Jian-guo Yuan,Yang Tian,Xia Hu,Sheng Huang,Jin-zhao Lin,Yu Pang.A novel BTC decoding algorithm based on the genetic algorithm in optical communication systems[J].Optoelectronics Letters,2014,10(2):123-125
A novel BTC decoding algorithm based on the genetic algorithm in optical communication systems
Author NameAffiliationE-mail
Jian-guo Yuan Key Lab. of Optical Fiber Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China yuanjg@cqupt.edu.cn 
Yang Tian Key Lab. of Optical Fiber Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China  
Xia Hu Key Lab. of Optical Fiber Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China  
Sheng Huang Key Lab. of Optical Fiber Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China  
Jin-zhao Lin Key Lab. of Optical Fiber Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China  
Yu Pang Key Lab. of Optical Fiber Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China  
Abstract:
      Combining the advantages of both the genetic algorithm (GA) and the chase decoding algorithm, a novel improved decoding algorithm of the block turbo code (BTC) with lower computation complexity and more rapid decoding speed is proposed in order to meet the developing demands of optical communication systems. Compared with the traditional chase decoding algorithm, the computation complexity can be reduced and the decoding speed can be accelerated by applying the novel algorithm. The simulation results show that the net coding gain (NCG) of the novel BTC decoding algorithm is 1.1 dB more than that of the traditional chase decoding algorithm at the bit error rate (BER) of 10?6. Therefore, the novel decoding algorithm has better decoding correction-error performance and is suitable for the BTC in optical communication systems.
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This work has been supported by the National Natural Science Foundation of China (Nos.61371096 and 61275077), the Natural Science Foundation of CQ CSTC (No.2010BB2409), and the Program for the Innovation Team Building at Institutions of Higher Education in Chongqing.
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