234 research outputs found
Distributed Interference-Aware Energy-Efficient Resource Allocation for Device-to-Device Communications Underlaying Cellular Networks
The introduction of device-to-device (D2D) into cellular networks poses many
new challenges in the resource allocation design due to the co-channel
interference caused by spectrum reuse and limited battery life of user
equipments (UEs). In this paper, we propose a distributed interference-aware
energy-efficient resource allocation algorithm to maximize each UE's energy
efficiency (EE) subject to its specific quality of service (QoS) and maximum
transmission power constraints. We model the resource allocation problem as a
noncooperative game, in which each player is self-interested and wants to
maximize its own EE. The formulated EE maximization problem is a non-convex
problem and is transformed into a convex optimization problem by exploiting the
properties of the nonlinear fractional programming. An iterative optimization
algorithm is proposed and verified through computer simulations.Comment: 6 pages, 3 figures, IEEE GLOBECOM 201
A Game-Theoretic Approach to Energy-Efficient Resource Allocation in Device-to-Device Underlay Communications
Despite the numerous benefits brought by Device-to-Device (D2D)
communications, the introduction of D2D into cellular networks poses many new
challenges in the resource allocation design due to the co-channel interference
caused by spectrum reuse and limited battery life of User Equipments (UEs).
Most of the previous studies mainly focus on how to maximize the Spectral
Efficiency (SE) and ignore the energy consumption of UEs. In this paper, we
study how to maximize each UE's Energy Efficiency (EE) in an
interference-limited environment subject to its specific Quality of Service
(QoS) and maximum transmission power constraints. We model the resource
allocation problem as a noncooperative game, in which each player is
self-interested and wants to maximize its own EE. A distributed
interference-aware energy-efficient resource allocation algorithm is proposed
by exploiting the properties of the nonlinear fractional programming. We prove
that the optimum solution obtained by the proposed algorithm is the Nash
equilibrium of the noncooperative game. We also analyze the tradeoff between EE
and SE and derive closed-form expressions for EE and SE gaps.Comment: submitted to IET Communications. arXiv admin note: substantial text
overlap with arXiv:1405.1963, arXiv:1407.155
Energy Efficiency and Spectral Efficiency Tradeoff in Device-to-Device (D2D) Communications
In this letter, we investigate the tradeoff between energy efficiency (EE)
and spectral efficiency (SE) in device-to-device (D2D) communications
underlaying cellular networks with uplink channel reuse. The resource
allocation problem is modeled as a noncooperative game, in which each user
equipment (UE) is self-interested and wants to maximize its own EE. Given the
SE requirement and maximum transmission power constraints, a distributed
energy-efficient resource allocation algorithm is proposed by exploiting the
properties of the nonlinear fractional programming. The relationships between
the EE and SE tradeoff of the proposed algorithm and system parameters are
analyzed and verified through computer simulations.Comment: 8 pages, 6 figures, long version paper of IEEE Wireless
Communications Letters, accepted for publication. arXiv admin note: text
overlap with arXiv:1405.196
Efficiency Resource Allocation for Device-to-Device Underlay Communication Systems: A Reverse Iterative Combinatorial Auction Based Approach
Peer-to-peer communication has been recently considered as a popular issue
for local area services. An innovative resource allocation scheme is proposed
to improve the performance of mobile peer-to-peer, i.e., device-to-device
(D2D), communications as an underlay in the downlink (DL) cellular networks. To
optimize the system sum rate over the resource sharing of both D2D and cellular
modes, we introduce a reverse iterative combinatorial auction as the allocation
mechanism. In the auction, all the spectrum resources are considered as a set
of resource units, which as bidders compete to obtain business while the
packages of the D2D pairs are auctioned off as goods in each auction round. We
first formulate the valuation of each resource unit, as a basis of the proposed
auction. And then a detailed non-monotonic descending price auction algorithm
is explained depending on the utility function that accounts for the channel
gain from D2D and the costs for the system. Further, we prove that the proposed
auction-based scheme is cheat-proof, and converges in a finite number of
iteration rounds. We explain non-monotonicity in the price update process and
show lower complexity compared to a traditional combinatorial allocation. The
simulation results demonstrate that the algorithm efficiently leads to a good
performance on the system sum rate.Comment: 26 pages, 6 fgures; IEEE Journals on Selected Areas in
Communications, 201
Secure Full-Duplex Device-to-Device Communication
This paper considers full-duplex (FD) device-to-device (D2D) communications
in a downlink MISO cellular system in the presence of multiple eavesdroppers.
The D2D pair communicate sharing the same frequency band allocated to the
cellular users (CUs). Since the D2D users share the same frequency as the CUs,
both the base station (BS) and D2D transmissions interfere each other. In
addition, due to limited processing capability, D2D users are susceptible to
external attacks. Our aim is to design optimal beamforming and power control
mechanism to guarantee secure communication while delivering the required
quality-of-service (QoS) for the D2D link. In order to improve security,
artificial noise (AN) is transmitted by the BS. We design robust beamforming
for secure message as well as the AN in the worst-case sense for minimizing
total transmit power with imperfect channel state information (CSI) of all
links available at the BS. The problem is strictly non-convex with infinitely
many constraints. By discovering the hidden convexity of the problem, we derive
a rank-one optimal solution for the power minimization problem.Comment: Accepted in IEEE GLOBECOM 2017, Singapore, 4-8 Dec. 201
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