27,052 research outputs found
Game-theoretic Resource Allocation Methods for Device-to-Device (D2D) Communication
Device-to-device (D2D) communication underlaying cellular networks allows
mobile devices such as smartphones and tablets to use the licensed spectrum
allocated to cellular services for direct peer-to-peer transmission. D2D
communication can use either one-hop transmission (i.e., in D2D direct
communication) or multi-hop cluster-based transmission (i.e., in D2D local area
networks). The D2D devices can compete or cooperate with each other to reuse
the radio resources in D2D networks. Therefore, resource allocation and access
for D2D communication can be treated as games. The theories behind these games
provide a variety of mathematical tools to effectively model and analyze the
individual or group behaviors of D2D users. In addition, game models can
provide distributed solutions to the resource allocation problems for D2D
communication. The aim of this article is to demonstrate the applications of
game-theoretic models to study the radio resource allocation issues in D2D
communication. The article also outlines several key open research directions.Comment: Accepted. IEEE Wireless Comms Mag. 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
Optimization Framework and Graph-Based Approach for Relay-Assisted Bidirectional OFDMA Cellular Networks
This paper considers a relay-assisted bidirectional cellular network where
the base station (BS) communicates with each mobile station (MS) using OFDMA
for both uplink and downlink. The goal is to improve the overall system
performance by exploring the full potential of the network in various
dimensions including user, subcarrier, relay, and bidirectional traffic. In
this work, we first introduce a novel three-time-slot time-division duplexing
(TDD) transmission protocol. This protocol unifies direct transmission, one-way
relaying and network-coded two-way relaying between the BS and each MS. Using
the proposed three-time-slot TDD protocol, we then propose an optimization
framework for resource allocation to achieve the following gains: cooperative
diversity (via relay selection), network coding gain (via bidirectional
transmission mode selection), and multiuser diversity (via subcarrier
assignment). We formulate the problem as a combinatorial optimization problem,
which is NP-complete. To make it more tractable, we adopt a graph-based
approach. We first establish the equivalence between the original problem and a
maximum weighted clique problem in graph theory. A metaheuristic algorithm
based on any colony optimization (ACO) is then employed to find the solution in
polynomial time. Simulation results demonstrate that the proposed protocol
together with the ACO algorithm significantly enhances the system total
throughput.Comment: 27 pages, 8 figures, 2 table
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