21 research outputs found
Distributed Power Allocation with Rate Constraints in Gaussian Parallel Interference Channels
This paper considers the minimization of transmit power in Gaussian parallel
interference channels, subject to a rate constraint for each user. To derive
decentralized solutions that do not require any cooperation among the users, we
formulate this power control problem as a (generalized) Nash equilibrium game.
We obtain sufficient conditions that guarantee the existence and nonemptiness
of the solution set to our problem. Then, to compute the solutions of the game,
we propose two distributed algorithms based on the single user waterfilling
solution: The \emph{sequential} and the \emph{simultaneous} iterative
waterfilling algorithms, wherein the users update their own strategies
sequentially and simultaneously, respectively. We derive a unified set of
sufficient conditions that guarantee the uniqueness of the solution and global
convergence of both algorithms. Our results are applicable to all practical
distributed multipoint-to-multipoint interference systems, either wired or
wireless, where a quality of service in terms of information rate must be
guaranteed for each link.Comment: Paper submitted to IEEE Transactions on Information Theory, February
17, 2007. Revised January 11, 200
Distributed cognitive radio systems with temperature-interference constraints and overlay scheme
Cognitive radio represents a promising paradigm to further increase transmission rates in wireless networks, as well as to facilitate the deployment of self-organized networks such as femtocells. Within this framework, secondary users (SU) may exploit the channel under the premise to maintain the quality of service (QoS) on primary users (PU) above a certain level. To achieve this goal, we present a noncooperative game where SU maximize their transmission rates, and may act as well as relays of the PU in order to hold their perceived QoS above the given threshold. In the paper, we analyze the properties of the game within the theory of variational inequalities, and provide an algorithm that converges to one Nash Equilibrium of the game. Finally, we present some simulations and compare the algorithm with another method that does not consider SU acting as relays
Decomposable Penalty Method for Generalized Game Problems with Joint Constraints
We consider an extension of a noncooperative game problem where players have
joint binding constraints. In this case, justification of a generalized
equilibrium point needs a reasonable mechanism for attaining this state. We
suggest to combine a penalty method together with shares allocation of
right-hand sides, which replaces the initial problem with a sequence of the
usual Nash equilibrium problems together with an upper level variational
inequality as a master problem. We show convergence of solutions of these
auxiliary penalized problems to a solution of the initial game problem under
weak coercivity conditions.Comment: 13 page
Competitive Spectrum Management with Incomplete Information
This paper studies an interference interaction (game) between selfish and
independent wireless communication systems in the same frequency band. Each
system (player) has incomplete information about the other player's channel
conditions. A trivial Nash equilibrium point in this game is where players
mutually full spread (FS) their transmit spectrum and interfere with each
other. This point may lead to poor spectrum utilization from a global network
point of view and even for each user individually.
In this paper, we provide a closed form expression for a non pure-FS
epsilon-Nash equilibrium point; i.e., an equilibrium point where players choose
FDM for some channel realizations and FS for the others. We show that operating
in this non pure-FS epsilon-Nash equilibrium point increases each user's
throughput and therefore improves the spectrum utilization, and demonstrate
that this performance gain can be substantial. Finally, important insights are
provided into the behaviour of selfish and rational wireless users as a
function of the channel parameters such as fading probabilities, the
interference-to-signal ratio
Quality-Of-Service Provisioning in Decentralized Networks: A Satisfaction Equilibrium Approach
This paper introduces a particular game formulation and its corresponding
notion of equilibrium, namely the satisfaction form (SF) and the satisfaction
equilibrium (SE). A game in SF models the case where players are uniquely
interested in the satisfaction of some individual performance constraints,
instead of individual performance optimization. Under this formulation, the
notion of equilibrium corresponds to the situation where all players can
simultaneously satisfy their individual constraints. The notion of SE, models
the problem of QoS provisioning in decentralized self-configuring networks.
Here, radio devices are satisfied if they are able to provide the requested
QoS. Within this framework, the concept of SE is formalized for both pure and
mixed strategies considering finite sets of players and actions. In both cases,
sufficient conditions for the existence and uniqueness of the SE are presented.
When multiple SE exist, we introduce the idea of effort or cost of satisfaction
and we propose a refinement of the SE, namely the efficient SE (ESE). At the
ESE, all players adopt the action which requires the lowest effort for
satisfaction. A learning method that allows radio devices to achieve a SE in
pure strategies in finite time and requiring only one-bit feedback is also
presented. Finally, a power control game in the interference channel is used to
highlight the advantages of modeling QoS problems following the notion of SE
rather than other equilibrium concepts, e.g., generalized Nash equilibrium.Comment: Article accepted for publication in IEEE Journal on Selected Topics
in Signal Processing, special issue in Game Theory in Signal Processing. 16
pages, 6 figure