Results 1  10
of
48
On the Base Station Selection and Base Station Sharing in SelfConfiguring Networks
"... We model the interaction of several radio devices aiming to obtain wireless connectivity by using a set of base stations (BS) as a noncooperative game. Each radio device aims to maximize its own spectral efficiency (SE) in two different scenarios: First, we let each player to use a unique BS (BS se ..."
Abstract

Cited by 13 (11 self)
 Add to MetaCart
(Show Context)
We model the interaction of several radio devices aiming to obtain wireless connectivity by using a set of base stations (BS) as a noncooperative game. Each radio device aims to maximize its own spectral efficiency (SE) in two different scenarios: First, we let each player to use a unique BS (BS selection) and second, we let them to simultaneously use several BSs (BS Sharing). In both cases, we show that the resulting game is an exact potential game. We found that the BS selection game posses multiple Nash equilibria (NE) while the BS sharing game posses a unique one. We provide fully decentralized algorithms which always converge to a NE in both games. We analyze the price of anarchy and the price of stability for the case of BS selection. Finally, we observed that depending on the number of transmitters, the BS selection technique might provide a better global performance (network spectral efficiency) than BS sharing, which suggests the existence of a Braess type paradox.
A Packet DroppingBased Incentive Mechanism for M/M/1 Queues with Selfish Users
"... Abstract—We study a novel game theoretic incentive mechanism design problem for network congestion control in the context of selfish users sending data through a single storeandforward router (a.k.a. “server ” in this work). The scenario is modeled as an M/M/1 queueing game with each user (a.k.a. “ ..."
Abstract

Cited by 9 (1 self)
 Add to MetaCart
(Show Context)
Abstract—We study a novel game theoretic incentive mechanism design problem for network congestion control in the context of selfish users sending data through a single storeandforward router (a.k.a. “server ” in this work). The scenario is modeled as an M/M/1 queueing game with each user (a.k.a. “player”) aiming to optimize a tradeoff between throughput and delay in a selfish distributed manner. We first show that the original game has an inefficient unique Nash Equilibrium (NE). In order to improve the outcome efficiency, we propose an incentivizing packet dropping scheme that can be easily implemented at the server. We then show that if the packet dropping scheme is a function of the sum of arrival rates, we have a modified M/M/1 queueing game that is an ordinal potential game with a unique NE. In particular, for a linear packet dropping scheme, which is similar to the Random Early Detection (RED) algorithm used with TCP, we show that there exists a unique Nash Equilibrium. For this scheme, the social welfare (expressed either as the summation of utilities of all players or log summation of utilities of all players) at the equilibrium point can be arbitrarily close to the social welfare at the global optimal point. Finally, we show that the simple best response dynamic converges to this unique efficient Nash Equilibrium. I.
HOW CAN IGNORANT BUT PATIENT COGNITIVE TERMINALS LEARN THEIR STRATEGY AND UTILITY?
"... This paper aims to contribute to bridge the gap between existing theoretical results in distributed radio resource allocation policies based on equilibria in games (assuming complete information and rational players) and practical design of signal processing algorithms for selfconfiguring wireless ..."
Abstract

Cited by 7 (5 self)
 Add to MetaCart
(Show Context)
This paper aims to contribute to bridge the gap between existing theoretical results in distributed radio resource allocation policies based on equilibria in games (assuming complete information and rational players) and practical design of signal processing algorithms for selfconfiguring wireless networks. For this purpose, the framework of learning theory in games is exploited. Here, a new learning algorithm based on mild information assumptions at the transmitters is presented. This algorithm possesses attractive convergence properties not available for standard reinforcement learning algorithms and in addition, it allows each transmitter to learn both its optimal strategy and the values of its expected utility for all its actions. A detailed convergence analysis is conducted. In particular, a framework for studying heterogeneous wireless networks where transmitters do not learn at the same rate is provided. The proposed algorithm, which can be applied to any wireless network verifying the information assumptions stated, is applied to the case of multiple access channels in order to provide some numerical results. 1.
Dynamic power allocation games in parallel multiple access channels
 in ValueTools ’11: ACM Proceedings of the 5th International Conference on Performance Evaluation Methodologies and Tools
, 2011
"... Abstract. We analyze the distributed power allocation problem in parallel multiple access channels (MAC) by studying an associated noncooperative game which admits an exact potential function. Even though games of this type have been the subject of considerable study in the literature [1–4], we fin ..."
Abstract

Cited by 7 (6 self)
 Add to MetaCart
(Show Context)
Abstract. We analyze the distributed power allocation problem in parallel multiple access channels (MAC) by studying an associated noncooperative game which admits an exact potential function. Even though games of this type have been the subject of considerable study in the literature [1–4], we find that the sufficient conditions which ensure uniqueness of Nash equilibrium points typically do not hold in this context. Nonetheless, we show that the parallel MAC game admits a unique equilibrium almost surely, thus establishing an important class of counterexamples where these sufficient conditions are not necessary. Furthermore, if the network’s users employ a distributed learning scheme based on the replicator dynamics, we show that they converge to equilibrium from almost any initial condition, even though users only have local information at their disposal. 1.
A Bayesian GameTheoretic Approach for Distributed Resource Allocation in Fading Multiple Access Channels
"... A Bayesian gametheoretic model is developed to design and analyze the resource allocation problem in Kuser fading multiple access channels (MAC), where users are assumed to selfishly maximize their average achievable rates with incomplete information about the fading channel gains. In such a game ..."
Abstract

Cited by 6 (4 self)
 Add to MetaCart
(Show Context)
A Bayesian gametheoretic model is developed to design and analyze the resource allocation problem in Kuser fading multiple access channels (MAC), where users are assumed to selfishly maximize their average achievable rates with incomplete information about the fading channel gains. In such a gametheoretic study, the central question is whether a Bayesian equilibrium exists, and if so, whether the network operates efficiently at the equilibrium point. We prove that there exists exactly one Bayesian equilibrium in our game. Furthermore, we study the network sumrate maximization problem by assuming that users coordinate to the symmetric strategy profile. This result also serves as an upper bound for the Bayesian equilibrium. Finally, simulation results are provided to show the network efficiency at the unique Bayesian equilibrium, and compare it with other strategies.
1 Satisfaction Equilibrium: A General Framework for QoS Provisioning in SelfConfiguring Networks
"... Abstract—This paper is concerned with the concept of equilibrium and quality of service (QoS) provisioning in selfconfiguring wireless networks with noncooperative radio devices (RD). In contrast with the Nash equilibrium (NE), where RDs are interested in selfishly maximizing its QoS, we present a ..."
Abstract

Cited by 5 (3 self)
 Add to MetaCart
(Show Context)
Abstract—This paper is concerned with the concept of equilibrium and quality of service (QoS) provisioning in selfconfiguring wireless networks with noncooperative radio devices (RD). In contrast with the Nash equilibrium (NE), where RDs are interested in selfishly maximizing its QoS, we present a concept of equilibrium, named satisfaction equilibrium (SE), where RDs are interested only in guaranteing a minimum QoS. We provide the conditions for the existence and the uniqueness of the SE. Later, in order to provide an equilibrium selection framework for the SE, we introduce the concept of effort or cost of satisfaction, for instance, in terms of transmit power levels, constellation sizes, etc. Using the idea of effort, the set of efficient SE (ESE) is defined. At the ESE, transmitters satisfy their minimum QoS incurring in the lowest effort. We prove that contrary to the (generalized) NE, at least one ESE always exists whenever the network is able to simultaneously support the individual QoS requests. Finally, we provide a fully decentralized algorithm to allow selfconfiguring networks to converge to one of the SE relying only on local information. I.
1 Distributed Power Splitting for SWIPT in Relay Interference Channels using Game Theory
"... ar ..."
(Show Context)