Inferensys

Glossary

Sample Rate Conversion (SRC)

Sample Rate Conversion (SRC) is the process of changing the sampling rate of a discrete signal, essential in digital predistortion (DPD) systems to align the observation receiver's bandwidth with the predistorter's processing rate.
Developer building agentic RAG system, retrieval pipeline diagram on laptop, technical workspace with notes.
DIGITAL SIGNAL PROCESSING FUNDAMENTAL

What is Sample Rate Conversion (SRC)?

Sample rate conversion is the computational process of altering the discrete sampling frequency of a digital signal to a new, desired rate, a critical operation for interfacing subsystems operating at different clock domains.

Sample Rate Conversion (SRC) is the digital signal processing technique that resamples a discrete-time signal from one sampling frequency to another. In the context of a DPD feedback path, SRC is essential to bridge the bandwidth mismatch between a high-speed observation receiver ADC and the predistorter core's processing rate, ensuring the captured power amplifier output is spectrally coherent with the forward-path reference signal.

The process is mathematically implemented through interpolation, decimation, or non-integer resampling using polyphase filter structures. Efficient SRC implementations on FPGAs leverage polyphase decomposition to minimize computational redundancy, allowing the high-throughput JESD204B data stream from an RF ADC to be seamlessly adapted to the clock domain of the predistorter core without introducing aliasing or imaging artifacts.

SIGNAL INTEGRITY

Key Characteristics of SRC in FPGA DPD

Sample Rate Conversion (SRC) in the DPD feedback path is not a trivial resampling task. It is a precision alignment operation that directly determines the fidelity of the observed power amplifier distortion and, consequently, the correction accuracy of the predistorter.

01

Arbitrary Ratio Rational Resampling

Unlike simple integer-ratio decimation, FPGA-based DPD systems require arbitrary rational resampling to align the observation receiver's fixed ADC clock with the transmitter's baseband rate. This is typically implemented using a Farrow structure or a polyphase filter bank that computes fractional interpolation and decimation factors on the fly. The resampling ratio is often an irrational number derived from non-coherent clock sources, demanding high-precision phase accumulator arithmetic to prevent long-term timing drift between the reference and feedback signals.

02

Phase-Coherent Interpolation

The SRC block must preserve absolute phase coherence between the transmitted reference waveform and the resampled feedback signal. Any phase discontinuity introduced by the resampling filter destroys the alignment required for memory polynomial model extraction. This is achieved through linear-phase FIR filter designs with symmetric coefficient sets. The group delay through the SRC must be constant and known to the sample, allowing the time alignment block to apply a static integer delay correction without residual fractional skew.

03

Spectral Image Rejection

During interpolation, the SRC introduces spectral images at multiples of the input sample rate. These images must be suppressed below the DPD observation path's noise floor to prevent aliasing into the band of interest during subsequent decimation. The anti-imaging filter is integrated into the polyphase decomposition of the resampler, with stop-band attenuation typically exceeding -80 dBc. Insufficient rejection causes the coefficient estimation algorithm to model the SRC's artifacts rather than the power amplifier's true nonlinear behavior.

04

Dynamic Latency Management

The SRC's processing latency is not static; it varies fractionally with the instantaneous resampling ratio. The DPD system must account for this dynamic group delay in its time alignment loop. A common approach pairs the SRC with a FIFO-based delay compensation buffer that absorbs the variable latency. The buffer's read pointer is controlled by the same phase accumulator that drives the resampler, ensuring that the output sample stream maintains a fixed temporal relationship with the system's master timing reference.

05

Fixed-Point Precision Floor

The SRC's internal arithmetic word length directly sets the noise floor of the resampled signal. Insufficient bit width in the phase accumulator causes spurious phase modulation, which manifests as jitter sidebands on the feedback signal. Similarly, coefficient quantization in the polyphase filter introduces a stationary error floor. For wideband 5G signals with high peak-to-average power ratios, SRC implementations typically require 18-bit to 24-bit data paths and 32-bit phase accumulators to keep quantization artifacts below the power amplifier's residual distortion level after linearization.

06

Polyphase Decomposition for Throughput

To meet the multi-gigasample per second throughput demands of wideband DPD, the SRC is decomposed into a polyphase architecture. The interpolation filter is partitioned into N parallel sub-filters, each operating at 1/N of the output sample rate. This allows the FPGA's DSP48 slices to be time-shared efficiently, with each slice computing a partial output sample per clock cycle. The polyphase structure naturally maps to the parallel data paths of JESD204B interfaces, enabling seamless integration with high-speed ADCs without requiring a serial-to-parallel conversion bottleneck.

SAMPLE RATE CONVERSION

Frequently Asked Questions

Essential questions about sample rate conversion in digital predistortion systems, covering fractional resampling, polyphase filter banks, and hardware implementation trade-offs.

Sample rate conversion (SRC) is the digital signal processing operation that changes the sampling rate of a discrete-time signal without altering its underlying spectral content. In digital predistortion systems, SRC is critical because the observation receiver in the DPD feedback path typically digitizes the power amplifier output at a different rate than the transmit path's baseband processing rate. The predistorter operates at the transmit sample rate to apply corrections to the forward signal, while the feedback ADC may sample at a higher rate to capture spectral regrowth into adjacent channels. SRC bridges this rate mismatch, enabling accurate time alignment between the reference and observed signals for proper coefficient extraction. Without precise SRC, the model extraction algorithms in either the Indirect Learning Architecture (ILA) or Direct Learning Architecture (DLA) would receive misaligned data, corrupting the predistorter coefficient estimation and degrading linearization performance.

Prasad Kumkar

About the author

Prasad Kumkar

CEO & MD, Inference Systems

Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.

His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.