Minimizing electromagnetic pollution and power consumption in green heterogeneous small cell network deployment

An enormously increasing number of mobile communications devices and IoT sensors have driven rapid advance in wireless and cellular network technologies. Owing to limited energy resources, 5G technology has been expected to be designed as a 'green' network system. To achieve the requirement of future 'green' 5G networks to serve a huge number of mobile devices, this work investigates the problem of deployment and sleep control of a 'green' heterogeneous cellular network along a highway composed of base stations (BSs), legacy relay stations (RSs), and small cells (SCs), with two objectives: minimizing the energy consumption to decrease the impact of limited energy; as well as minimizing the electromagnet pollution from radiation of the three device types to avoid the potential harm to creatures. For decision variables, the deployment and sleep control of legacy RSs and SCs affect the total power consumption, and their coverage affects the total electromagnet pollution. First, this work creates a mathematical model for the optimization problem, and then proposes a hybrid algorithm of genetic algorithm (GA) and differential evolution (DE) with three local search operators to solve the problem, in which GA and DE can effectively handle discrete and continues decision variables, respectively. Simulation of the concerned green cellular networks verifies performance of the proposed algorithm.