SymXplorer: Symbolic Analog Topology Exploration of a Tunable Common-Gate Bandpass TIA for Radio-over-Fiber Applications
Abstract
While circuit parameter optimization has matured significantly, the systematic discovery of novel circuit topologies remains a bottleneck in analog design automation. This work presents SymXplorer, an open-source Python framework designed for automated topology exploration through symbolic modeling of analog components. The framework enables a component-agnostic approach to architecture-level synthesis, integrating stability analysis and higher-order filter exploration within a streamlined API. By modeling non-idealities as lumped parameters, the framework accounts for physical constraints directly within the symbolic analysis. To facilitate circuit sizing, SymXplorer incorporates a multi-objective optimization toolbox featuring Bayesian optimization and evolutionary algorithms for simulation-in-the-loop evaluation. Using this framework, we conduct a systematic search for differential Common-Gate (CG) Bandpass Transimpedance Amplifier (TIA) topologies tailored for 5G New Radio (NR) Radio-over-Fiber applications. We propose a novel, orthogonally tunable Bandpass TIA architecture identified by the tool. Implementation in 65 nm CMOS technology demonstrates the efficacy of the framework. Post-layout results exhibit a tunable gain of 30–50 dBΩ, a center frequency of 3.5 GHz, and a tuning range of 500 MHz. The design maintains a power consumption of less than 400 μW and an input-referred noise density of less than 50 pA/Hz across the passband. Finally, we discuss how this symbolic framework can be integrated into future agentic EDA workflows to further automate the analog design cycle. SymXplorer is open-sourced to encourage innovation in symbolic-driven analog design automation.
Fields of Study & Subjects
VLSI and FPGA Design Techniques
Radio Frequency Integrated Circuit Design
Advanced Power Amplifier Design
Publication details
- Journal / source
- Electronics
- Publisher
- MDPI AG
- Volume
- 15
- Issue
- 3
- Pages
- 515–515
- Publication date
- 25 January 2026
- Language
- EN