Joint Beamforming Design for Multi-User Wireless Information and Power Transfer

Son, Hyukmin; Clerckx, Bruno

doi:10.1109/twc.2014.2349511

Cited by 71 publications

(54 citation statements)

References 33 publications

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“…Several constraints in (17) for the optimization problem (16) can ensure that the solution is feasible. The first constraint C1 is to make sure that one subchannel is used for the cellular link and one for the D2D link.…”

Section: C1mentioning

confidence: 99%

“…Similarly, in the context of multiple antenna transmission with wireless power transfer, there has been some work, e.g. [17], [18], dedicated to the development of beamforming design. In [17], the authors propose a joint beamforming algorithm for a multiuser SWIPT system with multiple user (MU) MIMO transmission with the objective to maximize the harvested energy.…”

Section: Introductionmentioning

confidence: 99%

“…[17], [18], dedicated to the development of beamforming design. In [17], the authors propose a joint beamforming algorithm for a multiuser SWIPT system with multiple user (MU) MIMO transmission with the objective to maximize the harvested energy. The authors of [18] also study a similar model and propose the algorithms to maximize the weighted sum-power transferred to all energy receivers.…”

Section: Introductionmentioning

confidence: 99%

“…The reformed problem (36) is also subject to the constraints in (17). Therefore, the proposed algorithm should select K DORs that can minimize the energy consumption during transmission process.…”

mentioning

confidence: 99%

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Energy Efficient Resource Allocation for Wireless Power Transfer Enabled Collaborative Mobile Clouds

Chang

Gong

et al. 2016

IEEE J. Select. Areas Commun.

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Abstract-In order to fully enjoy high rate broadband multimedia services, prolonging the battery lifetime of user equipment is critical for mobile users, especially for smartphone users. In this work, the problem of distributing cellular data via a wireless power transfer enabled collaborative mobile cloud (WeCMC) in an energy efficient manner is investigated. WeCMC is formed by a group of users who have both functionalities of information decoding and energy harvesting, and are interested for cooperating in downloading content from the operators. Through Device-to-Device communications, the users inside WeCMC are able to cooperate during the downloading procedure and offload data from the base station to other WeCMC members. When considering MIMO wireless channel and wireless power transfer, an efficient algorithm is presented to optimally schedule the data offloading and radio resources in order to maximize energy efficiency as well as fairness among mobile users. Specifically, the proposed framework takes energy minimization and Quality of Service (QoS) requirement into consideration. Performance evaluations demonstrate that a significant energy saving gain can be achieved by the proposed schemes.

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Section: C1mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Energy Efficient Resource Allocation for Wireless Power Transfer Enabled Collaborative Mobile Clouds

Chang

Gong

et al. 2016

IEEE J. Select. Areas Commun.

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“…Beamforming approaches were proposed to maximize the total harvested energy at a set of ERs in [7] or the weighted sum-power transferred to a set of ERs in [9] subject to the signal to interference plus noise ratio (SINR) constraint at each information receiver (IR) and the transmit power constraint at the transmitter. However, Son and Klerckx [7] and Xu et. al.…”

Section: Introductionmentioning

confidence: 99%

Secure Information Transmission in the Presence of Energy-Harvesting Eavesdroppers in Multi-Cell Networks

Lê¹,

Nguyen²,

Vien³

et al. 2014

2015 IEEE Global Communications Conference (GLOBECOM)

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In this paper, we study simultaneous data transmission and power transfer for multiple information receivers (IRs) and energy-harvesting receivers (ERs) in cellular networks. We propose an optimization problem to maximize a linear combination of the useful signal power at each IR and total received power at each ER subject to the following three sets of constraints: i) data reliability by maintaining the required level of signal to interference plus noise ratio (SINR) for all IRs; ii) information security by keeping leakage SINR levels of all IRs at every ER below a predefined value, which helps prevent possible eavesdroppers, i.e., ERs, from detecting information aimed for the IRs; and iii) power consumption by guaranteeing that the transmit power at each base station is within its available budget. Using semidefinite relaxation (SDR) technique, we then transform the proposed problem into a convex form. We further prove that the transformed problem always yields rank-one optimal solution. Hence, our approach does not require any computationally expensive randomization procedure, as usually utilized in a typical SDR method, in obtaining optimal solutions. Simulation results indicate that the proposed approach prevails conventional scheme in terms of providing higher IRs' total throughput, higher received power level at each ER and more secure for the transmission of information.

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Energy-Efficient Resource Allocation for Wireless Powered Massive MIMO System with Imperfect CSI

Zhou¹,

Chang²,

Liao³

2020

Wireless Networks

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Joint Beamforming Design for Multi-User Wireless Information and Power Transfer

Cited by 71 publications

References 33 publications

Energy Efficient Resource Allocation for Wireless Power Transfer Enabled Collaborative Mobile Clouds

Energy Efficient Resource Allocation for Wireless Power Transfer Enabled Collaborative Mobile Clouds

Secure Information Transmission in the Presence of Energy-Harvesting Eavesdroppers in Multi-Cell Networks

Energy-Efficient Resource Allocation for Wireless Powered Massive MIMO System with Imperfect CSI

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