On the efficient search of punctured convolutional codes with simulated annealing algorithm  

作　　者：ZOU Wei-xia WANG Zhen-yu WANG Gui-ye DU Guang-long GAO Ying 

机构地区：[1]Key Laboratory of Wireless Universal Communications, Beijing University of Posts and Telecommunications [2]School of Electronic Engineering, Beijing University of Posts and Telecommunications

出　　处：《The Journal of China Universities of Posts and Telecommunications》2014年第2期69-74,82,共7页中国邮电高校学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(61171104)

摘　　要：Punctured convolution codes （PCCs） have a lot of applications in modem communication system. The efficient way to search for best PCCs with longer constraint lengths is desired since the complexity of exhaustive search becomes unacceptable. An efficient search method to find PCCs is proposed and simulated. At first, PCCs＇ searching problem is turned into an optimization problem through analysis of PCCs＇ judging criteria, and the inefficiency to use pattern search （PS） for many local optimums is pointed out. The simulated annealing （SA） is adapted to the non-convex optimization problem to find best PCCs with low complexity. Simulation indicates that SA performs very well both in complexity and success ratio, and PCCs with memories varying from 9 to 12 and rates varying from 2/3 to 4/5 searched by SA are presented.Punctured convolution codes （PCCs） have a lot of applications in modem communication system. The efficient way to search for best PCCs with longer constraint lengths is desired since the complexity of exhaustive search becomes unacceptable. An efficient search method to find PCCs is proposed and simulated. At first, PCCs＇ searching problem is turned into an optimization problem through analysis of PCCs＇ judging criteria, and the inefficiency to use pattern search （PS） for many local optimums is pointed out. The simulated annealing （SA） is adapted to the non-convex optimization problem to find best PCCs with low complexity. Simulation indicates that SA performs very well both in complexity and success ratio, and PCCs with memories varying from 9 to 12 and rates varying from 2/3 to 4/5 searched by SA are presented.

关 键 词：PCCs optimization problem pattern search simulated annealing 

分 类 号：TN911.2[电子电信—通信与信息系统]