# EfficientFi: Towards Large-Scale Lightweight WiFi Sensing via CSI Compression

arXiv: https://arxiv.org/abs/2204.04138 · HTML: https://mlsanity.com/paper/2204.04138/

## Key facts

- Cited by 35 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 44 references that are in the map.
- First posted on arXiv 8 Apr 2022.

## Builds on (most cited first, 9 of 9)

- [Neural Discrete Representation Learning](https://mlsanity.com/paper/1711.00937/) (2017)
- [Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation](https://mlsanity.com/paper/1308.3432/) (2013)
- [Model compression via distillation and quantization](https://mlsanity.com/paper/1802.05668/) (2018)
- [From Denoising to Compressed Sensing](https://mlsanity.com/paper/1406.4175/) (2014)
- [ARID: A New Dataset for Recognizing Action in the Dark](https://mlsanity.com/paper/2006.03876/) (2020)
- [CSI-based Fingerprinting for Indoor Localization: A Deep Learning Approach](https://mlsanity.com/paper/1603.07080/) (2016)
- [Distributed Deep Convolutional Compression for Massive MIMO CSI Feedback](https://mlsanity.com/paper/2003.04684/) (2020)
- [Deep Learning Based NLOS Identification with Commodity WLAN Devices](https://mlsanity.com/paper/1710.07450/) (2017)
- [CloudCV: Large Scale Distributed Computer Vision as a Cloud Service](https://mlsanity.com/paper/1506.04130/) (2015)

## Built on by (most cited first, 30 of 35)

- [Overview of Deep Learning-based CSI Feedback in Massive MIMO Systems](https://mlsanity.com/paper/2206.14383/) (2022)
- [SenseFi: A Library and Benchmark on Deep-Learning-Empowered WiFi Human Sensing](https://mlsanity.com/paper/2207.07859/) (2022)
- [TENT: Connect Language Models with IoT Sensors for Zero-Shot Activity Recognition](https://mlsanity.com/paper/2311.08245/) (2023)
- [WiMANS: A Benchmark Dataset for WiFi-based Multi-user Activity Sensing](https://mlsanity.com/paper/2402.09430/) (2024)
- [AutoFi: Towards Automatic WiFi Human Sensing via Geometric Self-Supervised Learning](https://mlsanity.com/paper/2205.01629/) (2022)
- [AirFi: Empowering WiFi-based Passive Human Gesture Recognition to Unseen Environment via Domain Generalization](https://mlsanity.com/paper/2209.10285/) (2022)
- [6G WavesFM: A Foundation Model for Sensing, Communication, and Localization](https://mlsanity.com/paper/2504.14100/) (2025)
- [GaitFi: Robust Device-Free Human Identification via WiFi and Vision Multimodal Learning](https://mlsanity.com/paper/2208.14326/) (2022)
- [Building 6G Radio Foundation Models with Transformer Architectures](https://mlsanity.com/paper/2411.09996/) (2024)
- [A Survey on Wi-Fi Sensing Generalizability: Taxonomy, Techniques, Datasets, and Future Research Prospects](https://mlsanity.com/paper/2503.08008/) (2025)
- [Multimodal Wireless Foundation Models](https://mlsanity.com/paper/2511.15162/) (2025)
- [RSCNet: Dynamic CSI Compression for Cloud-based WiFi Sensing](https://mlsanity.com/paper/2402.04888/) (2024)
- [Autosen: improving automatic wifi human sensing through cross-modal autoencoder](https://mlsanity.com/paper/2401.05440/) (2024)
- [Vector Quantization for Deep-Learning-Based CSI Feedback in Massive MIMO Systems](https://mlsanity.com/paper/2403.07355/) (2024)
- [Streamlining Multimodal Data Fusion in Wireless Communication and Sensor Networks](https://mlsanity.com/paper/2302.12636/) (2023)
- [Validation of Practicality for CSI Sensing Utilizing Machine Learning](https://mlsanity.com/paper/2409.07495/) (2024)
- [IBIS: A Hybrid Inception-BiLSTM and SVM Ensemble for Robust Doppler-based Human Activity Recognition](https://mlsanity.com/paper/2510.24936/) (2025)
- [LatentWave: JEPA Pretraining for Wireless Foundation Models](https://mlsanity.com/paper/2606.06373/) (2026)
- [HoloLLM: Multisensory Foundation Model for Language-Grounded Human Sensing and Reasoning](https://mlsanity.com/paper/2505.17645/) (2025)
- [VST-Pose: A Velocity-Integrated Spatiotem-poral Attention Network for Human WiFi Pose Estimation](https://mlsanity.com/paper/2507.09672/) (2025)
- [Generative AI Meets Wireless Sensing: Towards Wireless Foundation Model](https://mlsanity.com/paper/2509.15258/) (2025)
- [TinySense: Effective CSI Compression for Scalable and Accurate Wi-Fi Sensing](https://mlsanity.com/paper/2601.15838/) (2026)
- [SGSM: A Foundation-model-like Semi-generalist Sensing Model](https://mlsanity.com/paper/2406.16933/) (2024)
- [A Transformer-based Multimodal Fusion Model for Efficient Crowd Counting Using Visual and Wireless Signals](https://mlsanity.com/paper/2504.20178/) (2025)
- [Synergistic Localization and Sensing in MIMO-OFDM Systems via Mixed-Integer Bilevel Learning](https://mlsanity.com/paper/2507.07118/) (2025)
- [Anti-Jamming Sensing with Distributed Reconfigurable Intelligent Metasurface Antennas](https://mlsanity.com/paper/2508.04964/) (2025)
- [Cross-Domain Multi-Person Human Activity Recognition via Near-Field Wi-Fi Sensing](https://mlsanity.com/paper/2510.17816/) (2025)
- [Towards Trustworthy Wi-Fi CSI-based Sensing: Systematic Evaluation of Adversarial Robustness](https://mlsanity.com/paper/2511.20456/) (2025)
- [Hybrid Deep Learning Framework for CSI-Based Activity Recognition in Bandwidth-Constrained Wi-Fi Sensing](https://mlsanity.com/paper/2602.06983/) (2026)
- [Human Presence Detection via Wi-Fi Range-Filtered Doppler Spectrum on Commodity Laptops](https://mlsanity.com/paper/2603.10845/) (2026)

## Abstract (arXiv)

WiFi technology has been applied to various places due to the increasing requirement of high-speed Internet access. Recently, besides network services, WiFi sensing is appealing in smart homes since it is device-free, cost-effective and privacy-preserving. Though numerous WiFi sensing methods have been developed, most of them only consider single smart home scenario. Without the connection of powerful cloud server and massive users, large-scale WiFi sensing is still difficult. In this paper, we firstly analyze and summarize these obstacles, and propose an efficient large-scale WiFi sensing framework, namely EfficientFi. The EfficientFi works with edge computing at WiFi APs and cloud computing at center servers. It consists of a novel deep neural network that can compress fine-grained WiFi Channel State Information (CSI) at edge, restore CSI at cloud, and perform sensing tasks simultaneously. A quantized auto-encoder and a joint classifier are designed to achieve these goals in an end-to-end fashion. To the best of our knowledge, the EfficientFi is the first IoT-cloud-enabled WiFi sensing framework that significantly reduces communication overhead while realizing sensing tasks accurately. We utilized human activity recognition and identification via WiFi sensing as two case studies, and conduct extensive experiments to evaluate the EfficientFi. The results show that it compresses CSI data from 1.368Mb/s to 0.768Kb/s with extremely low error of data reconstruction and achieves over 98% accuracy for human activity recognition.