Abstract
The massive wireless networks (MWNs) enable surging applications for the Internet of Things and cyber physical systems. In these applications, nodes typically exhibit stringent power constraints, limited computing capabilities, and sporadic traffic patterns. This paper develops a spatiotemporal model to characterize and design uncoordinated multiple access (UMA) strategies for MWNs. By combining stochastic geometry and queueing theory, the paper quantifies the scalability of UMA via the maximum spatiotemporal traffic density that can be accommodated in the network, while satisfying the target operational constraints (e.g., stability) for a given percentile of the nodes. The developed framework is then used to design UMA strategies that stabilize the node data buffers and achieve desirable latency, buffer size, and data rate.
| Original language | English |
|---|---|
| Article number | 8688635 |
| Pages (from-to) | 918-931 |
| Number of pages | 14 |
| Journal | IEEE/ACM Transactions on Networking |
| Volume | 27 |
| Issue number | 3 |
| DOIs | |
| State | Published - Jun 2019 |
Bibliographical note
Publisher Copyright:© 1993-2012 IEEE.
Keywords
- Internet of Things
- Wireless networks
- meta distribution of the SINR
- uncoordinated multiple access
ASJC Scopus subject areas
- Software
- Computer Science Applications
- Computer Networks and Communications
- Electrical and Electronic Engineering