Optimal energy beamforming under per‐antenna power constraint

Rezaei, Zahra; Yazdian, Ehsan; Tabataba, Foroogh S.; Gazor, Saeed

doi:10.1002/ett.3846

Cited by 1 publication

(2 citation statements)

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“…Moreover, we also found that the proposed cooperation is most effective when selecting the WD closest to the cluster center as the CH, both the intra-cluster and cluster-to-HAP communication links are strong, and the number of cooperating WDs is moderate. 15 20 25 30…”

Section: Discussionmentioning

confidence: 99%

“…Instead, when the HAP is equipped with multiple antennas, it can apply energy beamforming (EB) technique [12] to focus the transferred energy to desired directions to enhance the energy transfer efficiency to specific devices, and thus the data rates of energy-harvesting devices. The optimal EB design has been studied in several practical setups, e.g., training sequence design [13], hardware feedback complexity constraints [14], and under per-antenna transmit power constraint [15]. Besides, the multiple antennas can also improve the communication performance by leveraging spatial diversity or multiplexing gains in the uplink.…”

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confidence: 99%

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Multi-Antenna Enabled Cluster-Based Cooperation in Wireless Powered Communication Networks

Yuan

Zhang

et al. 2017

IEEE Access

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In this paper, we consider a wireless powered communication network (WPCN) consisting of a multi-antenna hybrid access point (HAP) that transfers wireless energy to and receives sensing data from a cluster of low-power wireless devices (WDs). To enhance the throughput performance of some faraway WDs, we allow one of the WDs to act as the cluster head (CH) that helps forward the messages of the other cluster members (CMs). However, the performance of the proposed cluster-based cooperation is fundamentally limited by the high energy consumption of the CH, who needs to transmit all the WDs' messages including its own. To tackle this issue, we exploit the capability of multi-antenna energy beamforming (EB) at the HAP, which can focus more transferred power to the CH to balance its energy consumption in assisting the other WDs. Specifically, we first derive the throughput performance of each individual WD under the proposed scheme. Then, we jointly optimize the EB design, the transmit time allocation among the HAP and the WDs, and the transmit power allocation of the CH to maximize the minimum data rate achievable among all the WDs (the max-min throughput) for improved throughput fairness among the WDs. An efficient optimal algorithm is proposed to solve the joint optimization problem. Moreover, we simulate under practical network setups and show that the proposed multi-antenna enabled cluster-based cooperation can effectively improve the throughput fairness of WPCN.Index Terms-Wireless sensor networks, wireless powered communication, resource allocation, user fairness. I. INTRODUCTIONT HE performance of modern communication networks is largely constrained by the limited battery life of wireless devices (WDs). Once the energy is depleted, a WD needs manual replacement/recharging of its battery, which can result in frequent interruption to normal device operation and severe communication performance degradation. Alternatively, the recent development of wireless energy transfer (WET) technology enables a novel networking paradigm named wireless powered communications network (WPCN) [1]- [3], where the information transmissions of WDs can be continuously and remotely powered by the microwave energy transmitted by dedicated energy nodes. The use of WET can effectively reduce the battery replacement/recharging cost and also improve the communication quality with reduced energy outages. With its potential to tackle the critical energy constraints, we can expect that WET will be an important building block in future wireless communication networks.There are extensive studies on implementing WPCN in lowpower applications, such as wireless sensor network (WSN)The authors are with the College

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%