M-BCJR algorithm with channel shortening based on ungerboeck observation model for faster-than-Nyquist signaling
M-BCJR algorithm with channel shortening based on ungerboeck observation model for faster-than-Nyquist signaling
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DOI：
10.23919/jcc.2021.04.007
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发表时间：
2021-04
影响因子：
4.1
通讯作者：
Hui Che;Yong Bai
中科院分区：
文献类型：
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作者：
Hui Che;Yong Bai
基于Ungerboeck观测模型的M-BCJR算法是最近的一项研究，旨在降低快于奈奎斯特（FTN）信令的计算复杂度[1]。在本文中，我们提出了一种方法，可以进一步降低复杂度与近似相同或更好的误码率（BER）性能相比，[1]。所提出的方法的信息速率（IR）损失小于1%相比，真正可实现的IR（AIR）。所提出的改进主要是通过在M-BCJR均衡器之前引入信道缩短（CS）。在我们的建议中，Ungerboeck M-BCJR算法和CS可以一起工作，以克服严重的符号间干扰（ISI）引入FTN信令。基于IR最大化准则，优化了带CS的M-BCJR算法的码间干扰长度。对于τ = 0.5和τ = 0.35两种情况，与Ungerboeck M-BCJR无CS基准[1]相比，有CS的Ungerboeck M-BCJR的计算复杂度降低了75%。此外，在τ = 0.35的情况下，在低信噪比区域，具有CS的Ungerboeck M-BCJR的BER性能优于文献[1]中的传统M-BCJR。
The M-BCJR algorithm based on the Ungerboeck observation model is a recent study to reduce the computational complexity for faster-than-Nyquist (FTN) signaling [1]. In this paper, we propose a method that can further reduce the complexity with the approximately same or better bit error rate (BER) performance compared to [1]. The information rate (IR) loss for the proposed method is less than 1% compared to the true achievable IR (AIR). The proposed improvement is mainly by introducing channel shortening (CS) before the M-BCJR equalizer. In our proposal, the Ungerboeck M-BCJR algorithm and CS can work together to defeat severe inter-symbol interference (ISI) introduced by FTN signaling. The ISI length for the M-BCJR algorithm with CS is optimized based on the criterion of the IR maximization. For the two cases τ = 0.5 and τ = 0.35, compared to Ungerboeck M-BCJR without CS benchmark [1], the computational complexities of Ungerboeck M-BCJR with CS are reduced by 75%. Moreover, for the case τ = 0.35, the BER performance of Ungerboeck M-BCJR with CS outperforms that of the conventional M-BCJR in [1] at the low signal to noise ratio region.