Trust- Aware and Energy-Optimized Enhanced Coverage Routing Protocol for 6G Networks

In cellular networks, multiple devices are rapidly and increasingly being connected. It is indeed a challenge for the upcoming generation to handle these wide spread networks. 6G is considered to be the most challenging future generation communication technology, were new methods for data exchange and communication can be incorporated. There is a need for the devices to rely on either mesh-based networks or ad-hoc networks, especially during a post disaster scenario where the network infrastructure gets damaged. There is also a need for a communication network such as an ad-hoc network to be functioned by using the fundamental requirements of a 6G communication technology. The basic requirements include latency, data rate and communication frequency. To achieve the specified necessities, there is a need for the prevalence of the devices in its close proximity to one another. Solutions are formulated to design a broad network coverage area using the predominant Artificial Intelligence (AI) technologies. The paper presents Network Extension and Security (NEXUS), a 6G routing protocol that supports Artificial Intelligence (AI) for extending the network coverage area. Here the connection of the nodes to an Access Point (AP) is also taken into account. NEXUS uses multiple messages to reach the nodes that are far away from the AP for communication. In case of the absence of such nodes, the protocol chooses one of its connected neighbours to see through the gap. To bolster the performance of the protocol, Reinforcement Learning (RL), Supervised Learning (SL), and Graph Neural Network (GNN) are combined to provide a sophisticated AI-based approach. The inferred RL, SL and GNN are incorporated in 6G routing protocol to increase the network coverage. NEXUS provides a high data rate with acceptable latency and low energy and storage costs. Additionally, it also offers an enhanced security level by integrating trust as an additional parameter at the network level.