We propose a novel integrated sensing and communication (ISAC) system, where the base station (BS) passively senses the channel parameters using the information carrying signals from a user. To simultaneously guarantee decoding and sensing performance, the user adopts sparse regression codes (SPARCs) with cyclic redundancy check (CRC) to transmit its information bits. The BS generates an initial coarse channel estimation of the parameters after receiving the pilot signal. Then, a novel iterative decoding and parameter sensing algorithm is proposed, where the correctly decoded codewords indicated by the CRC bits are utilized to improve the sensing and channel estimation performance at the BS. In turn, the improved estimate of the channel parameters lead to a better decoding performance. Simulation results show the effectiveness of the proposed iterative decoding and sensing algorithm, where both the sensing and the communication performance are significantly improved with a few iterations. Extensive ablation studies concerning different channel estimation methods and number of CRC bits are carried out for a comprehensive evaluation of the proposed scheme.

翻译：本文提出了一种新型的集成感知与通信（ISAC）系统，其中基站（BS）利用来自用户的信息承载信号被动感知信道参数。为了同时保证解码与感知性能，用户采用带循环冗余校验（CRC）的稀疏回归码（SPARCs）传输其信息比特。基站在接收导频信号后生成参数的初始粗粒度信道估计。随后，本文提出了一种新颖的迭代解码与参数感知算法，该算法利用CRC比特指示的正确解码码字来提升基站的感知与信道估计性能。反过来，改进的信道参数估计又带来了更好的解码性能。仿真结果表明了所提迭代解码与感知算法的有效性，经过数次迭代后，感知与通信性能均得到显著提升。本文还针对不同信道估计方法和CRC比特数量进行了广泛的消融研究，以全面评估所提方案。