Overview of narrowband IoT in LTE Rel-13

Ratasuk, Rapeepat; Mangalvedhe, Nitin; Zhang, Yanji; Robert, Michel; Koskinen, J.

doi:10.1109/cscn.2016.7785170

Cited by 197 publications

(119 citation statements)

References 4 publications

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“…In the literature, the studies [7,[9][10][11] give an overview of NB-IoT and conclude that NB-IoT can enhance bandwidth efficiency and increase network coverage. Reference [12] proposes a new procedure for cell search and initial synchronization in NB-IoT which can speed up the access operation for the devices with low SNR.…”

Section: Related Workmentioning

confidence: 99%

Energy‐Efficient Uplink Resource Units Scheduling for Ultra‐Reliable Communications in NB‐IoT Networks

Liang

Chen

et al. 2018

Wireless Communications and Mobile Computing

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For 5G wireless communications, the 3GPP Narrowband Internet of Things (NB-IoT) is one of the most promising technologies, which provides multiple types of resource unit (RU) with a special repetition mechanism to improve the scheduling flexibility and enhance the coverage and transmission reliability. Besides, NB-IoT supports different operation modes to reuse the spectrum of LTE and GSM, which can make use of bandwidth more efficiently. The IoT application grows rapidly; however, those massive IoT devices need to operate for a very long time. Thus, the energy consumption becomes a critical issue. Therefore, NB-IoT provides discontinuous reception operation to save devices' energy. But, how to further reduce the transmission energy while ensuring the required ultra-reliability is still an open issue. In this paper, we study how to guarantee the reliable communication and satisfy the quality of service (QoS) while minimizing the energy consumption for IoT devices. We first model the problem as an optimization problem and prove it to be NP-complete. Then, we propose an energy-efficient, ultra-reliable, and low-complexity scheme, which consists of two phases. The first phase tries to optimize the default transmit configurations of devices which incur the lowest energy consumption and satisfy the QoS requirement. The second phase leverages a weighting strategy to balance the emergency and inflexibility for determining the scheduling order to ensure the delay constraint while maintaining energy efficiency. Extensive simulation results show that our scheme can serve more devices with guaranteed QoS while saving their energy effectively.

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Section: Related Workmentioning

confidence: 99%

Energy‐Efficient Uplink Resource Units Scheduling for Ultra‐Reliable Communications in NB‐IoT Networks

Liang

Chen

et al. 2018

Wireless Communications and Mobile Computing

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“…With repetition cod-ing, the capacity will be reduced to n/r · C(W r ) since we transmit n/r times over the channel W r . For any β ∈ [0, 1], we ask what is the largest repetition size r β such that n r β C(W r β ) ≥ βnC(W).…”

Section: How Much Repetition Is Needed?mentioning

confidence: 99%

Channel Coding at Low Capacity

Fereydounian

Jamali

Hassani

et al. 2019

2019 IEEE Information Theory Workshop (ITW)

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Low-capacity scenarios have become increasingly important in the technology of Internet of Things (IoT) and next generation of mobile networks. Such scenarios require efficient, reliable transmission of information over channels with extremely small capacity. Within these constraints, the performance of state-of-the-art coding techniques is far from optimal in terms of either rate or complexity. Moreover, the current non-asymptotic laws of optimal channel coding provide inaccurate predictions for coding in the low-capacity regime. In this paper, we provide the first comprehensive study of channel coding in the lowcapacity regime. We will investigate the fundamental non-asymptotic limits for channel coding as well as challenges that must be overcome for efficient code design in low-capacity scenarios.

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“…NB-IoT can be deployed in Global System for Mobile Communications (GSM) or Long-Term Evolution (LTE) networks, and can co-exist with LTE. NB-IoT uses a new physical layer design that facilitates a wide range of IoT applications in the licensed spectrum that require long range, deep indoor penetration, low cost, low data rate, low power consumption, and massive capacity [2].…”

Section: Introductionmentioning

confidence: 99%

Evaluation, Modeling and Optimization of Coverage Enhancement Methods of NB-IoT

Ravi

Zand

Soussi

et al. 2019

2019 IEEE 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

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Narrowband Internet of Things (NB-IoT) is a new Low Power Wide Area Network (LPWAN) technology released by 3GPP. The primary goals of NB-IoT are improved coverage, massive capacity, low cost, and long battery life. In order to improve coverage, NB-IoT has promising solutions, such as increasing transmission repetitions, decreasing bandwidth, and adapting the Modulation and Coding Scheme (MCS). In this paper, we present an implementation of coverage enhancement features of NB-IoT in NS-3, an end-to-end network simulator. The resource allocation and link adaptation in NS-3 are modified to comply with the new features of NB-IoT. Using the developed simulation framework, the influence of the new features on network reliability and latency is evaluated. Furthermore, an optimalhybrid link adaptation strategy based on all three features is proposed. To achieve this, we formulate an optimization problem that has an objective function based on latency, and constraint based on the Signal to Noise Ratio (SNR). Then, we propose several algorithms to minimize latency and compare them with respect to accuracy and speed. The best hybrid solution is chosen and implemented in the NS-3 simulator by which the latency formulation is verified. The numerical results show that the proposed optimization algorithm for hybrid link adaptation is eight times faster than the exhaustive search approach and yields similar latency.

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Overview of narrowband IoT in LTE Rel-13

Cited by 197 publications

References 4 publications

Energy‐Efficient Uplink Resource Units Scheduling for Ultra‐Reliable Communications in NB‐IoT Networks

Energy‐Efficient Uplink Resource Units Scheduling for Ultra‐Reliable Communications in NB‐IoT Networks

Channel Coding at Low Capacity

Evaluation, Modeling and Optimization of Coverage Enhancement Methods of NB-IoT

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