Data networks
Wireless Networks - Special issue transmitter power control
ICDCS '06 Proceedings of the 26th IEEE International Conference on Distributed Computing Systems
Proceedings of the 2nd international conference on Performance evaluation methodologies and tools
Stochastic learning solution for distributed discrete power control game in wireless data networks
IEEE/ACM Transactions on Networking (TON)
THE ALOHA SYSTEM: another alternative for computer communications
AFIPS '70 (Fall) Proceedings of the November 17-19, 1970, fall joint computer conference
A survey on networking games in telecommunications
Computers and Operations Research
Fixed-rate equilibrium in wireless collision channels
NET-COOP'07 Proceedings of the 1st EuroFGI international conference on Network control and optimization
Correlated equilibrium in access control for wireless communications
NETWORKING'06 Proceedings of the 5th international IFIP-TC6 conference on Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communications Systems
Slotted aloha with priorities and random power
NETWORKING'05 Proceedings of the 4th IFIP-TC6 international conference on Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communication Systems
IEEE Transactions on Wireless Communications
Achieving energy efficient equilibrium in power diversity-enabled collision channels
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies
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We consider finite number of users, with infinite buffer storage, sharing a single channel using the aloha medium access protocol. This is an interesting example of a non saturated collision channel. We investigate the uplink case of a cellular system where each user will select a desired throughput. The users then participate in a non cooperative game wherein they adjust their transmit rate to attain their desired throughput. We show that this game, in contrast to the saturated case, either has no Nash Equilibrium or has infinitely many Nash Equilibria. Further, we show that the region of NE coincides with an appropriate 'stability region'. We also discuss the efficiency of the equilibria in term of energy consumption and congestion rate. Next, we propose two learning algorithms using a stochastic iterative procedure that converges to the best Nash equilibrium. For instance, the first one needs partial information (transmit rates of other users during the last slot) whereas the second is an information less and fully distributed scheme. We approximate the control iterations by an equivalent ordinary differential equation in order to prove that the proposed stochastic learning algorithm converges to a Nash equilibrium even in the absence of any coordination or extra information. Extensive numerical examples and simulations are provided to validate our results.