In conventional dual-function radar-communication (DFRC) systems, the radar and communication channels are routinely estimated at fixed time intervals based on their worst-case operation scenarios. Such situation-agnostic repeated estimations cause significant training overhead and dramatically degrade the system performance, especially for applications with dynamic sensing/communication demands and limited radio resources. In this paper, we leverage the channel aging characteristics to reduce training overhead and to design a situation-dependent channel re-estimation interval optimization-based resource allocation for performance improvement in a multi-target tracking DFRC system. Specifically, we exploit the channel temporal correlation to predict radar and communication channels for reducing the need of training preamble retransmission.
Then, we characterize the channel aging effects on the Cramer-Rao lower bounds (CRLBs) for radar tracking performance analysis and achievable rates with maximum ratio transmission (MRT) and zero-forcing (ZF) transmit beamforming for communication performance analysis. In particular, the aged CRLBs and achievable rates are derived as closed-form expressions with respect to the channel aging time, bandwidth, and power. Based on the analyzed results, we optimize these factors to maximize the average total aged achievable rate subject to individual target tracking precision demand, communication rate requirement, and other practical constraints. Since the formulated problem belongs to a non-convex problem, we develop an efficient one-dimensional search based optimization algorithm to obtain its suboptimal solutions. Finally, simulation results are presented to validate the correctness of the derived theoretical results and the effectiveness of the proposed allocation scheme.
Performance Analysis and Power Allocation of Joint Communication and Sensing Towards Future Communication Networks
针对大规模设备接入导致的雷达和通信频率重叠问题，提出了一种新的联合通信与感知（Joint Communication and Sensing，JCS）系统，利用微基站（MicroBase Station，MiBS）同时实现目标感知和协作通信。具体地，作为感测设备的MiBS还可以用作全双工（FD）解码转发（DF）中继以辅助端到端通信。为了进一步提高频谱利用率，采用非正交多址接入（NOMA），使得宏基站（MaBS）与物联网（IoT）设备之间的通信。为了便于性能评估，系统的精确和渐近中断概率，遍历率，感知概率的特点。随后，设计了两个最优功率分配（OPA）问题：最大化感知信号的接收信干噪比和最大化通信总速率，并利用拉格朗日方法和函数单调性进行求解。仿真结果表明：1）JCS NOMA系统在与非协作NOMA系统功耗相同的前提下，能够同时实现通信增强和感知功能; 2）所提出的OPA方案优于随机功率分配方案。
Resource Allocation for Secure Dual-UAV-Assisted ISAC System
Chongqing University of Posts and Telecommunications（重庆邮电大学）；King Abdullah University of Science and Technology (KAUST)（阿卜杜拉国王科技大学）；State Key Laboratory of Power Transmission Equipment Technology, School of Electrical Engineering, Chongqing University（重庆大学电气工程学院）；Hunan University（湖南大学）；School of Information Engineering, Changsha Medical University（长沙医学院信息工程学院）；Beijing Institute of Technology（北京理工大学）
