Filtering Methods for Efficient Dynamic Access Control in 5G Massive Machine-Type Communication Scenarios

[EN] One of the three main use cases of the fifth generation of mobile networks (5G) is massive machine-type communications (mMTC). The latter refers to the highly synchronized accesses to the cellular base stations from a great number of wireless devices, as a product of the automated exchange of small amounts of data. Clearly, an efficient mMTC is required to support the Internet-of-Things (IoT). Nevertheless, the method to change from idle to connected mode, known as the random access procedure (RAP), of 4G has been directly inherited by 5G, at least, until the first phase of standardization. Research has demonstrated the RAP is inefficient to support mMTC, hence, access control schemes are needed to obtain an adequate performance. In this paper, we compare the benefits of using different filtering methods to configure an access control scheme included in the 5G standards: the access class barring (ACB), according to the intensity of access requests. These filtering methods are a key component of our proposed ACB configuration scheme, which can lead to more than a three-fold increase in the probability of successfully completing the random access procedure under the most typical network configuration and mMTC scenario.This research has been supported in part by the Ministry of Economy and Competitiveness of Spain under Grant TIN2013-47272-C2-1-R and Grant TEC2015-71932-REDT. The research of I. Leyva-Mayorga was partially funded by grant 383936 CONACYT-GEM 2014.Leyva-Mayorga, I.; Rodríguez-Hernández, MA.; Pla, V.; Martínez Bauset, J. (2019). Filtering Methods for Efficient Dynamic Access Control in 5G Massive Machine-Type Communication Scenarios. Electronics. 8(1):1-18. https://doi.org/10.3390/electronics8010027S11881Laya, A., Alonso, L., & Alonso-Zarate, J. (2014). Is the Random Access Channel of LTE and LTE-A Suitable for M2M Communications? A Survey of Alternatives. 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Adaptive access class barring for efficient mMTC

[EN] In massive machine-type communications (mMTC), an immense number of wireless devices communicate autonomously to provide users with ubiquitous access to information and services. The current 4G LTE-A cellular system and its Internet of Things (IoT) implementation, the narrowband IoT (NB-IoT), present appealing options for the interconnection of these wireless devices. However, severe congestion may arise whenever a massive number of highly-synchronized access requests occur. Consequently, access control schemes, such as the access class barring (ACB), have become a major research topic. In the latter, the precise selection of the barring parameters in a real-time fashion is needed to maximize performance, but is hindered by numerous characteristics and limitations of the current cellular systems. In this paper, we present a novel ACB configuration (ACBC) scheme that can be directly implemented at the cellular base stations. In our ACBC scheme, we calculate the ratio of idle to total available resources, which then serves as the input to an adaptive filtering algorithm. The main objective of the latter is to enhance the selection of the barring parameters by reducing the effect of the inherent randomness of the system. Results show that our ACBC scheme greatly enhances the performance of the system during periods of high congestion. In addition, the increase in the access delay during periods of light traffic load is minimal.This research has been supported in part by the Ministry of Economy and Competitiveness of Spain under Grant TIN2013-47272-C2-1-R and Grant TEC2015-71932-REDT. The research of I. Leyva-Mayorga was partially funded by grant 383936 CONACYT-GEM 2014.Leyva-Mayorga, I.; Rodríguez-Hernández, MA.; Pla, V.; Martínez Bauset, J.; Tello-Oquendo, L. (2019). Adaptive access class barring for efficient mMTC. Computer Networks. 149:252-264. https://doi.org/10.1016/j.comnet.2018.12.003S25226414

Code-Expanded Random Access for Machine-Type Communications

The random access methods used for support of machine-type communications (MTC) in current cellular standards are derivatives of traditional framed slotted ALOHA and therefore do not support high user loads efficiently. Motivated by the random access method employed in LTE, we propose a novel approach that is able to sustain a wide random access load range, while preserving the physical layer unchanged and incurring minor changes in the medium access control layer. The proposed scheme increases the amount of available contention resources, without resorting to the increase of system resources, such as contention sub-frames and preambles. This increase is accomplished by expanding the contention space to the code domain, through the creation of random access codewords. Specifically, in the proposed scheme, users perform random access by transmitting one or none of the available LTE orthogonal preambles in multiple random access sub-frames, thus creating access codewords that are used for contention. In this way, for the same number of random access sub-frames and orthogonal preambles, the amount of available contention resources is drastically increased, enabling the support of an increased number of MTC users. We present the framework and analysis of the proposed code-expanded random access method and show that our approach supports load regions that are beyond the reach of current systems.Comment: 6 Pages, 7 figures, This paper has been submitted to GC'12 Workshop: Second International Workshop on Machine-to-Machine Communications 'Key' to the Future Internet of Thing

Massive M2M Access with Reliability Guarantees in LTE Systems

Machine-to-Machine (M2M) communications are one of the major drivers of the cellular network evolution towards 5G systems. One of the key challenges is on how to provide reliability guarantees to each accessing device in a situation in which there is a massive number of almost-simultaneous arrivals from a large set of M2M devices. The existing solutions take a reactive approach in dealing with massive arrivals, such as non-selective barring when a massive arrival event occurs, which implies that the devices cannot get individual reliability guarantees. In this paper we propose a proactive approach, based on a standard operation of the cellular access. The access procedure is divided into two phases, an estimation phase and a serving phase. In the estimation phase the number of arrivals is estimated and this information is used to tune the amount of resources allocated in the serving phase. Our results show that the proactive approach is instrumental in delivering high access reliability to the M2M devices.Comment: Accepted for presentation in ICC 201

On the Reliability of LTE Random Access: Performance Bounds for Machine-to-Machine Burst Resolution Time

Random Access Channel (RACH) has been identified as one of the major bottlenecks for accommodating massive number of machine-to-machine (M2M) users in LTE networks, especially for the case of burst arrival of connection requests. As a consequence, the burst resolution problem has sparked a large number of works in the area, analyzing and optimizing the average performance of RACH. However, the understanding of what are the probabilistic performance limits of RACH is still missing. To address this limitation, in the paper, we investigate the reliability of RACH with access class barring (ACB). We model RACH as a queuing system, and apply stochastic network calculus to derive probabilistic performance bounds for burst resolution time, i.e., the worst case time it takes to connect a burst of M2M devices to the base station. We illustrate the accuracy of the proposed methodology and its potential applications in performance assessment and system dimensioning.Comment: Presented at IEEE International Conference on Communications (ICC), 201

Exploiting the Capture Effect to Enhance RACH Performance in Cellular-Based M2M Communications

Cellular-based machine-to-machine (M2M) communication is expected to facilitate services for the Internet of Things (IoT). However, because cellular networks are designed for human users, they have some limitations. Random access channel (RACH) congestion caused by massive access from M2M devices is one of the biggest factors hindering cellular-based M2M services because the RACH congestion causes random access (RA) throughput degradation and connection failures to the devices. In this paper, we show the possibility exploiting the capture effects, which have been known to have a positive impact on the wireless network system, on RA procedure for improving the RA performance of M2M devices. For this purpose, we analyze an RA procedure using a capture model. Through this analysis, we examine the effects of capture on RA performance and propose an Msg3 power-ramping (Msg3 PR) scheme to increase the capture probability (thereby increasing the RA success probability) even when severe RACH congestion problem occurs. The proposed analysis models are validated using simulations. The results show that the proposed scheme, with proper parameters, further improves the RA throughput and reduces the connection failure probability, by slightly increasing the energy consumption. Finally, we demonstrate the effects of coexistence with other RA-related schemes through simulation results