Density-aware power allocation in mobile networks using edge computing

While the main concern in mobile networks was increasing network capacity and expanding coverage in the past, green operation have recently become a major concern. To conserve energy in mobile networks, we employ mobile edge computing to access real-time data and offload processing tasks to the edges for reducing complexity and latency. An edge cloud has a larger view of the network than a base station. Therefore, it can evaluate the probability of coverage by considering the density of base stations to enhance the overall system throughput while preventing coverage holes. This may enhance user experience and decrease response time in the network. We propose a density-adaptive power control algorithm that reduces energy consumption in an LTE network and improves the mean throughput. We show how power allocation and interference may affect system performance. The simulation results show that the proposed algorithm can reduce the energy wastage up to 67% in comparison with the basic model (without any power allocation model) and 28% in comparison with a recent work while the mean throughput can be improved by 22%.