文件名称:turbo_sys_demo

  • 所属分类:
  • 3G开发
  • 资源属性:
  • [Matlab] [源码]
  • 上传时间:
  • 2012-11-26
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  • 2kb
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  • y*
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This scr ipt simulates the classical turbo encoding-decoding system.

It simulates parallel concatenated convolutional codes.

Two component rate 1/2 RSC (Recursive Systematic Convolutional) component encoders are assumed.

First encoder is terminated with tails bits. (Info + tail) bits are scrambled and passed to

the second encoder, while second encoder is left open without tail bits of itself.



Random information bits are modulated into +1/-1, and transmitted through a AWGN channel.

Interleavers are randomly generated for each fr a me.



Log-MAP algorithm without quantization or approximation is used.

By making use of ln(e^x+e^y) = max(x,y) + ln(1+e^(-abs(x-y))),

the Log-MAP can be simplified with a look-up table for the correction function.

If use approximation ln(e^x+e^y) = max(x,y), it becomes MAX-Log-MAP.- This scr ipt simulates the classical turbo encoding-decoding system.

 It simulates parallel concatenated convolutional codes.

 Two component rate 1/2 RSC (Recursive Systematic Convolutional) component encoders are assumed.

 First encoder is terminated with tails bits. (Info + tail) bits are scrambled and passed to

 the second encoder, while second encoder is left open without tail bits of itself.



 Random information bits are modulated into +1/-1, and transmitted through a AWGN channel.

 Interleavers are randomly generated for each fr a me.



 Log-MAP algorithm without quantization or approximation is used.

 By making use of ln(e^x+e^y) = max(x,y) + ln(1+e^(-abs(x-y))),

 the Log-MAP can be simplified with a look-up table for the correction function.

 If use approximation ln(e^x+e^y) = max(x,y), it becomes MAX-Log-MAP.
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turbo_sys_demo.m

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