Narrowband Internet Of Things Research Articles

A Design for Increasing the Capacity Fourfold in NB-IoT Systems using A Modified Symbol Time Compression Approach

One of the most significant obstacles facing the Internet of Things (IoT) is how to offer support for communication to an expanding number of linked items. Narrow-band Internet of Things (NB-IoT), which is currently an aspect of fifth-generation (5G), is a new narrow-band wireless communication technology that has evolved in recent years to address this issue. To save power, NB-IoT currently exploits modulation schemes that are characterized by low order to deliver low data rate. However, as the number of applications dependent on data rate increases, NB-IoT needs to use data rate improvement technologies that do not consume additional power. This paper proposes a design for quadrupling the total number of linked items in the NB-IoT system using a symbol time compression methodology. A modified symbol time compression (MSTC) approach is specifically suggested, which could preserve 75% of the bandwidth (BW) by reducing the symbol time to a quarter (25%). This study suggests a design that uses the MSTC method four times in orthogonal frequency division multiplexing (4-MSTC-OFDM) to take advantage of the unused bandwidth and has the capability to deliver a quadruple quantity of information in comparison to the standard OFDM system. Simulations show that the suggested design (4-MSTC-OFDM) lowers the signal-to-noise ratio (SNR) by 3.9 dB (at BER = 10-6) and 4.4 dB (at BER = 10-4) compared to the OFDM system with 16-QAM (16-QAM-OFDM) when sending the same amount of data over the Rayleigh fading channel and additive white Gaussian noise channel (AWGN). Moreover, the results of simulations indicate that the proposed design possesses an identical BER as the conventional OFDM technique, implying that using the suggested method does not degrade the BER.

A Fully Integrated Pulling Mitigation Synthesizer for NB-IoT Transmitter

This article presents the pulling mitigation scheme implemented in the frequency synthesizer integrated with the dual-band narrowband-internet-of-things (NB-IoT) transmitter (TX). The proposed pulling mitigation in the synthesizer employs a hybrid phase compensation and sampled filter to mitigate the pulling effects by the transmitter. The synthesizer covers frequencies from 700–900 MHz and 1.7–2 GHz in the low band and high band, respectively, satisfying the dual-band NB-IoT frequency tuning specifications. The proposed pulling mitigation in the synthesizer improves the error vector magnitude (EVM) by 11.5% with 16 quadrature amplitude modulation (QAM) modulation and in single-tone measurements, the achieved pulling suppression is 24 dB. Implemented in 40 nm CMOS, the pulling mitigation occupies a small area of 0.18 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times$</tex-math> </inline-formula> 0.18 mm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{2}$</tex-math> </inline-formula> and the dc power consumption is 1 mW with a supply voltage of 1.1 V.

EP-CuMAC: Energy and performance-efficient integrity protection for narrow-band IoT

Narrowband Internet of Things (NB-IoT) is a LPWAN radio standard developed by 3GPP to provide devices with longer battery life and broader coverage. Many authors have proposed algorithms to maximise battery life by optimising devices’ Active periods. However, more research is required to develop integrity-protection algorithms for NB-IoT and study their impact on battery life. NB-IoT, being bandwidth-constrained, transmits data as truncated packets at discrete intervals to maximise battery life. However, truncated MACs reduce cryptographic strength leading to brute-force attacks. Cumulative MAC (CuMAC), generating 256-bit authentication tags by aggregating truncated MACs, alleviates this limitation. However, CuMAC is prone to replay attacks and reduced performance due to re-transmissions, resulting in delayed responses, packet loss and battery overhead. In this paper, we propose Energy-Performance CuMAC (EP-CuMAC) by modifying CuMAC to overcome inherent flaws and suit NB-IoT’s requirements. Feedback-based mechanism is developed to improve channel quality by regulating abnormal packet delays and SINR. Machine and deep learning algorithms predict and authenticate lost messages and tags to minimise re-transmissions. EP-CuMAC re-transmits the aggregated lost packets and new messages in upcoming Active state to reduce re-transmissions. Energy-performance-security trade-offs of EP-CuMAC are studied for various encryption parameters using ns-3 and Raspberry Pi. Although EP-CuMAC consumes approximately 17.73%, 33.33% and 45.59% power, memory and execution time, respectively and thrice the re-transmitted aggregated-packet authentication time compared to CuMAC, it has 68.42% enhanced packet delivery ratio and 66.66% higher security against replay attacks. Our analysis reveals that EP-CuMAC can effectively replace CuMAC as lightweight and performance-efficient alternative for NB-IoT.

A Framework for Selecting Optimal Network Protocols for IoT Technologies in Image and Vision-based Applications

The growth of Internet-of-Things (IoT) technologies and the rapid advances in image- and video-based applications make it necessary to select the most appropriate network protocols that ensure reliable, efficient and robust system performance. This study presents a framework to help select appropriate network protocols for Narrowband IoT applications. This framework evaluates and compares the most popular wireless and wired IoT technologies, especially Narrowband IoT (NB -IoT) and 5G, based on their characteristics, strengths and limitations. The research considers factors such as latency, bandwidth, scalability, energy efficiency and reliability to determine the suitability of these protocols for each application area. This study investigated the performance of these technologies in different environments, including underwater, airborne and land environments. By providing a structured approach to selecting the optimal network protocol for specific applications, this study aims to streamline and improve the deployment and performance of IoT technologies in various industries. While this study offers comprehensive insights into the optimal selection of network protocols for various IoT applications, it primarily focuses on popular technologies and does not account for emerging technologies.

An Efficient NB-IoT Compatible GF-NOMA PHY Mechanism for mMTC

The third generation partnership project (3GPP) has proposed the narrowband Internet of things (NB-IoT) standard for serving IoT users. Improvements to the NB-IoT standard are being considered to efficiently support massive machine-type communication (mMTC) IoT applications. Subsequent releases of the NB-IoT standard envision to support mMTC using different access mechanisms. In this work, a grant-free (GF) non-orthogonal multiple access (NOMA) system compatible with the current NB-IoT standard is proposed, where the resources are divided into transmission opportunities (TOs). The TOs are further divided into multiple groups based on the repetitions adopted by the users in the system. Physical (PHY) layer procedures for preamble transmission/detection, channel estimation, data transmission/decoding, and acknowledgment (ACK) transmission/reception are described in detail for the proposed GF-NOMA system. Specifically, the preamble sequences are also used as spreading sequences for data transmission and three types of sequences -Zadoff-Chu, random Gaussian and Golay sequences are explored. Results are presented for per-user success probability, latency and energy consumption considering two NB-IoT compatible settings along with repetitions and retransmissions. It is demonstrated that the proposed GF-NOMA scheme meets the mMTC requirement recommended by the 3GPP with more than 99% per-user success probability and with the energy consumption reduced by at least 80% compared to NB-IoT, while being readily compatible with the current NB-IoT standard.

An effective technique for increasing capacity and improving bandwidth in 5G narrow-band internet of things

&lt;p&gt;In recent years, the wireless spectrum has become increasingly scarce as demand for wireless services has grown, requiring imaginative approaches to increase capacity within a limited spectral resource. This article proposes a new method that combines modified symbol time compression with orthogonal frequency division multiplexing (MSTC-OFDM), to enhance capacity for the narrow-band internet of things (NB-IoT) system. The suggested method, MSTC-OFDM, is based on the modified symbol time compression (MSTC) technique. The MSTC is a compressed waveform technique that increases capacity by compressing the occupied symbol time without losing bit error rate (BER) performance or data throughput. A comparative analysis is provided between the traditional orthogonal frequency division multiplexing (OFDM) system and the MSTC-OFDM method. The simulation results show that the MSTC-OFDM scheme drastically decreases the symbol time (ST) by 75% compared to a standard OFDM system. As a result, the MSTC-OFDM system offers four times the bit rate of a typical OFDM system using the same bandwidth and modulation but with a little increase in complexity. Moreover, compared to an OFDM system with 16 quadrature amplitude modulation (16QAM-OFDM), the MSTC-OFDM system reduces the signal-to-noise ratio (SNR) by 3.9 dB to transmit the same amount of data.&lt;/p&gt;

Pemanfaatan Narrowband IoT (NB-IoT) dalam Peningkatan Produktivitas Peternakan melalui Monitoring Otomatis

The rapid advancements in Narrowband IoT (NB-IoT) technology present significant opportunities for creating innovative products that can be implemented in daily life. One of these innovative products is the utilization of NB-IoT for monitoring cage conditions, maintenance, and boosting livestock productivity under challenging conditions that are difficult to manually control. This study aims to design an automated system capable of maintaining ideal cage conditions, including temperature, humidity, levels of ammonia (NH3 and CO2), as well as providing feed/water to livestock automatically and periodically. The research methodology involves the integration of various sensors mounted on a microcontroller, such as temperature sensors, humidity sensors, ammonia sensors, water level sensors, and pH sensors. The program executed by this microcontroller is connected to a control panel, and through the internet network, control and monitoring can be carried out using mobile and desktop devices. The test results indicate that this system is capable of providing ease in controlling the chicken coop for owners and workers, maintaining poultry health, and increasing livestock product yields from 97.17% of harvested poultry to 98.263%, with a decrease in the mortality rate from 2.830% to 1.737%. Overall, the utilization of NB-IoT technology in this research provides a positive impact on livestock management, offering an automated solution that enhances efficiency and productivity in the agricultural sector.

Dynamic spectrum access‐based augmenting coverage in narrow band Internet of Things

SummaryThe Third Generation Partnership Project launched the Narrowband Internet of Things (NB‐IoT) as part of 5G technology under Release‐13. These networks are authorized Low Power Wide Area Networks. It uses less power and sends message over long distances. The NB‐IoT is can be used widely in industries, environment, and home for automation. While comparing NB‐IoT to regular Long Term Evaluation Machine Type Communication, the repetition in uplink is 128. The extreme coverage by 164 dB in terms of Maximum Coupling Loss. The NB‐IoT is employed in deep coverage for users. If we use many repetitions in NB‐IoT technology, the results are shorter battery life and higher maintenance cost. Hence, we suggest abandoning the random spectrum access strategy in favor of a novel technique termed Dynamic Spectrum Access, which uses reinforcement learning algorithm to eliminate the shortcomings. This method is used to decrease the number of re‐transmissions so that NB‐IoT system power goes to less and augments coverage.

Electronic Sheepdog: A Novel Method in With UAV-Assisted Wearable Grazing Monitoring

The application of Internet of Things (IoT) and unmanned aerial vehicle (UAV) technology to help herders monitor livestock makes intelligent and scientific grazing possible. In order to solve the limited functionality of the existing monitoring equipment and reduce the flight time of the UAV, a novel wearable grazing system with UAV-assisted monitoring is proposed in this paper. First, the system can monitor physiological parameters such as running, falling, and feeding, as well as geographic parameters. The acquired geographic location is used to implement electronic fences. When the livestock leave the specified area, the voice playback module simulates the sound of sheepdogs to drive them back. Then, Narrowband Internet of Things (NB-IoT) technology is used to transmit data. The monitoring values of physiological and geographic parameters can be displayed on a terminal. Finally, when an alarm occurs, an UAV instead of a herder arrives at the grazing area, where the UAV is used as an auxiliary device. Combining these technologies can realize the design of electronic sheepdogs. The standby algorithm is used to reduce the system’s power consumption. The experimental results show that the reliability of livestock posture monitoring was improved by the Kalman filter algorithm, the accuracy rate of the alarm was 97.2%, the maximum positioning error was 9.378 m, the minimum positioning error was 1.259 m, and the UAV could return safely at a flying distance of 6 kilometers. Therefore, using a combination of UAV and IoT systems greatly improved the efficiency of grazing monitoring.

Active Metamaterial Antenna with Tunable Zeroth-Order Resonances for Narrowband Internet of Things

With unique electromagnetic properties, metamaterials (MTMs) provide more freedom for antenna design, particularly with the combination of active-device-enabling effective tuning. By integrating the active device and the periodical cells of MTMs, the electromagnetic characteristics of individual cells can be manipulated independently, thereby realizing multiple tunable states for MTM antennas consisting of several periodical cells. In this paper, we employ active devices such as PIN diodes to each periodical cell to tune each cell independently, thereby realizing 36 tunable zeroth-order resonances (ZORs) for the metamaterial antenna with three cells in a frequency range of 4.48–5.34 GHz. Moreover, each ZOR has a bandwidth as narrow as 0.09 GHz, indicating that the tunable ZOR antenna can be potentially applied to 5G Narrowband Internet of Things (NB-IoT).

Blockwise Joint Detection of Physical Cell Identity and Carrier Frequency Offset for Narrowband IoT Applications

This paper presents a novel formulation for detecting the secondary synchronization signal in a narrowband Internet of Things communication system. The proposed approach is supported by a noncoherent algorithm that eliminates the need for channel information. A robust joint synchronization scheme is developed by decoupling the estimations of the physical cell identity and the carrier frequency offset. We derive the detection probability of the proposed physical cell identity detector and the mean squared error of the carrier frequency offset estimator, demonstrating their accuracy through simulation results. The performance of the proposed detection scheme is compared with that of existing detection schemes in terms of both estimation accuracy and computational complexity. Experimental results confirm that the proposed synchronization method exhibits superior performance while maintaining relatively lower complexity compared with benchmark methods.

Energy-Efficient Scheduling for Search-Space Periods in NB-IoT Networks

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%.

A Design for a Lithium-Ion Battery Pack Monitoring System Based on NB-IoT-ZigBee

With environmental issues arising from the excessive use of fossil fuels, clean energy has gained widespread attention, particularly the application of lithium-ion batteries. Lithium-ion batteries are integrated into various industrial products, which necessitates higher safety requirements. Narrowband Internet of Things (NB-IoT) is an LPWA (Low Power Wide Area Network) technology that provides IoT devices with low-power, low-cost, long-endurance, and wide-coverage wireless connectivity. This study addresses the shortcomings of existing lithium-ion battery pack detection systems and proposes a lithium-ion battery monitoring system based on NB-IoT-ZigBee technology. The system operates in a master-slave mode, with the subordinate module collecting and fusing multi-source sensor data, while the master control module uploads the data to local monitoring centers and cloud platforms via TCP and NB-IoT. Experimental validation demonstrates that the design functions effectively, accomplishing the monitoring and protection of lithium-ion battery packs in energy storage power stations.

Enabling secure lightweight mobile Narrowband Internet of Things (NB-IoT) applications using blockchain

Narrowband Internet of Things (NB-IoT) is a low bandwidth 3GPP communication standard transmitting small quantities of data over long distances at random intervals. However, as NB-IoT cannot support seamless handover between base stations, its applications are limited to stationary devices, which may result in the potential risk of fake base station connections in an attempt to maintain connectivity across cells. Considering characteristics such as low power consumption and high connection density, researchers envision using NB-IoT in mobile applications such as public-bike sharing, pet tracking etc. Connecting NB-IoT devices using decentralised architecture such as blockchain ensures seamless communication in mobile applications and eliminates bottlenecks due to multiple data requests observed in centralised networks. In this paper, we develop a hybrid blockchain framework facilitating mutual authentication between base stations to enhance user privacy and prevent fake base station connections and certificate transfers. Zero-knowledge proof used as the consensus algorithm enhances user privacy and message confidentiality. IoT devices are designed to store the hashes of their approved transactions as a linear hash chain instead of the complete merkle tree to minimise hash verification complexity. Additionally, base station memory is partitioned dynamically to enhance scalability and memory utilisation efficiency. We prototype our framework on Remix IDE in Ethereum and implement it on Raspberry Pi 4. The security of the proposed framework is formally verified using Scyther. Further, we show that our approach achieves 80.50% lower computational power, 74.73% lower execution time and 50% lower memory, respectively, in comparison with existing schemes making our proposed scheme lightweight.

Self-Powered Wireless Temperature and Vibration Monitoring System by Weak Vibrational Energy for Industrial Internet of Things.

Developing self-powered smart wireless sensor networks by harvesting industrial environmental weak vibration energy remains a challenge and an impending need for enabling the widespread rollout of the industrial internet of things (IIoT). This work reports a self-powered wireless temperature and vibration monitoring system (WTVMS) based on a vibrational triboelectric nanogenerator (V-TENG) and a piezoelectric nanogenerator (PENG) for weak vibration energy collection and information sensing. Therein, the V-TENG can scavenge weak vibration energy down to 80 μm to power the system through a power management module, while the PENG is able to supply the frequency signal to the system by a comparison circuit. In an industrial vibration environment where the vibration frequency and amplitude are 20 Hz and 100 μm, respectively, the WTVMS can upload temperature and frequency information on the equipment to the cloud in combination with the narrowband IoT technology to realize real-time information monitoring. Furthermore, the WTVMS can work continuously for more than 2 months, during which the V-TENG can operate up to 100 million cycles, achieving ultrahigh stability and durability. By integrating weak vibration energy harvesting and active sensing technology, the WTVMS can be used for real-time online monitoring and early fault diagnosis of vibration equipment, which has great application prospects in industrial production, machinery manufacturing, traffic transportation, and intelligent IIoT.

Hybrid NOMA Protocol with Relay Adaptive AF/DF Collaboration and Its Modeling Analysis in NB-IoT

In order to meet the demand for large-scale device access in Narrowband Internet of Things (NB-IoT) and to overcome the problem that some resources are wasted due to the use of single decode-and-forward (DF) or amplify-and-forward (AF) collaboration in traditional collaborative communication, this paper introduces a non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) hybrid access method into the NB-IoT and proposes a new Hybrid NOMA transmission protocol with relay adaptively selectable collaboration, which is represented as an algorithm. Based on this protocol, we classify the whole transmission process into five states after deriving the outage probability of each link. We then consider the system as a discrete-time Markov model, the closed expressions of the system outage probability and throughput are derived based on the system steady-state probability. In order to improve the system’s reliability, we further optimize the above protocol by allowing the source node to retransmit the unsuccessful received superimposed signals a limited number of times. Numerical results and simulations show that the outage probability is lower when multiple retransmissions are possible. The proposed relay adaptive collaborative hybrid NOMA transmission protocol has advantages over the pure OMA transmission mode.

Quantifying the Economic and Financial Viability of NB-IoT and LoRaWAN Technologies: A Comprehensive Life Cycle Cost Analysis Using Pragmatic Computational Tools

This paper focuses on quantifying the economic and financial viability of NB-IoT and LoRaWAN technologies, two low-power wide-area network (LPWAN) technologies with unique characteristics that make them suitable for IoT applications. The purpose of this study is to propose a “pragmatic” artifact for performing life cycle cost analysis and demonstrate its application to these technologies. The methodology uses pragmatic computational tools to facilitate the analysis and considers all relevant economic and financial factors, such as operating costs, equipment costs, and revenue potential. The main finding of this study is that Narrow Band-Internet of Things (NB-IoT) and Long Range Wide Area Network (LoRaWAN) technologies have different cost structures and revenue potentials, which may affect their economic and financial viability for different IoT applications. Ultimately, the study concludes that a comprehensive life cycle cost analysis is critical to making informed decisions about technology adoption, and that the proposed methodology can be applied to other IoT technologies to gain insight into their economic and financial viability.

Monitoring and control of smart urban drainage systems using NB-IoT cellular sensor networks.

Narrow-Band-Internet of Things (NB-IoT) is a promising wireless communication technology for harsh signal propagation conditions, including underground connectivity. The purpose of this study is to evaluate the real-life signal quality of an NB-IoT cellular sensor network for the monitoring and control of urban drainage systems. The implementation of the control systems toward smart infrastructures increase the need for low-cost and low-energy-consumption underground sensing devices. A measurement campaign was conducted in Rakvere, Estonia, to analyze the NB-IoT network's coverage and underground signal quality. The results were used to analyze the flood risk reduction potential in the pilot catchment, considering the quality of NB-IoT cellular network coverage. The signal measurements showed that in the case of plastic manholes, the best cellular transmitter placement is 0.5 m below the manhole cover, and at the ground level NB-RSRP reference signal strength of -104 dBm or better must be ensured to have a link budget with optimal energy consumption for communication. The results of flood risk reduction showed that excluding control locations with insufficient signal strength increased the number of major flooding nodes by 3.9% and mean flooding duration by 4.2% which is a relatively small change and characterizes the flexibility of the developed control system.

Development of a power station unit in a distributed hybrid acquisition system of seismic and electrical methods based on the narrowband Internet of Things (NB-IoT)

Abstract. In this paper, we propose a new type of power station unit with wireless data transmission capability. This work breaks the limitation that conventional equipment is unable to upload data directly to a central unit. Based on that, a novel distributed geophysical data acquisition architecture is also proposed, enhancing the work efficiency by simplifying the system structure while maintaining core features. Designs that realise key functions including isolated high-power output, power management, wireless data transmission and high-precision clock synchronisation are introduced in this article. The prototype was packaged then, and a series of evaluation experiments were implemented to verify the key parameters of the instrument. Experiment results proved that the overall design of the instrument is feasible, and the key parameters outperform the industry leading instrument LAUL-428. Due to the wireless networking strategy, the proposed instrument further realises remote control and real-time data playback through the host computer software, making it suitable for joint geophysical exploration as well as microseismic monitoring. As for the system level, it could be customised by connecting different kinds of conventional acquisition stations for many kinds of prospecting targets.

Two-hop network design of LoRaWAN with a meta-heuristic optimization algorithm for improving downlinks

Low power wide area networks (LPWANs) are made to survive conditions of extensive installation. Technological innovations, including Global Network Operator, Long Range Wide Area Network (LoRaWAN), Narrowband Internet of Things (NB-IoT), Weightless, Sigfox, etc., have adopted LPWANs. LoRaWAN is currently regarded to be one of the most cutting-edge and intriguing technology for the widespread implementation of the IoT. Although LoRaWAN offers the best features that make it fit with Internet - of - things specifications, there are still certain technical issues to overcome, such as link coordination, resource allocation and reliable transmission. In LoRaWAN, End-devices transmit randomized uplink frames to the gateways using un-slotted random-access protocol. This randomness with the restrictions placed on the gateways is a reason that leads to a considerable decline in network performance, in particular downlink frames. In this paper, we propose a new approach to increase Acknowledgement (ACK) messages throughput. The suggested method takes advantage of both class A and class B features to enhance and assist LoRaWAN’s reliability by ensuring that an ACK message is sent for every confirmed uplink while retaining the minimum energy level that is utilized by nodes.