Multi-Dimensional Resource Optimization for Incremental AF-OFDM Systems With RF Energy Harvesting Relay

• Published in: IEEE transactions on vehicular technology Vol. 68; no. 1; pp. 613 - 627
• Main Authors: Zhang, Yang, Bai, Kaiyang, Pang, Lihua, Han, Ruiyu, Li, Yi, Liang, Shuang, Luan, Yingzi, Ren, Guangliang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: achievable rate; amplify-and-forward; Audio frequencies; Complexity; Computer simulation; Energy harvesting; incremental relaying; multi-carrier system; Nonlinear programming; OFDM; Optimization; Orthogonal Frequency Division Multiplexing; Power management; Power transfer; Protocols; Relaying; Relays; resource allocation; Resource management; Subcarriers; SWIPT; Throughput; Wireless communication; Wireless communications; Wireless networks
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2018.2882910

Integrating radio frequency energy harvesting into wireless communications to support simultaneous wireless information and power transfer (SWIPT) is a promising technique to extend lifetime of energy-limited wireless cooperative networks. In this paper, multiuser resource optimization for incremental amplify-and-forward orthogonal frequency division multiplexing relaying systems with SWIPT is investigated. To maximize the overall achievable rate, multi-dimensional degrees of freedom (e.g., power allocation, subcarrier assignment, incremental policy, and power splitting ratio) are jointly optimized, subject to the transmission power as well as the quality of service constraints. The optimization problem is formulated as a mixed-integer nonlinear programming and the corresponding solution entails prohibitively high computational complexity. This motivates us to find a suboptimal solution with the aim of realizing a better tradeoff between performance and complexity. Specifically, dual decomposition and subgradient algorithm are applied to achieve this goal and the essence of our proposal is that the variables to be optimized are sequentially and iteratively derived. Finally, complexity analysis and simulation results are shown to verify the effectiveness of the proposed scheme.