140 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
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
User Association in 5G Networks: A Survey and an Outlook
26 pages; accepted to appear in IEEE Communications Surveys and Tutorial
Joint Wireless Information and Power Transfer for an Autonomous Multiple Antenna Relay System
Considering a three-node multiple antenna relay system, this paper proposes a
two-phase amplify-and-forward (AF) relaying protocol, which enables the
autonomous relay to simultaneously harvest wireless power from the source
information signal and from an energy signal conveyed by the destination. We
first study this energy-flow-assisted (EFA) relaying in a single-input
single-output (SISO) relay system and aim at maximizing the rate. By
transforming the optimization problem into an equivalent convex form, a global
optimum can be found. We then extend the protocol to a multiple antenna relay
system. The relay processing matrix is optimized to maximize the rate. The
optimization problem can be efficiently solved by eigenvalue decomposition,
after linear algebra manipulation. It is observed that the benefits of the
energy flow are interestingly shown only in the multiple antenna case, and it
is revealed that the received information signal and the energy leakage at the
relay can be nearly separated by making use of the signal space, such that the
desired signal can be amplified with a larger coefficient.Comment: Accepted to IEEE Communications Letter
Energy-efficiency for MISO-OFDMA based user-relay assisted cellular networks
The concept of improving energy-efficiency (EE) without sacrificing the service quality has become important nowadays. The combination of orthogonal frequency-division multiple-access (OFDMA) multi-antenna transmission technology and relaying is one of the key technologies to deliver the promise of reliable and high-data-rate coverage in the most cost-effective manner. In this paper, EE is studied for the downlink multiple-input single-output (MISO)-OFDMA based user-relay assisted cellular networks. EE maximization is formulated for decode and forward (DF) relaying scheme with the consideration of both transmit and circuit power consumption as well as the data rate requirements for the mobile users. The quality of-service (QoS)-constrained EE maximization, which is defined for multi-carrier, multi-user, multi-relay and multi-antenna networks, is a non-convex and combinatorial problem so it is hard to tackle. To solve this difficult problem, a radio resource management (RRM) algorithm that solves the subcarrier allocation, mode selection and power allocation separately is proposed. The efficiency of the proposed algorithm is demonstrated by numerical results for different system parameter
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