Research Article10.1016/j.micpro.2026.105267Towards the end of the ECSEL Project “iRel40”: three years of Intelligent ReliabilityJun 01, 2026Microprocessors and MicrosystemsKlas Brinkfeldt + 15 more +15CiteListenSave
Research Article10.1016/j.micpro.2025.105243A digital beamforming receiver architecture implemented on a FPGA for space applicationsMar 01, 2026Microprocessors and MicrosystemsEduardo Ortega + 8 more +8The burgeoning interest within the space community in digital beamforming is largely attributable to the superior flexibility that satellites with active antenna systems offer for a wide range of applications, notably in communication services. This paper delves into the analysis and practical implementation of a Digital Beamforming and Digital Down Conversion (DDC) chain, leveraging a high-speed Analog-to-Digital Converter (ADC) certified for space applications alongside a high-performance Field-Programmable Gate Array (FPGA). The proposed design strategy focuses on optimizing resource efficiency and minimizing power consumption by strategically sequencing the beamformer processor ahead of the complex down-conversion operation. This innovative approach entails the application of demodulation and low-pass filtering exclusively to the aggregated beam channel, culminating in a marked reduction in the requisite digital signal processing resources relative to traditional, more resource-intensive digital beamforming and DDC architectures. In the experimental validation, an evaluation board integrating a high-speed ADC and a FPGA was utilized. This setup facilitated the empirical validation of the design’s efficacy by applying various RF input signals to the digital beamforming receiver system. The ADC employed is capable of high-resolution signal processing, while the FPGA provides the necessary computational flexibility and speed for real-time digital signal processing tasks. The findings underscore the potential of this design to significantly enhance the efficiency and performance of digital beamforming systems in space applications.Read moreCiteListenSave
Research Article10.1016/j.micpro.2026.105253Integrating XtratuM and hardware accelerators in a model-based engineering workflow: The METASAT approachMar 01, 2026Microprocessors and MicrosystemsAlejandro J Calderón + 8 more +8CiteListenSave
Research Article10.1016/j.micpro.2025.105241Scalable hardware designs for Median Filters based on separable sorting networksDec 01, 2025Microprocessors and MicrosystemsCameron Vogeli + 1 more +1CiteListenSave
Research Article10.1016/s0141-9331(25)00097-3Editorial BoardDec 01, 2025Microprocessors and MicrosystemsCiteListenSave
Research Article310.1016/j.micpro.2025.105172Evaluating the performance of TinyML singular and ensemble techniques for intrusion detection in IoT networksSep 01, 2025Microprocessors and MicrosystemsAbderahmane Hamdouchi + 1 more +1CiteListenSave
Research Article10.1016/j.micpro.2025.105184Implementation and characterization of a fault-tolerant CCSDS 123 hardware accelerator under neutron radiationSep 01, 2025Microprocessors and MicrosystemsWesley Grignani + 5 more +5CiteListenSave
Research Article10.1016/j.micpro.2025.105189Analog to digital memory modeling for testAug 20, 2025Microprocessors and MicrosystemsD Ronga + 4 more +4CiteListenSave
Research Article10.1016/s0141-9331(25)00035-3Editorial BoardJun 01, 2025Microprocessors and MicrosystemsCiteListenSave
Research Article110.1016/j.micpro.2025.105142Efficient Coarse-Grained Reconfigurable Array architecture for machine learning applications in space using DARE65T library platformMar 01, 2025Microprocessors and MicrosystemsLuca Zulberti + 5 more +5CiteListenSave