A neural approach to adaptive MAC protocols for wireless LANs

An adaptive MAC protocol for distributed wireless LANs, capable of operating efficiently under bursty traffic conditions, is introduced. According to the proposed protocol, the mobile station that is granted permission to transmit is selected by means of a neural-based algorithm. The neural-based algorithm takes into account the network feedback information in order to update the choice probability of each mobile station. The proposed protocol is compared via simulation to TDMA and IEEE 802.11 and is shown to exhibit superior performance under bursty traffic conditions even when the network feedback is noisy.