OPTIMAL DISTRIBUTION OF 5G RADIO RESOURCES BASED ON NEURAL NETWORKS
Published: 2026-04-18
Abstract
This paper discusses the problem of optimal allocation of radio resources in 5G networks to support mass M2M devices using neural networks. A modified ALOHA-EP random access algorithm is proposed, which takes into account packet priorities and delays. The mathematical model is used to estimate the probabilistic time characteristics of the system. Radio resource allocation is optimized using SQP and MultiStart methods in MATLAB. Based on the optimization results, a neural network is trained to predict the share of allocated radio resources for M2M devices. The dynamic time series of probabilities of the activity of M2M devices is predicted using LSTM (Long Short-Term Memory) and other machine learning methods. Efficiency of the proposed method is shown.
Keywords
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