This document summarizes research on optimization algorithms for spectrum sharing and sensing in cognitive radio networks. It discusses how cognitive radio allows unlicensed secondary users to access licensed spectrum when primary users are not using it. The key aspects covered are: 1. Throughput optimization aims to maximize data transfer from primary to secondary users while minimizing interference. Probability of detection and false alarms are important metrics. 2. Genetic and particle swarm optimization algorithms are population-based approaches studied for optimization. Genetic algorithms use crossover and mutation while particle swarm optimization updates particle positions and velocities over iterations. 3. The document reviews literature on spectrum sensing challenges and solutions, discussing detection methods and practical issues like noise uncertainty. Optimization is important for