A Joint Spectral Efficiency Optimization Algorithm Based on Greedy Algorithm and Improved PSO for Cell-free Massive MIMO Networks

Cell-free massive Multiple Input Multiple Output (MIMO) systems, which can be applied to deploy a large number of geographically dispersed access points within an area, have been playing an essential role in the operation of next-generation mobile communication networks due to their better performance in the flexibility of network deployment. The key to improving network service is to choose the appropriate APs and effectively control their transmission power for reduced co-channel interference and improved overall performance. To address co-channel interference and reduce computational complexity, a pilot allocation-based access point selection algorithm is proposed in this study that is used to iteratively allocate pilots, with access points selected to significantly reduce pilot contamination and serve user. However, considering the complexity of max-min power control, the particle swarm optimization (PSO) algorithm is applied in this paper as the solution. To prevent the algorithm from falling into local optima, the PSO algorithm is further improved by adjusting the inertia weight flexibly, thereby making the algorithm more efficient in searching for the global optimum. Simulation results are obtained to validate the proposed algorithm, which significantly enhances the overall spectral efficiency of the users while ensuring a consistent quality of services delivered to the users.