Power Efficient Time-Division Random-Access Model Based in Wireless Communication Networks

Abstract

The conventional infrastructure for mobile-communication is used for providing internet-of-things (IoT) services by the third-generation partnership project (3GPP) with the help of the recently developed cellular internet-of-things (CIoT) scheme. Random-access procedure can be used for connecting the large number of IoT devices using the CIoT systems. This process is advantages as the huge devices are accessed in a concurrent manner. When random access procedures are used simultaneously on a massive number of devices, the probability of congestion is high. This can be controlled to a certain extent through the time division scheme. A power efficient time-division random access model is developed in this paper to offer reliable coverage enhancement (CE) based on the coverage levels (CL). The quality of radio-channel is used for categorization of the CIoT devices after assigning them with CLs. The performance of random-access model can be improved and the instantaneous contention is relaxed greatly by distributing the loads based on their coverage levels into different time periods. Markov chain is used for mathematical analysis of the behavior and state of the devices. The probability of blocking access, success rate and collision control are enhanced by a significant level using this model in comparison to the conventional schemes.