On the use of population-based incremental learning in the medium access control of broadcast communication systems

The Time Division Multiple Access protocol suffers from poor performance when the offered traffic is bursty. In this paper, an adaptive Time Division Multiple Access protocol, which is capable of operating efficiently under bursty traffic conditions, is introduced. According to the proposed protocol, the station which is granted permission to transmit at each time slot is selected by means of a variation of the population-based incremental learning (PBIL) algorithm. The choice probability of the selected station is updated by taking into account the network feedback information. In this way, the proposed protocol is always capable of being adapted to the sharp changes of the station´s traffic.