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The accuracy and efficiency of current leakage fault diagnosis methods in rural areas are low. In view of this defect, a rural power leakage diagnosis system based on narrowband Internet of Things is studied and designed. Aiming a...
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The accuracy and efficiency of current leakage fault diagnosis methods in rural areas are low. In view of this defect, a rural power leakage diagnosis system based on narrowband Internet of Things is studied and designed. Aiming at the defect that the magnetic modulation sensor with single magnetic core structure is prone to zero drift and temperature drift, which increases the measurement error, a magnetic modulation sensor with double magnetic core structure is proposed. Aiming at the problem that the output voltage waveform of the sensor in the square wave excitation scheme is not ideal and the calculation is complex, a half-wave excitation scheme is proposed to make the output voltage waveform of the sensor more ideal and reduce the calculation complexity. The experimental results show that the diagnostic accuracy of the leakage diagnosis system of rural power grid designed according to the research has reached 95%. To sum up, the rural power grid leakage diagnosis system can effectively improve the diagnosis accuracy of power grid leakage, and provide guarantee for rural people’s livelihood and economic development.
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Coverage extension with limited transmission power devices is one of the requirements and research challenges for battery-operated IoT nodes, which use a narrowband IoT wireless communication protocol. The link adaptation mechanis...
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Coverage extension with limited transmission power devices is one of the requirements and research challenges for battery-operated IoT nodes, which use a narrowband IoT wireless communication protocol. The link adaptation mechanism can solve this problem by selecting optimal parameters using cognitive radio. This research work proposes a context-aware link adaptation mechanism using a cognitive radio that uses a machine-learning algorithm. The proposed mechanism achieves greater coverage in the long run with lower SINR (signal-to-interference and noise ratio) and BER (bit error rate) through optimal selection of repetition rate, modulation, coding scheme, transmission power, number of subcarriers, and frequency based on the wireless channel condition and QoS requirement of the application. Here, every Narrowband Internet of Things (NBIoT) node is considered a cognitive radio node, which uses a frequency that is available for free. The proposed system-generated NBIoT uplink waveform and evaluated the performance using the optimal parameter derived from the proposed context-aware machine learning-based link adaptation scheme.
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Abstract In this paper, we present the results of our investigation into the performance of in-band narrowband-Internet-of-things (NB-IoT) devices in downlink–uplink decoupled (DUDe)-enabled heterogeneous networks (Het- Nets). To...
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Abstract In this paper, we present the results of our investigation into the performance of in-band narrowband-Internet-of-things (NB-IoT) devices in downlink–uplink decoupled (DUDe)-enabled heterogeneous networks (Het- Nets). To develop a more generalized analytical framework, we have considered the impact of open-loop power control in uplink communication, cell range expansion, and different values of path loss exponents for base stations’ (BS) tiers to emulate diverse path loss environment. Using this system model, we have derived decoupled uplink coverage probability for narrowband physical uplink shared channel (NPUSCH), average data rate per device, energy efficiency, and access success probability for narrowband physical random access channel (NPRACH). The analytical framework developed in this paper has been validated by comparing the results obtained through Monte Carlo simulations.
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Providing Internet connectivity to a massive number of Internet-of-Things (IoT) objects over the unlicensed spectrum requires: 1) identifying a very large number of narrowband channels in a wideband spectrum and 2) aggressively re...
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Providing Internet connectivity to a massive number of Internet-of-Things (IoT) objects over the unlicensed spectrum requires: 1) identifying a very large number of narrowband channels in a wideband spectrum and 2) aggressively reusing the available channels over space to accommodate the high density of IoT devices. To this end, we propose a sensing-based architecture that identifies spectral and spatial resources at a fine resolution. In particular, we first propose a sensing assignment scheduler, where each base station (BS) is assigned a subset of the spectrum to sense at a high resolution. We then propose a distributed sensing algorithm, where BSs locally process and share their sensing reports, so that each BS obtains occupancy information of the wideband spectrum at its location. Once the spatio-spectral resource blocks are identified, we further propose a distributed resource allocation algorithm that maintains high spatial reuse of spectral opportunities while limiting the intra-network and inter-network interference. Numerical simulations are presented to validate the effectiveness of the proposed distributed algorithms, comparing them to centralized and non-cooperative schemes. It is shown that our architecture identifies more spatio-spectral resources, with lower misdetection of incumbents. As a result, more IoT devices are connected with limited interference into incumbents.
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One of the significant properties of narrowband Internet of Things (NB-IoT) devices is supporting a long battery life. In the NB-IoT, devices have different search-space periods based on channel qualities. However, because a subfr...
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One of the significant properties of narrowband Internet of Things (NB-IoT) devices is supporting a long battery life. In the NB-IoT, devices have different search-space periods based on channel qualities. However, because a subframe of 180 kHz is a basic unit in the downlink, a base station can generally only simultaneously schedule devices with the same search-space period and allocate radio resources at the start of the period. If scheduling does not consider search-space periods, a base station will miss the start of the search-space period of some devices or sacrifice some devices. Massive devices will attempt multiple periods for blind decoding (BD), resulting in huge energy consumption. This article investigates a new direction in reducing the energy consumption of devices by reducing the BD and idle time for the NB-IoT. The challenge of the target energy-efficient scheduling problem is how to schedule search-space periods to reduce each device's BD and idle time subject to the data requirements. We propose an algorithm to determine each device's search-space period and an energy-efficient scheduling algorithm to schedule the search-space periods. The simulation results show that, compared with two baselines, the proposed algorithms reduce the energy consumption by 77%.
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Recent years have seen a widespread deployment of NB-IoT networks for massive machine-to-machine communication in the emerging 5G era. Unfortunately, the key aspects of NB-IoT networks, such as radio access performance and power c...
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Recent years have seen a widespread deployment of NB-IoT networks for massive machine-to-machine communication in the emerging 5G era. Unfortunately, the key aspects of NB-IoT networks, such as radio access performance and power consumption have not been well-understood due to lack of effective tools and closed nature of operational cellular infrastructure. In this paper, we develop NB-Scope - the first hardware NB-IoT diagnostic tool that supports fine-grained fusion of power and protocol traces. We then conduct a large-scale field measurement study consisting of 30 nodes deployed at over 1,200 locations in 4 regions during a period of three months. Our in-depth analysis of the collected 49 GB traces showed that NB-IoT nodes yield significantly imbalanced energy consumption in the wild, up to a ratio of 75:1, which may lead to short battery lifetime and frequent network partition. Such a high performance variance can be attributed to several key factors including diverse network coverage levels, long tail power profile, and excessive control message repetitions. We then explore the optimization of NB-IoT base station settings on a software-defined eNodeB testbed, and suggest several important design aspects that can be considered by future NB-IoT specifications and chipsets.
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Smart objects and home automation tools are becoming increasingly popular, and the number of smart devices that each dedicated application has to manage is increasing accordingly. The emergence of technologies such as serverless c...
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Smart objects and home automation tools are becoming increasingly popular, and the number of smart devices that each dedicated application has to manage is increasing accordingly. The emergence of technologies such as serverless computing and dedicated machine-to-machine communication protocols represents a valuable opportunity to facilitate management of smart objects and replicability of new solutions. The aim of this paper is to propose a framework for home automation applications that can be applied to control and monitor any appliance or object in a smart home environment. The proposed framework makes use of a dedicated messages-exchange protocol based on MQTT and cloud-deployed serverless functions. Furthermore, a vocal command interface is implemented to let users control the smart object with vocal interactions, greatly increasing the accessibility and intuitiveness of the proposed solution. A smart object, namely a smart kitchen fan extractor system, was developed, prototyped, and tested to illustrate the viability of the proposed solution. The smart object is equipped with a narrowband IoT (NB-IoT) module to send and receive commands to and from the cloud. In order to evaluate the performance of the proposed solution, the suitability of NB-IoT for the transmission of MQTT messages was evaluated. The results show how NB-IoT has an acceptable latency performance despite some minimal packet loss.
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Narrowband Internet of Things (NB-IoT) is a critical technology for fifth-generation (5G) and next sixth-generation (6G) networks to meet the high density and latency requirements for massive devices. Before data transmission or r...
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Narrowband Internet of Things (NB-IoT) is a critical technology for fifth-generation (5G) and next sixth-generation (6G) networks to meet the high density and latency requirements for massive devices. Before data transmission or reception in NB-IoT networks, a device needs to monitor a search space in a narrowband physical downlink control channel (NPDCCH). When the NPDCCH resource is exhausted, neither data transmission in the narrowband uplink shared channel (NPUSCH) nor data reception in the narrowed downlink shared channel (NPDSCH) is possible, even if the two channels still have available radio resources. To solve the problem, the 3rd generation partnership project (3GPP) puts forth an NPDCCH offset mechanism for NB-IoT, which can set different offset values for different devices. Devices using different NPDCCH offset values can postpone different time intervals for monitoring their NPDCCH search spaces so that the devices do not need to contend for the same NPDCCH search space. However, this article finds that improper use of the NPDCCH offset mechanism will hurt the system’s performance. Therefore, this article investigates how to use the NPDCCH offset mechanism in uplink and downlink resource allocation. The objective is to minimize the consumption of uplink and downlink radio resources while each device can transmit and/or receive its data. We propose an offset-aware resource allocation algorithm to solve the problem. Compared with two resource allocation algorithms with and without using the NPDCCH offset, the simulation results provide several insights and show that the proposed algorithm effectively reduces radio resource consumption.
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It is very important to rapidly test the key indicators of water in the field to fully evaluate the quality of the regional water environment. However, a high-resolution measuring device that can generate small currents for low-co...
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It is very important to rapidly test the key indicators of water in the field to fully evaluate the quality of the regional water environment. However, a high-resolution measuring device that can generate small currents for low-concentration analytes in water samples is often bulky, complex to operate, and difficult for data sharing. This work introduces a portable multi-channel electrochemical device with a small volume, good interaction, and data-sharing capabilities called PMCED. The PMCED provides an easy-to-operate graphical interactive interface to conveniently set the parameters for cyclic voltammetry or a differential pulse method performed by the four electrode channels. At the same time, the device, with a current sensitivity of 100 nA V?1, was applied to the detection of water samples with high background current and achieved a high-resolution measurement at low current levels. The PMCED uses the Narrow Band Internet of Things (NB-IoT) to meet the needs for uploading data to the cloud in remote areas. The electrochemical signal preprocessing and chemometrics models run in the cloud, and the final results are visualized on a web page, providing a remote access channel for on-site testing results.
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Single-tone and multi-tone transmissions in the narrowband Internet of Things (NB-IoT) uplink system can be accomplished by employing different orthogonal basis. In this paper, we develop an uplink NB-IoT baseband system model and...
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Single-tone and multi-tone transmissions in the narrowband Internet of Things (NB-IoT) uplink system can be accomplished by employing different orthogonal basis. In this paper, we develop an uplink NB-IoT baseband system model and derive the corresponding analytical signal model based on the discrete cosine transform type-I (DCT-I) domain. Basically, the circular convolution and channel matrix diagonalization issues for designing DCT-based systems are addressed without exploiting any redundancy (a prefix and a suffix sequences, and zero-padding (ZP)) into each transmitted data symbol blocks. In our proposed DCT-I based transceiver, we employ a standard cyclic prefix (CP) and apply discrete Fourier transform (DFT) and inverse DFT (IDFT) operations directly to make the channel matrix circulant and diagonal, resulting in the use of one-tap frequency-domain channel equalizer without incorporating extra front-end prefilter at the receiver. Furthermore, we propose novel least squares (LS) and linear minimum mean square error (LMMSE) channel estimators by considering the energy concentration and spectral compaction properties of DCT-I for the uplink NB-IoT system. The expressions for the DCT-I domain LS and LMMSE estimators are derived for channel frequency response estimation and mean square error computation. Finally, the viability of the proposed CP-DCT-I-NB-IoT uplink system, as well as the channel estimators, are tested compared with the standardized CP-DFT-NB-IoT and ZP-DCT type-2 even based single-carrier frequency-division multiple access (SC-FDMA) systems through rigorous computer simulations. (C) 2021 Elsevier B.V. All rights reserved.
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