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Stochastic Iterative MIMO Detection System: Algorithm and Hardware Design
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DOI：10.1109/TCSI.2015.2390558.png)
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Abstract
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In this paper, we propose a Stochastic iterative multiple-input multiple-output (SIM) detection system based on the Markov chain Monte Carlo (MCMC) method. To improve the detection performance, the Gibbs sampler of the MCMC detector in the SIM is updated by the decoded bits from a channel decoder directly. The channel decoder is part of the updating unit that generates the new samples in the MCMC updating process. We also implement the SIM in a fully parallel scheme, which achieves a high detection speed. As a case study, we have designed and synthesized a 128-parallel 4 x 4 16-QAM SIM system using a CMOS 130 nm technology with a core area of 1.98 mm(2) and 457K logic gates. The SIM detection system can achieve a throughput of 787.5 Mbps with a frame error rate (FER) 10(-3) at E-b/N-o = 7dB, equaling the FER of a traditional iterative MIMO detection with four outer iterations.
Keywords:
Markov chain Monte Carlo (MCMC)
multiple-input multiple-output (MIMO) system
stochastic iterative MIMO (SIM)
stochastic logic
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