Cellular Internet Of Things Research Articles

RedCap Set Expand Device Ecosystem

An introduction to RedCap, a cellular IoT technology for the 5G era.

Medium Access Control Techniques for Massive Machine-Type Communications in Cellular IoT Networks

A key component of the Internet of things (IoT) ecosystem is wide-area network connectivity, for which cellular network technologies are a promising option through their support of massive machine-type communications (mMTC). However, numerous devices transmitting sporadically small data packets in a highly synchronized way can generate overload on the radio access network. This situation leads to a shortage of resources, especially those associated with the random access procedure for contention, control, and data transmission, causing preamble collision, control message blocking, and data collision. As a result, mMTC traffic can jeopardize the provisioning of quality of service (QoS) to end-devices, decrease the network efficiency, and increase access latency and device energy consumption. This paper proposes medium access control (MAC) techniques for addressing problems related to the support of mMTC in cellularnetworks. First, a solution for allocating control resources with QoS provisioning and access differentiation is provided, including a resource management model, a scheduling algorithm, and a message prioritization policy. Second, a mechanism for reducing data collisions is also proposed. This solution comprises a protocol in which every device with scheduled retransmission uses a probabilistic policy to decide whether to retransmit, a novel method at the device to estimate the number of nodes trying random access, and two different retransmission policies employing this estimation. Results show that the proposals support QoS, decrease access latency, decrease the device energy consumption, and increase resource utilization under massive random access.

A Micro-Acoustic Enhanced Low-Impedance Antenna System for IoT Wake-Up Receivers

In this work, we propose a passive radio frequency (RF) front-end tailored for wake-up receivers (WuRx) to be deployed in cellular IoT devices and wearables networks, featuring a low radiation resistance antenna and a high-Q matching network implemented with microacoustic resonators integrated to obtain a systematic higher node’s sensitivity at no cost in terms of power consumption. We show how these components can be co-designed to obtain high passive voltage gain, hardwarelevel blocker immunity, and increased resilience to integration parasitics, relaxing link budget for low-power IoT nodes. We report experimental validation of a PCB antenna with 2 dBi gain measured on an 11Ω input resistance at resonance, and an in-house fabricated Micro-Electro-Mechanical System (MEMS) thin-film aluminum nitride bulk acoustic resonator with a quality factor Q = 550 and a piezoelectric coupling coefficient k2 t =7%, hybridly integrated with a commercial off-the-shelf low-power WuRx circuit to benchmark the proposed RF front-end design at 850MHz. We demonstrate a passive voltage gain of 12 dB due to the MEMS resonator, and an additional 11 dB due to the proposed antenna design (for a total of an unprecedented 23 dB passive gain in this frequency range) leading to an over the air.61dBm minimum detectable input power and 23 dB blocker rejection.

Design and Implementation of a Framework for Smart Home Automation Based on Cellular IoT, MQTT, and Serverless Functions.

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.

Survey of Secure IoT using Machine Learning Approach

The future Internet of Things (IoT) will have a deep economical, commercial and social impact on our lives.[1] The participating nodes in IoT networks are usually resource constrained, which makes them luring targets for cyber-attacks [1]. Internet of Things security is attracting a growing attention from both academic and industry communities. Indeed, IoT devices are prone to various security attacks varying from Denial of Service (DoS) to network intrusion and data leakage [2]. The disruptive acceleration of Internet of Things (IoT)is drastically modifying the current ICT landscape with a massive number of cellular IoT devices expected to be deployed in the next few years. IoT devices are taking over a variety of aspects of our current lives, such as health care, transportation, and home environments [2]. Key Words: IOT, Machine Learning, Cyber Security, Security Attacks, Security, data privacy

Resource-Efficient Parallelized Random Access for Reliable Connection Establishment in Cellular IoT Networks.

The role of various internet-of-things (IoT) devices responsible for data collection and reporting becomes more important in the era of Industry 4.0. Due to the various advantages (e.g., wide coverage, robust security, etc.), the cellular networks have been continuously evolved to accommodate IoT scenario. In IoT scenario, connection establishment is essential and primary for enabling IoT devices to communicate with centralized unit (e.g., base station (BS)). This connection establishment procedure in cellular networks, random access procedure, is generally operated in a contention-based manner. So, it is vulnerable to simultaneous connection requests from multiple IoT devices to the BS, which becomes worse as the contention participants increase. In this article, we newly propose a resource-efficient parallelized random access (RePRA) procedure for resource-efficiently ensuring reliable connection establishment in cellular-based massive IoT networks. Key features of our proposed technique are twofold: (1) Each IoT device simultaneously performs multiple RA procedures in parallel to improve connection establishment success probability, and (2) the BS handles excessive use of radio resources based on newly proposed two types of redundancy elimination mechanisms. Through extensive simulations, we evaluate the performance of our proposed technique in terms of connection establishment success probability and resource efficiency under various combinations of control parameters. Consequently, we verify the feasibility of our proposed technique for reliably and radio-efficiently supporting a large number of IoT devices.

Minimizing age of information in the uplink multi-user networks via dynamic bandwidth allocation

Improving the information freshness is critical for the monitoring and controlling applications in the cellular Internet of Things (IoT). In this paper, we are interested in optimizing the bandwidth allocation dynamically to improve the information freshness of the short packet based uplink status updates, which is characterized by a recently proposed metric, age of information (AoI). We first design a status update scheme with channel distribution information (CDI). By relaxing the hard bandwidth constraint and introducing a Lagrangian multiplier, we first decouple the multi-MTCD bandwidth allocation problem into a single MTCD Markov decision process (MDP). Under the MDP framework, after variable substitution, we obtain the single-MTCD status update scheme by solving a linear programming problem. Then, we adjust the Lagrangian multiplier to make the obtained scheme satisfy the relaxed bandwidth constraint. Finally, a greedy policy is built on the proposed scheme to adjust the bandwidth allocation in each slot to satisfy the hard bandwidth constraint. In the unknown environment without CDI, we further design a bandwidth allocation scheme which only maximizes the expected sum AoI drop within each time slot. Simulation results show that in terms of AoI, the proposed schemes outperform the benchmark schemes.

Revolution in IoT with 5G Network

Abstract: Day by day Internet of Things (IoT) is gaining a huge popularity. With increase in popularity the technological advancement is required to fulfil its high data rate demand. The IoT devices will become primary need to next generation. The latest development of devices will build smaller but smart devices in field of IoT. With increase in demand of smart devices IoT architecture will become more complex. The 5G network will fulfil the need to these complex architectures. The 5G networks are expected to massively expand today’s IoT that can boost cellular operations, IoT security, and network challenges and drive the Internet future to the edge. This paper will review the revolution in IoT with introduction of 5G network along with its concept, use cases and security concerns.

Optimum GMSK based transceiver model for cellular IoT networks

This paper focuses on the evolution of cellular networks as part of their adaptation to the IoT, allowing their new belonging to the category of LPWAN networks. We will be more particularly interested in coverage extension mechanisms. The transmission chain used in this work based on GMSK scheme with maximum likelihood criterion for phase detection. During the theoretical study on the IQ-Prefilter mixed recombination mechanism, we determined an approximation expression of the mean SINR of the frame after recombination. This study allowed us to observe the impact of the temporal correlation of the propagation channel on the performance of the proposed mechanism. A TU6 (Typical Urban 6 paths) channel model will be used in this work. This model is adapted to the urban environment, in accordance with our study on the IoT and the smart city. The effect of the parameters introduced in the theoretical part such as recombination ratio, number of repetitions and duration between each repetition will be evaluated particularly regarding SINR and BER. Based on simulation, the performance of the proposed IQ-Prefilter mechanism is better than those of the IQ and Prefilter recombination for equivalent SNRs. Moreover, the performance of the IQ-Prefilter mechanism is better for low IQ-Prefilter ratios, that is to say when recombination by Prefilter is preferred to recombination by IQ. All the theoretical results and those obtained by simulation make it possible to better evaluate the performance of the suggested mechanisms in the IoT framework.

On the Age of Information and Energy Efficiency in Cellular IoT Networks With Data Compression

The Age of Information (AoI), which evaluates the information freshness, and the energy efficiency (EE) play key roles in cellular IoT networks. This is due to that outdated data can hardly provide any useful information for delay-sensitive applications and the IoT devices usually have limited battery life. In particular, the AoI can be significantly affected by the transmission latency, which becomes the bottleneck for the AoI performance in ultradensely deployed cellular IoT networks. Moreover, it is desirable for cellular IoT networks to achieve low AoI with high EE. The data compression (DC) can decrease the AoI and improve the EE by reducing the transmission latency. Therefore, in this work, the AoI and EE performance in a large-scale densely deployed uplink cellular IoT network are jointly analyzed with the DC technology. Specifically, the closed-form results of AoI are derived and validated by Monte Carlo simulations. Based on these results, the AoI–EE ratio is defined to evaluate the tradeoff between the AoI and the EE. Equipped with these results, the effects of compression ratio (CR) and status update packet generation rate (SUPGR) on both the AoI and the AoI–EE ratio are analyzed numerically. The results show that by jointly optimizing the CR and SUPGR, the AoI can be decreased by up to 82% and the AoI–EE ratio can be reduced by up to 83% as compared with the case that only adjusts the SUPGR without the DC. It indicates that the DC should be widely adopted in IoT devices, which can improve the information freshness with low-energy consumption, especially in an ultradensely deployed scenario.

Resource allocation and user assignment schemes in cellular supported industrial IoT networks

AbstractIndustrial Internet of Things (IIoT) deployment underlying cellular networks has been drawing increasing attention in recent years. In this work, we consider group based resource allocation for industrial IoT networks where cellular‐IoT (C‐IoT) devices support uplink transmission for multiple IoT groups/clusters. The joint group and subcarrier optimization problem is formulated for maximizing the cell/group throughput under the optimal group member selection, subcarrier and minimum data rate constraints. Depending on the interference information, the interference aware group allocation (IA‐GA) is proposed to find the cellular user and cellular‐IoT device grouping for each subcarrier. However, to achieve the maximizing the cell/group throughput, another iterative algorithm, namely genetic algorithm based group allocation (GA‐GA) method is proposed, which provides an optimal solution for the user grouping in the most of the cases where an iterative technique is used for the sub‐carrier allocation. Simulations results show that the proposed IA‐GA and GA‐GA methods provide enhanced cell throughput gain and accessibility of the C‐IoTs.

Short Packet-Based Status Updates in Cognitive Internet of Things: Analysis and Optimization

In the cellular Internet of Things (IoT), some machine type communication devices (MTCDs) are used to sample and send status information of monitored targets to help base station (BS) perform monitoring or controlling tasks. However, due to limited spectrum resources, the MTCDs often cannot occupy separate spectrum resources. This paper studies a cognitive IoT where the MTCDs exploit the spectrum resource vacated by cellular users to send status packets to the BS. The timeliness of status updates is characterized by the recently proposed metric, age of information (AoI). In the IoT, the packets sent by the MTCDs are often short, which means it is necessary to analyze the status updates under short packet communication theory (SPC). In this case, we adopt the automatic repeat request protocol to retransmit the erroneous packets, and the preemption policy is exploited to improve the status update performance. We first carefully analyze the evolution of AoI in the cognitive IoT, and adopt a recursive method to obtain the closed-form expression of the average peak AoI. Then, we analyze age-energy tradeoff, and propose a scheme of jointly optimizing transmit power, packet length, and spectrum sharing to reduce the average peak AoI of the network. The simulation results verify the correctness of the theoretical analysis, and show that the proposed scheme outperforms the benchmark schemes.

Real-Time Anomaly Detection in Cold Chain Transportation Using IoT Technology

There are approximately 88 million tonnes of food waste generated annually in the EU alone. Food spoilage during distribution accounts for some of this waste. To minimise this spoilage, it is of utmost importance to maintain the cold chain during the transportation of perishable foods such as meats, fruits, and vegetables. However, these products are often unfortunately wasted in large quantities when unpredictable failures occur in the refrigeration units of transport vehicles. This work proposes a real-time IoT anomaly detection system to detect equipment failures and provide decision support options to warehouse staff and delivery drivers, thus reducing potential food wastage. We developed a bespoke Internet of Things (IoT) solution for real-time product monitoring and alerting during cold chain transportation, which is based on the Digital Matter Eagle cellular data logger and two temperature probes. A visual dashboard was developed to allow logistics staff to perform monitoring, and business-defined temperature thresholds were used to develop a text and email decision support system, notifying relevant staff members if anomalies were detected. The IoT anomaly detection system was deployed with Musgrave Marketplace, Ireland’s largest grocery distributor, in three of their delivery vans operating in the greater Belfast area. Results show that the LTE-M cellular IoT system is power efficient and avoids sending false alerts due to the novel alerting system which was developed based on trip detection.

Short-Packet Communications in IoT-Aided Cellular Cooperative Networks With Non-Orthogonal Multiple Access

This paper investigates short-packet communications (SPCs) of a cooperative non-orthogonal multiple access (NOMA) Internet-of-Things (IoT)-based cellular network where an IoT master node acts as: (1) a relay for the cellular system and (2) a source for the IoT system. Accurate and asymptotic closed-form expressions for the average block error rates (BLERs) of cellular user (CU) and IoT user (IU) are derived in the presence of imperfect successive interference cancellation (SIC) and channel state information (CSI). Notably, numerical results show that: (i) IUs' performance is significantly improved by exploitation of NOMA technique and is not dominated by decode-and-forward (DF) or amplify-and-forward (AF) relaying protocol; (ii) CUs' performance may not perform well compared with orthogonal multiple access (OMA)-based systems for both AF and DF protocols; (iii) higher antenna configuration at the cellular transmitter results in a rapid BLER convergence for CU.

Secured Reliable Communication Through Authentication and Optimal Relay Selection in Blockchain Enabled Cellular IoT Networks

Secured Reliable Communication Through Authentication and Optimal Relay Selection in Blockchain Enabled Cellular IoT Networks

Joint Pilot and Data Power Control for Cell-Free Massive MIMO IoT Systems

Although cell-free massive multiple-input–multiple-output (mMIMO) Internet-of-Things (IoT) systems can improve spectral efficiency (SE) significantly compared with conventional cellular mMIMO IoT systems due to high coverage and no intercell interference, the pilot contamination and active sensors (ASs) interference can still seriously limit the further improvement of SE. In this article, we first develop a model of the cell-free mMIMO IoT system and then derive a mathematical expression of the SE to formulate a maximized sum SE optimization problem for jointly controlling pilot and data power. This problem is nonconvex; thus, a successive convex approximation (SCA) iteration algorithm is proposed, which, in fact, approximates the objective and constraint function in each iteration, and converts the initial optimization problem into an easy-to-solve geometric programming (GP) problem. Finally, simulation results show that our proposed algorithm outperforms the existing algorithms related to power control optimization in terms of the sum SE performance.

Robust off-grid analyser for autonomous remote in-situ monitoring of nitrate and nitrite in water

An off-grid, internet-of-things (IoT) connected ion chromatography analyser was developed for the real-time automated measurement of nitrate and nitrite levels in remote surface water applications. The system used KOH eluent with an AG15 guard column to achieve anion separation, in combination with a selective 235 nm UV-LED detector. A self-cleaning 3D printed Sediment Trap was developed to filter the sample before analysis, preventing silt and sediment from causing blockages and facilitating robust performance during long-term deployments. Laboratory tests showed reductions of up to 91% of total suspended solids and 61% of turbidity within the sample after a settling time of 5 min. In controlled temperature tests (7 to 40 °C), the average error in the detected concentration levels remained below 5%, indicating robust and repeatable performance of the analyser in varying environmental conditions. Two automated in-situ analysers were deployed at remote locations in West Cork, Ireland, for a period of one month. The deployments successfully demonstrated the capability of the system to detect transient pollution events, facilitating improved water-quality management of remote catchments. The analysers were monitored in real-time using a cellular IoT module and cloud-based dashboard.

Age of Information for the Cellular Internet of Things: Challenges, Key Techniques, and Future Trends

With the rapid development of cellular Internet of Things (CIoT), more and more real-time applications appear in our lives, which require timely status updates. To exactly characterize the information freshness, the concept of age of information (AoI) has received considerable interest. In this article, we start by introducing the characteristics and requirements of status updates in CIoT, and some AoI related functions are listed. However, it is nontrivial to realize real-time status updates over wireless fading channels, and we analyze the challenges for meeting AoI requirements. Next, we provide a survey on a variety of status update optimization methods and techniques. In particular, we introduce the prediction technique into the status update systems and propose a novel prediction-based status update scheme. Some numerical simulations are provided to show the performance gain obtained by the proposed scheme. Finally, we discuss some promising directions for future research in this emerging area of study.

Breaking Cellular IoT with Forged Data-plane Signaling: Attacks and Countermeasure

We devise new attacks exploiting the unprotected data-plane signaling in cellular IoT networks (a.k.a. both NB-IoT and Cat-M). We show that, despite the deployed security mechanisms on both control-plane signaling and data-plane packet forwarding, novel data-plane signaling attacks are still feasible. The attacker can forge both uplink and downlink data-plane signaling messages that pass the current security checks used by the receiver. With the capability of forging messages, the attacker can launch attacks that exhibit a variety of attack forms beyond simplistic packet-blasting, denial-of-service (DoS) threats, including location privacy breach, packet delivery loop, prolonged data delivery, throughput limiting, radio resource draining, connection reset, and multicast disabling. Our testbed evaluation and operational network validation have confirmed the attack viability. To combat the threat, we further propose a new defense solution within the 3GPP C-IoT standard framework. It leverages the synchronized timer clock information to protect the data-plane signaling messages with low overhead.

Self-Interference Cancelation-Based Workload-Driven Duplex-Model Selection in Machine-Type Communication Networks

The machine-type communication (MTC) enables a broad range of applications from mission-critical services to massive deployment of autonomous devices in the Internet of Things (IoT) networks. To release more spectrum resources for facilitating the explosive traffic of MTC in ultradense Cellular-IoT (CIoT) networks, full-duplex (FD) technology has been considered as a candidate mechanic due to its respective advantages in terms of the spectral efficiency (SE). Compared with the traditional half-duplex (HD) technology, the FD technology can (in theory) attain twice the SE gain. Nevertheless, the performance of FD technology is severely limited by both the self-interference (SI) and the mutual interference (MI) in the presence of multiple users. What is more serious is that when FD technology is used in a multiuser communication system, the system performance is very sensitive to the service load of the entire network, and it may even appear fragile in an ultrahigh load environment. In this article, we will delve into investigating the performance of the FD technique in the CIoT networks by considering the impacts of a variety of aspects, including the SI cancelation capability (SICC) of the FD-mode devices, the network’s workload, as well as the devices’ distribution density (DDD), the purpose of which is to maximize both the SE and the sum throughput (ST) of the network by optimizing those critical parameters. It is shown that the FD mode is capable of improving the ST of the CIoT networks in either the low-traffic-volume or low-device-density regime, provided that the devices’ SICC could be up to 100dB. At the same time, research results show that further increasing both the devices’ density and the traffic load, even without compromising the FD devices’ SICC, will still help improve the performance superiority of FD technology. Numerical results show that by implementing an appropriate workload-driven mode-selection scheme, we can sufficiently exploit the FD/HD gain according to the instantaneous radio frequency environment.