Eye prediction of digital driver with power distribution network noise

Abstract

Algorithms featuring fast and accurate estimation of worst-case eye diagram have been proposed to replace the time-consuming random bit simulation in channel design. However, when the interaction between nonlinear I/O circuits and power distribution network (PDN) noise is included, most of those approaches fail to maintain accuracy. Based on the superposition of multiple bit pattern responses (SMBP) concept, Ren and Oh [1] developed an algorithm to fast predict the eye diagram that theoretically captures any nonlinearity in the circuit. In this paper, a test circuit with PDN was constructed to examine the performance of this algorithm. The experiment results show good agreement with the results simulated by long PRBS in HSPICE.