Multi-Antenna Wireless Powered Communication With Energy Beamforming
By Liang Liu, Rui Zhang, Kee Chaing Chua. IEEE Transactions on Communications, 2013
456 citations recorded by the source corpus.
The newly emerging wireless powered communication networks (WPCNs) have recently drawn significant attention, where radio signals are used to power wireless terminals for information transmission. In this paper, we study a WPCN where one multi-antenna access point (AP) coordinates energy transfer and information transfer to/from a set of single-antenna users. A harvest-then-transmit protocol is assumed where the AP first broadcasts wireless power to all users via energy beamforming in the downlink (DL), and then, the users send their independent information to the AP simultaneously in the uplink (UL) using their harvested energy. To optimize the users' throughput and yet guarantee their rate fairness, we maximize the minimum throughput among all users by a joint design of the DL-UL time allocation, the DL energy beamforming, and the UL transmit power allocation, as well as receive beamforming. We solve this nonconvex problem optimally by two steps. First, we fix the DL-UL time allocation and obtain the optimal DL energy beamforming, UL power allocation, and receive beamforming to maximize the minimum signal-to-interference-plus-noise ratio of all users. This problem is shown to be still nonconvex; however, we convert it equivalently to a spectral radius minimization problem, which can be solved efficiently by applying the alternating optimization based on the nonnegative matrix theory. Then, the optimal time allocation is found by a one-dimensional search to maximize the minimum rate of all users. Furthermore, two suboptimal designs of lower complexity are also proposed, and their throughput performance is compared against that of the optimal solution.
Subfields: Aerospace Engineering, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/61464af8a0a72548d74278f8f870ef9c5cac63a6
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Citations in the corpus
- Wireless powered communication: opportunities and challenges (2014, methodology): “In this case, all the users transmit simultaneously to the HAP during the second phase and the HAP jointly decodes the user messages using multi-user detection (MUD) techniques.”
- Wireless Networks With RF Energy Harvesting: A Contemporary Survey (2014, methodology): “Moreover, various modern beamforming techniques are employed to improve power transfer efficiency [ 17]–[19] for mobile applications.”
- Throughput Optimization for Massive MIMO Systems Powered by Wireless Energy Transfer (2014, methodology): “Also assuming perfec t CSI, the multiuser WPCN was studied in [20], [21].”
- Communications and Signals Design for Wireless Power Transmission (2016, background): “[199]–[202], the energy for wireless communications at the devices is obtained via WPT upon usage.”
- Computation Rate Maximization for Wireless Powered Mobile-Edge Computing With Binary Computation Offloading (2017, background): “, [9], [10], we do not assume a maximum transmit power constraint for the WDs because of the small amount energy harvested from WPT in practice.”
- Wireless Charging Technologies: Fundamentals, Standards, and Network Applications (2015, background): “The objective of [280] is to maximize the minimum throughput of all devices.”
- Wireless powered communication networks: an overview (2015, background): “Communication and energy scheduling can also be performed i n the spatial domain when the EN and AP are equipped with multiple antennas [10].”