The article proposes an efficient technique for optimal resource allocation and delay minimization in NG networks. In 6G network, the density of the users will be very high, and to handle their demand, intelligent algorithms and techniques are required. Moreover, the 6G network has promised to enable many advanced ultra-low latency applications like holographic imaging, haptic communication, Tele driving, Tele Robotics, and many more. In this article, the condition of call drop due to the non-availability of resources has been addressed. Further, this condition induces an extra delay in the network, which is not acceptable in the case of latency-sensitive applications like haptic communication. The problem can be solved by incorporating Wireless Intelligent Router (WIR) in the network. The router will monitor the network and re-route the users if network congestion occurs. The WIR is a Reinforcement Learning based trained router that intelligently handles the user's demand by connecting it to the available proximal access point. It ensures an optimal power allocation to the user based on the demanded application. The simulation results show that the WIR has reduced the average power consumption and minimized the delay in the network.
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Dogra et al. (2023) studied this question.
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