The dense deployment of Femto Base Stations (FBS) assisting Macro Base Stations (MBS) in a Heterogeneous Network (HetNet) resolves the coverage issue of 5G signal transmission. However, the imprudent layout of FBSs results in extensive energy consumption and increased signal interference among base stations. Regulating the transmission power of each base station in the HetNets through the main controller or MBS is essential to maximize the power efficiency of the entire HetNets while adhering to the constraints of basic signal throughput and fairness. To address this challenge, this paper proposes an Adaptive Acceleration Particle Swarm Optimization (AA-PSO) algorithm. This algorithm dynamically determines the inertia weight based on each particle’s optimal position and the global optimal position, and introduces the concept of time-varying parameters to control the learning rate, thus managing the search range and convergence speed of the particle swarm. The results demonstrate that the AA-PSO algorithm can efficiently determine the optimal transmission power of each base station in the HetNets, reduce interference between MBS and FBSs, as well as among FBSs, and ultimately improve the service efficacy of the entire network.

The high efficacy of metro network services not only enhances residents’ travel quality but also brings significant socio-economic benefits, thus is of great importance to urban land use and city development. Existing methods for measuring metro service efficacy often overlook metro network connectivity and rely heavily on subjective questionnaire data analysis from the user experience perspective. This paper proposes a method to measure metro network service efficacy from the user’s perspective. The approach first calculates the connectivity index of metro network and estimates the housing premium brought by metro network connectivity, which reveals users’ willingness to pay for metro network connectivity. This method objectively measures metro network service efficacy from the user’s perspective. Based on this, efficacy optimization methods are proposed, providing quantitative simulation methods for metro expansion, site selection, operation quality adjustments, etc., which are of great reference value to metro management departments and even urban sustainable development.