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eess.SP updates on arXiv.org

ECG-biometrics-bench: A Unified Framework for Reproducible Benchmarking of ECG Biometrics Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning Towards Improving Speaker Distance Estimation through Generative Impulse Response Augmentation Federated Learning with Hypergradient-based Online Update of Aggregation Weights Soft Graph Diffusion Transformer for MIMO Detection SPLICE: Latent Diffusion over JEPA Embeddings for Conformal Time-Series Inpainting Sequential Inference for Gaussian Processes: A Signal Processing Perspective Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework Recent Advances in mm-Wave and Sub-THz/THz Oscillators for FutureG Technologies Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods Super-resolution Multi-signal Direction-of-Arrival Estimation by Hankel-structured Sensing and Decomposition Hankel and Toeplitz Rank-1 Decomposition of Arbitrary Matrices with Applications to Signal Direction-of-Arrival Estimation Adaptive Transform Coding for Semantic Compression EdgeSpike: Spiking Neural Networks for Low-Power Autonomous Sensing in Edge IoT Architectures Sparse Graph Learning from Sparse Data via Fiedler Number Maximization A Deep Learning Model for Battery State Prediction towards Intelligent Energy Management Transfer Learning for Tonal Noise Prediction in VRF Units Using Thermodynamic and Vibration Signals EVT-Based Generative AI for Tail-Aware Channel Estimation Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing BandRouteNet: An Adaptive Band Routing Neural Network for EEG Artifact Removal Phase-Separated Complex Hilbert PCA on Markerless 3D Pose Estimation Data: A Global Phase Network and Its Extension to a Continuous Field on the Body Surface Selective Correlation Based Knowledge Distillation for Ground Reaction Force Estimation Deep Learning-Enabled Dissolved Oxygen Sensing in Biofouling Environments for Ocean Monitoring Speech Enhancement Based on Drifting Models Robust and Clinically Reliable EEG Biomarkers: A Cross Population Framework for Generalizable Parkinson's Disease Detection An AI-Based Supervisory Measurement Integrity Validation Layer for Cyber-Resilient AC/DC Protection in Inverter-Based Microgrids Explainable AI in Speaker Recognition -- Making Latent Representations Understandable Time-Localized Parametric Decomposition of Respiratory Airflow for Sub-Breath Analysis NAKUL-Med: Spectral-Graph State Space Models with Dynamics Kernels for Medical Signals An Algorithm for On-Sensor Agnostic Detection of Changes in Human Activity for Ultra-Low-Power Applications
Hardware-Software Codesign for Software Defined Radio: IE...
Rafik Zitouni, Hacene Bouaroua, Benaoumeur Senouci · 2020-03-21 · via eess.SP updates on arXiv.org

Software Defined Radio (SDR) platforms are useful tools to design new wireless technologies or to improve specifications of existing ones. The IEEE 802.11p is the de-facto standard for Wireless Vehicular Ad-hoc NETworks (VANETs). It has been implemented on GNU Radio SDR [1], which experiences frames decoding/encoding latency. In this paper an FPGA based SDR is proposed as a solution to accelerate frame decoding of IEEE 802.11p waveforms. We share our experience in designing and validating an SDR on the top of real FPGA based embedded hardware architecture. On the top of an FPGA Zynq platform, we port an SDR GNU Radio following hardware/software (HW/SW) codesign approach. A real time profiling of the SDR system shows that the OFDM equalizer with FFT software function is the most time consuming task of the whole SDR receiver functions (34.74%). We suggest hardware acceleration of the FFT processing function using the free logic gates of the FPGA Zynq as a Hardware (HW) accelerator. The HW OFDM Equalizer with FFT sub-function could accelerate the SDR chain processing in comparison with a pure software implementation. Our FPGA based SDR design is a key step toward proposing an embedded SDR. It would be an alternative for not only the IEEE 802.11p standard but for any OFDM based SDR.