Paper Info
Title
Probabilistic Equalization With a Smoothing Expectation Propagation Approach.
Abstract
In this paper, we face the soft equalization of channels with inter-symbol interference for large constellation sizes, $ \\mathtt {M}$ . In this scenario, the optimal BCJR solution and most of their approximations are intractable, as the number of states they track grows fast with $ \\mathtt {M}$ . We present a probabilistic equalizer to approximate the posterior distributions of the transmitted symbols using the expectation propagation (EP) algorithm. The solution is presented as a recursive sliding window approach to ensure that the computational complexity is linear with the length of the frame. The estimations can be further improved with a forward–backward approach. This novel soft equalizer, denoted as smoothing EP (SEP), is also tested as a turbo equalizer, with a low-density parity-check (LDPC) channel decoder. The extensive results reported reveal remarkably good behavior of the SEP. In low dimensional cases, the bit error rate (BER) curves after decoding are closer than 1 dB from those of the BJCR, robust to the channel response. For large $ \\mathtt {M}$ , the SEP exhibits gains in the range of 3–5 dB compared to the linear minimum mean square error algorithm.
Year
DOI
Venue
2017
10.1109/TWC.2017.2672746
IEEE Trans. Wireless Communications
Keywords
Field
DocType
Equalizers,Wireless communication,Decoding,Smoothing methods,Estimation,Complexity theory,Covariance matrices
Equalization (audio),Low-density parity-check code,Algorithm,Minimum mean square error,Real-time computing,Adaptive equalizer,Theoretical computer science,Smoothing,Turbo equalizer,Expectation propagation,Mathematics,Bit error rate
Journal
Volume
Issue
ISSN
16
5
1536-1276
Citations 
PageRank 
References 
4
0.43
24
Authors
4
Name
Order
Citations
PageRank
Irene Santos Velázquez1161.72
Juan José Murillo-Fuentes218223.93
Eva Arias-de-Reyna3406.22
Pablo M. Olmos411418.97