惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

G
Google Developers Blog
阮一峰的网络日志
阮一峰的网络日志
IT之家
IT之家
人人都是产品经理
人人都是产品经理
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
博客园 - 【当耐特】
WordPress大学
WordPress大学
Hugging Face - Blog
Hugging Face - Blog
博客园 - 叶小钗
罗磊的独立博客
宝玉的分享
宝玉的分享
月光博客
月光博客
V
V2EX
博客园 - 司徒正美
Vercel News
Vercel News
量子位
Y
Y Combinator Blog
美团技术团队
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
T
Tailwind CSS Blog
博客园 - Franky
小众软件
小众软件
I
InfoQ
A
About on SuperTechFans

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-Redundant OFDM Receiver Windowing for 5G Frames &...
Berker Pekoz, Zekeriyya Esat Ankarali, Selcuk Kose, Huseyin Arsl · 2019-11-11 · via eess.SP updates on arXiv.org

Contemporary receiver windowed orthogonal frequency division multiplexing (RW-OFDM) algorithms have limited adjacent channel interference (ACI) rejection capability under high delay spread and small Fast Fourier Transform (FFT) sizes. Cyclic prefix (CP) is designed to be longer than the maximum excess delay (MED) of the channel to accommodate such algorithms in current standards. The robustness of these algorithms can only be improved against these conditions by adopting additional extensions in a new backward incompatible standard. Such extensions would deteriorate the performance of high mobility vehicular communication systems in particular. In this paper, we present a low-complexity Hann RW-OFDM scheme that provides resistance against ACI without requiring any intersymbol interference (ISI)-free redundancies. While this scheme is backward compatible with current and legacy standards and requires no changes to the conventionally transmitted signals, it also paves the way towards future spectrotemporally localized and efficient schemes suitable for higher mobility vehicular communications. A Hann window effectively rejects unstructured ACI at the expense of structured and limited intercarrier interference (ICI) across data carriers. A simple maximum ratio combining successive interference cancellation (MRC-SIC) receiver is therefore proposed to resolve this induced ICI and receive symbols transmitted by standard transmitters currently in use. The computational complexity of the proposed scheme is comparable to that of contemporary RW-OFDM algorithms, while ACI rejection and bit-error rate performance is superior in both long and short delay spreads. Channel estimation using Hann RW-OFDM symbols is also discussed.