Blind Parameter Estimation of Product and Turbo

 Future Generation Communication Systems Research Group

(Dr. Swaminathan R)

Blind Parameter Estimation of Product and Turbo Convolutional Codes: Product codes are multidimensional codes constructed using multiple component codes. Turbo convolutional codes (TCC) is a parallel concatenation of multiple convolutional codes. Both the forward error correction (FEC) codes play a vital role in improving the performance of modern digital/wireless communication and storage systems. In the existing communication systems, the code parameters are known at the receiver. However, in a non-cooperative scenario, which exists in military and spectrum surveillance systems, the FEC code parameters are not known at the receiver. Hence, it is essential to blindly estimate the code parameters for decoding the message symbols. In our recent works, novel algorithms over noisy channel conditions are proposed for the blind estimation of TCC and two-dimensional product code parameters considering Reed-Solomon (RS) and Bose-Chaudhuri-Hocquenghem (BCH) as component codes. The performance of the algorithms in terms of probability of correct estimation is investigated for different code and modulation parameters. It is observed that the accuracy improves with decrease in modulation order (M), code dimension, and constraint length (K) values as shown in Fig. 1(a) and (b).

(a)

(b)

Fig.1. Probability of correct estimation of Turbo Convolutional and Product code parameters with respect to SNR

For more details refer: https://www.researchgate.net/profile/Swaminathan_Ramabadran