An enhanced cooperative MAC protocol based on perceptron training

Cooperation among wireless nodes at the medium access control (MAC) layer has attracted a lot of research attention in recent years. Most of existing cooperative MAC protocols focus on the scenarios with static helpers (relay nodes). However, when the helpers are moving around, the source node may choose a leaving helper with out-of-date information, which could cause performance deterioration. Hence, an optimal helper should not only support a high transmission rate but also have a low mobility. It can be a challenging problem to distinguish such an optimal helper when there are moving helpers of various mobility. In this paper, we extend the cooperative MAC protocol in [1] by means of perceptron training, referred to as PTCoopMAC. Making use of the handshaking messages in the original CoopMAC protocol, PTCoopMAC collects history data on the signal strength of overheard packets. Then, PTCoopMAC applies the perceptron training technique to obtain a weight vector to examine the stability of the helpers. Extending the CoopTable, PTCoopMAC selects the optimal helper depending on the achievable data rate as well as the prediction on whether a helper is reliable. The simulations results well demonstrate the throughput improvement of PTCoopMAC and its robustness to high mobility of helper nodes.