2016/09/17 by Mohammad Gharbieh, Hesham ElSawy, Gharbieh, Mohammad +5
Computer Science · Engineering · #Advanced MIMO Systems Optimization #Cooperative Communication and Network Coding #FOS: Computer and information sciences #Information Theory (cs.IT) #Opportunistic and Delay-Tolerant Networks
paper · pdf · doi:10.48550/arxiv.1609.05384
openalex publication_date 2016/09/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The Internet of Things (IoT) is large-scale by nature, which is manifested by\nthe massive number of connected devices as well as their vast spatial\nexistence. Cellular networks, which provide ubiquitous, reliable, and efficient\nwireless access, are natural candidates to provide the first-mile access for\nthe data tsunami to be generated by the IoT. However, cellular networks may\nhave scalability problems to provide uplink connectivity to massive numbers of\nconnected things. To characterize the scalability of cellular uplink in the\ncontext of IoT networks, this paper develops a traffic-aware spatiotemporal\nmathematical model for IoT devices supported by cellular uplink connectivity.\nThe developed model is based on stochastic geometry and queueing theory to\naccount for the traffic requirement per IoT device, the different transmission\nstrategies, and the mutual interference between the IoT devices. To this end,\nthe developed model is utilized to characterize the extent to which cellular\nnetworks can accommodate IoT traffic as well as to assess and compare three\ndifferent transmission strategies that incorporate a combination of\ntransmission persistency, backoff, and power-ramping. The analysis and the\nresults clearly illustrate the scalability problem imposed by IoT on cellular\nnetwork and offer insights into effective scenarios for each transmission\nstrategy.\n