Considering the time delay and the energy consumption of terminal equipment caused by high-speed data transmission and calculation, a transmission scheme with equal power allocation in uplink was proposed. Firstly, based on collaborative properties of Augment Reality (AR) services, a system model for AR characteristics was established. Secondly, system frame structure was analyzed in detail, and the constraints to minimize total energy consumption of system were established. Finally, with the time delay and energy consumption constraints satisfied, a mathematical model of Mobile Edge Computing (MEC) resource optimization based on convex optimization was established to obtain an optimal communication and computing resource allocation scheme. Compared with user independent transmission scheme, the total energy consumption of the proposed scheme with a maximum time delay of 0.1 s and 0.15 s was both 14.6%. The simulation results show that under the same conditions, compared with the optimization scheme based on user independent transmission, the equal power MEC optimization scheme considering cooperative transmission between users can significantly reduce the total energy consumption of system.

To solve the coverage and capacity optimization problem of Self-Organizing Network (SON) in the 3rd Generation Partnership Project (3GPP), an active antenna down-tilt angle optimization method based on Particle Swarm Optimization (PSO) algorithm was proposed. First, the number of User Equipments (UE) served by evolved Node B (eNB) was determined, and the Reference Signal Received Power (RSRP) and position measured from the UE were obtained. Second, the Spectral Efficiency (SE) was regarded as the fitness function which defined by optimization goals. Then, down-tilt angle optimization was regarded as multidimensional optimization problem, and antenna down-tilt angle was regarded as the set of particles to resolve the optimal value by the PSO algorithm. Finally, the capacity and coverage self-optimization of Long Term Evolution (LTE) networks was achieved by adjusting down-tilt angle independently. By simulations, different objective functions made different optimization results. When the average spectrum efficiency was set as the optimization goal, the spectral efficiency of traditional golden section algorithm increased by 12.9% than primary settings, the spectral efficiency of PSO was increased by 22.5%. When the weighted average spectral efficiency was set as the optimization goal, the spectral efficiency of golden section algorithm was not significantly improved but that of PSO was increased by 19.3% for edge users. The experimental results show that the proposed method improves cell throughput and system performance.