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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
Non-Coherent and Backscatter Communications: Enabling Ult...
Syed Junaid Nawaz, Shree Krishna Sharma, Babar Mansoor, Mohmamma · 2020-05-22 · via eess.SP updates on arXiv.org

With the commencement of the 5G of wireless networks, researchers around the globe have started paying their attention to the imminent challenges that may emerge in the beyond 5G (B5G) era. Various revolutionary technologies and innovative services are offered in 5G networks, which, along with many principal advantages, are anticipated to bring a boom in the number of connected wireless devices and the types of use-cases that may cause the scarcity of network resources. These challenges partly emerged with the advent of massive machine-type communications (mMTC) services, require extensive research innovations to sustain the evolution towards enhanced-mMTC (e-mMTC) with the scalable network cost in 6\textsuperscript{th} generation (6G) wireless networks. Towards delivering the anticipated massive connectivity requirements with optimal energy and spectral efficiency besides low hardware cost, this paper presents an enabling framework for 6G networks, which utilizes two emerging technologies, namely, non-coherent communications and backscatter communications (BsC). Recognizing the coherence between these technologies for their joint potential of delivering e-mMTC services in the B5G era, a comprehensive review of their state-of-the-art is conducted. The joint scope of non-coherent and BsC with other emerging 6G technologies is also identified, where the reviewed technologies include unmanned aerial vehicles (UAVs)-assisted communications, visible light communications (VLC), quantum-assisted communications, reconfigurable large intelligent surfaces (RLIS), non-orthogonal multiple access (NOMA), and machine learning-aided intelligent networks. Subsequently, the scope of these enabling technologies for different device types, service types, and optimization parameters is analyzed...