3 research outputs found
Sum throughput maximization for heterogeneous multicell networks with RF-powered relays
This paper considers a heterogeneous multicell network
where the base station (BS) in each cell communicates with
its cell-edge user with the assistance of an amplify-and-forward
relay node. Equipped with a power splitter and a wireless energy
harvester, the relay scavenges RF energy from the received signals to
process and forward the information. In the face of strong intercell
interference and limited radio resources, we develop a resource
allocation scheme that jointly optimizes (i) BS transmit powers,
(ii) power splitting factors for energy harvesting and information
processing at the relays, and (iii) relay transmit powers. To solve the
highly non-convex problem formulation of sum-rate maximization,
we propose to apply the successive convex approximation (SCA)
approach and devise an iterative algorithm based on geometric
programming. The proposed algorithm transforms the nonconvex
problem into a sequence of convex problems, each of which is solved
very efficiently by the interior-point method. We prove that our
developed algorithm converges to an optimal solution that satisfies
the Karush-Kuhn-Tucker conditions of the original nonconvex
problem. Numerical results confirm that our joint optimization
solution substantially improves the network performance, compared
to the existing solution wherein only the received power splitting
factors at the relays are optimizedARC Discovery Projects Grant DP14010113
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
Sum Throughput Maximization for Heterogeneous Multicell Networks with RF-Powered Relays
Abstract-This paper considers a heterogeneous multicell network where the base station (BS) in each cell communicates with its cell-edge user with the assistance of an amplify-and-forward relay node. Equipped with a power splitter and a wireless energy harvester, the relay scavenges RF energy from the received signals to process and forward the information. In the face of strong intercell interference and limited radio resources, we develop a resource allocation scheme that jointly optimizes (i) BS transmit powers, (ii) power splitting factors for energy harvesting and information processing at the relays, and (iii) relay transmit powers. To solve the highly non-convex problem formulation of sum-rate maximization, we propose to apply the successive convex approximation (SCA) approach and devise an iterative algorithm based on geometric programming. The proposed algorithm transforms the nonconvex problem into a sequence of convex problems, each of which is solved very efficiently by the interior-point method. We prove that our developed algorithm converges to an optimal solution that satisfies the Karush-Kuhn-Tucker conditions of the original nonconvex problem. Numerical results confirm that our joint optimization solution substantially improves the network performance, compared to the existing solution wherein only the received power splitting factors at the relays are optimized. I. INTRODUCTION Heterogeneous multicell networks have been proposed as a promising solution for 5G communication standard The opportunistic nature of relay deployments may restrict the access to a main power supply. This problem can be circumvented by implementing wireless energy harvesting techniques at the relays, where energy is scavenged from the ambient propagating electromagnetic waves in the radio frequency (RF) [4]-[8]. Wireless energy harvesting solutions are feasible for heterogeneous relays, which only require significantly low transmit power due to their restricted network coverage In a heterogeneous multicell network with RF-powered relays, the key factors that determine the system performance include