Implementation of a Markov Chain Monte Carlo Based Multiuser/MIMO Detector

Multiuser/multiple-input-multiple-output detectors that use Markov chain Monte Carlo (MCMC) simulation techniques to obtain likelihood of information bits have been developed recently. In this paper, we explore the implementation details of one such detector and present an efficient hardware architecture of it. The first step in development of this architecture is to derive a log-domain version of the Gibbs sampler, an efficient method of obtaining samples of MCMC simulator. This formulation is numerically stable and can operate with low precision. The log- domain formulation also lends itself to a hardware architecture that involves only addition, subtraction, and compare operations. Moreover, pipelining is introduced in the proposed architecture straightforwardly. We also explore the word-length requirement of the developed architecture through computer simulations.

[1]  Shu Lin,et al.  Error control coding : fundamentals and applications , 1983 .

[2]  手塚 集.  Uniform random numbers : theory and practice , 1995 .

[3]  Sergio Verdu,et al.  Multiuser Detection , 1998 .

[4]  Christian P. Robert,et al.  Monte Carlo Statistical Methods , 2005, Springer Texts in Statistics.

[5]  H. Vincent Poor,et al.  Iterative (turbo) soft interference cancellation and decoding for coded CDMA , 1999, IEEE Trans. Commun..

[6]  Gerard J. Foschini,et al.  Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas , 1996, Bell Labs Technical Journal.

[7]  M. O. Damen,et al.  A unified framework for tree search decoding: rediscovering the sequential decoder , 2005, SPAWC 2005.

[8]  Rong Chen,et al.  Adaptive Bayesian multiuser detection for synchronous CDMA with Gaussian and impulsive noise , 2000, IEEE Trans. Signal Process..

[9]  B. Hochwald,et al.  Silicon complexity for maximum likelihood MIMO detection using spherical decoding , 2004, IEEE Journal of Solid-State Circuits.

[10]  A. Burg,et al.  VLSI implementation of MIMO detection using the sphere decoding algorithm , 2005, IEEE Journal of Solid-State Circuits.

[11]  A. Burg,et al.  VLSI Implementation of the List Sphere Algorithm , 2006, 2006 NORCHIP.

[12]  Haidong Zhu,et al.  MIMO detection using Markov chain Monte Carlo techniques for near-capacity performance , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[13]  Björn E. Ottersten,et al.  On the complexity of sphere decoding in digital communications , 2005, IEEE Transactions on Signal Processing.

[14]  Giuseppe Caire,et al.  On maximum-likelihood detection and the search for the closest lattice point , 2003, IEEE Trans. Inf. Theory.

[15]  Haidong Zhu,et al.  On performance of sphere decoding and Markov chain Monte Carlo detection methods , 2005, IEEE Signal Processing Letters.

[16]  Hesham El Gamal,et al.  A new approach to layered space-Time coding and signal processing , 2001, IEEE Trans. Inf. Theory.

[17]  Sergio Verdú,et al.  Minimum probability of error for asynchronous Gaussian multiple-access channels , 1986, IEEE Trans. Inf. Theory.

[18]  Christian P. Robert,et al.  Monte Carlo Statistical Methods (Springer Texts in Statistics) , 2005 .

[19]  Stephan ten Brink,et al.  Achieving near-capacity on a multiple-antenna channel , 2003, IEEE Trans. Commun..

[20]  Shu Tezuka,et al.  Uniform Random Numbers , 1995 .

[21]  Patrick Robertson,et al.  A comparison of optimal and sub-optimal MAP decoding algorithms operating in the log domain , 1995, Proceedings IEEE International Conference on Communications ICC '95.

[22]  Paul D. Alexander,et al.  Iterative multiuser interference reduction: turbo CDMA , 1999, IEEE Trans. Commun..

[23]  Behrouz Farhang-Boroujeny,et al.  Markov Chain Monte Carlo MIMO Detection Methods for High Signal-to-Noise Ratio Regimes , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[24]  E. Moulines,et al.  Turbo multiuser detection for coded DS-CDMA systems: a Gibbs sampling approach , 2000, Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154).

[25]  Petar M. Djuric,et al.  Multiuser detection of synchronous code-division multiple-access signals by perfect sampling , 2002, IEEE Trans. Signal Process..

[26]  Sylvia Richardson,et al.  Markov Chain Monte Carlo in Practice , 1997 .

[27]  Robert Chen-Hao Chang,et al.  A High-Speed SDM-MIMO Decoder Using Efficient Candidate Searching for Wireless Communication , 2008, IEEE Transactions on Circuits and Systems II: Express Briefs.

[28]  Emre Telatar,et al.  Capacity of Multi-antenna Gaussian Channels , 1999, Eur. Trans. Telecommun..

[29]  Keshab K. Parhi,et al.  Probabilistic List Sphere Decoding for LDPC-Coded MIMO-OFDM Systems , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[30]  Haidong Zhu,et al.  Markov chain Monte Carlo algorithms for CDMA and MIMO communication systems , 2006, IEEE Transactions on Signal Processing.