UAV Assisted BS Sleep Strategy for Green Communication

The evolving mobile communication technology is constantly striving to meet the growing demands for higher transmission rate, greater connection density, and lower end-to-end latency. However, the concomitant multi-fold increase in energy consumption leads to a severe loss of profit for operators and a great challenge for global climate change. To enable green communication, we propose a novel unmanned aerial vehicle (UAV) assisted ground base station (GBS) sleep network architecture, in which most of the communication components of the GBSs with low traffic are shut down, and meanwhile the UAVs are employed as aerial base stations (ABSs) to compensate for the service loss of the sleep GBSs. To further explore the strengths of the proposed architecture, we formulate a joint optimization problem of GBS sleep strategy, ABS trajectory, and ABS transmission power, with the goal to minimize the system energy consumption. For solving the formulated problem, we first relax the integer variables and design an iterative algorithm based on the block coordinate descent (BCD) and sequential convex approximation (SCA) techniques. Then, the iterative algorithm is embedded into the branch and bound (B&B) architecture to get the final mixed integer solution. Considering the high complexity of the B&B algorithm, we especially propose the external polygon contraction algorithm (EPCA) to drastically reduce the computation time for the delay sensitive service. Numerical simulation results demonstrate that the B&B based algorithm is superior to other comparison schemes and the EPCA significantly degrades the computation time with acceptable performance.