We considered a single hop ad-hoc network consisting of N source-destination pairs. Each transmitter is endowed with a finite buffer and accepts packets from a Poisson distributed arrival process. The channel is described by a Markov chain. We investigate distributed algorithms for joint admission control, rate and power allocation aiming at maximizing the individual or the global throughput defined as the average information rate successfully received. The decisions are based on the statistical knowledge of the channel and buffer states of the other communication pairs and on the exact knowledge of their own channel and buffer states. The problems are formulated as a cooperative and noncooperative games and reduced to the mathematical framework of the variational inequalities problems. The proposed algorithms provide sizable improvements with respect to straightforward extension of decentralized algorithms for multiple access channels to ad hoc networks.
We considered a single hop ad-hoc network consisting of N source-destination pairs. Each transmitter is endowed with a finite buffer and accepts packets from a Poisson distributed arrival process. The channel is described by a Markov chain. We investigate distributed algorithms for joint admission control, rate and power allocation aiming at maximizing the individual or the global throughput defined as the average information rate successfully received. The decisions are based on the statistical knowledge of the channel and buffer states of the other communication pairs and on the exact knowledge of their own channel and buffer states. The problems are formulated as a cooperative and noncooperative games and reduced to the mathematical framework of the variational inequalities problems. The proposed algorithms provide sizable improvements with respect to straightforward extension of decentralized algorithms for multiple access channels to ad hoc networks.
