2,177 research outputs found
Investment and Pricing with Spectrum Uncertainty: A Cognitive Operator's Perspective
This paper studies the optimal investment and pricing decisions of a
cognitive mobile virtual network operator (C-MVNO) under spectrum supply
uncertainty. Compared with a traditional MVNO who often leases spectrum via
long-term contracts, a C-MVNO can acquire spectrum dynamically in short-term by
both sensing the empty "spectrum holes" of licensed bands and dynamically
leasing from the spectrum owner. As a result, a C-MVNO can make flexible
investment and pricing decisions to match the current demands of the secondary
unlicensed users. Compared to dynamic spectrum leasing, spectrum sensing is
typically cheaper, but the obtained useful spectrum amount is random due to
primary licensed users' stochastic traffic. The C-MVNO needs to determine the
optimal amounts of spectrum sensing and leasing by evaluating the trade off
between cost and uncertainty. The C-MVNO also needs to determine the optimal
price to sell the spectrum to the secondary unlicensed users, taking into
account wireless heterogeneity of users such as different maximum transmission
power levels and channel gains. We model and analyze the interactions between
the C-MVNO and secondary unlicensed users as a Stackelberg game. We show
several interesting properties of the network equilibrium, including threshold
structures of the optimal investment and pricing decisions, the independence of
the optimal price on users' wireless characteristics, and guaranteed fair and
predictable QoS among users. We prove that these properties hold for general
SNR regime and general continuous distributions of sensing uncertainty. We show
that spectrum sensing can significantly improve the C-MVNO's expected profit
and users' payoffs.Comment: A shorter version appears in IEEE INFOCOM 2010. This version has been
submitted to IEEE Transactions on Mobile Computin
An Agent-Based Model for Secondary Use of Radio Spectrum
Wireless communications rely on access to radio spectrum. With a continuing proliferation of wireless applications and services, the spectrum resource becomes scarce. The measurement studies of spectrum usage, however, reveal that spectrum is being used sporadically in many geographical areas and times. In an attempt to promote efficiency of spectrum usage, the Federal Communications Commission has supported the use of market mechanism to allocate and assign radio spectrum. We focus on the secondary use of spectrum defined as a temporary access of existing licensed spectrum by a user who does not own a spectrum license. The secondary use of spectrum raises numerous technical, institutional, economic, and strategic issues that merit investigation. Central to the issues are the effects of transaction costs associated with the use of market mechanism and the uncertainties due to potential interference.The research objective is to identify the pre-conditions as to when and why the secondary use would emerge and in what form. We use transaction cost economics as the theoretical framework in this study. We propose a novel use of agent-based computational economics to model the development of the secondary use of spectrum. The agent-based model allows an integration of economic and technical considerations to the study of pre-conditions to the secondary use concept. The agent-based approach aims to observe the aggregate outcomes as a result of interactions among agents and understand the process that leads to the secondary use, which can then be used to create policy instruments in order to obtain the favorable outcomes of the spectrum management
Combining Spot and Futures Markets: A Hybrid Market Approach to Dynamic Spectrum Access
Dynamic spectrum access is a new paradigm of secondary spectrum utilization
and sharing. It allows unlicensed secondary users (SUs) to exploit
opportunistically the under-utilized licensed spectrum. Market mechanism is a
widely-used promising means to regulate the consuming behaviours of users and,
hence, achieves the efficient allocation and consumption of limited resources.
In this paper, we propose and study a hybrid secondary spectrum market
consisting of both the futures market and the spot market, in which SUs
(buyers) purchase under-utilized licensed spectrum from a spectrum regulator,
either through predefined contracts via the futures market, or through spot
transactions via the spot market. We focus on the optimal spectrum allocation
among SUs in an exogenous hybrid market that maximizes the secondary spectrum
utilization efficiency. The problem is challenging due to the stochasticity and
asymmetry of network information. To solve this problem, we first derive an
off-line optimal allocation policy that maximizes the ex-ante expected spectrum
utilization efficiency based on the stochastic distribution of network
information. We then propose an on-line VickreyCClarkeCGroves (VCG) auction
that determines the real-time allocation and pricing of every spectrum based on
the realized network information and the pre-derived off-line policy. We
further show that with the spatial frequency reuse, the proposed VCG auction is
NP-hard; hence, it is not suitable for on-line implementation, especially in a
large-scale market. To this end, we propose a heuristics approach based on an
on-line VCG-like mechanism with polynomial-time complexity, and further
characterize the corresponding performance loss bound analytically. We finally
provide extensive numerical results to evaluate the performance of the proposed
solutions.Comment: This manuscript is the complete technical report for the journal
version published in INFORMS Operations Researc
A Survey on Dynamic Spectrum Sharing Using Game Theory in Cognitive Radio Networks
Due to the tremendous increase in wireless data traffic, a usable radio spectrum is quickly being depleted. Current Fixed Spectrum Allocation (FSA) strategy give rise to the problem of spectrum scarcity and underutilization. Cognitive Radio (CR) is proposed as a new wireless paradigm to overcome the spectrum underutilization problem. CR is a promising technology which for future wireless communications. CRs can change its operating parameters intelligently in real time to account for dynamic changes in a wireless environment. CR enables a technique called Dynamic Spectrum Allocation (DSA) where the users are able to access unlicensed bands opportunistically. Since idle spectrum from PU is a valuable commodity, many cognitive users will be competing for it simultaneously. Therefore, there arises competition among the users. Users may be only concerned about maximizing their own benefits by behaving rationally and selfishly. Thus spectrum allocation problem falls under NP-hard complex based on its complexity to solve. Out of several solution approaches, Game theory is found to be an efficient mathematical tool since it deals with solving the conflicts among the users. This survey is aimed at providing a comprehensive overview on dynamic spectrum allocation using game theory
Vehicle as a Service (VaaS): Leverage Vehicles to Build Service Networks and Capabilities for Smart Cities
Smart cities demand resources for rich immersive sensing, ubiquitous
communications, powerful computing, large storage, and high intelligence
(SCCSI) to support various kinds of applications, such as public safety,
connected and autonomous driving, smart and connected health, and smart living.
At the same time, it is widely recognized that vehicles such as autonomous
cars, equipped with significantly powerful SCCSI capabilities, will become
ubiquitous in future smart cities. By observing the convergence of these two
trends, this article advocates the use of vehicles to build a cost-effective
service network, called the Vehicle as a Service (VaaS) paradigm, where
vehicles empowered with SCCSI capability form a web of mobile servers and
communicators to provide SCCSI services in smart cities. Towards this
direction, we first examine the potential use cases in smart cities and
possible upgrades required for the transition from traditional vehicular ad hoc
networks (VANETs) to VaaS. Then, we will introduce the system architecture of
the VaaS paradigm and discuss how it can provide SCCSI services in future smart
cities, respectively. At last, we identify the open problems of this paradigm
and future research directions, including architectural design, service
provisioning, incentive design, and security & privacy. We expect that this
paper paves the way towards developing a cost-effective and sustainable
approach for building smart cities.Comment: 32 pages, 11 figure
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Game theory for dynamic spectrum sharing cognitive radio
This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel University on 21 June 2010.âGame Theoryâ is the formal study of conflict and cooperation. The theory is based on a set of tools that have been developed in order to assist with the modelling and analysis of individual, independent decision makers. These actions potentially affect any decisions, which are made by other competitors. Therefore, it is well suited and capable of addressing the various issues linked to wireless communications. This work presents a Green Game-Based Hybrid Vertical Handover Model. The model is used for heterogeneous wireless networks, which combines both dynamic (Received Signal Strength and Node Mobility) and static (Cost, Power Consumption and Bandwidth) factors. These factors control the handover decision process; whereby the mechanism successfully eliminates any unnecessary handovers, reduces delay and overall number of handovers to 50% less and 70% less dropped packets and saves 50% more energy in comparison to other mechanisms. A novel Game-Based Multi-Interface Fast-Handover MIPv6 protocol is introduced in this thesis as an extension to the Multi-Interface Fast-handover MIPv6 protocol. The protocol works when the mobile node has more than one wireless interface. The protocol controls the handover decision process by deciding whether a handover is necessary and helps the node to choose the right access point at the right time. In addition, the protocol switches the mobile nodes interfaces âONâ and âOFFâ when needed to control the mobile nodeâs energy consumption and eliminate power lost of adding another interface. The protocol successfully reduces the number of handovers to 70%, 90% less dropped packets, 40% more received packets and acknowledgments and 85% less end-to-end delay in comparison to other Protocols. Furthermore, the thesis adapts a novel combination of both game and auction theory in dynamic resource allocation and price-power-based routing in wireless Ad-Hoc networks. Under auction schemes, destinations nodes bid the information data to access to the data stored in the server node. The server will allocate the data to the winner who values it most. Once the data has been allocated to the winner, another mechanism for dynamic routing is adopted. The routing mechanism is based on the source-destination cooperation, power consumption and source-compensation to the intermediate nodes. The mechanism dramatically increases the sellerâs revenue to 50% more when compared to random allocation scheme and briefly evaluates the reliability of predefined route with respect to data prices, source and destination cooperation for different network settings. Last but not least, this thesis adjusts an adaptive competitive second-price pay-to-bid sealed auction game and a reputation-based game. This solves the fairness problems associated with spectrum sharing amongst one primary user and a large number of secondary users in a cognitive radio environment. The proposed games create a competition between the bidders and offers better revenue to the players in terms of fairness to more than 60% in certain scenarios. The proposed game could reach the maximum total profit for both primary and secondary users with better fairness; this is illustrated through numerical results
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