Research On Congestion Control Of Random Access Channel In Machine Type Communications

With the rapid development of3GPP-LTE, it is possible that ubiquitous wire-less network coverage can be provided by the network service providers. Under this situation, a new type of communication so called Machine Type Communi-cations (MTC) has emerged, and it provides a broad prospect for a variety of electronic automatic applications. Nowadays, machine type communications have been deep into every corner of human life, such as smart meters in smart grid, bridge safety monitoring sensors and a variety of smart indoor applications. Thus, how to guarantee the network’s Quality of Service (QoS) and provide an excellent user experience become a common concern. A key issue is that when a massive number of MTC devices initiate random access to the base station simultaneously, it will cause serious Random Access Channel (RACH) congestion and thus reduce the network’s QoS. Therefore, this dissertation will give some solutions for the random access channel congestion problem in machine type communications.Though several studies have been made on this issue recently, they are most-ly based on back-off scheme while ignoring the information provided by random access preamble detection that may enhance the network’s performance. In this dissertation, we firstly propose a self-adaptive strategy based on random access preamble power detection, and then introduce two random access channel con-gestion control strategies based on back-off scheme.A self-adaptive congestion control strategy based on random access preamble power detection is proposed and it can let the base-station make a more accurate prediction about the number of MTC device. The MTC devices can adjust their access time adaptively based on the base-station’s broadcasting information and thus guarantee the base-station load balancing. Through this strategy, we can mitigate random access channel congestion significantly and provide an excellent quality of service. Moreover, we use the maximum entropy principle to prove the rationality of the proposed scheme from the perspective of information theory. We also introduce the optimal access control algorithm and a congestion control strategy based on access threshold.Finally, ACB strategy and self-adaptive strategy are compared from three performance indicators by simulation experiments. The results show that our proposed self-adaptive congestion control strategy can handle serious random ac-cess channel congestion problems with a better performance, i.e. a higher access success probability and a lower average access delay. Therefore, it can improve the network’s quality of service and optimize the applications of machine type communications.