期刊
IEEE WIRELESS COMMUNICATIONS LETTERS
卷 9, 期 8, 页码 1191-1195出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LWC.2020.2985010
关键词
Backscatter; Resource management; Power demand; Optimization; Wireless communication; Energy harvesting; Throughput; Backscatter communications; sum rate maximization; multi-carrier transmission; energy harvesting
资金
- National Natural Science Foundation of China [61601071]
- Scientific and Technological Research Program of Chongqing Municipal Education Commission [KJQN201800606]
- Shandong Provincial Key Laboratory of Wireless Communication Technologies [SDKLWCT-2019-04]
- National Natural Science Foundation of Chongqing [cstc2019jcyj-xfkxX0002]
- Chongqing Municipal Key Laboratory of Institutions of Higher Education [cqupt-mct-201802]
- Jiangsu Specially Appointed Professor [RK002STP16001]
- Innovation and Entrepreneurship of Jiangsu High-level Talent [CZ0010617002]
- Summit of the Six Top Talents Program of Jiangsu [XYDXX-010]
Backscatter communication (BackCom) is considered as one of important techniques to extend the lifetime of Internet of Things (IoT). How to achieve resource allocation (RA) is a key technique to optimize system performance. Existing RA schemes only focus on time scheduling under the fixed transmit power, however, the globally optimal solutions and power allocation are not considered. In this letter, we solve the total rate maximization problem for a multi-carrier wireless powered BackCom network, where a dedicated radio frequency power source (PS) transmits multi-carrier signals to a hybrid information transceiver device (ITD) during energy harvesting (EH) phase, and then the ITD deliveries the signals to the associated receiver during the information transmission (IT) phase. Our goal is to maximize the sum rate of the backscatter data rate and the transmission rate during the IT phase by jointly optimizing power allocation, time allocation, reflection coefficient, energy allocation coefficient, where the maximum transmit power constraint at the PS and the minimum circuit power consumption constraint are considered. Then an iterative RA algorithm is developed to find the optimal solutions. Simulation results confirm the superiority of the proposed scheme in terms of transmission rates.
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