Distortion losses of high-speed single-photon avalanche diode optical receivers approaching quantum sensitivity

Abstract

<jats:p> The high internal gain of single-photon avalanche diodes (SPADs) operating in Geiger mode allows the quantum limit of detection to be approached. This offers a significantly improved sensitivity for optical communication over existing photodiodes. A fully integrated CMOS SPAD array receiver (RX) is presented which achieves 500 Mb s <jats:sup>−1</jats:sup> four-level pulse amplitude modulation in a visible light communication link within 15.2 dB of the quantum limit. However, SPAD dead time induces around 5.7 dB of transient distortion which restricts error performance and data rate. We propose a model describing a discrete photon counting system which exhibits this nonlinear behaviour and compare it to practical measurements with the RX. A unipolar intensity modulated optical signal is considered, as opposed to bipolar electric fields in conventional radio frequency wireless systems. Intermodulation between the DC and harmonic components of the data-carrying waveform is investigated, and the resulting degradation of signal-to-noise-and-distortion ratio and bit error rate is evaluated. The model is developed as a tool for understanding distortion to ultimately allow rectification through RX architecture, modulation scheme, coding and equalization techniques. </jats:p> <jats:p>This article is part of the theme issue ‘Optical wireless communication’.</jats:p>

Optical wireless communication

“…SPADs operate in the Geiger mode and can detect single photons. This theme issue includes an article by Henderson and co-workers [15], who is a pioneer of digital SPAD devices in complementary metal-oxide semiconductor (CMOS).…”

Near-Nyquist-Limit Optical Communication and Ranging Method Based on Waveform Matched PPM

“…As SPAD and SNSPD cannot detect the signal within their dead time [29][30][31], inserting the guard time slot into the signal and receiving it by the detector array are applied to solve the problem [32,33]. The former can be realized by programming but reduces communication efficiency, whereas the latter increases hardware complexity and power consumption.…”