Related Experiment Video
Updated: Oct 3, 2025

06:42
Generation and Coherent Control of Pulsed Quantum Frequency Combs
Published on: June 8, 2018
9.1K
Low-Complexity Filter for Software-Defined Radio by Modulated Interpolated Coefficient Decimated Filter in a Hybrid
Temidayo O Otunniyi1, Hermanus C Myburgh1
1Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria 0002, South Africa.
Sensors (Basel, Switzerland)
|February 15, 2022
Summary
A novel hybrid Farrow (HFarrow) algorithm reduces computational complexity for software-defined radio channelization. This efficient Farrow filter design achieves significant multiplier reductions compared to existing methods.
Area of Science:
- Digital Signal Processing
- Software-Defined Radio
Background:
- Farrow filters are crucial for channelization in software-defined radio (SDR).
- Traditional Farrow filters exhibit performance degradation and high computational complexity in wideband applications, especially near the Nyquist region.
Purpose of the Study:
- To propose a novel hybrid Farrow (HFarrow) algorithm for low-complexity channelization in multi-standard SDR receivers.
- To design a filter with reduced computational load while maintaining channelization performance.
Main Methods:
- The proposed HFarrow algorithm integrates a modulated Farrow filter with a frequency response interpolated coefficient decimated masking filter.
- A comparative analysis was performed against non-uniform modulated discrete Fourier transform filter banks (NU MDFT FB), coefficient decimated filter banks (CD FB), and interpolated coefficient decimated (ICDM) filter algorithms.
Main Results:
- The HFarrow filter bank demonstrated significant multiplier reductions: 50% compared to NU MDFT FB, 70% compared to CD FB, and 64% compared to ICDM.
- The HFarrow filter bank provides an equivalent number of sub-band channels as the compared algorithms.
Conclusions:
- The proposed HFarrow algorithm offers a substantial reduction in computational complexity for wideband channelization in SDR.
- This novel approach enables efficient multi-standard receiver design without compromising the number of sub-band channels.
Related Concept Videos
Reconstruction of Signal using Interpolation
394
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
394
Upsampling
346
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
346
Downsampling
292
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
292
Linear Approximation in Frequency Domain
149
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
149
Passive Filters
640
Passive filters are utilized to shape the frequency spectrum of signals across a diverse array of applications. These filters, using only passive elements like resistors (R), inductors (L), and capacitors (C), are capable of selectively allowing or blocking certain frequency ranges without the need for external power sources.
Low-Pass Filters
Low-pass filters are designed to transmit signals with frequencies lower than the cutoff frequency, ωc, and attenuate those above it. The cutoff...
Low-Pass Filters
Low-pass filters are designed to transmit signals with frequencies lower than the cutoff frequency, ωc, and attenuate those above it. The cutoff...
640
Linear Approximation in Time Domain
135
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
135

