论文标题
带有训练开销的MIMO联合通信和无线电传感系统的波形优化
Waveform Optimization for MIMO Joint Communication and Radio Sensing Systems with Training Overhead
论文作者
论文摘要
在本文中,我们研究了最佳波形设计,以最大程度地提高共同信息(MI),以进行联合通信和(无线电)传感(JCAS,又称雷达通信)多输入多输出(MIMO)下行链路系统。我们考虑一种典型的基于数据包的信号结构,其中包括培训和数据符号。我们首先通过考虑训练开销和通道估计误差(CEE)来得出相关通道下传感和通信的条件MI。然后,我们为通道估计误差提供了一个下限,并优化了训练和数据符号之间的功率分配,以最大程度地减少CEE。基于最佳功率分配,我们为三种情况提供了最佳波形设计方法,包括最大程度地提高通信和仅传感的MI,并最大程度地提高加权总和MI以进行通信和传感。我们还提出了广泛的仿真结果,可提供有关波形设计的见解,并验证拟议设计的有效性。
In this paper, we study optimal waveform design to maximize mutual information (MI) for a joint communication and (radio) sensing (JCAS, a.k.a., radar-communication) multi-input multi-output (MIMO) downlink system. We consider a typical packet-based signal structure which includes training and data symbols. We first derive the conditional MI for both sensing and communication under correlated channels by considering the training overhead and channel estimation error (CEE). Then, we derive a lower bound for the channel estimation error and optimize the power allocation between the training and data symbols to minimize the CEE. Based on the optimal power allocation, we provide optimal waveform design methods for three scenarios, including maximizing MI for communication only and for sensing only, and maximizing a weighted sum MI for both communication and sensing. We also present extensive simulation results that provide insights on waveform design and validate the effectiveness of the proposed designs.