An enhanced EAB algorithm to reduce RACH congestion due to IoT traffic in LTE-A networks

Giluka, Mukesh Kumar; Priyadarshi, Tathagat; Kumar, Sandeep; Franklin, A. Antony; Tamma, Bheemarjuna Reddy

doi:10.1109/wf-iot.2018.8355156

Cited by 4 publications

(2 citation statements)

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“…In Figure 3, we compare the TLAB procedure to the EAB procedure of Cheng et al 8 and eEAB procedure of Giluka et al 9 The success probability is plotted versus the number of M2M devices trying to access the system. It can be deduced from the figure that the proposed procedure can achieve higher success probability than both the EAB and the eEAB procedures.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

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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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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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Section: Simulation Results and Discussionmentioning

confidence: 99%

“…In their study, Giluka et al, 9 presented a complete analysis of the performance of H2H and M2M devices and proposed an enhanced EAB (eEAB) algorithm. The enhanced algorithm avoids collective barring of IoT devices using a three states diagram.…”

Section: Related Workmentioning

confidence: 99%