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.