Multi-antenna Wireless Energy Transfer for Backscatter Communication Systems

• Published in: IEEE journal on selected areas in communications Vol. 33; no. 12; pp. 2974 - 2987
• Main Authors: Yang, Gang, Ho, Chin Keong, Guan, Yong Liang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-12-2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Array signal processing; Backscatter; Backscatter communication systems; Backscattering; biconvex optimization; Channel estimation; Communication systems; energy beamforming; Energy use; Estimates; Green communications; Mathematical models; Maximization; proportional fairness; Radio frequency identification; Receiving antennas; resource allocation; Transmitting antennas; Wireless communication; wireless energy transfer; biconvex optimization; channel estimation; resource allocation; proportional fairness; energy beamforming; Backscatter communication systems; wireless energy transfer (WET)
• ISSN: 0733-8716; 1558-0008
• DOI: 10.1109/JSAC.2015.2481258

We study RF-enabled wireless energy transfer (WET) via energy beamforming, from a multi-antenna energy transmitter (ET) to multiple energy receivers (ERs) in a backscatter communication system such as RFID. The acquisition of the forward-channel (i.e., ET-to-ER) state information (F-CSI) at the ET (or RFID reader) is challenging, since the ERs (or RFID tags) are typically too energy-and-hardware-constrained to estimate or feedback the F-CSI. The ET leverages its observed backscatter signals to estimate the backscatter-channel (i.e., ET-to-ER-to-ET) state information (BS-CSI) directly. We first analyze the harvested energy obtained using the estimated BS-CSI. Furthermore, we optimize the resource allocation to maximize the total utility of harvested energy. For WET to single ER, we obtain the optimal channel-training energy in a semiclosed form. For WET to multiple ERs, we optimize the channel-training energy and the energy allocation weights for different energy beams. For the straightforward weighted-sum-energy (WSE) maximization, the optimal WET scheme is shown to use only one energy beam, which leads to unfairness among ERs and motivates us to consider the complicated proportional-fair-energy (PFE) maximization. For PFE maximization, we show that it is a biconvex problem, and propose a block-coordinate-descent-based algorithm to find the close-to-optimal solution. Numerical results show that with the optimized solutions, the harvested energy suffers slight reduction of less than 10%, compared to that obtained using the perfect F-CSI.