Massive Access for Artificial Intelligent of Things (AIoT)

This GitHub repository is a collection of code from my doctoral research on multiple access.

This project aims to investigate and propose efficient multiple access mechanisms to optimize communication efficiency among massive devices in future wireless networks. The ultimate goal is to contribute to the advancement of next-generation wireless networks, making them more streamlined and intelligent.

[ISIT'23] Unsourced Random Access for AirComp

This paper proposes a communication-efficient digital over-the-air computation scheme, thereby enhancing compatibility with both present and future wireless networks.

The schematic diagram of the proposed massive digital AirComp scheme.

[TCOM'23] Integrated Sensing and Communication

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This paper proposes a grant-free massive access scheme based on the millimeter wave (mmWave) extra-large-scale multiple-input multiple-output (XL-MIMO), to support massive Internet-of-Things (IoT) devices with low latency, high data rate, and high localization accuracy in the next-generation networks.

Typical massive IoT access in smart factory scenarios.

XL-MIMO for massive access and the localization.

[JSAC'22] Non-Cohenrent Grant-Free Random Access

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A non-coherent grant-free random access scheme is proposed in MIMO-OFDM systems, enabling efficient massive access for cost- and energy-limited IoT devices.

Comparison of the coherent GFRA schemes and the proposed non-coherent GFRA scheme.

[TWC'21,TVT'20] Media-Modulation for Grant-Free Random Access

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As electromagnetic materials continue to advance, media-based modulation (MBM) has emerged as a promising technique to improve the energy and spectrum efficiency of transmitters. This paper suggests an effective grant-free random access scheme tailored for IoT devices employing MBM.

This letter proposes a media modulation based massive machine-type communications solution for increasing the throughput, where a massive multi-input multi-output based base station is used for enhancing the detection performance.

The MTDs adopt media modulation to access the mMIMO BSs.

Communication process for coded media modulation based mMTC.

Citations

If you use this project, please cite the relevant original publications for the models and datasets, and cite this project as:

Book and Survey

@article{gao2023compressive,
  title={Compressive sensing-based grant-free massive access for 6G massive communication},
  author={Gao, Zhen and Ke, Malong and Mei, Yikun and Qiao, Li and Chen, Sheng and Ng, Derrick Wing Kwan and Poor, H Vincent},
  journal={IEEE Internet of Things Journal},
  year={2023},
  publisher={IEEE}
}
@book{gao2022massive,
  author = {Gao, Z. and Ke, M. and Qiao, L. and Mei, Y.},
  title = {Massive IoT Access for 6G},
  year = {2022},
  publisher = {Springer},
  address = {Singapore}
}

Massive Digital AirComp

@inproceedings{qiao2023unsourced,
  title={Unsourced massive access-based digital over-the-air computation for efficient federated edge learning},
  author={Qiao, Li and Gao, Zhen and Li, Zhongxiang and G{\"u}nd{\"u}z, Deniz},
  booktitle={2023 IEEE International Symposium on Information Theory (ISIT)},
  pages={2003--2008},
  year={2023},
  organization={IEEE}
}

Near-Feild ISAC

@article{qiao2023sensing,
  title={Sensing User’s Activity, Channel, and Location with Near-Field Extra-Large-Scale MIMO},
  author={Qiao, Li and Liao, Anwen and Li, Zhuoran and Wang, Hua and Gao, Zhen and Gao, Xiang and Su, Yu and Xiao, Pei and You, Li and Ng, Derrick Wing Kwan},
  journal={IEEE transactions on communications},
  year={2023},
  publisher={IEEE}
}

Non-Cohenrent GFRA

@article{qiao2022joint,
  title={Joint activity and blind information detection for UAV-assisted massive IoT access},
  author={Qiao, Li and Zhang, Jun and Gao, Zhen and Zheng, Dezhi and Hossain, Md Jahangir and Gao, Yue and Ng, Derrick Wing Kwan and Di Renzo, Marco},
  journal={IEEE Journal on Selected Areas in Communications},
  year={2022},
  volume={40},
  number={5},
  pages={1489-1508},
  doi={10.1109/JSAC.2022.3143255}}
}

Media-Modulation GFRA

@article{qiao2021massive,
  title={Massive access in media modulation based massive machine-type communications},
  author={Qiao, Li and Zhang, Jun and Gao, Zhen and Ng, Derrick Wing Kwan and Di Renzo, Marco and Alouini, Mohamed-Slim},
  journal={IEEE Transactions on Wireless Communications},
  volume={21},
  number={1},
  pages={339--356},
  year={2021},
  publisher={IEEE}
}
@article{qiao2020compressive,
  title={Compressive sensing based massive access for IoT relying on media modulation aided machine type communications},
  author={Qiao, Li and Zhang, Jun and Gao, Zhen and Chen, Sheng and Hanzo, Lajos},
  journal={IEEE Transactions on Vehicular Technology},
  volume={69},
  number={9},
  pages={10391--10396},
  year={2020},
  publisher={IEEE}
}