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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
Spectral Coexistence of LDACS and DME: Analysis via Hardw...
Niharika Agrawal, S. J. Darak, Faouzi Bader · 2019-10-10 · via eess.SP updates on arXiv.org

To meet the exponentially increasing air traffic, L-band (960-1164 MHz) digital aeronautical communication system (LDACS) has been introduced. The LDACS aims to exploit the vacant spectrum between incumbent Distance Measuring Equipment (DME) signals and envisioned to follow an orthogonal frequency division multiplexing (OFDM) approach to support high-speed delay-sensitive multimedia services. This paper deals with the design and implementation of end-to-end LDACS the transceiver on the Zynq System on Chip platform, consisting of FPGA as programmable logic (PL) and ARM as processing system (PS). We consider OFDM based LDACS and improve it further using windowing and/or filtering. We propose a hardware-software co-design approach and analyze various transceiver configurations by dividing it into PL and PS. We demonstrate the flexibility offered by such a co-design approach to choose the configuration as well as word-length for a given area, delay and power constraints. The transceiver is also integrated with the programmable analog front-end to validate its functionality in the presence of various RF impairments and wireless channels and interference specific to the LDACS environment. Via in-depth performance analysis concerning parameters such as out-of-band attenuation, DME interference, bit-error-rate, word-length, and complexity, we demonstrate wide bandwidth filtered OFDM as an attractive solution for the next generation LDACS.