1,032 research outputs found
Spectrum Trading: An Abstracted Bibliography
This document contains a bibliographic list of major papers on spectrum
trading and their abstracts. The aim of the list is to offer researchers
entering this field a fast panorama of the current literature. The list is
continually updated on the webpage
\url{http://www.disp.uniroma2.it/users/naldi/Ricspt.html}. Omissions and papers
suggested for inclusion may be pointed out to the authors through e-mail
(\textit{[email protected]})
Matching Theory for Backhaul Management in Small Cell Networks with mmWave Capabilities
Designing cost-effective and scalable backhaul solutions is one of the main
challenges for emerging wireless small cell networks (SCNs). In this regard,
millimeter wave (mmW) communication technologies have recently emerged as an
attractive solution to realize the vision of a high-speed and reliable wireless
small cell backhaul network (SCBN). In this paper, a novel approach is proposed
for managing the spectral resources of a heterogeneous SCBN that can exploit
simultaneously mmW and conventional frequency bands via carrier aggregation. In
particular, a new SCBN model is proposed in which small cell base stations
(SCBSs) equipped with broadband fiber backhaul allocate their frequency
resources to SCBSs with wireless backhaul, by using aggregated bands. One
unique feature of the studied model is that it jointly accounts for both
wireless channel characteristics and economic factors during resource
allocation. The problem is then formulated as a one-to-many matching game and a
distributed algorithm is proposed to find a stable outcome of the game. The
convergence of the algorithm is proven and the properties of the resulting
matching are studied. Simulation results show that under the constraints of
wireless backhauling, the proposed approach achieves substantial performance
gains, reaching up to compared to a conventional best-effort approach.Comment: In Proc. of the IEEE International Conference on Communications
(ICC), Mobile and Wireless Networks Symposium, London, UK, June 201
Game-Theoretic Pricing and Selection with Fading Channels
We consider pricing and selection with fading channels in a Stackelberg game
framework. A channel server decides the channel prices and a client chooses
which channel to use based on the remote estimation quality. We prove the
existence of an optimal deterministic and Markovian policy for the client, and
show that the optimal policies of both the server and the client have threshold
structures when the time horizon is finite. Value iteration algorithm is
applied to obtain the optimal solutions for both the server and client, and
numerical simulations and examples are given to demonstrate the developed
result.Comment: 6 pages, 4 figures, accepted by the 2017 Asian Control Conferenc
Game theory for collaboration in future networks
Cooperative strategies have the great potential of improving network performance and spectrum utilization in future networking environments. This new paradigm in terms of network management, however, requires a novel design and analysis framework targeting a highly flexible networking solution with a distributed architecture. Game Theory is very suitable for this task, since it is a comprehensive mathematical tool for modeling the highly complex interactions among distributed and intelligent decision makers. In this way, the more convenient management policies for the diverse players (e.g. content providers, cloud providers, home providers, brokers, network providers or users) should be found to optimize the performance of the overall network infrastructure. The authors discuss in this chapter several Game Theory models/concepts that are highly relevant for enabling collaboration among the diverse players, using different ways to incentivize it, namely through pricing or reputation. In addition, the authors highlight several related open problems, such as the lack of proper models for dynamic and incomplete information games in this area.info:eu-repo/semantics/acceptedVersio
Incentive Mechanisms for Internet Congestion Management: Fixed-Budget Rebate versus Time-of-Day Pricing
Mobile data traffic has been steadily rising in the past years. This has
generated a significant interest in the deployment of incentive mechanisms to
reduce peak-time congestion. Typically, the design of these mechanisms requires
information about user demand and sensitivity to prices. Such information is
naturally imperfect. In this paper, we propose a \emph{fixed-budget rebate
mechanism} that gives each user a reward proportional to his percentage
contribution to the aggregate reduction in peak time demand. For comparison, we
also study a time-of-day pricing mechanism that gives each user a fixed reward
per unit reduction of his peak-time demand. To evaluate the two mechanisms, we
introduce a game-theoretic model that captures the \emph{public good} nature of
decongestion. For each mechanism, we demonstrate that the socially optimal
level of decongestion is achievable for a specific choice of the mechanism's
parameter. We then investigate how imperfect information about user demand
affects the mechanisms' effectiveness. From our results, the fixed-budget
rebate pricing is more robust when the users' sensitivity to congestion is
"sufficiently" convex. This feature of the fixed-budget rebate mechanism is
attractive for many situations of interest and is driven by its closed-loop
property, i.e., the unit reward decreases as the peak-time demand decreases.Comment: To appear in IEEE/ACM Transactions on Networkin
CSMA Local Area Networking under Dynamic Altruism
In this paper, we consider medium access control of local area networks
(LANs) under limited-information conditions as befits a distributed system.
Rather than assuming "by rule" conformance to a protocol designed to regulate
packet-flow rates (e.g., CSMA windowing), we begin with a non-cooperative game
framework and build a dynamic altruism term into the net utility. The effects
of altruism are analyzed at Nash equilibrium for both the ALOHA and CSMA
frameworks in the quasistationary (fictitious play) regime. We consider either
power or throughput based costs of networking, and the cases of identical or
heterogeneous (independent) users/players. In a numerical study we consider
diverse players, and we see that the effects of altruism for similar players
can be beneficial in the presence of significant congestion, but excessive
altruism may lead to underuse of the channel when demand is low
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