期刊
IEEE TRANSACTIONS ON SIGNAL PROCESSING
卷 71, 期 -, 页码 1952-1967出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSP.2023.3279900
关键词
Radar; MIMO communication; Radar antennas; US Department of Defense; MIMO radar; Downlink; Communication systems; Dual-function radar-communication (DFRC) system; Multiple-input multiple-output (MIMO); Cramer-Rao lower bound (CRLB); Sum-rate (SR); Fractional programming (FP)
In this paper, the authors utilize CRLB and SR metrics to evaluate waveform design and propose an FP framework based on MIMO DFRC systems to solve nonconvex and nonlinear fractional programming problems. The proposed method transforms and simplifies complex functions and separates the summation-log-fraction function to optimize the design solution.
The Cramer-Rao lower bound (CRLB) and sum-rate (SR) are widely-used metrics in the radar parameter estimation performance evaluation and communication quality-of-service (QoS) assessment, respectively. In this paper, we adopt these two metrics in waveform design for bistatic multiple-input multiple-output dual-function radar-communication (MIMO DFRC) systems, which is different from existing methods where only suboptimal optimization criteria are employed. However, both of the design formulations result in nonconvex and nonlinear fractional programming (FP) problems with complex fractional constraint and objective function. Especially, the CRLB for direction-of-departure (DOD) and direction-of-arrival (DOA) in bistatic DFRC MIMO system is a fraction with quadratic polynomial in the numerator and quartic polynomial in the denominator; whereas the SR expression corresponds to a summation-log-fraction function. By fractional function transformation and convexification, complex function design and simplification, and summation-log-fraction function separation, this article derives an FP framework to solve these complicated problems. Numerical results demonstrate the excellent performance of our design solutions.
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