Joint Iterative Channel Estimation and Frequency-Domain Turbo Equalization for Single-Carrier Spatial Modulation

Abstract

Single carrier frequency-domain turbo equalization (SC-FDTE) has gained widespread adoption in the emerging broadband spatial modulation (S-M) systems operating in frequency selective channels, where the channel model considered is a quasi-static Rayleigh fading channel. In this paper, a new class of robust FDTE designs based on the minimum meansquare error (MMSE) criterion is conceived for broadband single-carrier SM (SC-SM) systems relying on realistic imperfect channel knowledge. First, a robust time-domain soft-decision feedback (TDSDF) aided FDTE is proposed to cope with channel estimation errors at the receiver. Furthermore, its robust frequencydomain soft-decision feedback (FDSDF) aided counterpart is derived to offer a low-complexity approximate solution. Finally, by exploiting the carefully selected reliable soft-decision output of the channel decoder as pilots, we refine the resultant decision-directed channel estimation. As a benefit, the performance of the two robust FDTEs can be further improved. Both our simulation results and our extrinsic information transfer (EXIT) chart analysis demonstrate that the proposed robust FDTEs achieve significant performance improvements over the conventional FDTEs. Index Terms-Single-carrier (SC), spatial modulation (SM), frequency-domain turbo equalizer (FDTE), imperfect channel knowledge.

Iterative Equalization and Decoding over an Additive White Gaussian Noise Channel with ISI Using Low-Density Parity-Check Codes

“…Firstly, a summary of existing SISO equalization algorithms derived from classical equalization methods according to the maximum a posteriori (MAP) or minimum meansquare error (MMSE) criterion is presented. In this respect, we referred to [4,5,[16][17][18][19][20][21][22][23][24][25][26][27].…”

“…Using soft decisions provided by the decoder at the entry of an equalizer was demonstrated to considerably reduce the BER at the reception [16,17]. From this point of view, different SISO equalization techniques were built in the literature to improve the information from the decoding levels within the iterative decoding approach.…”

The research on channel estimation and signal‐noise ratio estimation based on minimum error entropy kalman filter for single carrier frequency domain equalization system

“…There are many excellent research works [3][4][5][6][7] and reviews [8][9][10] in the literature dealing with the channel estimation. In recent years, the research on channel estimation mainly focuses on the following aspects: channel estimation based on deep learning, 11,12 channel estimation based on iteration, [13][14][15] and channel estimation based on compressive sensing (CS). 16 For example, a novel approach to learn a low-complexity channel estimator was presented in David Neumann, 12 which is motivated by the structure of the MMSE estimator; to obtain accurate estimation of the channel parameters for a fluctuant multipath channel, a novel channel estimation algorithm based on iteration is proposed in Li et al 14 ; and the channel estimation of SC-FDE system was modeled as CS-based reconstruction of sparse signal in Si et al, 16 which match pursuit algorithms based on greedy search were adopted to reconstruct channel information.…”