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In order to overcome fading in wireless channels and increase the performance of wireless systems, cooperation is needed between the source node and relay node. In a cooperative wireless communication system, PA (Power Allocation) and RS (Relay Selection) are important issues for improving performance of the system. In particular, PA is an effective way to save transmit power and improve the coverage and capacity of the system. Some papers analyze full CSI (Channel State Information) for obtaining optimal power allocation. However, this makes the system increasingly complex and presents a practical problem. Thus, there is a need for partial CSI to reduce the complexity. With PSO (Particle Swarm Optimization), individuals referred to as particles are “flown” through hyper-dimensional search space. Changes to the position of a particle within a swarm are influenced by the knowledge of its neighbors. The PSO algorithm maintains a swarm of particles, where each particle represents a potential solution. Therefore, we propose an improved scheme for power allocation in relay-based cooperative wireless communications. For this purpose, we employ partial CSI and PSO algorithms to solve the optimization problem of power allocation with reduced system complexity as well as optimized performance.