New wireless services and applications have increased demand for spectrum. Communication between services and apps needs wireless spectrum. Cross-layer architecture connects the protocol layers to increase system efficiency. Not all layer functions are dumped into a network by cross-layer setup. Cross-layer architecture reduces network vulnerabilities to enhance communication. A self-determined time slot-based Cross-Layered Neighbor Route Discovery (C-LNRD) technique was developed to improve communication efficiency. Agents gather the data. The monitoring agent keeps track of the topology, time, and traffic of each neighbor at each level. The agent maintains a separate database for the data from each layer. Data is gathered at the physical, MAC, and network layers. Based on gathered metrics and updated routes, each node calculates its trust. PR ATTACK has no RTS, CTS, or RREQ in order to decrease false positives. Spectrum allocation that is adaptable and intelligent is made possible by cognitive radio and learning technology. Artificial Intelligence, Genetic Algorithm, Fuzzy Logic, and Game Theory are used to create Adaptive Cognitive Radio Networks (ACRN). High bandwidth is available from multi-hop cognitive radio networks (MCRNs) with DSA. The goal of this study is to develop MCRNs that reduce overhead, latency in routing, and spectral efficiency. The offered solution by Multi-hop CRN takes into account spectrum awareness, quality route establishment, and route maintenance in case of connection failure because of unavailability of the spectrum and node mobility. New methods enhance the cross-layer network layer protocols of MCRN. Spectrum awareness is enhanced through models. Routers and layered sensors communicate. The suggested routing method enhances performance and spectrum utilization.