CIF: Small: Robust Signal Recovery and Grant-Free Access for Massive IoT Connectivity

点击翻译按钮获取中文摘要

Recent advances in information technologies, computers, and microelectronics have led to transformative innovations and broad deployment of smart devices with data computation and communication capabilities. Internet of things (IoT) products and services are playing increasingly important roles in many fields such as smart city, e-health, agriculture, safety, security, and environmental protection. In particular, low-power massive IoT applications already account for over 60% of the IoT market which continues to expand at a relentless pace. Low-power wireless IoT devices are primarily deployed for sensing and data collection with uplink dominated traffic. Given the massive number of such devices, traditional channel access based on coordinated scheduling between base-station and the multitude of end-user devices consumes too much bandwidth and device energy. Uncoordinated uplink access can overcome both obstacles but at the risk of multi-device signal collisions. This research project develops novel technologies for reliable and efficient reception of simultaneous multi-device wireless transmissions in networks that support massive number of low power IoT terminals. This work contributes to vital technological advancement that can significantly impact the current and future applications of wireless IoT services. The research outcomes shall contribute substantially to the theoretical foundation of signal processing and optimization, as well as to the design of network protocols to support massive connectivity in practical 5G and Beyond wireless systems.Specifically, the project activities focus on the design, analysis, and optimization of advanced wireless network receivers to effectively decode and recover data packets that are often in collision when multiple devices spontaneously transmit over their shared wireless channel spectrum. Effective recovery of data packets under collision improves both spectral efficiency and energy efficiency for a large population of low power devices. Specifically, the researchers shall investigate novel solutions for simultaneous signal recovery from multiple device transmissions in both local area and wide area network environments. Subject to unknown channel distortions and mutual interference, wireless receivers must recover co-channel user packets from simultaneous uplink transmissions via blind demixing. The research team will tackle the challenging and difficult problem of blind demixing by advancing the theory, algorithm, and hardware for low-rank and sparse matrix completion. The researchers shall develop novel algorithms that are faster and more effective with desired global convergence.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.