Abstract

In this brief, a blind background calibration technique for super-regenerative receivers (SRRs) is presented. The proposed calibration scheme is designed to help SRRs to maintain their high sensitivity and immunity to negative transconductance (<inline-formula> <tex-math notation="LaTeX">${\mathrm {-}\mathrm {G}}_{\mathrm {m}}$ </tex-math></inline-formula>) variations under process-voltage- temperature (PVT) variations. Unlike the conventional foreground <inline-formula> <tex-math notation="LaTeX">${-\mathrm {G}}_{\mathrm {m}}$ </tex-math></inline-formula> variations calibration techniques that require interruption of the receiver input, the proposed calibration technique employs input signal statistics and does not require interruption of the input bit-stream for extraction of the errors. The proposed scheme is based on an adaptive algorithm that compares the probability distribution of the pseudorandom-input (PI) stream and the output of the super-regenerative oscillator (SRO) and forces them to coincide at the end of the calibration. The proposed technique is implemented using a mixed-signal detection circuit and a finite state machine (FSM) that drives an 8-bit successive approximation register (SAR) to adjust the compensation current in the SRO. The simulation results successfully verify the effectiveness and reliability of the proposed calibration technique and show significant improvements in terms of SRR sensitivity under different process corners.

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