In the rapidly evolving landscape of the Internet of Things (IoT), 5G communications, sensor readout, and high-fidelity audio, the demand for high-resolution Analog-to-Digital Converters (ADCs) is paramount. As CMOS technology scales into the deep-submicron regime, traditional analog-intensive architectures struggle to maintain precision due to reduced supply voltages and transistor mismatch. The Delta-Sigma (∆Σ) modulator has emerged as the robust solution to these challenges, leveraging oversampling and noise shaping to achieve high dynamic range with relaxed analog constraints. However, these modulators are susceptible to pattern-dependent limit cycles, known as idle tones, which degrade spectral purity. While classical dithering techniques can mitigate these artifacts, they inherently compromise the Signal-to-Noise Ratio (SNR) by injecting broadband noise into the signal path. This thesis investigates advanced strategies to overcome the trade-off between linearity and noise performance. A robust behavioral modeling framework is established in Simulink to analyze the internal state variables and stability boundaries of the modulator. Building upon this analysis, two architectures are proposed and validated: the Implicit Dither Cancellation topology and the Calibrated Subtractive Dithering scheme. These designs aim to decouple the linearization benefits of large-amplitude dithering from the associated noise penalty through digital processing. Simulation results demonstrate the efficacy of the proposed methods against classical topologies. The analysis reveals that the Calibrated Subtractive Dithering architecture, in particular, achieves near-perfect removal of idle tones while simultaneously extending the optimal dynamic range of the system. By effectively canceling the dither signal at the output, the two proposed design delivers a substantial SNR improvement of approximately 10 to 20 dB compared to standard dithered implementations. These findings confirm that both the techniques can successfully relax the design constraints of high-precision mixed-signal systems, enabling superior spectral performance without sacrificing dynamic range.
Nel panorama in rapida evoluzione dell'Internet of Things (IoT), delle comunicazioni 5G, della lettura dei sensori e dell'audio ad alta fedeltà, la richiesta di convertitori analogico-digitali (ADC) ad alta risoluzione è di primaria importanza. Man mano che la tecnologia CMOS si ridimensiona verso il regime deep-submicron, le tradizionali architetture a forte connotazione analogica faticano a mantenere la precisione a causa della riduzione delle tensioni di alimentazione e del mismatch dei transistor. Il modulatore Delta-Sigma (∆Σ) è emerso come una soluzione robusta a queste sfide, sfruttando il sovra campionamento (oversampling) il noise shaping per ottenere un'elevata dinamica con vincoli analogici più rilassati. Tuttavia, questi modulatori sono suscettibili a cicli limite dipendenti dall'ingresso, noti come idle tones (toni spuri), che degradano la purezza spettrale. Sebbene le classiche tecniche di dithering possano mitigare questi artefatti, esse compromettono intrinsecamente il rapporto segnale-rumore (SNR) iniettando rumore in banda. Questa tesi indaga strategie avanzate per superare il trade-off tra linearità e prestazioni relative al rumore. E' stato sviluppato in Simulinkun un modello comportamentale per analizzare le variabili di stato interne e i limiti di stabilità del modulatore. Sulla base di questa analisi, vengono proposte e validate due architetture: una topologia di cancellazione implicita del dither (Implicit Dither Cancellation) e lo schema di dithering sottrattivo calibrato (Calibrated Subtractive Dithering). Questi progetti mirano a separare, tramite l'elaborazione digitale, i vantaggi di linearizzazione forniti dal dither dalla conseguente penalizzazione in termini di rumore. I risultati delle simulazioni dimostrano l'efficacia dei metodi proposti rispetto alle topologie classiche. L'analisi rivela che l'architettura Calibrated Subtractive Dithering, in particolare, ottiene una rimozione quasi perfetta degli idle tones, estendendo al contempo la gamma dinamica ottimale del sistema. Cancellando efficacemente il segnale di dither in uscita, le due architetture proposte offrono un sostanziale miglioramento dell'SNR di circa 10-20 dB rispetto alle implementazioni con dither standard. Questi risultati confermano che entrambe le tecniche possono migliorare con successo i vincoli di progettazione dei sistemi mixed-signal ad alta precisione, consentendo prestazioni spettrali superiori senza sacrificare la dinamica.
Dithering techniques for Delta-Sigma modulators
Mussone, Antonio Augusto
2025/2026
Abstract
In the rapidly evolving landscape of the Internet of Things (IoT), 5G communications, sensor readout, and high-fidelity audio, the demand for high-resolution Analog-to-Digital Converters (ADCs) is paramount. As CMOS technology scales into the deep-submicron regime, traditional analog-intensive architectures struggle to maintain precision due to reduced supply voltages and transistor mismatch. The Delta-Sigma (∆Σ) modulator has emerged as the robust solution to these challenges, leveraging oversampling and noise shaping to achieve high dynamic range with relaxed analog constraints. However, these modulators are susceptible to pattern-dependent limit cycles, known as idle tones, which degrade spectral purity. While classical dithering techniques can mitigate these artifacts, they inherently compromise the Signal-to-Noise Ratio (SNR) by injecting broadband noise into the signal path. This thesis investigates advanced strategies to overcome the trade-off between linearity and noise performance. A robust behavioral modeling framework is established in Simulink to analyze the internal state variables and stability boundaries of the modulator. Building upon this analysis, two architectures are proposed and validated: the Implicit Dither Cancellation topology and the Calibrated Subtractive Dithering scheme. These designs aim to decouple the linearization benefits of large-amplitude dithering from the associated noise penalty through digital processing. Simulation results demonstrate the efficacy of the proposed methods against classical topologies. The analysis reveals that the Calibrated Subtractive Dithering architecture, in particular, achieves near-perfect removal of idle tones while simultaneously extending the optimal dynamic range of the system. By effectively canceling the dither signal at the output, the two proposed design delivers a substantial SNR improvement of approximately 10 to 20 dB compared to standard dithered implementations. These findings confirm that both the techniques can successfully relax the design constraints of high-precision mixed-signal systems, enabling superior spectral performance without sacrificing dynamic range.| File | Dimensione | Formato | |
|---|---|---|---|
|
Thesis_final.pdf
non accessibile
Descrizione: Thesis
Dimensione
9.86 MB
Formato
Adobe PDF
|
9.86 MB | Adobe PDF | Visualizza/Apri |
|
Executive_Summary.pdf
non accessibile
Descrizione: Executive summary
Dimensione
688.03 kB
Formato
Adobe PDF
|
688.03 kB | Adobe PDF | Visualizza/Apri |
I documenti in POLITesi sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/10589/252030