Elements of information theory
Elements of information theory
Stochastic approximation with two time scales
Systems & Control Letters
Actor-Critic--Type Learning Algorithms for Markov Decision Processes
SIAM Journal on Control and Optimization
SIAM Journal on Control and Optimization
Stochastic learning solution for distributed discrete power control game in wireless data networks
IEEE/ACM Transactions on Networking (TON)
The MIMO iterative waterfilling algorithm
IEEE Transactions on Signal Processing
On the base station selection and base station sharing in self-configuring networks
Proceedings of the Fourth International ICST Conference on Performance Evaluation Methodologies and Tools
Game Theory and Learning for Wireless Networks: Fundamentals and Applications
Game Theory and Learning for Wireless Networks: Fundamentals and Applications
IEEE Transactions on Signal Processing
Distributed Power Allocation With Rate Constraints in Gaussian Parallel Interference Channels
IEEE Transactions on Information Theory
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In this paper, we study the particular scenario where several transmitter-receiver pairs communicate subject to mutual interference due to the usage of the same frequency bands. In particular, we focus on the case of heterogeneous networks, where radio devices have different interests (utility functions), transmit configurations (sets of actions), as well as different signal processing and calculation capabilities. The underlying assumptions of this work are the followings: (i) the network is described by a set of states, for instance, the channel realization vector; (ii) radio devices are interested in their long-term average performance rather than instantaneous performance; (iii) each radio device is able to obtain a measure of its achieved performance at least once after updating its transmission configuration. Considering these conditions, we model the heterogenous network by a stochastic game. Our main contribution consists of a family of behavioral rules that allow radio devices to achieve an epsilon-Nash equilibrium of the corresponding stochastic game, namely a logit equilibrium. A thorough analysis of the convergence properties of these behavioral rules is presented. Finally, our approach is used in the context of a classical parallel interference channel in order to compare with existing results.