Optimal Resource Allocation Policy for Multi-Rate Opportunistic Forwarding

Many opportunistic routing protocols for wireless multi-hop networks rely on a fixed channel rate and a fixed priority order to manage the access to the channel by the involved nodes. Thereby, the actual channel capacities in the network are not considered and the diversity of links is not fully exploited. Furthermore, the data buffer of the nodes is not taken into account. In this work, we consider a wireless multi-hop scenario consisting of multiple cooperative nodes within each hop that share channel resources and adapt their channel rates based on local channel knowledge. A Markov Decision Process (MDP) model is used to derive an optimal resource allocation policy that minimizes the number of required time slots to forward all data packets to the next hop. Furthermore, we propose a state approximation technique that limits the required number of states, but captures the most important features of the problem. Simulation results demonstrate that the proposed policy achieves throughput gains of up to 25% compared to a fixed order transmission policy and up to 49% compared to a unipath approach.