A Comprehensive Distributed Queue-Based Random Access Framework for mMTC in LTE/LTE-A Networks With Mixed-Type Traffic

• Published in: IEEE transactions on vehicular technology 2019-12, Vol.68 (12), p.12107-12120
• Main Authors: Bui, Anh-Tuan H., Nguyen, Chuyen T., Thang, Truong Cong, Pham, Anh T.
• Format: Article
• Language: English
• Subjects: 3GPP; 5G mobile communication; Computer simulation; Delay; Delays; Distributed Queue (DQ); Energy consumption; Estimation; Long Term Evolution; Long-Term Evolution (LTE); massive Machine-Type Communications (mMTC); Mobile communication systems; Protocols; Queues; Random access; random access (RA); Sociology; Traffic congestion; Traffic models; Wireless communications
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2019.2949024

Thanks to their ubiquitous coverage, Long-Term Evolution (LTE) networks are considered the most potential enabler for massive Machine-Type Communications (mMTC) service in fifth-generation (5G) context. LTE standard, however, was not designed for mMTC and scenarios where the massive Machine-Type Devices (MTDs) population try to access a network over a short period may overload the Random Access CHannel (RACH). Furthermore, there is no mechanism to prioritize urgent MTDs in such overload situation. The baseline Access Class Barring (B-ACB) scheme is thus adopted by the 3GPP to address both issues at a substantial cost of access delay. This paper follows a different approach and proposes a complete solution to the two main issues of cellular mMTC. We promote the use of a mechanism called Distributed Queueing (DQ), aided by a MAC-layer load estimation technique, to effectively resolve contentions between the MTDs to improve delay performance with minimal impacts to LTE access procedure and air interface. Then, by exploiting information related to congestion level from the DQ process, a dynamic access prioritization scheme can be realized without additional signaling overhead. Computer simulation under an mMTC-oriented traffic model shows that our framework outperforms the B-ACB in terms of both access delay and energy consumption when all devices are of equal importance. On the other hand, when devices of different priorities coexist, our framework with proper tuning also offers lower delay for all classes and lower overall energy consumption compared to both the baseline and a dynamic ACB solutions in massive bursty access scenarios.