Joint Target and User Assignment as well as Dwell Time and Spectrum Allocation in a Distributed Radar-Communication Coexistence Network

被引:4
|
作者
Zhang, Haowei [1 ]
Liu, Weijian [2 ]
Liu, Yuan [3 ]
Zhang, Qun [4 ]
Liu, Baobao [5 ]
机构
[1] Air Force Engn Univ, Air & Missile Def Coll, Xian 710051, Peoples R China
[2] Wuhan Elect Informat Inst, Wuhan 410039, Peoples R China
[3] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
[4] Air Force Engn Univ, Inst Informat & Nav, Xian 710077, Peoples R China
[5] Xian Polytech Univ, Sch Comp Sci, Xian 710048, Peoples R China
基金
中国国家自然科学基金;
关键词
Resource management; Radar; Radar tracking; Target tracking; Optimization methods; Interference; Transmitters; Bayesian Cramer-Rao lower bound (BCRLB); convex optimization; multitarget tracking; radar-communication coexistence (RCC); resource allocation; WAVE-FORM DESIGN; POWER ALLOCATION; MULTITARGET TRACKING; RESOURCE-ALLOCATION; MANAGEMENT; SYSTEMS; LOCALIZATION; STRATEGIES; SELECTION;
D O I
10.1109/TAES.2023.3335179
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
The optimal resource sharing is key to delivering the promise of radar-communication systems, since the spectrum is shared while competed to perform radar and communication tasks. In this article, a joint target and user assignment as well as dwell time and spectrum allocation strategy is proposed for the distributed radar-communication coexistence network. The optimization model is formulated as minimizing the sum of weighted position Bayesian Cramer-Rao lower bounds under the dwell time and spectrum budgets while meeting the communication downlink requirements. The optimization model is shown to be a mixed-integer programming problem, where the binary assignment variables and continuous resource allocation variables are coupled in both the objective function and constraints. A three-stage alternate optimization method (TSAOM) is developed for problem solving. The target assignment and dwell time allocation (TADTA) problem and the user assignment and spectrum allocation (UASA) problem are separately relaxed as convex ones. Then, a cyclical minimizer framework is applied for the suboptimal solution. Simulations confirm the tracking performance improvement of the proposed strategy compared with two baseline allocation strategies. The results also show the effectiveness and efficiency of the developed TSAOM in comparison with the baseline algorithm.
引用
收藏
页码:1159 / 1175
页数:17
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