DocumentCode :
1750900
Title :
A new adaptive strategy for turbo decoder with prior statistical knowledge of extrinsic information over AWGN and fading channels
Author :
Yang, Fengfan ; Tafazolli, Rahim ; Evans, Barry
Author_Institution :
Dept. of Electron. Eng., Nanjing Univ. of Aeronaut. & Astronaut., China
Volume :
2
fYear :
2001
fDate :
2001
Firstpage :
1367
Abstract :
A new adaptive strategy for a turbo decoder with prior statistical knowledge of extrinsic information is proposed. A test pseudorandom bits block, with distribution patterns of 1s and 0s known by both the transmitter and receiver, is sent to the receiver when the channel status changes and is detected by the receiver. The turbo decoder computes the conditional probability mass functions of the extrinsic information for both arms at each iterative decoding by using the test block. These updated probability mass functions are kept in the turbo decoder to replace the conventional Gaussian assumptions for iterative decoding of an information bits block over AWGN and various fading channels. The simulation results show that the novel iterative turbo decoding has considerable performance gains over conventional ones under the same channel conditions
Keywords :
AWGN channels; adaptive decoding; cellular radio; fading channels; iterative decoding; statistical analysis; turbo codes; AWGN channels; UMTS; adaptive turbo decoder; channel status; conditional probability mass functions; extrinsic information; fading channels; iterative decoding; prior statistical knowledge; test pseudorandom bits block; universal mobile telecommunication systems; AWGN; Additive white noise; Arm; Bit error rate; Fading; Gaussian distribution; Iterative decoding; Signal to noise ratio; Testing; Turbo codes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Vehicular Technology Conference, 2001. VTC 2001 Spring. IEEE VTS 53rd
Conference_Location :
Rhodes
ISSN :
1090-3038
Print_ISBN :
0-7803-6728-6
Type :
conf
DOI :
10.1109/VETECS.2001.944610
Filename :
944610
Link To Document :
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