Beamforming Design for Max-Min Fairness Performance Balancing in ISAC Systems
Fang, Tianyu; Nguyen, Nhan Thanh; Juntti, Markku (2024-10-07)
IEEE
07.10.2024
T. Fang, N. T. Nguyen and M. Juntti, "Beamforming Design for Max-Min Fairness Performance Balancing in ISAC Systems," 2024 IEEE 25th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Lucca, Italy, 2024, pp. 336-340, doi: 10.1109/SPAWC60668.2024.10694453
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© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists,or reuse of any copyrighted component of this work in other works.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202412097104
https://urn.fi/URN:NBN:fi:oulu-202412097104
Tiivistelmä
Abstract
Integrated sensing and communications (ISAC) is envisioned as a key technology for future wireless communications. In this paper, we consider a downlink monostatic ISAC system wherein the base station serves multiple communications users and sensing targets at the same time in the presence of clutter. We aim at both guaranteeing fairness among the communications users while simultaneously balancing the performances of communications and sensing functionalities. Therefore, we optimize the transmit and receive beamformers to maximize the weighted minimum signal-to-interference and clutter-plus-noise ratios. The design problem is highly challenging due to the non-smooth and non-convex objective function and strongly coupled variables. We propose two efficient methods to solve the problem. First, we rely on fractional programming and transform the original problem into convex sub-problems, which can be solved with standard convex optimization tools. To further reduce the complexity and dependence on numerical tools, we develop a novel approach to address the inherent non-smoothness of the formulated problem. Finally, the efficiencies of the proposed designs are demonstrated by numerical results.
Integrated sensing and communications (ISAC) is envisioned as a key technology for future wireless communications. In this paper, we consider a downlink monostatic ISAC system wherein the base station serves multiple communications users and sensing targets at the same time in the presence of clutter. We aim at both guaranteeing fairness among the communications users while simultaneously balancing the performances of communications and sensing functionalities. Therefore, we optimize the transmit and receive beamformers to maximize the weighted minimum signal-to-interference and clutter-plus-noise ratios. The design problem is highly challenging due to the non-smooth and non-convex objective function and strongly coupled variables. We propose two efficient methods to solve the problem. First, we rely on fractional programming and transform the original problem into convex sub-problems, which can be solved with standard convex optimization tools. To further reduce the complexity and dependence on numerical tools, we develop a novel approach to address the inherent non-smoothness of the formulated problem. Finally, the efficiencies of the proposed designs are demonstrated by numerical results.
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