Joint Channel Estimation and Precoding for Faster-Than-Nyquist Signaling | IEEE Journals & Magazine | IEEE Xplore

Joint Channel Estimation and Precoding for Faster-Than-Nyquist Signaling


Abstract:

The performance of existing frequency-domain channel estimation and equalization algorithms for faster-than-Nyquist (FTN) signaling is seriously hampered with the noise e...Show More

Abstract:

The performance of existing frequency-domain channel estimation and equalization algorithms for faster-than-Nyquist (FTN) signaling is seriously hampered with the noise enhancement phenomenon that results from their inverse or pseudo-inverse operations. Through simulations, we show that the linear precoding can effectively mitigate the above-mentioned noise enhancement phenomenon. At first, a low complexity precoding-based channel estimation (PCE) algorithm is proposed for FTN signaling over frequency-selective fading channels. In contrast with most existing frequency-domain channel estimation algorithms, the proposed PCE algorithm has much better mean square error performance, and the performance improvement enlarges with the increase of signal to noise ratio. Furthermore, a joint channel estimation and precoding (JCEP) algorithm is proposed to perform data detection for FTN signaling over frequency-selective fading channels. On the one hand, compared with the existing frequency-domain channel estimation and equalization algorithms, the JCEP algorithm greatly reduces the complexity of signal processing at receivers since it performs the linear precoding processing at transmitters. On the other hand, even with estimated channel state information (CSI), the proposed JCEP algorithm can approach the bit error rate (BER) performance of the Nyquist signaling for all the modulation types adopted in digital video broadcasting-satellite-second generation extension (DVB-S2X). More precisely, the BER performance degradation with perfect and estimated CSI is 0.06 dB and 0.07 dB respectively when the time acceleration parameter equals to 0.7 and the rolling factor is 0.45.
Published in: IEEE Transactions on Vehicular Technology ( Volume: 69, Issue: 11, November 2020)
Page(s): 13139 - 13147
Date of Publication: 02 September 2020

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