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Compressed Receiver for Multipath DSSS Signals

机译:多径DSSS信号的压缩接收器

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摘要

A compressed sensing (CS) assisted receiver for direct sequence spread spectrum (DSSS) signals transmitted over multipath frequency-selective channels is studied in this paper. We present a bit-error-rate analysis for the CS-domain maximum ratio combining receiver with perfect channel state information (CSI), and hence, the CS-induced signal-to-noise ratio (SNR) penalty is quantized. Moreover, to alleviate such penalty, we build a deterministic low pass sinusoid (LPS) matrix, which proves more suitable for the pulse-shaped DSSS signals than the commonly-used random sensing matrices. Furthermore, a joint channel estimation and symbol detection (JCESD) scheme based on structured least-squares search (SLSS) is proposed, whose performance is very close to the analytical lower bound and is far better than that of the orthogonal matching pursuit (OMP) based approach. Our numerical results show that, in contrast to a conventional receiver sampling at a Nyquist rate and relying on perfect CSI, the proposed CS-assisted SLSS-JCESD receiver may reduce the sampling rate requirement by 50% at SNR loss of about 1.2 dB.
机译:本文研究了一种压缩感测(CS)辅助接收机,用于通过多径频率选择信道传输的直接序列扩频(DSSS)信号。我们针对结合接收器和完美信道状态信息(CSI)的CS域最大比率提出了误码率分析,因此,对CS引起的信噪比(SNR)损失进行了量化。此外,为了减轻这种损失,我们建立了一个“确定性的”低通正弦曲线(LPS)矩阵,与常用的随机传感矩阵相比,该矩阵更适合于脉冲形DSSS信号。此外,提出了一种基于结构化最小二乘搜索(SLSS)的联合信道估计和符号检测(JCESD)方案,其性能非常接近解析下限,并且远优于正交匹配追踪(OMP)。基于方法。我们的数值结果表明,与以奈奎斯特速率和依靠完美CSI的常规接收器采样相反,所提出的CS辅助SLSS-JCESD接收器可以在SNR降低约1.2 dB的情况下将采样率要求降低50%。 / p>

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