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A novel compressed data transmission scheme in slowly time-varying channel

机译：慢时变信道中一种新颖的压缩数据传输方案

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摘要

Compressed sensing (CS) has attracted a lot of research interests in data transmission, since it can significantly reduce the redundancy of the data while still holding the information completely. Generally, in order to deal with the experienced time-varying channel, the data transmission scheme based on CS needs to estimate the channel frequently. In this paper, we propose a novel CS-based data transmission scheme for slowly time-varying channel, which estimates channel and reconstructs data jointly. Specifically, the scheme consists of a data reconstruction part and a channel state information (CSI) update part. The former reconstructs the data with inaccurate CSI by modeling the problem as a perturbed CS reconstruction problem. The latter updates the CSI with the reconstruction result as a semi-blind channel estimation problem. Comparing with the classical scheme, the proposed one enjoys a reduced cost by avoiding inserting pilots into data frame frequently. Simulation results demonstrate that our proposed scheme works robustly in slowly time-varying channel and the performance is comparable to that of the scheme reconstructing the data with perfect CSI.
机译：压缩感知（CS）可以极大地减少数据的冗余性，同时仍然完全保留信息，因此在数据传输方面吸引了许多研究兴趣。通常，为了处理经验丰富的时变信道，基于CS的数据传输方案需要频繁地估计信道。在本文中，我们提出了一种新颖的基于CS的慢时变信道数据传输方案，该方案可以估计信道并共同重建数据。具体地，该方案包括数据重建部分和信道状态信息（CSI）更新部分。前者通过将问题建模为受干扰的CS重建问题来重建具有不正确CSI的数据。后者利用重建结果来更新CSI，作为半盲信道估计问题。与经典方案相比，所提出的方案通过避免将导频频繁插入数据帧而降低了成本。仿真结果表明，本文提出的方案在时变缓慢的信道中具有良好的鲁棒性，其性能与具有理想CSI的数据重构方案的性能相当。

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