithm, low-density parity-check codes, Markov chain Monte Carlo methods, turbo decoding, two-dimensional intersymbol interference.
In this paper, we present a thorough and comprehensive study for bit-patterned media recording (BPMR), from a signal processing and coding perspective. We first propose a recording-physics-based generic channel model for BPMR, which includes all the major characteristics and impairments of the system. It also provides a fair basis for the performance comparison of different coding and detection schemes. We further propose various channel algorithms and techniques for BPMR, including a two-dimensional (2D) equalization scheme with onedimensional (1D) generalized partial response (GPR) target to mitigate inter-track interference (ITI) and media noise, a maximum a posteriori (MAP) detector for BPMR with write errors, various low-density parity-check (LDPC) codes, as well as the iterative detection and decoding schemes. The corresponding performance gains are illustrated at 4Tb/in 2 .
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