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首页> 外文会议>International Conference on Control, Instrumentation, Energy Communication >Optimum power allocation of parallel concatenated convolution turbo code using flower pollination algorithm
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Optimum power allocation of parallel concatenated convolution turbo code using flower pollination algorithm

机译：基于花授粉算法的并行级联卷积Turbo码的最优功率分配

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摘要

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.
机译：高效，可靠的数据传输和存储是现代通信系统中的难题。通过在嘈杂的环境中控制错误，可以实现可靠数据的再现。为了控制此错误，已通过考虑不同的编码技术对数据进行了正确编码。 Turbo码（TC）被认为是接近香农极限的高性能前向纠错编码方案之一。这里，已经提出了新颖的并行级联卷积Turbo码（PCCTC），以通过在系统位和奇偶校验位中分配优化的功率来显着提高误码率（BER）性能。通过使用两个对称卷积编码器，提高了系统的BER性能。通过仿真结果，可以看出，与基于均匀功率分配（UPA）的PCCTC以及和声搜索（HS），粒子相比，所提出的花授粉算法（FPA）优化的并行级联卷积Turbo码（PCCTC）具有更好的错误性能。群体优化（PSO）和遗传算法（GA）优化的PCCTC。

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