Wireless channel sensing is one of the key enablers for integrated sensing and communication (ISAC) which helps communication networks understand the surrounding environment. In this work, we consider MIMO-OFDM systems and aim to design optimal and robust waveforms for accurate channel parameter estimation given allocated OFDM resources. The Fisher information matrix (FIM) is derived first, and the waveform design problem is formulated by maximizing the log determinant of the FIM. We then consider the uncertainty in the parameters and state the stochastic optimization problem for a robust design. We propose the Riemannian Exact Penalty Method via Smoothing (REPMS) and its stochastic version SREPMS to solve the constrained non-convex problems. In simulations, we show that the REPMS yields comparable results to the semidefinite relaxation (SDR) but with a much shorter running time. Finally, the designed robust waveforms using SREMPS are investigated, and are shown to have a good performance under channel perturbations.
翻译:无线频道遥感是综合遥感和通信(ISAC)的关键推进器之一,它有助于通信网络了解周围环境。 在这项工作中,我们考虑MIMO-OFDM系统,目的是设计最佳和稳健的波形,以便根据分配的OFDM资源进行准确的频道参数估计。首先得出了渔业信息矩阵(FIM),而波形设计问题是通过最大限度地增加FIM的日志决定因素来拟订的。然后我们考虑了参数的不确定性,并说明了稳健设计的蒸汽优化问题。我们提出通过平滑(REPMS)和其随机版SREPMS来解决受限制的非电离子问题。在模拟中,我们显示REPMS产生与半确定性放松(SPR)相似的结果,但运行时间要短得多。最后,对使用SREMPS设计的稳健的波形进行了调查,并显示在频道扰动下有良好的性能。