3,104 research outputs found
Joint Resource Optimization for Multicell Networks with Wireless Energy Harvesting Relays
This paper first considers a multicell network deployment where the base
station (BS) of each cell communicates with its cell-edge user with the
assistance of an amplify-and-forward (AF) relay node. Equipped with a power
splitter and a wireless energy harvester, the self-sustaining relay scavenges
radio frequency (RF) energy from the received signals to process and forward
the information. Our aim is to develop a resource allocation scheme that
jointly optimizes (i) BS transmit powers, (ii) received power splitting factors
for energy harvesting and information processing at the relays, and (iii) relay
transmit powers. In the face of strong intercell interference and limited radio
resources, we formulate three highly-nonconvex problems with the objectives of
sum-rate maximization, max-min throughput fairness and sum-power minimization.
To solve such challenging problems, we propose to apply the successive convex
approximation (SCA) approach and devise iterative algorithms based on geometric
programming and difference-of-convex-functions programming. The proposed
algorithms transform the nonconvex problems into a sequence of convex problems,
each of which is solved very efficiently by the interior-point method. We prove
that our algorithms converge to the locally optimal solutions that satisfy the
Karush-Kuhn-Tucker conditions of the original nonconvex problems. We then
extend our results to the case of decode-and-forward (DF) relaying with
variable timeslot durations. We show that our resource allocation solutions in
this case offer better throughput than that of the AF counterpart with equal
timeslot durations, albeit at a higher computational complexity. Numerical
results confirm that the proposed joint optimization solutions substantially
improve the network performance, compared with cases where the radio resource
parameters are individually optimized
Linear Precoders for Non-Regenerative Asymmetric Two-way Relaying in Cellular Systems
Two-way relaying (TWR) reduces the spectral-efficiency loss caused in
conventional half-duplex relaying. TWR is possible when two nodes exchange data
simultaneously through a relay. In cellular systems, data exchange between base
station (BS) and users is usually not simultaneous e.g., a user (TUE) has
uplink data to transmit during multiple access (MAC) phase, but does not have
downlink data to receive during broadcast (BC) phase. This non-simultaneous
data exchange will reduce TWR to spectrally-inefficient conventional
half-duplex relaying. With infrastructure relays, where multiple users
communicate through a relay, a new transmission protocol is proposed to recover
the spectral loss. The BC phase following the MAC phase of TUE is now used by
the relay to transmit downlink data to another user (RUE). RUE will not be able
to cancel the back-propagating interference. A structured precoder is designed
at the multi-antenna relay to cancel this interference. With multiple-input
multiple-output (MIMO) nodes, the proposed precoder also triangulates the
compound MAC and BC phase MIMO channels. The channel triangulation reduces the
weighted sum-rate optimization to power allocation problem, which is then cast
as a geometric program. Simulation results illustrate the effectiveness of the
proposed protocol over conventional solutions.Comment: 30 pages, 7 figures, submitted to IEEE Transactions on Wireless
Communication
Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication
The adoption of a Reconfigurable Intelligent Surface (RIS) for downlink
multi-user communication from a multi-antenna base station is investigated in
this paper. We develop energy-efficient designs for both the transmit power
allocation and the phase shifts of the surface reflecting elements, subject to
individual link budget guarantees for the mobile users. This leads to
non-convex design optimization problems for which to tackle we propose two
computationally affordable approaches, capitalizing on alternating
maximization, gradient descent search, and sequential fractional programming.
Specifically, one algorithm employs gradient descent for obtaining the RIS
phase coefficients, and fractional programming for optimal transmit power
allocation. Instead, the second algorithm employs sequential fractional
programming for the optimization of the RIS phase shifts. In addition, a
realistic power consumption model for RIS-based systems is presented, and the
performance of the proposed methods is analyzed in a realistic outdoor
environment. In particular, our results show that the proposed RIS-based
resource allocation methods are able to provide up to higher energy
efficiency, in comparison with the use of regular multi-antenna
amplify-and-forward relaying.Comment: Accepted by IEEE TWC; additional materials on the topic are included
in the 2018 conference publications at ICASSP
(https://ieeexplore.ieee.org/abstract/document/8461496) and GLOBECOM 2018
(arXiv:1809.05397
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