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

Last Week in AI
Last Week in AI
阮一峰的网络日志
阮一峰的网络日志
P
Proofpoint News Feed
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
MongoDB | Blog
MongoDB | Blog
云风的 BLOG
云风的 BLOG
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
J
Java Code Geeks
WordPress大学
WordPress大学
T
The Blog of Author Tim Ferriss
V
Visual Studio Blog
小众软件
小众软件
Microsoft Azure Blog
Microsoft Azure Blog
博客园_首页
IT之家
IT之家
Vercel News
Vercel News
C
Check Point Blog
Google DeepMind News
Google DeepMind News
月光博客
月光博客
D
DataBreaches.Net
酷 壳 – CoolShell
酷 壳 – CoolShell
美团技术团队
Y
Y Combinator Blog
Hugging Face - Blog
Hugging Face - Blog

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
Transmit Power Optimization for Integrated Sensing and Ba...
S. Zargari, D. Galappaththige, C. Tellambura · 2024-04-30 · via eess.SP updates on arXiv.org

Ambient Internet of Things networks use low-cost, low-power backscatter tags in various industry applications. By exploiting those tags, we introduce the integrated sensing and backscatter communication (ISABC) system, featuring multiple backscatter tags, a user (reader), and a full-duplex base station (BS) that integrates sensing and (backscatter) communications. The BS undertakes dual roles of detecting backscatter tags and communicating with the user, leveraging the same temporal and frequency resources. The tag-reflected BS signals offer data to the user and enable the BS to sense the environment simultaneously. We derive both user and tag communication rates and the sensing rate of the BS. We jointly optimize the transmit/received beamformers and tag reflection coefficients to minimize the total BS power. To solve this problem, we employ the alternating optimization technique. We offer a closed-form solution for the received beamformers while utilizing semi-definite relaxation and slack-optimization for transmit beamformers and power reflection coefficients, respectively. For example, with ten transmit/reception antennas at the BS, ISABC delivers a 75% sum communication and sensing rates gain over a traditional backscatter while requiring a 3.4% increase in transmit power. Furthermore, ISABC with active tags only requires a 0.24% increase in transmit power over conventional integrated sensing and communication.