Optimum power allocation of parallel concatenated convolution turbo code using flower pollination algorithm

Efficient and reliable data transmission and storage are the challenging issues in modern communication system. Reproduction of reliable data has been achieved by controlling the errors in a noisy environment. To control this errors data has been coded properly by considering different coding techniques. Turbo Code (TC) is considered as one of the high-performance forward error correcting coding schemes which approaches to the Shannon limit. Here, a novel Parallel Concatenated Convolution Turbo code (PCCTC) has been proposed to improve the Bit Error Rate (BER) performance portentously by allocating optimized power in systematic and parity bits. BER performance of the system has been improved by using two symmetrical convolutional encoders. Through the simulation result, it is observed that the proposed Flower Pollination Algorithm (FPA) optimized Parallel Concatenated Convolution Turbo Code (PCCTC) provides better error performance over Uniform Power Allocation (UPA) based PCCTC as well as Harmony-Search (HS), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) optimized PCCTC.