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

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...

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Bibliographic Details
Published in:China communications Vol. 21; no. 2; pp. 129 - 142
Main Authors: Zhu, Jia, Mu, Junsheng, Cui, Yuanhao, Jing, Xiaojun
Format: Journal Article
Language:English
Published: China Institute of Communications 01.02.2024
School of Information and Communication Engineering,Beijing University of Posts and Telecommunications,Beijing 100876,China
Subjects:
coexistence
Communication systems
communications
multicarrier radar
mutual information
Optimization
Radar
Radar scattering
Resource management
Scattering
Sensors
spectrum sharing
multicar-rier radar
communications
mutual information
coexistence
spectrum sharing
ISSN:1673-5447
Online Access:Get full text
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Summary: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.
ISSN:1673-5447
DOI:10.23919/JCC.fa.2023-0138.202402