Optimizing FPGA Resource Allocation in SDR Remote Laboratories via Partial Reconfiguration

In wireless communications and radio frequency courses, Software-Defined Radios (SDRs) offer students hands-on experience with software-based signal processing on programmable hardware platforms such as Field Programmable Gate Arrays (FPGAs). While some remote SDR laboratories enable students to access real hardware, they typically lack support for Partial Reconfiguration (PR)—a powerful FPGA capability that allows sections of a design to be reconfigured at runtime without disrupting the main system operation. This capability enhances real-time adaptability and optimizes resource utilization, making it highly relevant for modern SDR applications. This study addresses this gap by extending an existing SDR remote lab to support PR, enabling students to explore reconfigurable hardware design within a remote learning environment. Two integration architectures were developed: one based on a graphical user interface (UI) and another utilizing a command-line workflow, both accessible via a web browser. Preliminary experiments using Red Pitaya SDR platforms—reportedly the first use of these devices for educational PR exploration—examined the impact of PR on logic resource utilization and total power consumption across three levels of design complexity. These results were compared to equivalent static FPGA designs performing the same functionality without PR. By making PR experimentation accessible through a remote platform, this work enhances STEM education by bridging advanced FPGA techniques with practical learning. It will equip students with industry-relevant skills for developing agile, resource-efficient wireless systems and foster a deeper understanding of adaptive hardware design.

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Publication Details

Journal
Electronics
Published
2025-07-20
DOI
https://doi.org/10.3390/electronics14142908
Citations
2
Primary Topic
Experimental Learning in Engineering
Type
article
Field-Weighted Citation Impact
2.27

Funders

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article

Optimizing FPGA Resource Allocation in SDR Remote Laboratories via Partial Reconfiguration

Rania Hussein, Zhiyun Zhang
2 citations
Electronics
Experimental Learning in Engineering
2.27
article

Optimizing FPGA Resource Allocation in SDR Remote Laboratories via Partial Reconfiguration

Rania Hussein, Zhiyun Zhang
article en
2 citations

Abstract

In wireless communications and radio frequency courses, Software-Defined Radios (SDRs) offer students hands-on experience with software-based signal processing on programmable hardware platforms such as Field Programmable Gate Arrays (FPGAs). While some remote SDR laboratories enable students to access real hardware, they typically lack support for Partial Reconfiguration (PR)—a powerful FPGA capability that allows sections of a design to be reconfigured at runtime without disrupting the main system operation. This capability enhances real-time adaptability and optimizes resource utilization, making it highly relevant for modern SDR applications. This study addresses this gap by extending an existing SDR remote lab to support PR, enabling students to explore reconfigurable hardware design within a remote learning environment. Two integration architectures were developed: one based on a graphical user interface (UI) and another utilizing a command-line workflow, both accessible via a web browser. Preliminary experiments using Red Pitaya SDR platforms—reportedly the first use of these devices for educational PR exploration—examined the impact of PR on logic resource utilization and total power consumption across three levels of design complexity. These results were compared to equivalent static FPGA designs performing the same functionality without PR. By making PR experimentation accessible through a remote platform, this work enhances STEM education by bridging advanced FPGA techniques with practical learning. It will equip students with industry-relevant skills for developing agile, resource-efficient wireless systems and foster a deeper understanding of adaptive hardware design.

ElectronicsVol. 14(14)
University of Washington (US)
National Science Foundation
Openalex Percentile: Top 10%
Experimental Learning in Engineering
2.27
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Optimizing FPGA Resource Allocation in SDR Remote Laboratories via Partial Reconfiguration — Rania Hussein, Zhiyun Zhang · Electronics (2025) | TGRS Research Map | TGRS