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Optimized Markov Chain Monte Carlo for Signal Detection in MIMO Systems: An Analysis of the Stationary Distribution and Mixing Time

, , , , and . Signal Processing, IEEE Transactions on, 62 (17): 4436-4450 (September 2014)
DOI: 10.1109/TSP.2014.2334558

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Receiver design of MIMO systems in a mixture of Gaussian noise and impulsive noise., , , and . VTC Fall (2), page 1493-1497. IEEE, (2004)BER Analysis of the box relaxation for BPSK Signal Recovery., , , and . CoRR, (2015)Efficient and Robust Compressed Sensing using High-Quality Expander Graphs, , , and . CoRR, (2008)Performance Analysis and Receiver Design for SDMA-Based Wireless Networks in Impulsive Noise., , , , and . PWC, volume 3260 of Lecture Notes in Computer Science, page 379-388. Springer, (2004)Fast alternating projected gradient descent algorithms for recovering spectrally sparse signals., , , , and . ICASSP, page 4638-4642. IEEE, (2016)Compressed sensing with corrupted participants., , and . ICASSP, page 4653-4657. IEEE, (2013)Efficient optimal joint channel estimation and data detection for massive MIMO systems., and . ISIT, page 875-879. IEEE, (2016)Improved sparse recovery thresholds with two-step reweighted ℓ1 minimization., , , and . ISIT, page 1603-1607. IEEE, (2010)Weighted ℓ1 minimization for sparse recovery with prior information., , , and . ISIT, page 483-487. IEEE, (2009)Maximum-likelihood joint channel estimation and data detection for space time block coded MIMO systems., and . ACSSC, page 962-965. IEEE, (2014)