Dynamic Inter-Channel Resource Allocation for Massive M2M Control Signaling Storm Mitigation

Chen, Ting-Hua; Chang, Junwei; Wei, Hung‐Yu

doi:10.1109/vtcfall.2016.7880970

Cited by 6 publications

(6 citation statements)

References 11 publications

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“…In this case, we can obtain q − 1−q β ≤ 0, so (27) holds for n = i, • • • , I and thus a i, n > 0 (n = i, i + 1, ...I). Then, we have…”

Section: B Optimization Problem Formulationmentioning

confidence: 92%

“…Moreover, since different MTCDs usually have diverse Quality-of-Service (QoS) requirements, such as latency, outage probability, and reliability, grouping multiple MTCDs having similar QoS requirements into one cluster is beneficial to increase the successful access probability. Correspondingly, cluster-based resource allocation schemes for mMTC network were also studied [24]- [27]. In addition, while using the traditional four-message handshake RA procedure, large amounts of PA collisions will occur in the first handshake and these collisions can only be detected in the third handshake, which not only waste the limited resource, but also increase the access delay.…”

Section: Introductionmentioning

confidence: 99%

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Throughput-Oriented Non-Orthogonal Random Access Scheme for Massive MTC Networks

Wang

Yang

et al. 2020

IEEE Trans. Commun.

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Machine-type communications (MTC) technology, which enables direct communications among devices, plays an important role in realizing Internet-of-Things. However, a large number of MTC devices can cause severe collisions. As a result, the network throughput is decreased and the access delay is increased. To address this issue, a throughput-oriented non-orthogonal random access (NORA) scheme is proposed for massive machine-type communications (mMTC) networks. Specifically, by employing the technique of tagged preambles (PAs), multiple MTC devices (MTCDs) choosing the same PA can be distinguished and regarded as a non-orthogonal multiple access (NOMA) group, which enables multiple MTCDs to share the same physical uplink shared channel for transmissions by multiplexing in the power domain. The Sukhatme's classic theory and the characteristic function approach are adopted to formulate an optimization problem. The aim is to maximize the throughput subject to the constraints on the power back-off factor, the number of MTCDs included in a NOMA group, and the successful transmission probability. Based on the particle swarm optimization (PSO) algorithm, the formulated optimization problem is efficiently solved. The derived solution can be used to adjust the access class barring factor such that more MTCDs can obtain the access opportunities. Moreover, a lowcomplexity suboptimal solution is also developed, which can achieve near-PSO performance under high data rate requirement. Simulation results show that the proposed scheme can efficiently improve the network performance and comparison is made with the existing schemes. Index Terms-Massive machine-type communications (MTC) networks, non-orthogonal random access, power back-off.

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“…In this case, we can obtain q − 1−q β ≤ 0, so (27) holds for n = i, • • • , I and thus a i, n > 0 (n = i, i + 1, ...I). Then, we have…”

Section: B Optimization Problem Formulationmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Throughput-Oriented Non-Orthogonal Random Access Scheme for Massive MTC Networks

Wang

Yang

et al. 2020

IEEE Trans. Commun.

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“…Reference [49] presents a dynamic inter-channel resource allocation technique for massive M2M control signaling storm mitigation. Their model calculates the demand on the control and data channels and re-allocates the resources among these two types of channels.…”

Section: Relationship To the State Of The Artmentioning

confidence: 99%

“…8 displays the fraction of utilization of the entire slot-channel grid. 49 We shall analyze the utilization of MC-LAPAL completely before we move onto those of the reactive protocols. In all of the four subplots of this figure, we see that the utilization of MC-LAPAL under both perfect forecasts and MLP forecasting increases approximately linearly until a point at which saturation occurs (i.e.…”

Section: ) Performance Comparison For the General Casementioning

confidence: 99%

Multi-Channel Joint Forecasting-Scheduling for the Internet of Things

et al. 2020

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We develop a methodology for Multi-Channel Joint Forecasting-Scheduling (MC-JFS) targeted at solving the Medium Access Control (MAC) layer Massive Access Problem of Machine-to-Machine (M2M) communication in the presence of multiple channels, as found in Orthogonal Frequency Division Multiple Access (OFDMA) systems. In contrast with the existing schemes that merely react to current traffic demand, Joint Forecasting-Scheduling (JFS) forecasts the traffic generation pattern of each Internet of Things (IoT) device in the coverage area of an IoT Gateway and schedules the uplink transmissions of the IoT devices over multiple channels in advance, thus obviating contention, collision and handshaking, which are found in reactive protocols. In this paper, we present the general form of a deterministic scheduling optimization program for MC-JFS that maximizes the total number of bits that are delivered over multiple channels by the delay deadlines of the IoT applications. In order to enable real-time operation of the MC-JFS system, first, we design a heuristic, called Multi-Channel Look Ahead Priority based on Average Load (MC-LAPAL), that solves the general form of the scheduling problem. Second, for the special case of identical channels, we develop a reduction technique by virtue of which an optimal solution of the scheduling problem is computed in real time. We compare the network performance of our MC-JFS scheme against Multi-Channel Reservation-based Access Barring (MC-RAB) and Multi-Channel Enhanced Reservation-based Access Barring (MC-ERAB), both of which serve as benchmark reactive protocols. Our results show that MC-JFS outperforms both MC-RAB and MC-ERAB with respect to uplink cross-layer throughput and transmit energy consumption, and that MC-LAPAL provides high performance as an MC-JFS heuristic. Furthermore, we show that the computation time of MC-LAPAL scales approximately linearly with the number of IoT devices. This work serves as a foundation for building scalable JFS schemes at IoT Gateways in the near future.

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“… Excessive Signaling Overhead: One of the biggest issues in handling the M2M traffic is massive increase of signaling overhead due numerous of machines under a mobile cell area. When this huge M2M devices access the network, excessive access request to BS creates congestion resulting overhead signaling storm [11]. Thus, the whole cellular network becomes unable to serve and shows degraded performance.…”

Section: Machine To Machine Communicationsmentioning

confidence: 99%

An Architecture for M2M Communications Over Cellular Networks Using Clustering and Hybrid TDMA-NOMA

Rozario

Hossain

2018

2018 6th International Conference on Information and Communication Technology (ICoICT)

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It is hereby declared that 1. The thesis submitted is my own original work while completing degree at BRAC University.2. The thesis does not contain material previously published or written by a third party, except where this is appropriately cited through full and accurate referencing.3. The thesis does not contain material which has been accepted, or submitted, for any other degree or diploma at a university or other institution.4. I have acknowledged all main sources of help.

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Dynamic Inter-Channel Resource Allocation for Massive M2M Control Signaling Storm Mitigation

Cited by 6 publications

References 11 publications

Throughput-Oriented Non-Orthogonal Random Access Scheme for Massive MTC Networks

Throughput-Oriented Non-Orthogonal Random Access Scheme for Massive MTC Networks

Multi-Channel Joint Forecasting-Scheduling for the Internet of Things

An Architecture for M2M Communications Over Cellular Networks Using Clustering and Hybrid TDMA-NOMA

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