5764 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 18, NO. 12, DECEMBER 2019 Buffer-Aided Adaptive Wireless Powered Communication Network With Finite Energy Storage and Data Buffer Xiaolong Lan, Qingchun Chen , Senior Member, IEEE , Lin Cai, Senior Member, IEEE, and Lisheng Fan Abstract—In this paper, the access point (AP) in a wireless network is assumed to provide energy supply via wireless energy transfer to multiple terminals in the downlink, and all the terminals use the harvested energy to transmit their collected data to the AP in the uplink in a time division multiple access (TDMA) manner. Each terminal is provisioned with a finite energy storage and a finite data buffer to store the harvested energy and to buffer the arrived data traffic, respectively. Due to the limited data buffer and energy storage size, there might be data loss due to either data buffer overflow or energy storage depletion. Firstly, we aim at maximizing the long-term weighted sum-rate through energy beamforming vector design, power allocations, rate control, time allocations, and transmission mode selection subject to average transmit power, peak transmit power, data loss ratio requirements, practical data buffer as well as energy storage constraints. Secondly, the weighted max-min scheduling scheme is proposed to guarantee the fair access requirement by multiple terminals. Numerical analyses are presented to show that, the proposed adaptive design can substantially improve the average achievable rate region, while the proposed weighted max-min fair scheduling can effectively ensure the fair access requirements. Index Terms— Wireless energy transfer (WET), energy beam- forming, achievable rate region, finite energy storage and data buffer. I. I NTRODUCTION R ADIO frequency (RF) energy harvesting technology pro- vides a promising routine to realize energy sustainabil- Manuscript received December 11, 2018; revised April 27, 2019 and July 12, 2019; accepted August 26, 2019. Date of publication September 10, 2019; date of current version December 10, 2019. The work of X. Lan and Q. Chen was supported in part by the National Natural Science Foundation of China under Grant 61771406 and in part by the Chinese Scholarship Council (CSC). The work of L. Cai was supported in part by the Natural Sciences and Engineering Research Council of Canada (NSERC). The work of L. Fan was supported by the National Natural Science Foundation of China under Grant 61871139. The associate editor coordinating the review of this article and approving it for publication was W. Chen. (Corresponding author: Qingchun Chen.) X. Lan is with the School of Information Science and Technology, Southwest Jiaotong University, Chengdu 611756, China, and also with the Department of Electronics and Communication Engineering, Guangzhou University, Guangzhou 510006, China (e-mail: xiaolonglan1112@gmail.com). Q. Chen is with the Department of Electronics and Communication Engineering, Guangzhou University, Guangzhou 510006, China (e-mail: qcchen@gzhu.edu.cn). L. Cai is with the Department of Electrical and Computer Engineer- ing, University of Victoria, Victoria, BC V8W 3P6, Canada (e-mail: cai@ece.uvic.edu). L. Fan is with the School of Computer Science and Cyber Engi- neering, Guangzhou University, Guangzhou 510006, China (e-mail: lsfan@gzhu.edu.cn). Color versions of one or more of the figures in this article are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TWC.2019.2938958 ity, which is critical for a massive deployment of energy- constrained wireless systems such as Internet of Things (IoTs) and wireless sensor networks (WSNs). Different from nat- ural resource-based energy harvesting technologies, wireless energy transfer can provide permanent and reliable energy sources for the energy-constrained wireless system without being affected by environmental changes. Although the RF energy transfer technology suffers from low energy efficiency caused by the large-scale fading of RF signals, narrow beams can be used to improve the energy transfer efficiency by employing multiple antennas at the transmitter side, which fits 5G applications of Massive MIMO and millimeter-wave very well [1]. Moreover, 5G technologies based on short- range communications such as ultra-dense networks (UDNs) and device-to-device (D2D) communications can significantly improve the wireless energy transfer efficiency by reducing communication distances. The spectrum is heavily reused in UDNs and D2D communications, resulting in strong co- channel interference, but this co-channel interference can be regarded as a potential energy source for energy-constrained devices [1], which has a huge potential for achieving green 5G networks. Recently, the simultaneous wireless information and power transfer (SWIPT) has evolved as a technical frame- work to flexibly fulfill the wireless energy transfer (WET) and wireless information transmission (WIT) requirements [2]–[7]. As an example, wireless powered communication network (WPCN) was extensively investigated to effectively support wireless energy-constrained communication [8]–[19]. Basically, the WPCN operates in two phases of downlink WET and uplink WIT. In the downlink WET phase, some energy-constrained nodes harvest energy from the RF signals of some access point (AP). In the successive uplink WIT phase, the nodes use the harvested energy to send their data to the AP. A single antenna WPCN was studied in [8], while the multiple-antenna empowered WPCN was addressed in [10]. In [9] and [11], the full duplex technique was applied in WPCN. User cooperation in the WPCN was studied in [12]–[14], where the user closer to the AP acts as a relay to help the user far away from the AP to forward data in the uplink WIT phase. At the same time, exploiting buffers in the physical layer and link layer has attracted much attention as an effective way to provide new degree of freedom to better schedule the transmission for an improved performance [21]–[23], [25]–[29]. In buffer-aided communication networks, data traffic from higher layer applications can be firstly stored in a data buffer and adaptively transmitted when 1536-1276 © 2019 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. Authorized licensed use limited to: UNIVERSITY OF VICTORIA. Downloaded on December 12,2020 at 06:30:49 UTC from IEEE Xplore. Restrictions apply.