CRII:CNS: Towards Spectrum and Energy Efficient Large-scale IoT Communications: A Cross-layer Optimization Approach

List of Personnel

Principle Investigator

  • Haijian Sun, Assistant Professor

Students

  • Hanwen Zhang (PhD Student)

  • Paul Kudyba (Graduate Student)

  • Xiaona Gao (co-advised by Dr. Yinghui Ye)

  • John Song (REU student)

  • Sterling Strohauer (Undergraduate Student)

Project Description

Recent years have witnessed the increasing proliferation of Internet of Things (IoT) devices, fueled by wide applications on healthcare, entertainment, monitoring, and smart homes. Enabling ubiquitous connectivity, massive traffic, and sustainable deployment of IoT demand for higher spectrum and energy efficiency (SE and EE). Existing approaches such as active communication (LoRA, Sigfox, etc) and passive ambient backscatter communication (AmBC) cannot meet those requirements. In particular, AmBC is widely considered as the solution to simultaneously address both spectrum and energy scarcity challenges. However, its inherit spectrum sharing mechanism limits device density and passive communication alone cannot provide quality of service (QoS).
The objective for this project is to improve both SE and EE performance while providing guaranteed QoS for IoT network at large-scale. Our approach is to enable IoT device with a Wireless Powered Hybrid Communication (WPHC) structure that can not only minimize energy footprint with energy harvesting from ambient signals, but also integrate both passive and active communication to support versatile QoS needs with efficient spectrum utilization through user cooperation. We focus on a cross-layer design with both physical (PHY) and medium access control (MAC) layer for SE and EE optimization. Software and hardware testbed will be developed to evaluate performance of this co-design.

overview 



This project starts from 05/2022. So far, the project has resulted the following publications.

Publications

  • Kudyba and H. Sun, “Autonomous Agricultural Monitoring with Aerial Drones and RF Energy-Harvesting Sensor Tags”, to appear, IEEE ISICN 2025.

  • H. Sun, X. Ma, R. Q. Hu, and R. Christensen, “Precise coil alignment for dynamic wireless charging of electric vehicles with rfid sensing”, IEEE Wireless Communications, 2025.

  • Song, X., Han, D., Shi, L., Sun, H., & Hu, R. Q. (2024). Relay assisted cooperative ambient backscatter communication with hybrid long-short packets. IEEE Transactions on Vehicular Technology. 2024.

  • Lu, Shuang, Yinghui Ye, Haijian Sun, Liqin Shi, and Rose Qingyang Hu. “Minimizing Total Transmission Time in Hybrid Active-Passive Mutualistic Symbiotic Radio.” IEEE Wireless Communications Letters, 2025.

  • Zhou, Wengang, Liqin Shi, Yinghui Ye, Xi Song, Haijian Sun, and Gan Zheng. “Performance Analysis for Relay Assisted Short-Packet Backscatter Communications.” IEEE Internet of Things Journal (2024).

  • Liqin Shi, Xiaoli Chu, Haijian Sun, and Guangyue Lu. “Wireless Powered OFDMA-MEC Networks with Hybrid Active-Passive Communications”. In: IEEE Internet of Things Journal (2023), pp. 1–1. DOI: 10.1109/JIOT.2023.3241088.

  • Zhipeng Liu, Yinghui Ye, Xiaoli Chu, and Haijian Sun. “Secrecy Performance of Backscatter Communications With Multiple Self-Powered Tags”. In: IEEE Communications Letters 26.12 (2022), pp. 2875–2879. DOI: 10.1109/LCOMM.2022.3201031.

  • Xiaona Gao, Yinghui Ye, Guangyue Lu, and Haijian Sun. “Throughput Fairness-Aware Optimization of Cognitive Backscatter Networks with Finite Alphabet Inputs”. In: 2022 IEEECIC International Conference on Communications in China (ICCC). 2022, pp. 463–467. DOI: 10.1109ICCC55456.2022.9880808.

  • Rui Xu, Liqin Shi, Yinghui Ye, and Haijian Sun. “Relay-Enabled Backscatter Communications: Linear Mapping and Resource Allocation”. In: IEEE Transactions on Vehicular Technology (2023, submitted).

  • Xiang Ma, Haijian Sun, Rose Qingyang Hu, and Yi Qian. “Approximate Wireless Communication for Federated Learning”. In Proceedings of the 2023 ACM Workshop on Wireless Security and Machine Learning (WiseML ’23), June 1, 2023, Guildford, United Kingdom.

REU Activities

  • We have our first REU student, John Song, joined our lab in Spring 2025! John is a freshman majored computer science at UGA. He is currently working on wireless channel simulation. John has contributed to a conference paper that plans to submit to IEEE Globecom.

  • We have another opening for REU, if you are interested, please send me your CV. (Please check eligibility before your application.)

Broader Impacts and Other Diseemination Activities

  • We will participate AERPAW's

  • We have tested battery-less tags in NSF AERPAW platform, resulted in our paper that summarized our findings. P. Kudyba and H. Sun, “Autonomous Agricultural Monitoring with Aerial Drones and RF Energy-Harvesting Sensor Tags”, to appear, IEEE ISICN 2025.

  • Paul leads our efforts in NSF AERPAW's “Find A Rover Challenge”, ranked 2nd and 3rd place in the final competition. See news from NSF: NSF PAWR Announcement

  • Undergraduate student Sterling Strohauer has designed a FM backscatter communication system and presented his design in UGA ECE's first student EXPO.

  • Graduate student Paul Kudyba has been testing a latest wireless power transfer and active BLE system (from a startup company). He is currently working on data collection, gateway design, and future integration to WPHC.

wphc 
aerpaw-test 

(a) AERPAW live test on our battery-less tags. (b) Stationary test.

Award Information

This project is generous supported by National Science Foundation CNS-2236449. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the foundation. NSF Link:

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