11,007 research outputs found
Price-Based Resource Allocation for Spectrum-Sharing Femtocell Networks: A Stackelberg Game Approach
This paper investigates the price-based resource allocation strategies for
the uplink transmission of a spectrum-sharing femtocell network, in which a
central macrocell is underlaid with distributed femtocells, all operating over
the same frequency band as the macrocell. Assuming that the macrocell base
station (MBS) protects itself by pricing the interference from the femtocell
users, a Stackelberg game is formulated to study the joint utility maximization
of the macrocell and the femtocells subject to a maximum tolerable interference
power constraint at the MBS. Especially, two practical femtocell channel
models: sparsely deployed scenario for rural areas and densely deployed
scenario for urban areas, are investigated. For each scenario, two pricing
schemes: uniform pricing and non-uniform pricing, are proposed. Then, the
Stackelberg equilibriums for these proposed games are studied, and an effective
distributed interference price bargaining algorithm with guaranteed convergence
is proposed for the uniform-pricing case. Finally, numerical examples are
presented to verify the proposed studies. It is shown that the proposed
algorithms are effective in resource allocation and macrocell protection
requiring minimal network overhead for spectrum-sharing-based two-tier
femtocell networks.Comment: 27 pages, 7 figures, Submitted to JSA
Spectrum sharing models in cognitive radio networks
Spectrum scarcity demands thinking new ways to
manage the distribution of radio frequency bands so that its use is more effective. The emerging technology that can enable this paradigm shift is the cognitive radio. Different models for
organizing and managing cognitive radios have emerged, all with specific strategic purposes. In this article we review the allocation spectrum patterns of cognitive radio networks and
analyse which are the common basis of each model.We expose the vulnerabilities and open challenges that still threaten the adoption
and exploitation of cognitive radios for open civil networks.L'escassetat de demandes d'espectre fan pensar en noves formes de gestionar la distribució de les bandes de freqüència de ràdio perquè el seu ús sigui més efectiu. La tecnologia emergent que pot permetre aquest canvi de paradigma és la ràdio cognitiva. Han sorgit diferents models d'organització i gestió de les ràdios cognitives, tots amb determinats fins estratègics. En aquest article es revisen els patrons d'assignació de l'espectre de les xarxes de ràdio cognitiva i s'analitzen quals són la base comuna de cada model. S'exposen les vulnerabilitats i els desafiaments oberts que segueixen amenaçant l'adopció i l'explotació de les ràdios cognitives per obrir les xarxes civils.La escasez de demandas de espectro hacen pensar en nuevas formas de gestionar la distribución de las bandas de frecuencia de radio para que su uso sea más efectivo. La tecnología emergente que puede permitir este cambio de paradigma es la radio cognitiva. Han surgido diferentes modelos de organización y gestión de las radios cognitivas, todos con determinados fines estratégicos. En este artículo se revisan los patrones de asignación del espectro de las redes de radio cognitiva y se analizan cuales son la base común de cada modelo. Se exponen las vulnerabilidades y los desafíos abiertos que siguen amenazando la adopción y la explotación de las radios cognitivas para abrir las redes civiles
Applications of Repeated Games in Wireless Networks: A Survey
A repeated game is an effective tool to model interactions and conflicts for
players aiming to achieve their objectives in a long-term basis. Contrary to
static noncooperative games that model an interaction among players in only one
period, in repeated games, interactions of players repeat for multiple periods;
and thus the players become aware of other players' past behaviors and their
future benefits, and will adapt their behavior accordingly. In wireless
networks, conflicts among wireless nodes can lead to selfish behaviors,
resulting in poor network performances and detrimental individual payoffs. In
this paper, we survey the applications of repeated games in different wireless
networks. The main goal is to demonstrate the use of repeated games to
encourage wireless nodes to cooperate, thereby improving network performances
and avoiding network disruption due to selfish behaviors. Furthermore, various
problems in wireless networks and variations of repeated game models together
with the corresponding solutions are discussed in this survey. Finally, we
outline some open issues and future research directions.Comment: 32 pages, 15 figures, 5 tables, 168 reference
Dynamic Geospatial Spectrum Modelling: Taxonomy, Options and Consequences
Much of the research in Dynamic Spectrum Access (DSA) has focused on opportunistic access in the temporal domain. While this has been quite useful in establishing the technical feasibility of DSA systems, it has missed large sections of the overall DSA problem space. In this paper, we argue that the spatio-temporal operating context of specific environments matters to the selection of the appropriate technology for learning context information. We identify twelve potential operating environments and compare four context awareness approaches (on-board sensing, databases, sensor networks, and cooperative sharing) for these environments. Since our point of view is overall system cost and efficiency, this analysis has utility for those regulators whose objectives are reducing system costs and enhancing system efficiency. We conclude that regulators should pay attention to the operating environment of DSA systems when determining which approaches to context learning to encourage
Enforcement in Dynamic Spectrum Access Systems
The spectrum access rights granted by the Federal government to spectrum users come with the expectation of protection from harmful interference. As a consequence of the growth of wireless demand and services of all types, technical progress enabling smart agile radio networks, and on-going spectrum management reform, there is both a need and opportunity to use and share spectrum more intensively and dynamically. A key element of any framework for managing harmful interference is the mechanism for enforcement of those rights. Since the rights to use spectrum and to protection from harmful interference vary by band (licensed/unlicensed, legacy/newly reformed) and type of use/users (primary/secondary, overlay/underlay), it is reasonable to expect that the enforcement mechanisms may need to vary as well.\ud
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In this paper, we present a taxonomy for evaluating alternative mechanisms for enforcing interference protection for spectrum usage rights, with special attention to the potential changes that may be expected from wider deployment of Dynamic Spectrum Access (DSA) systems. Our exploration of how the design of the enforcement regime interacts with and influences the incentives of radio operators under different rights regimes and market scenarios is intended to assist in refining thinking about appropriate access rights regimes and how best to incentivize investment and growth in more efficient and valuable uses of the radio frequency spectrum
Distributed Game Theoretic Optimization and Management of Multichannel ALOHA Networks
The problem of distributed rate maximization in multi-channel ALOHA networks
is considered. First, we study the problem of constrained distributed rate
maximization, where user rates are subject to total transmission probability
constraints. We propose a best-response algorithm, where each user updates its
strategy to increase its rate according to the channel state information and
the current channel utilization. We prove the convergence of the algorithm to a
Nash equilibrium in both homogeneous and heterogeneous networks using the
theory of potential games. The performance of the best-response dynamic is
analyzed and compared to a simple transmission scheme, where users transmit
over the channel with the highest collision-free utility. Then, we consider the
case where users are not restricted by transmission probability constraints.
Distributed rate maximization under uncertainty is considered to achieve both
efficiency and fairness among users. We propose a distributed scheme where
users adjust their transmission probability to maximize their rates according
to the current network state, while maintaining the desired load on the
channels. We show that our approach plays an important role in achieving the
Nash bargaining solution among users. Sequential and parallel algorithms are
proposed to achieve the target solution in a distributed manner. The
efficiencies of the algorithms are demonstrated through both theoretical and
simulation results.Comment: 34 pages, 6 figures, accepted for publication in the IEEE/ACM
Transactions on Networking, part of this work was presented at IEEE CAMSAP
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