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85
Competitive design of multiuser MIMO systems based on game theory: A unified view
- IEEE Journal on Selected Areas in Communications
, 2008
"... Abstract—This paper considers the noncooperative maximization of mutual information in the Gaussian interference channel in a fully distributed fashion via game theory. This problem has been studied in a number of papers during the past decade for the case of frequency-selective channels. A variety ..."
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Cited by 60 (5 self)
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Abstract—This paper considers the noncooperative maximization of mutual information in the Gaussian interference channel in a fully distributed fashion via game theory. This problem has been studied in a number of papers during the past decade for the case of frequency-selective channels. A variety of conditions guaranteeing the uniqueness of the Nash Equilibrium (NE) and convergence of many different distributed algorithms have been derived. In this paper we provide a unified view of the state-ofthe-art results, showing that most of the techniques proposed in the literature to study the game, even though apparently different, can be unified using our recent interpretation of the waterfilling operator as a projection onto a proper polyhedral set. Based on this interpretation, we then provide a mathematical framework, useful to derive a unified set of sufficient conditions guaranteeing the uniqueness of the NE and the global convergence of waterfilling based asynchronous distributed algorithms. The proposed mathematical framework is also instrumental to study the extension of the game to the more general MIMO case, for which only few results are available in the current literature. The resulting algorithm is, similarly to the frequency-selective case, an iterative asynchronous MIMO waterfilling algorithm. The proof of convergence hinges again on the interpretation of the MIMO waterfilling as a matrix projection, which is the natural generalization of our results obtained for the waterfilling mapping in the frequency-selective case. Index Terms—Game Theory, MIMO Gaussian interference channel, Nash equilibrium, totally asynchronous algorithms, waterfilling. I.
Optimal resource allocation for MIMO ad hoc cognitive radio networks
- in Proc. 46th Annu. Allerton Conf. Commun., Control, Comput
, 2008
"... Abstract—Maximization of the weighted sum-rate of secondary users (SUs) possibly equipped with multiantenna transmitters and receivers is considered in the context of cognitive radio (CR) net-works with coexisting primary users (PUs). The total interference power received at the primary receiver is ..."
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Cited by 39 (0 self)
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Abstract—Maximization of the weighted sum-rate of secondary users (SUs) possibly equipped with multiantenna transmitters and receivers is considered in the context of cognitive radio (CR) net-works with coexisting primary users (PUs). The total interference power received at the primary receiver is constrained to main-tain reliable communication for the PU. An interference channel configuration is considered for ad hoc networking, where the re-ceivers treat the interference from undesired transmitters as noise. Without the CR constraint, a convergent distributed algorithm is developed to obtain (at least) a locally optimal solution. With the CR constraint, a semidistributed algorithm is introduced. An al-ternative centralized algorithm based on geometric programming and network duality is also developed. Numerical results show the efficacy of the proposed algorithms. The novel approach is flexible to accommodate modifications aiming at interference alignment. However, the stand-alone weighted sum-rate optimal schemes pro-posed here have merits over interference-alignment alternatives es-pecially for practical SNR values. Index Terms—Ad hoc network, cognitive radio, interference net-work, MIMO, optimization. I.
Linear Transceiver Design for Interference Alignment: Complexity and Computation,” Available on arxiv:1009.3481
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Decomposition by partial linearization: Parallel optimization of multiuser systems
- IEEE Trans. on Signal Processing
, 2014
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MIMO cognitive radio: A game theoretical approach
- in Proc. Workshop Signal Process. Adv. Wireless Commun
, 2008
"... Abstract—The concept of cognitive radio (CR) has recently re-ceived great attention from the research community as a promising paradigm to achieve efficient use of the frequency resource by al-lowing the coexistence of licensed (primary) and unlicensed (sec-ondary) users in the same bandwidth. In th ..."
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Cited by 23 (3 self)
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Abstract—The concept of cognitive radio (CR) has recently re-ceived great attention from the research community as a promising paradigm to achieve efficient use of the frequency resource by al-lowing the coexistence of licensed (primary) and unlicensed (sec-ondary) users in the same bandwidth. In this paper we propose and analyze a totally decentralized approach, based on game theory, to design cognitive MIMO transceivers, who compete with each other to maximize their information rate. The formulation incor-porates constraints on the transmit power as well as null and/or soft shaping constraints on the transmit covariance matrix, so that the interference generated by secondary users be confined within the temperature-interference limit required by the primary users. We provide a unified set of conditions that guarantee the unique-ness and global asymptotic stability of the Nash equilibrium of all the proposed games through totally distributed and asynchronous algorithms. Interestingly, the proposed algorithms overcome the main drawback of classical waterfilling based algorithms—the vi-olation of the temperature-interference limit—and they have the desired features required for CR applications, such as low-com-plexity, distributed implementation, robustness against missing or outdated updates of the users, and fast convergence behavior. Index Terms—Cognitive radio, game theory, interference con-straints, MIMO Gaussian interference channel, Nash equilibrium, totally asynchronous distributed algorithms.
Distributed Dynamic Pricing for MIMO Interfering Multiuser Systems: A Unified Approach
"... Abstract—Wireless networks are composed of many users that usually have conflicting objectives and generate interference to each other. The system design is typically formulated as the optimization of the weighted sum of the users ’ utility functions. In an attempt to obtain distributed algorithms i ..."
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Cited by 17 (5 self)
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Abstract—Wireless networks are composed of many users that usually have conflicting objectives and generate interference to each other. The system design is typically formulated as the optimization of the weighted sum of the users ’ utility functions. In an attempt to obtain distributed algorithms in the case this sum is nonconvex, researchers have proposed pricing mechanisms which however are based on heuristics and valid only for a restricted class of problems. In this paper we propose a general framework for the distributed optimization of the nonconvex sum-utility function. Our main contributions are: i) the derivation for the first time of a general dynamic pricing mechanism, ii) a framework that can be easily particularized to well-known applications, giving rise to very efficient practical algorithms that outperform existing methods; and iii) the solution to the currently open problem of social optimization for MIMO multiuser systems. I.
On the Nash equilibria in decentralized parallel interference channels
- in IEEE Workshop on Game Theory and Resource Allocation for 4G
, 2011
"... Abstract—In this paper, the 2-dimensional decentralized parallel interference channel (IC) with 2 transmitter-receiver pairs is modelled as a non-cooperative static game. Each transmitter is assumed to be a fully rational entity with complete information on the game, aiming to maximize its own indiv ..."
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Cited by 14 (11 self)
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Abstract—In this paper, the 2-dimensional decentralized parallel interference channel (IC) with 2 transmitter-receiver pairs is modelled as a non-cooperative static game. Each transmitter is assumed to be a fully rational entity with complete information on the game, aiming to maximize its own individual spectral efficiency by tuning its own power allocation (PA) vector. Two scenarios are analysed. First, we consider that transmitters can split their transmit power between both dimensions (PA game). Second, we consider that each transmitter is limited to use only one dimension (channel selection CS game). In the first scenario, the game might have either one or three NE in pure strategies (PS). However, two or infinitely many NE in PS might also be observed with zero probability. In the second scenario, there always exists either one or two NE in PS. Using Monte-Carlo simulations, we show that in both games there always exists a non-zero probability of observing more than one NE. More interestingly, we show that the highest and lowest network spectral efficiency at any of the NE in the CS game are always higher than the ones in the PA.
Joint sensing and power allocation in nonconvex cognitive radio games: Quasi-nash equilibria
- in Proc. of the 17th International Conference on Digital Signal Processing (DSP2011), Corfu
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Game theoretic solutions for precoding strategies over interference channels
- in Proc. IEEE GLOBECOM
, 2008
"... Abstract—In this paper, precoding strategies over interference channels are analyzed from a game-theoretic perspective. The Nash equilibrium and Nash bargaining solutions of precoding matrices, as the optimal precoding strategies in non-cooperative and cooperative cases, respectively, are derived fo ..."
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Cited by 9 (5 self)
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Abstract—In this paper, precoding strategies over interference channels are analyzed from a game-theoretic perspective. The Nash equilibrium and Nash bargaining solutions of precoding matrices, as the optimal precoding strategies in non-cooperative and cooperative cases, respectively, are derived for a two-player game over both flat fading and frequency selective channels. It is shown that the non-cooperative and cooperative solutions of precoding matrices are the same over multiple-input single-output (MISO) flat fading interference channels under a total power constraint. The solution in flat fading channel case is also extended to an M-player case.
Spectrum sharing games on the interference channel
- in Proc. IEEE Intl. Conf. on Game Theory for Networks (Gamenets
, 2010
"... Abstract—In this paper, we address the problem of spectrum sharing where competitive operators coexist in the same frequency band. First, we model this problem as a strategic non-cooperative game where operators simultaneously share the spectrum according to the Nash Equilibrium (N.E). Given a set o ..."
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Cited by 9 (4 self)
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Abstract—In this paper, we address the problem of spectrum sharing where competitive operators coexist in the same frequency band. First, we model this problem as a strategic non-cooperative game where operators simultaneously share the spectrum according to the Nash Equilibrium (N.E). Given a set of channel realizations, several Nash equilibria exist which renders the outcome of the game unpredictable. For this reason, the spectrum sharing problem is reformulated as a Stackelberg game where the first operator is already being deployed and the secondary operator follows next. The Stackelberg equilibrium (S.E) is reached where the best response of the secondary operator is taken into account upon maximizing the primary operator’s utility function. Finally, we assess the goodness of the proposed distributed approach by comparing its performance to the centralized approach. I.
