Is the Random Access Channel of LTE and LTE-A Suitable for M2M Communications? A Survey of Alternatives

By Andres Laya, L. Alonso, J. Alonso-Zarate. IEEE Communications Surveys and Tutorials, 2014

586 citations recorded by the source corpus.

The 3GPP has raised the need to revisit the design of next generations of cellular networks in order to make them capable and efficient to provide M2M services. One of the key challenges that has been identified is the need to enhance the operation of the random access channel of LTE and LTE-A. The current mechanism to request access to the system is known to suffer from congestion and overloading in the presence of a huge number of devices. For this reason, different research groups around the globe are working towards the design of more efficient ways of managing the access to these networks in such circumstances. This paper aims to provide a survey of the alternatives that have been proposed over the last years to improve the operation of the random access channel of LTE and LTE-A. A comprehensive discussion of the different alternatives is provided, identifying strengths and weaknesses of each one of them, while drawing future trends to steer the efforts over the same shooting line. In addition, while existing literature has been focused on the performance in terms of delay, the energy efficiency of the access mechanism of LTE will play a key role in the deployment of M2M networks. For this reason, a comprehensive performance evaluation of the energy efficiency of the random access mechanism of LTE is provided in this paper. The aim of this computer-based simulation study is to set a baseline performance upon which new and more energy-efficient mechanisms can be designed in the near future.

Subfields: Biomedical Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/5db0590ecb3708b46dbf95da65b5ff29613457ce

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

In Electrical and Electronic Engineering

Citations in the corpus

Cellular, Wide-Area, and Non-Terrestrial IoT: A Survey on 5G Advances and the Road Toward 6G (2021, methodology): “For this purpose, an access protocol is used to coordinate the data exchange between multiple active devices and the BS [249].”
M2M Communications in 3GPP LTE/LTE-A Networks: Architectures, Service Requirements, Challenges, and Applications (2015, background): “To support M2M communications in LTE/LTE-A, the following solutions have been proposed for controlling PRACH overload [46], [47].”
Software Defined Optical Networks (SDONs): A Comprehensive Survey (2015, background): “At the same time, machine-to-machine communication [462], [463] and energy savings [464], [465] have drawn research attention.”
Narrow Band Internet of Things (2017, methodology): “Researches generally set service arrival process as a homogeneous/compound Poisson process or an independent Bernoulli process [41] with identical distribution [40] and retransmission user number and packet retransmission number at queue head or channel state (busy/idle) in a certain time slot as st”
A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective (2018, background): “Along with the research and development of the 3rd Generation Partnership Project (3GPP) on LongTerm Evolution (LTE) and Long-Term Evolution Advanced (LTE-A) [54], and the fifth generation wireless network (5G), M2M has been identified as a key technology for the future of communication.”
Compressive Sensing-Based Adaptive Active User Detection and Channel Estimation: Massive Access Meets Massive MIMO (2019, background): “However, such grant-based solutions generally suffer from high access latency and require complicated collision resolution schemes in massive access scenarios [8].”
Dedicated networks for IoT : PHY / MAC state of the art and challenges (2015, methodology): “Although di ﬀ erent subtleties have been suggested to share optimally the RACH channel [4], the most e ﬃ cient way relies on providing MTDs and UEs (User Equipment) with separate access channels.”
Toward Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions (2018, methodology): “Sub-topics References Enabling technologies/protocols, challenges and applications [1,2,6,11,14,28–32] Random access schemes [22,33–35] IoT/mMTC Trafﬁc characterization and issues [36] Transmission scheduling [37,38] IoT big data analytics [19,39,40] QoS provisioning [41] Intelligence in 5G…”