Channel Allocation Scheme to Mitigate Interference in 5G Backhaul Wireless Mesh Networks

Fifth-generation (5G) is the next cellular generation and is expected to quench the growing thirst for taxing data rates and to enable the internet of things. The challenge for next-generation wireless networks is efficient channel management to meet the increasing bandwidth demand and transmission rate requirements. In this paper, we study the channel allocation problem for joint uplink/downlink non-orthogonal multiple access (NOMA) network, where the base station has the facility to allocate spectrum and power resources to a set of users. We propose a scheduling approach for 5G backhaul mesh networks based on the traffic demands in small cells that maximize the small cell utility. This scheduling approach is intended to work with any transmission scheme’s physical layer. We aim to jointly optimize the uplink/downlink channel assignment to maximize user fairness. Here the channel allocation problem is formulated as a traveling salesman problem (TSP) which is then associated with a many-to-many two-sided user channel allocation. We introduce a decreasing coefficient to the updating principle so that modified particle swarm optimization (MPSO) can be viewed as a standard stochastic approximation algorithm. A random velocity is added to improve exploration ability in order to balance exploration behavior and convergence rate with respect to different optimization problems. With these features base stations (BSs) guarantee the end-user’s quality of service by committing the necessary resources. This algorithm investigates the maximization of network capacity and the fairness among stations. The performance of the proposed scheme is evaluated through simulation in terms of throughput and spectral efficiency.