MIMO Detection with Imperfect Channel State Information Using Expectation Propagation
Expectation propagation (EP) has been recently proposed as a low-complexity algorithm for symbol detection in massive MIMO systems, where its performance is evaluated on the premise that perfect channel state information (CSI) is available at the receiver. However, in practical systems, exact CSI is not available due to a variety of reasons including channel estimation errors, quantization errors, and aging. In this paper, we study the performance of EP in the presence of imperfect CSI due to channel estimation errors and show that in this case, the EP detector experiences significant performance loss. Moreover, the EP detector shows a higher sensitivity to channel estimation errors in the high signal-to-noise ratio (SNR) regions, where the rate of its performance improvement decreases. We investigate this behavior of the EP detector and propose a modified EP detector for colored noise, which utilizes the correlation matrix of the channel estimation error. Simulation results verify that the modified algorithm is robust against imperfect CSI and that its performance is significantly improved over the EP algorithm, particularly in the higher SNR regions and that for the modified detector, the slope of the symbol error rate (SER) versus SNR plots are similar to the case of perfect CSI.
Publication Source (Journal or Book title)
IEEE Transactions on Vehicular Technology
Ghavami, K., & Naraghi-Pour, M. (2017). MIMO Detection with Imperfect Channel State Information Using Expectation Propagation. IEEE Transactions on Vehicular Technology, 66 (9), 8129-8138. https://doi.org/10.1109/TVT.2017.2683527