<p>Current research on spectrum allocation reveals that licensed users are underutilising their allotted spectrum at any given time and place. In this work, we create a modified version of the Modified Gannet Optimization Algorithm Entropy Detection (MGOAED) for Cognitive Radio Networks (CRN) spectrum sensing and energy detection. One of the spectrum sensing detection procedures, the suggested entropy detection approach, is thought to enhance the sensing validation at low Signal Noise to Ratio (SNR). The entropy of a uniform distribution and the entropy of a Gaussian distribution are two examples of the various entropy techniques. The Modified Gannet Optimization Algorithm (MGOA) is used to choose the Gaussian variable in this entropy energy detection method. The Oppositional Function (OF) is used in the Gannet Optimization Algorithm (GOA) to improve the solution initialisation process. Here, the cognitive radio networks’ energy efficiency is achieved by the development of MGOAED technology. Performance and comparative analysis are used to put the suggested approach into practice and examine it. The suggested approach is contrasted with traditional methods. The proposed technique obtained high energy efficiency (5.2) and high average throughput (3.2Mbps).</p>