Statistical Eye Diagram Analysis Based on Double-Edge Responses for Coding Buses

Abstract

For high-speed coding buses, it is a great challenge to evaluate the eye diagram accurately. Assuming that all data bits are independent and have uniform probabilities as previous estimation methods have done is not valid. In this paper, a new statistical method is proposed to estimate the worst-case eye diagrams and bit-error-rate (BER) eye diagrams for coding buses. The probability distribution of coded bus bit vectors is modeled based on the coding rule constraints. Then, actual worst pattern and eye diagram calculation is derived based on bus bit transition probabilities and double-edge responses. In order to validate the method, a parallel link with data bus inversion coding and 4b/6b coding is simulated, respectively. Worst case eye diagrams and BER eye diagrams are calculated and compared with that of no consideration of coding. Compared to the traditional statistical methods, this method eliminates the error due to the invalid assumption and provides more accurate results for designers.