LTE/LTE-A Random Access for Massive Machine-Type Communications in Smart Cities

Ali, Shipon; Hossain, Ekram; Kim, Dong In

doi:10.1109/mcom.2017.1600215cm

Cited by 158 publications

(102 citation statements)

References 10 publications

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“…A different scheme has been recently proposed that tries to resolve collisions and, presumably, improve performance by reassigning a subset of available preambles to calls that failed an access attempt [9]. However, they use a simplified error calculation based on slotted ALOHA, which does not account for interference caused by simultaneous random access attempts and/or other channels in the neighbouring cells.…”

Section: Discussionmentioning

confidence: 99%

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Priority-Based Machine-To-Machine Overlay Network over LTE for a Smart City

Khan

Mišić

2018

JSAN

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Long-Term Evolution (LTE) and its improvement, Long-Term Evolution-Advanced (LTE-A), are attractive choices for Machine-to-Machine (M2M) communication due to their ubiquitous coverage and high bandwidth. However, the focus of LTE design was high performance connection-based communications between human-operated devices (also known as human-to-human, or H2H traffic), which was initially established over the Physical Random Access Channel (PRACH). On the other hand, M2M traffic is mostly based on contention-based transmission of short messages and does not need connection establishment. As a result, M2M traffic transmitted over LTE PRACH has to use the inefficient four-way handshake and compete for resources with H2H traffic. When a large number of M2M devices attempts to access the PRACH, an outage condition may occur; furthermore, traffic prioritization is regulated only through age-based power ramping, which drives the network even faster towards the outage condition. In this article, we describe an overlay network that allows a massive number of M2M devices to coexist with H2H traffic and access the network without going through the full LTE handshake. The overlay network is patterned after IEEE 802.15.6 to support multiple priority classes of M2M traffic. We analyse the performance of the joint M2M and H2H system and investigate the trade-offs needed to keep satisfactory performance and reliability for M2M traffic in the presence of H2H traffic of known intensity. Our results confirm the validity of this approach for applications in crowd sensing, monitoring and others utilized in smart city development.

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Section: Discussionmentioning

confidence: 99%

“…7. Failed calls may be allocated a specific set of preambles to use for repeated access attempts [9].…”

Section: Introductionmentioning

confidence: 99%

Priority-Based Machine-To-Machine Overlay Network over LTE for a Smart City

Khan

Mišić

2018

JSAN

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“…In practice, the reason not to perform a sufficient coordination among the users trying to access the system might be various, e.g., the low latency requirement to restrict the coordination establishment, a lack of global scheduling information, or the bursty and random access pattern for the activity of the users. Uncoordinated multiple access technology has been widely used in the initial access process of both cellular terrestrial and satellite communication networks [1], [2], where an unsourced random access mechanism is implemented.…”

Section: B Uncoordinated Multiple Accessmentioning

confidence: 99%

Massive Access for Future Wireless Communication Systems

Gao

Zhou

et al. 2020

IEEE Wireless Commun.

163

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Multiple access technology plays an important role in wireless communication in the last decades: it increases the capacity of the channel and allows different users to access the system simultaneously. However, the conventional multiple access technology, as originally designed for current human-centric wireless networks, is not scalable for future machine-centric wireless networks.Massive access (also known as "Massive-device Multiple Access", "Unsourced Massive Random Access", "Massive Connectivity", "Massive Machine-type Communication", and "Many-Access Channels") exhibits a clean break with current networks by potentially supporting millions of devices in each cellular network. The exponential growth in the number of devices requires entirely new "massive" access technologies to tackle the fundamental challenges which needs prompt attention: the fundamental framework of the communication from a massive number of bursty devices transmitting simultaneously with short packets, the low complexity and energy-efficient massive access coding and communication schemes, the effective active user detection method among a large number of potential user devices with sporadic device activity patterns, and the integration of massive access with massive Y. Wu is with the

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“…6,7 The LTE/LTE-A technology plays a major role in back filling of MTC applications. 8 However, because of the diverse characteristics of quality of service (QoS) requirement, power efficiency, transmission periodicity, and payload size, MTC poses huge challenges to LTE/LTE-A technologies. 9,10 Devaluation of user equipment (UE) cost and radio access network (RAN) overload control issue is mainly focused by the LTE-A standards.…”

Section: Introductionmentioning

confidence: 99%

“…Some of them are class barring scheme, back-off technique, slotted access method, pull-based scheme, dynamic physical random access channel (PRACH) resource allocation method, and PRACH resource separation scheme. 8,[16][17][18][19] However, these techniques have some advantages and disadvantages. In this context, the method adopted a cooperative swarm intelligence algorithm in the LTE-A network for the UL resource allocation.…”

Section: Introductionmentioning

confidence: 99%

Multiobjective cooperative swarm intelligence algorithm for uplink resource allocation in LTE‐A networks

Moses¹,

Balakrishnan²

2019

Trans Emerging Tel Tech

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Nowadays, Long-Term Evolution Advanced (LTE-A) network is the primary innovation in 4G networks. The LTE-A networks convey exceptional data rates and low latency for few sorts of application. Sometimes, in LTE-A, the multiobjective uplink resource allocation is the perplexing optimization problem, and this problem is considered as 0-1 multiobjective knapsack trouble. In order to overcome this trouble, a multiobjective cooperative swarm intelligence algorithm for resource allocation is proposed in this paper. In our proposed work, hybrid firefly algorithm (FFA) and particle swarm optimization (PSO) algorithm are utilized to solve 0-1 multiobjective knapsack problem. Initially, a priority and urgency factor (urgency of packets)-based user ranking and quantifying scheme is designed for scheduling process. After the scheduling process, the resource allocations employ three objective functions, such as maximization of resource utilization, maximization of quality of service (QoS), and interference minimization. The optimization problem is overcome by using the hybrid FFA and PSO algorithm. The experimental outcomes demonstrate that it has the best QoS and less interference in the resource allocation in LTE-A network than state-of-art methods in the proposed strategy.Trans Emerging Tel Tech. 2019;30:e3748.wileyonlinelibrary.com/journal/ett

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LTE/LTE-A Random Access for Massive Machine-Type Communications in Smart Cities

Cited by 158 publications

References 10 publications

Priority-Based Machine-To-Machine Overlay Network over LTE for a Smart City

Priority-Based Machine-To-Machine Overlay Network over LTE for a Smart City

Massive Access for Future Wireless Communication Systems

Multiobjective cooperative swarm intelligence algorithm for uplink resource allocation in LTE‐A networks

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