Swarm Algorithm-based Power Optimization in Cooperative Communication Network

Background: Due to the environmental effects, the signal fades abruptly and is sometimes lost in the transmission path, which results in weak signal reception at the destination node. The Cooperative Communication Network (CCN) overcomes this problem and provides better spectral efficiency. The source node and the helper node both send the information to the receiver. In spite of many advantages, there are some limitations to such networks. Improving the system efficiency by power, energy, or relay selection optimization is quite desirable as multiple helper nodes are used in the network. Considering this crucial requirement of optimization, the proposed work presents optimal power allocation of the system. Methods: Here, tunicate-swarm optimization is implemented to improve the system parameters, symbol error rate (SER), outage probability, and bit error rate (BER). Two relaying protocols are used for analysis, i.e., Amplify-and-Forward (AF) and Differential AF (Diff-AF), with two combining schemes: Selection-Combining (SC) and Maximal-Ratio-Combining (MRC). Results: The results obtained are further compared with other metaheuristics algorithms, such as Particle-Swarm-Algorithm (PSO), Black-Widow-Optimization (BWO), and the traditional method of Equal-Power-Allocation (EPA). Conclusion: The simulation result shows that the proposed algorithm improves the system parameters compared to algorithms with less time.