Optimizing the operation of a wireless network is associated with effective data caching, i.e. storing information on the server closest to the user for quick access. However, important issues are choosing which data to cache and determining the optimal amount of data to store.
The new technology, called D-REC, uses a digital twin to model a wireless network and predict user needs. The system analyzes real network data and runs simulations to determine what data will be in demand in the near future. The resulting predictions are fed back to the network to make decisions about data caching.
Tests have shown that D-REC outperforms traditional prediction methods, allowing data to be distributed more efficiently across the network. The digital twin can also predict potential issues such as base station congestion, allowing proactive measures to be taken to maintain network stability.
Source: Ferra
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