Invited Session Mon.2.MA 041

Monday, 13:15 - 14:45 h, Room: MA 041

Cluster 3: Complementarity & variational inequalities [...]

Game theoretic analysis and optimization for resource allocation in communication systems

 

Chair: Zhi-Quan (Tom) Luo

 

 

Monday, 13:15 - 13:40 h, Room: MA 041, Talk 1

Slawomir Stanczak
Progress and challenges in decentralized resource allocation optimization

 

Abstract:
This talk presents an overview of algorithmic solutions to optimization problems that naturally appear in the radio resource management for wireless networks. A wireless network is modeled as a weighted graph, in which pairs of nodes form communication links, while the weighted edges capture the interference effects between different links. The focus is on utility maximization approaches. We will show how primal-dual methods can provide quadratic convergence, while still allowing for efficient implementation in decentralized wireless networks. Given the limited and costly nature of wireless resources, decentralized algorithms are required to minimize the control message overhead for each iteration step. Therefore we present a distributed handshake scheme based on the use of so-called adjoint network to efficiently estimate iteration updates from some locally measurable quantities. Due to estimation errors and other distorting factors, the proposed algorithm has to be analyzed in a more general context of stochastic approximation.

 

 

Monday, 13:45 - 14:10 h, Room: MA 041, Talk 2

Zhi-Quan (Tom) Luo
Linear precoder optimization and base station selection for heterogeneous networks

Coauthors: Mingyi Hong, Razaviyayn Meisam, Sun Ruoyu

 

Abstract:
Consider the problem of weighted sum rate maximization in a MIMO
interference communicationnetwork. We propose to jointly optimize the users' linear procoders as well as their base station (BS) associations. This approach enables the users to avoid
congested BSs and can improve system performance as well as user
fairness. In this paper we first show that this joint optimization problem is NP-hard and thus is difficult to solve to global optimality. We also identify a special case (single antenna case) where the joint maximization of the minimum rate problem is solvable via an appropriate weighted bipartite matching for base station assignment and then a simple linear program for power allocation.
To find a locally optimal solution, we formulate the problem as a noncooperative game in which the users and the BSs act as players who autonomously optimize their own utility functions.
We then develop an algorithm that allows the players to distributedly reach the Nash Equilibrium (NE)
of the game. Moreover, we introduce a set of utility functions for the players and
show that every NE of the resulting game is a stationary
solution of the weighted sum rate maximization problem.

 

 

Monday, 14:15 - 14:40 h, Room: MA 041, Talk 3

Gesualdo Scutari
Monotone communication games

Coauthors: Francisco Facchinei, Jong-Shi Pang

 

Abstract:
In recent years, there has been a growing interest in the use of noncooperative games to model and solve many resource allocation problems in communications and networking, wherein the interaction among several agents is by no means negligible and centralized approaches are not suitable. In this talk we present a mathematical treatment of (generalized) Nash equilibrium (NE) problems based on the variational inequality approach. Our emphasis is on the design of distributed algorithms using best-response iterations along with their convergence properties. The proposed framework has many desirable new features: i) it can be applied to (monotone) games having no specific structure; ii) the algorithms proposed for computing a NE converge under mild conditions that do not imply the uniqueness of the equilibrium; and iii) in the presence of multiple NE, one can control the quality of the computed solution by guaranteeing convergence to the "best'' NE, according to some prescribed criterion, while keeping the distributed implementation of the algorithm. These are new features enlarge considerably the applicability and flexibility of game-theoretic models in wireless distributed networks.

 

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