An Edge Computing Paradigm for Massive IoT Connectivity over High-Altitude Platform Networks
Malong Ke, Zhen Gao, Yang Huang, Guoru Ding, Derrick Wing Kwan Ng,, Qihui Wu, and Jun Zhang

TL;DR
This paper proposes a high-altitude platform network-enabled edge computing paradigm to address massive IoT connectivity challenges, leveraging aerial cell-free massive MIMO and grant-free access for low latency and high efficiency.
Contribution
It introduces a novel HAP-enabled aerial cell-free massive MIMO network with cooperative edge servers and grant-free access schemes for scalable IoT connectivity.
Findings
Demonstrates the effectiveness of the proposed HAP network architecture.
Shows improved connectivity and latency performance in case studies.
Identifies key challenges and future research directions.
Abstract
With the advent of the Internet-of-Things (IoT) era, the ever-increasing number of devices and emerging applications have triggered the need for ubiquitous connectivity and more efficient computing paradigms. These stringent demands have posed significant challenges to the current wireless networks and their computing architectures. In this article, we propose a high-altitude platform (HAP) network-enabled edge computing paradigm to tackle the key issues of massive IoT connectivity. Specifically, we first provide a comprehensive overview of the recent advances in non-terrestrial network-based edge computing architectures. Then, the limitations of the existing solutions are further summarized from the perspectives of the network architecture, random access procedure, and multiple access techniques. To overcome the limitations, we propose a HAP-enabled aerial cell-free massive…
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Taxonomy
TopicsUAV Applications and Optimization · Opportunistic and Delay-Tolerant Networks · Advanced Neural Network Applications
