In this study, the authors study the max-min fairness for wireless energy transfer in a multiuser multiple-input multiple-output communication system with simultaneous wireless information and power transfer. In parti...
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In this study, the authors study the max-min fairness for wireless energy transfer in a multiuser multiple-input multiple-output communication system with simultaneous wireless information and power transfer. In particular, they aim to maximise the minimum harvested energy among the multiple multi-antenna energy receivers while guaranteeing secure communication for multi-antenna information receiver. The dual use of artificial noise to facilitate both wireless energy transfer and secure communication is exploited in the authors' proposed problem. Both scenarios of perfect and imperfect channel state information (CSI) known at the transmitter are considered. For the perfect CSI case, the formulated max-min energy harvesting (MM-EH) problem is non-convex and intractable. To circumvent it, an iterative optimisation algorithm based on Taylor series expansion is proposed. Then, they turn their attention to the imperfect CSI case, where a max-min robust energy harvesting (MMR-EH) problem is considered. Though the MMR-EH problem is more complicated than the MM-EH problem, they reveal that the iterative optimisation method can be extended to the solution of the former, wherein the S-procedure is introduced. Simulation results show the efficiency of their proposed solutions in terms of energy harvesting.
Assume that a multi-user multiple-inputmultipleoutput (MIMO) communicationsystem must be designed to cover a given area with maximal energy efficiency (bits/Joule). What are the optimal values for the number of ant...
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ISBN:
(纸本)9781479930838
Assume that a multi-user multiple-inputmultipleoutput (MIMO) communicationsystem must be designed to cover a given area with maximal energy efficiency (bits/Joule). What are the optimal values for the number of antennas, active users, and transmit power? By using a new model that describes how these three parameters affect the total energy efficiency of the system, this work provides closed-form expressions for their optimal values and interactions. In sharp contrast to common belief, the transmit power is found to increase (not decrease) with the number of antennas. This implies that energy efficient systems can operate at high signal-to-noise ratio (SNR) regimes in which the use of interference-suppressing precoding schemes is essential. Numerical results show that the maximal energy efficiency is achieved by a massive MIMO setup wherein hundreds of antennas are deployed to serve relatively many users using interference-suppressing regularized zero-forcing precoding.
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