Blind detection in MIMO systems via sequential Monte Carlo

Authors:
Dong Guo;Xiaodong Wang
Affiliations:
Dept. of Electr. Eng., Columbia Univ., New York, NY, USA;-
Venue:
IEEE Journal on Selected Areas in Communications
Year:
2006

Citing 0
Cited 5

Space-time coding and signal processing for MIMO communications

Journal of Computer Science and Technology
Multilevel mixture Kalman filter

EURASIP Journal on Applied Signal Processing
Sequential Monte Carlo methods for complexity-constrained MAP equalization of dispersive MIMO channels

Signal Processing
Minimum Kullback-Leibler-Based Turbo Multiuser Detector over Decomposition CDMA Signal

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
A fixed-lag particle smoother for blind SISO equalization of time-varying channels

IEEE Transactions on Wireless Communications

Quantified Score

Hi-index	0.07

Visualization

Abstract

We provide a novel sequential estimation and detection approach for multiple-input-multiple-output (MIMO) systems. The basic idea is to design a probabilistic approximation method for the computation of the maximum a posterior distribution (MAP) via the sequential Monte Carlo methods (SMC). The SMC method has two advantages over the other methods in that it is a blind method and can be computed in parallel. Furthermore, the SMC has characteristics of soft-input and soft-output in nature and, thus, it can be employed as the first stage demodulator in a turbo receiver for a coded MIMO system. Such a turbo receiver successively improves the receiver performance by iteratively exchanging the so-called extrinsic information with the MAP outer channel decoder. Finally, the performance of the proposed sequential Monte Carlo receiver is demonstrated through computer simulations for MIMO systems over single-path and multipath fading channels.