Cross-layer optimal policies for stochastic reliable transmission in Wireless Sensor Networks

In Wireless Sensor Networks (WSNs), stochastic reliable transmission protocols, which improve reliability of the delivery process by transmitting redundant packets, have been proved to have advantage of energy efficiency over the retransmission one. But the burst and deep fading characteristic of the error prone wireless links in WSNs reduces the practicability of this kind of protocols. To solve this problem, a Markov Decision Process (MDP) based optimal scheduling algorithm is exploited in our work. Perfect channel state information (CSI) and cross-layer designs are combined artfully in the sequential decision process to make the protocol channel-adaptive. The objective of the optimization is to minimize the average energy consumption of the delivery process with constrained of desired delivery probability. The optimal policy which is proved to be monotone in accumulative successful probability and buffer state is computationally efficient and inexpensive to implement. Numerical examples are presented to evaluate the performance of the proposed strategy. The results demonstrate the superiority of our optimal policies over original scheme.