MANET (Mobile Ad hoc Network) comprises of a set of wireless mobile node connected in a self-healing and self-configured network devoid of any fixed infrastructure. The major challenge in this ad-hoc network is that the network should adapts the multicast interactions to the condition at which there is an occurrence of infinite flexibility and repeated failures. The cognitive radio (CR) in the MANET system has been developed for addressing this problem of spectrum congestion thereby enabling the cognitive users to utilize the spectrum that are underused in that way mitigating the interference among the users. Also, at the transmission process there is a problem of primary radio’s protection (PRs). In traditional approaches, the problem of transmission process is rectified by employing an optimal solution based on various algorithms and in turn reduces the PRs interference. However, the existing techniques failed to solves the complex convex problem of channel assignment. To address this issue, the proposed protocol is designed. In the proposed scheme, both primary user (PU) and secondary user (SU) are clustered initially based on the graph theory process. After that, in each cluster, formation of Robust spatial Gabriel Graph takes place at which the neighbouring nodes are predicted by estimating the weighted end-to-end delay approach. Once the multi path decision making condition is satisfied, the route path is established, and the communication takes place based on QoS constraint. This RS-GG can easily update their neighbouring list and is capable of adjusting the transmission power. This can lead to the improved rate of PDR, network connectivity maintenance and too enhances the network lifetime. The performance analysis of the proposed methods is carried out in terms of PDR, control overheads, energy consumption, and End-to-End delay and the analysis is compared with existing protocols to compare the variation and to prove the effectiveness of proposed protocol designed. The simulation outcomes illustrate that the suggested strategy performs well and improves the transmission of data with the best optimal solutions.