Energy Efficient Routing for Wireless Mesh Networks with Directional Antennas: When Q-learning meets Ant systems

Energy Efficiency (EE) is a key performance metric to design future wireless networks. Since Directional Antennas (DAs) focus the transmission energy towards the destination, it has been shown as a cost-effective solution when used in a backhaul network. In this paper we propose a new joint optimization framework of energy consumption and throughput in backhaul Wireless Mesh Networks (WMNs) equipped with DAs. We first formulate the joint optimization problem as a Mixed Integer Linear Problem (MILP) using a weighted objective function of both the consumed energy and the throughput. Then, we propose to use the Ant-Q algorithm, a Reinforcement Learning (RL) based approach, to reduce the solution complexity and enhance its convergence. Considering a discrete power control scheme, we define a new routing scheme based on the Ant-Q heuristic to select jointly the transmission beam and the transmission power. Using ILOG Cplex to find the optimal solution and NS-3 to conduct extensive simulations, we show the effectiveness and the accuracy of the proposed routing algorithm. Moreover, we analyze the optimization tradeoff depending on the beamwidth, the network topology, the gateway position and the optimization weight factor.