Reducing Hovering and Motion Energy Consumptions for UAV-enabled Collaborative Beamforming

Unmanned aerial vehicles (UAVs) Communications and networks are of paramount importance in the 5G/6G networks. However, how to deploy the limited on-board energy and restricted transmit power of the UAV so that enhancing the communication efficiency is still a key issue. In this work, we consider a UAV-enabled communication scenario that a set of UAVs perform a virtual antenna array (VAA) to communicate with different remote base stations (BSs) by using collaborative beamforming (CB). For achieving a better energy efficiency, we formulate a hovering and motion energy consumption multiobjective optimization problem (HMECMOP) of UAV-enable CB to simultaneously minimize the total hovering and motion energy consumptions of UAVs by jointly optimizing the positions, excitation current weights of UAVs and the order of communicating with different BSs. Then, we propose an improved multiobjective multi-verse optimizer (IMOMVO) to solve the formulated HMECMOP. IMOMVO uses the vertical and horizontal renewal strategy and nearest neighbor procedure (NNP) to deal with the complex solution space which contains continuous and discrete solutions, so that making the algorithm more suitable for solving the formulated optimization problem. Simulation results demonstrate that the proposed algorithm is effective for solving the HMECMOP and it has better performance than some other comparison algorithms.