Optimal Resource Allocation Design for Wideband Integrated Sensing and Communication Systems

This paper investigates resource allocation design for wideband integrated sensing and communication (ISAC) systems. To tackle the severe propagation attenuation issue in designing high-frequency ISAC systems, we adopt the hybrid beamformer at the transmitter to achieve substantial beamforming gains...

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Vydáno v:IEEE transactions on wireless communications Ročník 24; číslo 3; s. 2140 - 2156
Hlavní autoři: Wang, Wenhao, Qiao, Deli, Yang, Lei, Zhan, Yueying, Wing Kwan Ng, Derrick
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.03.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Array signal processing
beam split
Beamforming
Broadband
Communication
Communications systems
Complexity
Constraints
Cramer-Rao bounds
Design optimization
generalized Bender’s decomposition
Integrated sensing and communication
Linear programming
Mixed integer
Nonlinear programming
Optimization
Performance degradation
Radio frequency
Radio spectrum management
Resource allocation
Resource management
Simulation
Subcarriers
Symbols
Terahertz communications
Wideband
Wireless communication
ISSN:1536-1276, 1558-2248
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Shrnutí:This paper investigates resource allocation design for wideband integrated sensing and communication (ISAC) systems. To tackle the severe propagation attenuation issue in designing high-frequency ISAC systems, we adopt the hybrid beamformer at the transmitter to achieve substantial beamforming gains by generating highly directional beams. However, the well-known beam-split effect introduces multiple spatial directions at each subcarrier, due to the employment of wider bandwidth and a larger number of antennas, which may lead to system performance degradation. Fortunately, the notion of a true-time-delayer (TTD) has emerged as a crucial solution for compensating for the beam split by generating frequency-dependent phase shifts. To fully unleash its potential, we aim to minimize the Cramér-Rao Bound (CRB) for target estimation by jointly optimizing subcarrier allocation, digital beamforming matrices, and frequency-independent and frequency-dependent analog beamforming matrices at base station (BS). We formulate the optimization design as a non-convex mixed-integer non-linear programming (MINLP) problem, subject to the transmit power budget constraint of the BS, the rate quality-of-service (QoS) constraints for users, and the discrete nature of the analog beamformer. To achieve a globally optimal solution for the complex design problem, an iterative resource allocation algorithm is proposed by exploiting the generalized Bender's decomposition (GBD) method. Moreover, we develop a computationally-efficient suboptimal algorithm to strike an effective balance between system performance and complexity. Our simulation results demonstrate the crucial importance of simultaneously optimizing all available degrees-of-freedom (DoFs) in wideband ISAC systems jointly and optimally. Furthermore, our proposed schemes are able to significantly improve the sensing accuracy over the traditional alternating optimization (AO) scheme adopted in existing solutions. Besides, our results unveil that deploying TTD units with limited bit-resolution time delays can achieve substantial gains in both communication and sensing performances.
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ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2024.3516777