A Joint Optimization on Cross-Layer for mmWave Wireless Network

With the severe spectrum shortage in conventional cellular networks, millimeter-wave (mmWave) technology has been proposed and is expected to be used in small cells to meet the increase spectrum efficiency, especially for those small cells are deployed with high density and forming as a multi-hop backhaul structure different from conventional schemes with priori given routes, a cross-layer optimization model aiming at maximizing the energy efficiency while taking into account both route selection and resource allocation. This paper decomposes the original problem into two sub-problems: resource allocation sub-problem at the link-physical layer and route selection sub-problem at the network layer. To reflect the interplay property between these two problems, we further propose two joint optimization strategies. The first is using genetic algorithm (GA) for resource allocation with given routes and using linear programming for routes selection with given resource allocation. The second is using the linear programming to evaluate the fitness of each individual in the GA. The simulation results show our solution can efficiently scale with the energy and spectrum efficiency and properly route the traffic without overloading any one of the base stations.