Mutual information maximization via joint power allocation in integrated sensing and communications system

Jia Zhu, Junsheng Mu, Yuanhao Cui, Xia Jing
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Abstract

In this paper, we focus on the power allocation of Integrated Sensing and Communication (ISAC) with orthogonal frequency division multiplexing (OFDM) waveform. In order to improve the spectrum utilization efficiency in ISAC, we propose a design scheme based on spectrum sharing, that is, to maximize the mutual information (MI) of radar sensing while ensuring certain communication rate and transmission power constraints. In the proposed scheme, three cases are considered for the scattering off the target due to the communication signals, as negligible signal, beneficial signal, and interference signal to radar sensing, respectively, thus requiring three power allocation schemes. However, the corresponding power allocation schemes are nonconvex and their closed-form solutions are unavailable as a consequence. Motivated by this, alternating optimization (AO), sequence convex programming (SCP) and Lagrange multiplier are individually combined for three suboptimal solutions corresponding with three power allocation schemes. By combining the three algorithms, we transform the non-convex problem which is difficult to deal with into a convex problem which is easy to solve and obtain the suboptimal solution of the corresponding optimization problem. Numerical results show that, compared with the allocation results of the existing algorithms, the proposed joint design algorithm significantly improves the radar performance.
在综合传感与通信系统中通过联合功率分配实现互信息最大化
本文重点研究了采用正交频分复用(OFDM)波形的综合传感与通信(ISAC)的功率分配问题。为了提高 ISAC 的频谱利用效率,我们提出了一种基于频谱共享的设计方案,即在保证一定通信速率和传输功率约束的前提下,最大化雷达传感的互信息(MI)。在提出的方案中,考虑了通信信号对目标的散射的三种情况,分别为可忽略信号、有利信号和对雷达传感的干扰信号,因此需要三种功率分配方案。然而,相应的功率分配方案是非凸的,因此无法获得其闭式解。受此启发,交替优化 (AO)、序列凸编程 (SCP) 和拉格朗日乘法器被单独结合起来,以获得与三种功率分配方案相对应的三种次优解。通过三种算法的结合,我们将难以处理的非凸问题转化为易于求解的凸问题,并得到相应优化问题的次优解。数值结果表明,与现有算法的分配结果相比,所提出的联合设计算法显著提高了雷达性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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