Uplink access control for machine-type communications in LTE-A networks

Summary A major challenge for the development of the upcoming generations of wireless systems is to match the massive expansion of the Internet of things (IoT) applications along with the traditional human communication. Recently, 3rd Generation Partnership Project (3GPP) has suggested the use of LTE‐A to support machine‐to‐machine (M2M) communications to realize the IoT applications. One of the key concerns is the random‐access procedure in LTE‐A, the existence of a massive number of M2M devices results in system overload and congestion in the random‐access channel (RACH). In this paper, we present a new extension to the active barring‐based random‐access scheme. The proposed traffic load access barring (TLAB) RACH access scheme considers the dynamic changes in system traffic when setting the barring information. At the same time, the proposed scheme avoids unnecessary barring of some M2M devices. Our scheme improves the access delay that results from the barring of M2M devices by applying a new rule in the selection of classes to bar and classes to unbar. The simulation results show the superiority of our scheme in terms of success probability, average access delay, and average power consumption.

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“…The Hwang et al 4 propose a dynamic random‐access scheme for LTE‐A. The proposed scheme reduces the effect of M2M communication on H2H traffic.…”

Section: Related Workmentioning

confidence: 99%

Traffic load access barring scheme for random‐access channel in massive machine‐to‐machine and human‐to‐human devices coexistence in LTE‐A

Shukry

Fahmy

2021

Int J Communication

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“…However, unlike the 3GPP specifications, the authors assume that a control-loop for congestion between the UEs and the eNodeB is available, which creates signaling overhead. In [13], a dynamic mechanism for access control in LTE-A is proposed, to reduce the impact that massive M2M communications can have on H2H traffic. Also, in this work the authors classify the traffic, allowing prioritization.…”

Section: Related Workmentioning

confidence: 99%

Dynamic access class barring parameter tuning in LTE-A networks with massive M2M traffic

Tello-Oquendo

Vidal

Pla

et al. 2018

2018 17th Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net)

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Machine-to-machine (M2M) communication is one of the leading facilitators of the Internet of Things environment by offering ubiquitous applications and services. Using cellular networks for providing M2M connectivity brings several advantages such as extended coverage, security, robust management, and lower deployment costs; however, coexistence with a large number of M2M devices is still an essential challenge in LTE-A networks, in part due to the difficulty in allowing simultaneous access. Although the random access procedure in LTE-A is adequate for human-to-human (H2H) communications, when M2M communications are involved congestion control is required. One of the congestion control schemes suggested by the 3GPP is Access Class Barring (ACB), which can reduce the number of simultaneous users contending for access. However, it is still not clear how to adapt ACB parameters in bursty and heavy-loaded scenarios, such as those that appear in M2M communications. We propose a dynamic ACB scheme in which an estimate of the current number of M2M devices in backoff state is used to adjust in real-time the barring rate parameter. We evaluate the key performance indicators (KPIs) of dynamic ACB in several scenarios with different degrees of traffic load and compare them with those of a static ACB with optimal parameters. We show that the dynamic ACB outperforms the static one offering shorter access delay and higher successful access probability, while its impact on H2H communications KPIs is negligible. Besides, our proposed scheme conforms with the LTE-A specification so that it can be included as a viable solution. Index Terms-Access class barring (ACB); cellular-systems; machine-to-machine communications; performance analysis; 5G. I. INTRODUCTION I NTERNET of Things (IoT) is emerging as one of the key transforming technologies to interconnect physical objects that interact with people, other physical objects, and systems to benefit society in unprecedented ways. It is predicted that the number of connected devices increases to 29 billion by 2022 [1], and the global mobile data traffic achieves 49 exabytes (10 18 bytes) by 2021 [2]. Machine-to-machine (M2M) communication is one of the leading facilitators of the IoT environment by offering ubiquitous applications and services. Unlike human-to-human (H2H) communication, distinct features of M2M traffic requires specialized and inter-operable communication technologies. Cellular networks are the natural choice to satisfy these requirements and handling a significant part of this emerging traffic due to their already existing infrastructures, extensive area coverage, and high-performance capabilities. Therefore, M2M communication over cellular

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“…In the literature, several studies address the EAB mechanism. Some of them misinterpret the EAB behavior or do not conform to 3GPP specifications (Kim et al, 2017;Hwang et al, 2016). On the other hand, studies such as (Phuyal et al, 2012;Larmo & Susitaival, 2012;Cheng et al, 2015;Toor & Jin, 2017) analyze EAB mainly in terms of access success probability and access delay.…”

Section: Introductionmentioning

confidence: 99%

Restricción de Acceso Extendida para Manejar Despliegues Masivos de Comunicaciones Tipo Máquina (mMTC)

et al. 2018

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La comunicación masiva tipo máquina (mMTC) ha presentado un momento prometedor para generar conexiones potentes y ubicuas que enfrentan muchos desafíos nuevos. Las redes celulares son la solución potencial debido a su amplio despliegue de infraestructura, confiabilidad, seguridad y eficiencia. En las redes mMTC basadas en comunicación celular, el canal de acceso aleatorio se utiliza para establecer la conexión entre los dispositivos MTC y las estaciones base (eNBs), donde el principal desafío es la conectividad escalable y eficiente para una enorme cantidad de dispositivos. Para hacer frente a esto, el Third Generation Partnership Project (3GPP) ha sugerido la restricción de acceso extendida (EAB) como un mecanismo para el control de la congestión. Las eNBs activan o desactivan EAB utilizando un coeficiente de congestión. En este documento se presenta un enfoque para implementar el coeficiente de congestión de modo que EAB pueda operar y así manejar los episodios de congestión en escenarios de mMTC. También se examina el rendimiento de EAB bajo diferentes cargas de tráfico de MTC y configuraciones de ciclo de paginación en términos de indicadores clave de rendimiento de la red (KPIs). Los resultados numéricos demuestran la efectividad del método propuesto para detectar episodios de congestión. Además se demuestra que el aumento del valor de la configuración del ciclo de paginación influye en el comportamiento de la red bajo EAB.

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Uplink access control for machine-type communications in LTE-A networks

Cited by 9 publications

References 15 publications

Traffic load access barring scheme for random‐access channel in massive machine‐to‐machine and human‐to‐human devices coexistence in LTE‐A

Traffic load access barring scheme for random‐access channel in massive machine‐to‐machine and human‐to‐human devices coexistence in LTE‐A

Dynamic access class barring parameter tuning in LTE-A networks with massive M2M traffic

Restricción de Acceso Extendida para Manejar Despliegues Masivos de Comunicaciones Tipo Máquina (mMTC)

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