9,908 research outputs found
Improving Macrocell - Small Cell Coexistence through Adaptive Interference Draining
The deployment of underlay small base stations (SBSs) is expected to
significantly boost the spectrum efficiency and the coverage of next-generation
cellular networks. However, the coexistence of SBSs underlaid to an existing
macro-cellular network faces important challenges, notably in terms of spectrum
sharing and interference management. In this paper, we propose a novel
game-theoretic model that enables the SBSs to optimize their transmission rates
by making decisions on the resource occupation jointly in the frequency and
spatial domains. This procedure, known as interference draining, is performed
among cooperative SBSs and allows to drastically reduce the interference
experienced by both macro- and small cell users. At the macrocell side, we
consider a modified water-filling policy for the power allocation that allows
each macrocell user (MUE) to focus the transmissions on the degrees of freedom
over which the MUE experiences the best channel and interference conditions.
This approach not only represents an effective way to decrease the received
interference at the MUEs but also grants the SBSs tier additional transmission
opportunities and allows for a more agile interference management. Simulation
results show that the proposed approach yields significant gains at both
macrocell and small cell tiers, in terms of average achievable rate per user,
reaching up to 37%, relative to the non-cooperative case, for a network with
150 MUEs and 200 SBSs
MIMO-OFDM Based Energy Harvesting Cooperative Communications Using Coalitional Game Algorithm
This document is the Accepted Manuscript version. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper, we consider the problem of cooperative communication between relays and base station in an advanced MIMO-OFDM framework, under the assumption that the relays are supplied by electric power drawn from energy harvesting (EH) sources. In particular, we focus on the relay selection, with the goal to guarantee the required performance in terms of capacity. In order to maximize the data throughput under the EH constraint, we model the transmission scheme as a non-transferable coalition formation game, with characteristic function based on an approximated capacity expression. Then, we introduce a powerful mathematical tool inherent to coalitional game theory, namely: the Shapley value (Sv) to provide a reliable solution concept to the game. The selected relays will form a virtual dynamically-configuredMIMO network that is able to transmit data to destination using efficient space-time coding techniques. Numerical results, obtained by simulating the EH-powered cooperativeMIMO-OFDMtransmission with Algebraic Space-Time Coding (ASTC), prove that the proposed coalitional game-based relay selection allows to achieve performance very close to that obtained by the same system operated by guaranteed power supply. The proposed methodology is finally compared with some recent related state-of-the-art techniques showing clear advantages in terms of link performance and goodput.Peer reviewe
Distributed Cooperative Sensing in Cognitive Radio Networks: An Overlapping Coalition Formation Approach
Cooperative spectrum sensing has been shown to yield a significant
performance improvement in cognitive radio networks. In this paper, we consider
distributed cooperative sensing (DCS) in which secondary users (SUs) exchange
data with one another instead of reporting to a common fusion center. In most
existing DCS algorithms, the SUs are grouped into disjoint cooperative groups
or coalitions, and within each coalition the local sensing data is exchanged.
However, these schemes do not account for the possibility that an SU can be
involved in multiple cooperative coalitions thus forming overlapping
coalitions. Here, we address this problem using novel techniques from a class
of cooperative games, known as overlapping coalition formation games, and based
on the game model, we propose a distributed DCS algorithm in which the SUs
self-organize into a desirable network structure with overlapping coalitions.
Simulation results show that the proposed overlapping algorithm yields
significant performance improvements, decreasing the total error probability up
to 25% in the Q_m+Q_f criterion, the missed detection probability up to 20% in
the Q_m/Q_f criterion, the overhead up to 80%, and the total report number up
to 10%, compared with the state-of-the-art non-overlapping algorithm
Hierarchical Cooperation for Operator-Controlled Device-to-Device Communications: A Layered Coalitional Game Approach
Device-to-Device (D2D) communications, which allow direct communication among
mobile devices, have been proposed as an enabler of local services in 3GPP
LTE-Advanced (LTE-A) cellular networks. This work investigates a hierarchical
LTE-A network framework consisting of multiple D2D operators at the upper layer
and a group of devices at the lower layer. We propose a cooperative model that
allows the operators to improve their utility in terms of revenue by sharing
their devices, and the devices to improve their payoff in terms of end-to-end
throughput by collaboratively performing multi-path routing. To help
understanding the interaction among operators and devices, we present a
game-theoretic framework to model the cooperation behavior, and further, we
propose a layered coalitional game (LCG) to address the decision making
problems among them. Specifically, the cooperation of operators is modeled as
an overlapping coalition formation game (CFG) in a partition form, in which
operators should form a stable coalitional structure. Moreover, the cooperation
of devices is modeled as a coalitional graphical game (CGG), in which devices
establish links among each other to form a stable network structure for
multi-path routing.We adopt the extended recursive core, and Nash network, as
the stability concept for the proposed CFG and CGG, respectively. Numerical
results demonstrate that the proposed LCG yields notable gains compared to both
the non-cooperative case and a LCG variant and achieves good convergence speed.Comment: IEEE Wireless Communications and Networking Conference 201
An analysis on decentralized adaptive MAC protocols for Cognitive Radio networks
The scarcity of bandwidth in the radio spectrum has become more vital since the demand for more and more wireless applications has increased. Most of the spectrum bands have been allocated although many studies have shown that these bands are significantly underutilized most of the time. The problem of unavailability of spectrum and inefficiency in its utilization has been smartly addressed by the Cognitive Radio (CR) Technology which is an opportunistic network that senses the environment, observes the network changes, and then using knowledge gained from the prior interaction with the network, makes intelligent decisions by dynamically adapting their transmission characteristics. In this paper some of the decentralized adaptive MAC protocols for CR networks have been critically analyzed and a novel adaptive MAC protocol for CR networks, DNG-MAC which is decentralized and non-global in nature, has been proposed. The results show the DNG-MAC out performs other CR MAC protocols in terms of time and energy efficiency
Hedonic Coalition Formation for Distributed Task Allocation among Wireless Agents
Autonomous wireless agents such as unmanned aerial vehicles or mobile base
stations present a great potential for deployment in next-generation wireless
networks. While current literature has been mainly focused on the use of agents
within robotics or software applications, we propose a novel usage model for
self-organizing agents suited to wireless networks. In the proposed model, a
number of agents are required to collect data from several arbitrarily located
tasks. Each task represents a queue of packets that require collection and
subsequent wireless transmission by the agents to a central receiver. The
problem is modeled as a hedonic coalition formation game between the agents and
the tasks that interact in order to form disjoint coalitions. Each formed
coalition is modeled as a polling system consisting of a number of agents which
move between the different tasks present in the coalition, collect and transmit
the packets. Within each coalition, some agents can also take the role of a
relay for improving the packet success rate of the transmission. The proposed
algorithm allows the tasks and the agents to take distributed decisions to join
or leave a coalition, based on the achieved benefit in terms of effective
throughput, and the cost in terms of delay. As a result of these decisions, the
agents and tasks structure themselves into independent disjoint coalitions
which constitute a Nash-stable network partition. Moreover, the proposed
algorithm allows the agents and tasks to adapt the topology to environmental
changes such as the arrival/removal of tasks or the mobility of the tasks.
Simulation results show how the proposed algorithm improves the performance, in
terms of average player (agent or task) payoff, of at least 30.26% (for a
network of 5 agents with up to 25 tasks) relatively to a scheme that allocates
nearby tasks equally among agents.Comment: to appear, IEEE Transactions on Mobile Computin
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