Blind parameter estimation of turbo convolutional codes: Noisy and non-synchronized scenario

Abstract

Blind estimation of forward error correction code parameters at the receiver plays a significant role in non-cooperative communication, adaptive modulation and coding systems, and reconfigurable receiver systems. Turbo convolutional codes, a parallel concatenation of multiple convolutional codes, are used in digital communication and storage systems to achieve low bit error rate. The present paper proposes innovative algorithms for the blind estimation of code parameters and reconstruction of turbo convolutional encoder over noisy scenario. The turbo convolutional code is designed using two component codes along with an interleaver. Recursive systematic convolutional codes are used as component codes. Any imperfection in synchronization of received data for the proposed code parameter estimation algorithm is compensated through a bit position adjustment parameter. The performance of the proposed algorithms in terms of parameter estimation accuracy is investigated for different modulation order, code rate, and constraint length values. It is observed that the performance improves with decrease in modulation order and constraint length values.