7,413 research outputs found
RIS-Enhanced WPCNs: Joint Radio Resource Allocation and Passive Beamforming Optimization
Wireless-powered communication and reconfigurable intelligent surface (RIS) can complement each other for increasing energy utilization and spectrum efficiency by reconfiguring the surrounding radio environment, however, which has not been sufficiently studied by the existing works. In this paper, we propose a joint radio resource and passive beamforming optimization scheme for a downlink RIS-assisted wireless-powered communication network with a harvest-then-transmit protocol to improve system energy efficiency (EE). In the considered model, the single-antenna wireless devices (WDs) harvest wireless energy from a multi-antenna dedicated power station (PS) through the RIS in the downlink and transmit their independent information to a single-antenna receiver in the uplink by a time-division-multiple-access mode. Our goal is to maximize the total EE of all WDs. To make full use of the beamforming gain provided by both the PS and the RIS, we jointly optimize the active beamforming of the PS and the passive beamforming of the RIS. To deal with the challenging non-convex optimization problem with multiple coupled variables, we first consider fixing the passive beamforming, and converting the remaining radio resource allocation problem into an equivalent convex problem which is solved by using Lagrange dual theory. Then, we fix the optimized resource allocation parameters and optimize the passive beamforming of the RIS by using a semidefinite programming method. Simulation results demonstrate that the proposed algorithm achieves higher EE compared to the conventional schemes
Optimization and Analysis of Wireless Powered Multi-antenna Cooperative Systems
In this paper, we consider a three-node cooperative wireless powered
communication system consisting of a multi-antenna hybrid access point (H-AP)
and a single-antenna relay and a single-antenna user. The energy constrained
relay and user first harvest energy in the downlink and then the relay assists
the user using the harvested power for information transmission in the uplink.
The optimal energy beamforming vector and the time split between harvest and
cooperation are investigated. To reduce the computational complexity,
suboptimal designs are also studied, where closed-form expressions are derived
for the energy beamforming vector and the time split. For comparison purposes,
we also present a detailed performance analysis in terms of the achievable
outage probability and the average throughput of an intuitive energy
beamforming scheme, where the H-AP directs all the energy towards the user. The
findings of the paper suggest that implementing multiple antennas at the H-AP
can significantly improve the system performance, and the closed-form
suboptimal energy beamforming vector and time split yields near optimal
performance. Also, for the intuitive beamforming scheme, a diversity order of
(N+1)/2 can be achieved, where N is the number of antennas at the H-AP
Robust Transmissions in Wireless Powered Multi-Relay Networks with Chance Interference Constraints
In this paper, we consider a wireless powered multi-relay network in which a
multi-antenna hybrid access point underlaying a cellular system transmits
information to distant receivers. Multiple relays capable of energy harvesting
are deployed in the network to assist the information transmission. The hybrid
access point can wirelessly supply energy to the relays, achieving multi-user
gains from signal and energy cooperation. We propose a joint optimization for
signal beamforming of the hybrid access point as well as wireless energy
harvesting and collaborative beamforming strategies of the relays. The
objective is to maximize network throughput subject to probabilistic
interference constraints at the cellular user equipment. We formulate the
throughput maximization with both the time-switching and power-splitting
schemes, which impose very different couplings between the operating parameters
for wireless power and information transfer. Although the optimization problems
are inherently non-convex, they share similar structural properties that can be
leveraged for efficient algorithm design. In particular, by exploiting
monotonicity in the throughput, we maximize it iteratively via customized
polyblock approximation with reduced complexity. The numerical results show
that the proposed algorithms can achieve close to optimal performance in terms
of the energy efficiency and throughput.Comment: 14 pages, 8 figure
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