Analysis and performance of coded symbol recovery loop using oversampling

Abstract

Abstract In this work, we propose a closed-loop analog system to detect the source information of a binary data stream coded by a flexible finite automaton. We initially consider the dual sideband suppressed-carrier modulation of a base band binary amplitude waveform. The automaton introduces a symbol redundancy as phase contribution of the modulated signal by a simple mapping scheme. The proposed recovery system performs a coherent demodulation, presenting the base-band binary wave to a maximum likelihood hard detector, a simple analog trigger that estimates the source data within the symbol period. This wave is over-sampled, and the final decision comes by counting the positive samples and a majority vote. We prove our approach is valid answering the most important concerns: the stability of the closed loop, a first analytical expression of the error rate when a Markov birth process models the counting phase, and finally the role of this last loop to lower the bit error rate compared to a simple Costas loop. The analysis continues by solving the problem of carrier and symbol rate recovery and the impact of non-linearity and noise in the basic analog blocks. Behavioral simulations describe a competitive scenario in terms of error rate, comparing the proposed approach to the Costas Loop and the basic convolutional decoding strategies based on Viterbi algorithm both in the hard (Hamming metrics) and soft (Euclidean metrics) versions.

Keywords

• Closed loop system
• Decoding
• Error analysis
• Finite automata’s theory
• Stability analysis
• Viterbi algorithm