A survey on NB-IoT downlink scheduling: Issues and potential solutions

Boisguene, Rubbens; Tseng, Sheng-Chia; Huang, Chih‐Wei; Lin, Pengzhi

doi:10.1109/iwcmc.2017.7986344

Cited by 57 publications

(31 citation statements)

References 9 publications

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“…This is because the user has to wait for all the NS × R subframes to arrive to decode the NPDSCH data. The NB-IoT has a delay requirement (Dmax) of 10 seconds [17] [18]. Fig.…”

Section: Evaluation Resultsmentioning

confidence: 99%

NB-IoT: A Candidate Technology for Massive IoT in the 5G Era

Narayanan

Tsolkas

Passas

et al. 2018

2018 IEEE 23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)

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The existing mobile network infrastructure is currently optimized to support the Narrow-Band Internet of Things (NB-IoT), which is meant to provide numerous services in poor coverage areas, with ultra-low power consumption. The question that arises is whether (and to what extent) NB-IoT can meet the requirement for massive Machine Type Communications (mMTC) in the 5G era. In view of this, we study coverage enhancement in NB-IoT. We describe the subframe structure for various physical channels of NB-IoT and explain the repetition mechanism used for downlink transmissions in poor coverage areas. Focusing on optimizing this mechanism, we analyze how the latency and user blockage can be reduced by a proper selection of the downlink radio resources.

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“…This is because the user has to wait for all the NS × R subframes to arrive to decode the NPDSCH data. The NB-IoT has a delay requirement (Dmax) of 10 seconds [17] [18]. Fig.…”

Section: Evaluation Resultsmentioning

confidence: 99%

NB-IoT: A Candidate Technology for Massive IoT in the 5G Era

Narayanan

Tsolkas

Passas

et al. 2018

2018 IEEE 23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)

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“…The scheduling delay couples the downlink and uplink transmission in NB-IoT, thus requiring joint optimisation of the resources. Furthermore, even with the best selection of the scheduling delay, there is still a significant resource wastage due to signalling overhead [6]. To address this issue, the authors in [6] proposed a pre-divided resource allocation that uses a dynamic data slicing technique for splitting the user resource requirements and fitting in the scattered available resources.…”

Section: Research Challenges For Radio Resourcementioning

confidence: 99%

Radio Resource Management in NB-IoT Systems: Empowered by Interference Prediction and Flexible Duplexing

et al. 2020

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Narrowband Internet of Things (NB-IoT) is a promising cellular technology for enabling low cost, low power, long-range connectivity to the IoT devices. With the bandwidth requirement of 180 kHz, it provides the flexibility to deploy within the existing Long Term Evolution (LTE) band. However, this raises serious concerns about the performance of the technology due to severe interference from multi-tier 5G heterogeneous networks (HetNets). Furthermore, as NB-IoT is based on halfduplex frequency division duplexing (HD-FDD), the symmetric allocation of spectrum band between downlink and uplink results in underutilization of resource, particularly in case of asymmetric traffic distribution. Therefore, an innovative radio resource management (RRM) strategy needs to be devised to improve the spectrum efficiency and device connectivity. This article presents the detailed design challenges that need to be addressed for the RRM of NB-IoT and proposes a novel framework to devise an efficient resource allocation scheme by exploiting cooperative interference prediction and flexible duplexing techniques.

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“…The design of downlink scheduling techniques for M2M communications should take into account the fact that MTCDs in M2M communications may have strict delay requirements. In addition, scheduling should take into account the fact that a significant number of MTCDs can contend for limited radio resources [17].…”

Section: Resource Allocation For M2m Communicationsmentioning

confidence: 99%

New Method Based on Priority of Heterogeneous Traffic for Scheduling Techniques in M2M Communications over LTE Networks

Ouaissa¹,

Rhattoy²

2018

IJIES

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Machine to Machine (M2M) communication is a technology for machines communicating with each other without human intervention. Long Term Evolution (LTE) and Long-Term Evolution-Advanced (LTE-A) cellular networks technologies provide the resources required for M2M communication. However, LTE is required to meet M2M communication requirements, such as power management and support for a large number of devices while maintaining the Quality of Service (QoS) requirements for these devices. Resource allocation or scheduling is one of the key challenges facing M2M communications over Long-Term Evolution networks. M2M traffic has unique characteristics; it usually consists of a large number of small data packets, with specific delays, generated by a potentially large number of devices competing on scarce radio resources. In this article, we will present the scheduling techniques on the Packet Downlink Control Channel (PDCCH) in a M2M scenario based on the priority and differentiation between heterogeneous traffic (real time and non-real time) to achieve high spectral efficiency in cellular systems and provide quality of service guarantees for system users. The results obtained show that the FLS downlink scheduler is the optimal solution based on our proposed method which offers more priority to the real time service (video and voip) than the non real time service (best effort).

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A survey on NB-IoT downlink scheduling: Issues and potential solutions

Cited by 57 publications

References 9 publications

NB-IoT: A Candidate Technology for Massive IoT in the 5G Era

NB-IoT: A Candidate Technology for Massive IoT in the 5G Era

Radio Resource Management in NB-IoT Systems: Empowered by Interference Prediction and Flexible Duplexing

New Method Based on Priority of Heterogeneous Traffic for Scheduling Techniques in M2M Communications over LTE Networks

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