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Gaussian Approximation Based Mixture Reduction for Joint Channel Estimation and Detection in MIMO Systems

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4 Author(s)
Jia, Y. ; Philips Res. East Asia, Shanghai ; Andrieu, C. ; Piechocki, R.J. ; Sandell, M.

A novel Gaussian approximation based mixture reduction algorithm is proposed for semi-blind joint channel tracking and symbol detection for spatial multiplexing multiple-input multiple-output (MIMO) systems with frequency-flat time-selective channels. The proposed algorithm is based on a modified sequential Gaussian approximation detector (SGA) which takes into account channel uncertainty, and the first order generalized pseudo-Bayesian (GPB1) channel estimator. Simulation results show that the proposed algorithm performs better than the conventional and computationally expensive decision-directed method with Kalman filter based channel estimation and a posteriori probability (APP) symbol detection.

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Wireless Communications, IEEE Transactions on  (Volume:6 ,  Issue: 7 )