301 research outputs found
A Cooperative Bayesian Nonparametric Framework for Primary User Activity Monitoring in Cognitive Radio Network
This paper introduces a novel approach that enables a number of cognitive
radio devices that are observing the availability pattern of a number of
primary users(PUs), to cooperate and use \emph{Bayesian nonparametric}
techniques to estimate the distributions of the PUs' activity pattern, assumed
to be completely unknown. In the proposed model, each cognitive node may have
its own individual view on each PU's distribution, and, hence, seeks to find
partners having a correlated perception. To address this problem, a coalitional
game is formulated between the cognitive devices and an algorithm for
cooperative coalition formation is proposed. It is shown that the proposed
coalition formation algorithm allows the cognitive nodes that are experiencing
a similar behavior from some PUs to self-organize into disjoint, independent
coalitions. Inside each coalition, the cooperative cognitive nodes use a
combination of Bayesian nonparametric models such as the Dirichlet process and
statistical goodness of fit techniques in order to improve the accuracy of the
estimated PUs' activity distributions. Simulation results show that the
proposed algorithm significantly improves the estimates of the PUs'
distributions and yields a performance advantage, in terms of reduction of the
average achieved Kullback-Leibler distance between the real and the estimated
distributions, reaching up to 36.5% relative the non-cooperative estimates. The
results also show that the proposed algorithm enables the cognitive nodes to
adapt their cooperative decisions when the actual PUs' distributions change due
to, for example, PU mobility.Comment: IEEE Journal on Selected Areas in Communications (JSAC), to appear,
201
Cooperative games with incomplete information for secondary base stations in cognitive radio networks
Cognitive radio (CR) technology is considered to be an effective solution for enhancing overall spectrum efficiency. Using CR technology fully involves the providing of incentives to Primary Radio Networks (PRNs) and revenue to the service provider so that Secondary Base Stations (SBSs) may utilize PRN spectrum bands accordingly. In this paper, a cooperative games with incomplete information for SBSs in a CR network is presented. Each SBS can cooperate with neighboring SBSs in order to improve its view of the spectrum. Moreover, proposed game-theory models assume that the devices have incomplete information about their components, meaning that some players do not completely know the structure of the game. Using the proposed algorithm, each SBS can leave or join the coalition while maximizing its overall utility. The simulation results illustrate that the proposed algorithm allows us to reduce the average payoff per SBS up to 140% relative to a CR network without cooperation among SBSs
Fast convergence cooperative dynamic spectrum access for cognitive radio networks
Cognitive radio and dynamic spectrum access can reform the way that radiofrequency spectrum is accessed. Problems of spectrum scarcity, coexistence, and unreliable wireless communication that affect industrial wireless networks can be addressed. In this paper, a game theoretic dynamic spectrum access algorithm that improves upon on a hedonic coalition formation algorithm for spectrum sensing and access is presented. The modified algorithm is tailored for faster convergence and scalability and makes use of a novel simultaneous multichannel sensing and access technique. Results to demonstrate the performance improvements of the adapted algorithm are presented and the use of different decision rules are investigated revealing that a conservative decision rule for exploiting spectrum opportunities performs better than an aggressive decision rule in most scenarios. The algorithm that was developed could be a key enabler for future cognitive radio networks.http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=9424hj2018Electrical, Electronic and Computer Engineerin
Coalitional Games in Partition Form for Joint Spectrum Sensing and Access in Cognitive Radio Networks
Unlicensed secondary users (SUs) in cognitive radio networks are subject to
an inherent tradeoff between spectrum sensing and spectrum access. Although
each SU has an incentive to sense the primary user (PU) channels for locating
spectrum holes, this exploration of the spectrum can come at the expense of a
shorter transmission time, and, hence, a possibly smaller capacity for data
transmission. This paper investigates the impact of this tradeoff on the
cooperative strategies of a network of SUs that seek to cooperate in order to
improve their view of the spectrum (sensing), reduce the possibility of
interference among each other, and improve their transmission capacity
(access). The problem is modeled as a coalitional game in partition form and an
algorithm for coalition formation is proposed. Using the proposed algorithm,
the SUs can make individual distributed decisions to join or leave a coalition
while maximizing their utilities which capture the average time spent for
sensing as well as the capacity achieved while accessing the spectrum. It is
shown that, by using the proposed algorithm, the SUs can self-organize into a
network partition composed of disjoint coalitions, with the members of each
coalition cooperating to jointly optimize their sensing and access performance.
Simulation results show the performance improvement that the proposed algorithm
yields with respect to the non-cooperative case. The results also show how the
algorithm allows the SUs to self-adapt to changes in the environment such as
the change in the traffic of the PUs, or slow mobility.Comment: IEEE Journal on Selected Topics in Signal Processing (JSTSP), Special
Issue on Game Theory, to appear, 201
Coalitional Game Theory for Communication Networks: A Tutorial
Game theoretical techniques have recently become prevalent in many
engineering applications, notably in communications. With the emergence of
cooperation as a new communication paradigm, and the need for self-organizing,
decentralized, and autonomic networks, it has become imperative to seek
suitable game theoretical tools that allow to analyze and study the behavior
and interactions of the nodes in future communication networks. In this
context, this tutorial introduces the concepts of cooperative game theory,
namely coalitional games, and their potential applications in communication and
wireless networks. For this purpose, we classify coalitional games into three
categories: Canonical coalitional games, coalition formation games, and
coalitional graph games. This new classification represents an
application-oriented approach for understanding and analyzing coalitional
games. For each class of coalitional games, we present the fundamental
components, introduce the key properties, mathematical techniques, and solution
concepts, and describe the methodologies for applying these games in several
applications drawn from the state-of-the-art research in communications. In a
nutshell, this article constitutes a unified treatment of coalitional game
theory tailored to the demands of communications and network engineers.Comment: IEEE Signal Processing Magazine, Special Issue on Game Theory, to
appear, 2009. IEEE Signal Processing Magazine, Special Issue on Game Theory,
to appear, 200
Pilot Clustering in Asymmetric Massive MIMO Networks
We consider the uplink of a cellular massive MIMO network. Since the spectral
efficiency of these networks is limited by pilot contamination, the pilot
allocation across cells is of paramount importance. However, finding efficient
pilot reuse patterns is non-trivial especially in practical asymmetric base
station deployments. In this paper, we approach this problem using coalitional
game theory. Each cell has its own unique pilots and can form coalitions with
other cells to gain access to more pilots. We develop a low-complexity
distributed algorithm and prove convergence to an individually stable coalition
structure. Simulations reveal fast algorithmic convergence and substantial
performance gains over one-cell coalitions and full pilot reuse.Comment: Published in Proc. of IEEE International Workshop on Signal
Processing Advances in Wireless Communications (SPAWC '15), 5 pages, 1
tables, 5 figure
Interference Alignment-Aided Base Station Clustering using Coalition Formation
Base station clustering is necessary in large interference networks, where
the channel state information (CSI) acquisition overhead otherwise would be
overwhelming. In this paper, we propose a novel long-term throughput model for
the clustered users which addresses the balance between interference mitigation
capability and CSI acquisition overhead. The model only depends on statistical
CSI, thus enabling long-term clustering. Based on notions from coalitional game
theory, we propose a low-complexity distributed clustering method. The
algorithm converges in a couple of iterations, and only requires limited
communication between base stations. Numerical simulations show the viability
of the proposed approach.Comment: 2nd Prize, Student Paper Contest. Copyright 2015 SS&C. Published in
the Proceedings of the 49th Asilomar Conference on Signals, Systems and
Computers, Nov 8-11, 2015, Pacific Grove, CA, US
The Spectrum Shortage Problem: Channel Assignment and Cognitive Networks
Recent studies have shown that the proliferation of wireless applications and services, experienced in the last decade, is leading to the challenging spectrum shortage problem.
We provide a general overview regarding the spectrum shortage problem from the point of view of different technologies.
First, we propose solutions based on multi-radio multi-channel wireless mesh networks in order to improve the usage of unlicensed wireless resources.
Then, we move our focus on cognitive networks in order to analyze issues and solutions to opportunistically use licensed wireless resources.
In wireless mesh networks, the spectrum shortage problem is addressed equipping each device with multiple radios which are turned on different orthogonal channels.
We propose G-PaMeLA, which splits in local sub-problems the joint channel assignment and routing problem in multi-radio multi-channel wireless mesh networks.
Results demonstrate that G-PaMeLA significantly improves network performance, in terms of packet loss and throughput fairness compared to algorithms in the literature.
Unfortunately, even if orthogonal channels are used, wireless mesh networks result in what is called spectrum overcrowding.
In order to address the spectrum overcrowding problem, careful analysis on spectrum frequencies has been conducted.
These studies identified the possibility of transmitting on licensed channels, which are surprisingly underutilized.
With the aim of addressing the resources problem using licensed channels, cognitive access and mesh networks have been developed.
In cognitive access networks, we identify as the major problem the self-coexistence, which is the ability to access channels on a non-interfering basis with respect to licensed and unlicensed wireless devices.
We propose two game theoretic frameworks which differentiate in having non-cooperative (NoRa) and cooperative (HeCtor) cognitive devices, respectively.
Results show that HeCtor achieves higher throughput than NoRa but at the cost of higher computational complexity, which leads to a smaller throughput in cases where rapid changes occur in channels' occupancy.
In contrast, NoRa attains the same throughput independent of the variability in channels' occupancy, hence cognitive devices adapt faster to such changes.
In cognitive mesh networks, we analyze the coordination problem among cognitive devices because it is the major concern in implementing mesh networks in environments which change in time and space.
We propose Connor, a clustering algorithm to address the coordination problem, which establishes common local control channels.
Connor, in contrast with existing algorithms in the literature, does not require synchronization among cognitive mesh devices and allows a fast re-clustering when changes occur in channel's occupancy by licensed users.
Results show that Connor performs better than existing algorithms in term of number of channels used for control purposes and time to reach and stay on stable configurations
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