Delay Optimization of Wi-Fi Mesh in Neighbourhood Area Network Using Deep Reinforcement Learning

A smart grid is an electrical network that uses digital technology to provide two-way communication between all system components, thereby managing the transmission of electricity from all generation sources to consumers. Neighbourhood Area Networks (NAN) are communication networks that enable data sharing between smart meters, sensors, and other devices. Wi-Fi can provide wireless access in homes, businesses, and public spaces, but it has a restricted range. Mesh networks can enhance the performance of Wi-Fi in terms of NAN coverage since several nodes can communicate with one another. However, mesh networks may have delays due to their spread nature, interference, and node failure. Deep Reinforcement Learning is utilized to simulate and eliminate these delays, with the goal of reducing Wi-Fi mesh delay in NAN. The significant results show a significant reduction in network delays, which improves overall network performance and reliability, thus increasing the reliability of smart grid communication within NANs.