10,026 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
Energy Efficiency in MIMO Underlay and Overlay Device-to-Device Communications and Cognitive Radio Systems
This paper addresses the problem of resource allocation for systems in which
a primary and a secondary link share the available spectrum by an underlay or
overlay approach. After observing that such a scenario models both cognitive
radio and D2D communications, we formulate the problem as the maximization of
the secondary energy efficiency subject to a minimum rate requirement for the
primary user. This leads to challenging non-convex, fractional problems. In the
underlay scenario, we obtain the global solution by means of a suitable
reformulation. In the overlay scenario, two algorithms are proposed. The first
one yields a resource allocation fulfilling the first-order optimality
conditions of the resource allocation problem, by solving a sequence of easier
fractional problems. The second one enjoys a weaker optimality claim, but an
even lower computational complexity. Numerical results demonstrate the merits
of the proposed algorithms both in terms of energy-efficient performance and
complexity, also showing that the two proposed algorithms for the overlay
scenario perform very similarly, despite the different complexity.Comment: to appear in IEEE Transactions on Signal Processin
Energy-Efficient Power Allocation in OFDM Systems with Wireless Information and Power Transfer
This paper considers an orthogonal frequency division multiplexing (OFDM)
downlink point-to-point system with simultaneous wireless information and power
transfer. It is assumed that the receiver is able to harvest energy from noise,
interference, and the desired signals.
We study the design of power allocation algorithms maximizing the energy
efficiency of data transmission (bit/Joule delivered to the receiver). In
particular, the algorithm design is formulated as a high-dimensional non-convex
optimization problem which takes into account the circuit power consumption,
the minimum required data rate, and a constraint on the minimum power delivered
to the receiver. Subsequently, by exploiting the properties of nonlinear
fractional programming, the considered non-convex optimization problem, whose
objective function is in fractional form, is transformed into an equivalent
optimization problem having an objective function in subtractive form, which
enables the derivation of an efficient iterative power allocation algorithm. In
each iteration, the optimal power allocation solution is derived based on dual
decomposition and a one-dimensional search. Simulation results illustrate that
the proposed iterative power allocation algorithm converges to the optimal
solution, and unveil the trade-off between energy efficiency, system capacity,
and wireless power transfer: (1) In the low transmit power regime, maximizing
the system capacity may maximize the energy efficiency. (2) Wireless power
transfer can enhance the energy efficiency, especially in the interference
limited regime.Comment: 6 pages, Accepted for presentation at the IEEE International
Conference on Communications (ICC) 201
Resource Allocation for Secure Communication in Systems with Wireless Information and Power Transfer
This paper considers secure communication in a multiuser multiple-input
single-output (MISO) downlink system with simultaneous wireless information and
power transfer. We study the design of resource allocation algorithms
minimizing the total transmit power for the case when the receivers are able to
harvest energy from the radio frequency. In particular, the algorithm design is
formulated as a non-convex optimization problem which takes into account
artificial noise generation to combat potential eavesdroppers, a minimum
required signal-to-interference-plus-noise ratio (SINR) at the desired
receiver, maximum tolerable SINRs at the potential eavesdroppers, and a minimum
required power delivered to the receivers. We adopt a semidefinite programming
(SDP) relaxation approach to obtain an upper bound solution for the considered
problem. The tightness of the upper bound is revealed by examining a sufficient
condition for the global optimal solution. Inspired by the sufficient
condition, we propose two suboptimal resource allocation schemes enhancing
secure communication and facilitating efficient energy harvesting. Simulation
results demonstrate a close-to-optimal performance achieved by the proposed
suboptimal schemes and significant transmit power savings by optimization of
the artificial noise generation.Comment: 7 pages, 5 figures, and 1 table. Submitted for possible conference
publicatio
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