Abstract
In this paper, a particle filter (PF) with simulated annealing algorithm is proposed to estimate and track Rayleigh channel state information (CSI) using decision directed scheme. By iteratively cooling in PF, there are two superiorities in our proposed algorithm. First, there is no degeneration problem in this method. Second, the proposed algorithm converges globally. The proposed algorithm has been implemented in a system on Rayleigh channel with BPSK modulation. Also, the consistency and sensitivity of the algorithm has been tested and the simulation results show that the proposed algorithm is good enough to be applied to wireless communication practice. The relationships between channel estimation and measurement noise, SNR and Doppler frequency have been shown by simulations.
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References
Manikas A, Sethi M. A Space-Time Channel Estimation and Single-User Receiver for Code-Reuse DS-CDMA System[J]. IEEE Transaction on Signal Processing, 2003, 51(1): 39–51.
Vander A J, Paulraj A. A Subspace Approach to Blind Space-Time Signal Processing for Wireless Communication Systems [J]. IEEE Transactions on Signal Processing, 1997, 45(1): 173–190.
Efthimios E T, Nicholas D S, Ananthram S. Optimal Particle Filters for Tracking a Time-Varying Harmonic or Chirp signal[J]. IEEE Transactions on Signal Processing, 2008, 56(10): 4598–4610.
Pradeep A, Wang X D. Multilevel Sequential Monte Carlo Algorithm for MIMO Demodulation[J]. IEEE Transactions on Wireless Communications, 2007, 6(2): 750–758.
Steven M K. Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory [M]. New York: Prentice Hall, 1993.
Gordon N, Salmond D, Smith A F M. Novel Approach to Nonlinear/Nongaussian Bayesian State Estimation[C]//IEE Proceedings F, Radar and Signal Processing, 1993, 140: 107–113.
Arulampalam M S, Maskell S, Gordan N, et al. A Tutorial on Particle Filters for Online Nonlinear/Non-Gaussian Bayesian Tracking[J]. IEEE Transactions on Signal Processing, 2002, 50(2): 174–188.
Liu J S, Chen R. Sequential Monte Carlo Methods for Dynamic Systems[J]. Journal on American Statistical Association, 1998, 93(443): 1032–1044.
Mark B Y, Yan Z, Yu T Y. Spectral Signature Calculations and Target Tracking for Remote Sensing[J]. IEEE Transaction on Instrumentation and Measurement, 2006, 55(4): 1430–1442.
Kirkpatric S, Gelatt C D, Vecchi M P. Optimization by Simulated Annealing[J]. Science, 1983, 220(4598): 671–680.
Simon H, Kris H, Chen Z. Bayesian Sequential State Estimation for MIMO Wireless Communications[J]. Proceedings of the IEEE, 2004, 92(3): 439–454.
Wang H, Chang P. On Verifying the First-Order Markovian Assumption for a Rayleigh Fading Channel Model[J]. IEEE Transactions on Vehicle Technology, 1996, 45(2): 353–357.
Christopher C T, Norman C B. On First-Order Markov Modeling for the Rayleigh Fading Channel[J]. IEEE Transactions on Communications, 2000, 48(12): 2032–2040.
Kenneth L B, Theodore S R, Charles W B. Measurements and Models of Radio Frequency Impulsive Noise for Indoor Wireless Communications[J]. IEEE Journal on Selected Areas in Communications, 1993, 11(7): 991–1001.
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Wang, W., Zhu, Q. & Xu, X. Rayleigh channel estimation based on particle filter with simulated annealing algorithm. Wuhan Univ. J. Nat. Sci. 14, 153–157 (2009). https://doi.org/10.1007/s11859-009-0212-y
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DOI: https://doi.org/10.1007/s11859-009-0212-y