5G Internet Of Things Research Articles

Machine Learning Prediction Approach to Enhance Congestion Control in 5G IoT Environment

The 5G network is a next-generation wireless form of communication and the latest mobile technology. In practice, 5G utilizes the Internet of Things (IoT) to work in high-traffic networks with multiple nodes/sensors in an attempt to transmit their packets to a destination simultaneously, which is a characteristic of IoT applications. Due to this, 5G offers vast bandwidth, low delay, and extremely high data transfer speed. Thus, 5G presents opportunities and motivations for utilizing next-generation protocols, especially the stream control transmission protocol (SCTP). However, the congestion control mechanisms of the conventional SCTP negatively influence overall performance. Moreover, existing mechanisms contribute to reduce 5G and IoT performance. Thus, a new machine learning model based on a decision tree (DT) algorithm is proposed in this study to predict optimal enhancement of congestion control in the wireless sensors of 5G IoT networks. The model was implemented on a training dataset to determine the optimal parametric setting in a 5G environment. The dataset was used to train the machine learning model and enable the prediction of optimal alternatives that can enhance the performance of the congestion control approach. The DT approach can be used for other functions, especially prediction and classification. DT algorithms provide graphs that can be used by any user to understand the prediction approach. The DT C4.5 provided promising results, with more than 92% precision and recall.

Compact high isolation wideband 4G and 5G multi‐input multi‐output antenna system for handheld and internet of things applications

This article presents a compact wideband multi-input multi-output (MIMO) antenna with a high port-to-port isolation, having a height h = 3.5 mm for 4G, 5G, and Internet of things (IoT) applications. Two identical planar inverted-F antennas (PIFA) are used in this antenna system. For achieving wideband characteristics, closed-ended and open-ended rectangular slots are etched out on top plate of each PIFA, whereas a slot is etched in ground plane under the top plate of each PIFA. For achieving high isolation, a rectangular slot is etched out in the center of ground plane between two PIFAs. For further reduction in mutual coupling, a small rectangular strip is connected between the top plates of two PIFAs that introduce an antiresonance for enhancing isolation between two PIFA elements. The minimum isolation obtained between the ports of the two PIFAs is about −20 dB. The minimum impedance bandwidth obtained by the two PIFAs is from 2 to around 3.6 GHz, thus become a wide band antenna covering WLAN band (2.45GHz), 4G-LTE bands, WiMAX bands (IMT-2.1 GHz, IMT-2.3 GHz, and IMT-E 2.6 GHz), and a sub-6 GHz 5G band (3.4-3.6 GHz). The simulated results are compared with the measured ones that are generally found in good agreement. Being low profile and compact, this antenna can be used for advanced 5G communication systems and IoT devices.

Ultra-Low Power Wake-up Radio for 5G IoT

5G Internet of Things (5G IoT), which is currently under development by 3GPP, paves the way for connecting diverse categories of devices to the IoT via cellular networks. For battery-powered low-cost IoT devices, wake-up radio (WuR) appears as an eminent technique for prolonging the lifetime of such devices, thanks to its outstanding energy consumption performance. However, only some small-size battery-powered IoT devices are able to transmit to a cellular IoT base station (BS) directly. In this article, we present W2B-IoT, a prototype implementation of a WuR-based twotier system, which bridges cellular IoT BS and WuR via a Bluetooth low energy (BLE)-enabled Android smartphone. Such a WuR-enabled IoT device features a current consumption of merely 390 nA and a response time of 95 ms for decoding a wake-up call.

Distributed signal processing for dense 5G IoT platforms: Networking, synchronization, interference detection and radio sensing

Driven by the fourth industrial revolution (Industry 4.0), future and emerging Internet of Things (IoT) technologies will be required to support unprecedented services and demanding applications for massive machine-type connectivity, with low latency, high reliability and distributed information processing capability. In this article, distributed signal processing methodologies are highlighted as enablers for next generation cloud-assisted IoT systems. The proposed distributed algorithms run inside a wireless cloud network (WCN) platform and are exploited for WCN self-organization, distributed synchronization, networking and sensing. The WCN can lease augmented communication and sensing services to off-the-shelf industrial wireless devices via a dense, self-organizing “cloud” of wireless nodes. The paper introduces, at first, the WCN architecture and illustrates an experimental case study inside a pilot industrial plant. Next, it proposes a re-design of consensus-based algorithms for enabling a selected set of distributed information processing functionalities within the WCN platform, with application in practical IoT scenarios. In particular, cooperative communication algorithms are adopted to support reliable communication services. Distributed timing and carrier frequency offset estimation methods are investigated to enable low-latency services through accurate synchronization. Autonomous identification of recurring interference patterns is proposed for multiple access coordination in the shared 5G spectrum. Finally, localization and vision applications based on distributed processing of wireless signals are investigated to support contact-free human–machine interfaces.

Performance Analysis of Cognitive Clustered M2M Random Networks With Joint User and Machine Device Selection

In this paper, a machine-to-machine (M2M) communication system is proposed with joint M2M and cellular user equipment (CUE) device selection schemes to decrease the outage probability of the system. The machine devices and CUEs are positioned randomly according to a binomial point process (BPP), and two novel ordering metrics are proposed for the joint selection scheme: one based on the locations of the M2M devices and the other based on instantaneous channel gains. The simulation results confirm that the proposed selection scheme attains a significant reduction in the outage probability for M2M networks while limiting the interference to the base station (BS) by a delimited threshold. A hybrid-duplex BS is employed to switch between a half-duplex (HD) and a full-duplex (FD) to attain the best performance corresponding to various levels of residual self-interference. The closed-form formulas of the outage probability are derived for each of these ordering policies corresponding to different path loss exponents, and the analytical results are verified through Monte Carlo simulations. The proposed model and its related analysis is given in this paper lead the way for further work in the 5G Internet of Things (IoT) area.

The Role of Cloud-MANET Framework in the Internet of Things (IoT)

In the next generation of computing, Mobile ad-hoc network (MANET) will play a very important role in the Internet of Things (IoT). The MANET is a kind of wireless networks that are self-organizing and auto connected in a decentralized system. Every device in MANET can be moved freely from one location to another in any direction. They can create a network with their neighbors’ smart devices and forward data to another device. The IoT-Cloud-MANET framework of smart devices is composed of IoT, cloud computing, and MANET. This framework can access and deliver cloud services to the MANET users through their smart devices in the IoT framework where all computations, data handling, and resource management are performed. The smart devices can move from one location to another within the range of the MANET network. Various MANETs can connect to the same cloud, they can use cloud service in a real time. For connecting the smart device of MANET to cloud needs integration with mobile apps. My main contribution in this research links a new methodology for providing secure communication on the internet of smart devices using MANET Concept in 5G. The research methodology uses the correct and efficient simulation of the desired study and can be implemented in a framework of the Internet of Things in 5G.

Compressive Sensing-Based Multiuser Detection via Iterative Reweighed Approach in M2M Communications

Massive machine-to-machine (M2M) is an important application for Internet of Things in 5G. In this letter, we focus on solving the multiuser detection problem supported by low-activity code division multiple access for M2M communications. To address the user activity factor unknown issue in the optimal maximum a posterior probability and improve the signal reconstruction ability, we propose iterative reweighed and minimum mean-square-error iterative reweighed algorithms based on compressive sensing theory. The simulation results demonstrate that the proposed algorithms achieve substantial performance gain over traditional detectors.

Collaborative Sensor Network Localization: Algorithms and Practical Issues

Emerging communication network applications including fifth-generation (5G) cellular and the Internet-of-Things (IoT) will almost certainly require location information at as many network nodes as possible. Given the energy requirements and lack of indoor coverage of Global Positioning System (GPS), collaborative localization appears to be a powerful tool for such networks. In this paper, we survey the state of the art in collaborative localization with an eye toward 5G cellular and IoT applications. In particular, we discuss theoretical limits, algorithms, and practical challenges associated with collaborative localization based on range-based as well as range-angle-based techniques.

Optimal Routing for Multihop Social-Based D2D Communications in the Internet of Things

With the development of wireless communications and the intellectualization of machines, the Internet of Things (IoT) has been of interest to both industry and academia. Multihop routing and relaying are key technologies that will underpin IoT mesh networks in the future. This paper investigates optimal routing based on the trusted connectivity probability (T-CP) for multihop, underlay, device-to-device (D2D) communications with decode-and-forward relaying. Both random and fixed locations for base stations (BSs) are considered, where the former case assumes that the locations of the BSs are modeled as a Poisson point process (PPP). First, we derive two expressions for the connectivity probability (CP): 1) a tight lower bound and 2) an exact closed-form. Analysis is carried out for the cases where the channel state information (CSI) between BSs and the D2D transmitter is known (CSI-aware) and unknown (no-CSI). Interference from active cellular user equipments (CUEs) is characterized by modeling CUE locations as a PPP. Moreover, motivated by results that have shown that social behavior leads to D2D devices communicating with nearby neighbors, we derive the trust probability for D2D connections by using a rank-based model. Finally, we propose a novel routing algorithm that can achieve the highest T-CP for any pair of D2D devices in a distributed manner. The derived analytical results are verified by Monte Carlo simulations. We show that the proposed routing algorithm achieves almost the same performance as that attained through an exhaustive search. When BSs are located randomly, the optimal path based on the CP is the shortest path between the D2D transmitter and receiver. However, for fixed BSs, the optimal path selection depends on the locations of the BSs, which provides a very useful insight in designing the multihop D2D system for 5G IoT.

5G Internet of Things: A survey

Abstract The existing 4G networks have been widely used in the Internet of Things (IoT) and is continuously evolving to match the needs of the future Internet of Things (IoT) applications. The 5G networks are expected to massive expand today’s IoT that can boost cellular operations, IoT security, and network challenges and driving the Internet future to the edge. The existing IoT solutions are facing a number of challenges such as large number of connection of nodes, security, and new standards. This paper reviews the current research state-of-the-art of 5G IoT, key enabling technologies, and main research trends and challenges in 5G IoT.

A Survey of Clustering Techniques in WSNs and Consideration of the Challenges of Applying Such to 5G IoT Scenarios

Wireless sensor network (WSN) systems are typically composed of thousands of sensors that are powered by limited energy resources. To extend the networks longevity, clustering techniques have been introduced to enhance energy efficiency. This paper presents a survey on clustering over the last two decades. Existing protocols are analyzed from a quality of service (QoS) perspective including three common objectives, those of energy efficiency, reliable communication and latency awareness. This review reveals that QoS aware clustering demands more attention. Furthermore, there is a need to clarify how to improve quality of user experience (QoE) through clustering. Understanding the users’ requirements is critical in intelligent systems for the purpose of enabling the ability of supporting diverse scenarios. User awareness or user oriented design is one remaining challenging problem in clustering. In additional, this paper discusses the potential challenges of implementing clustering schemes to Internet of Things (IoT) systems in 5G networks. We indicate that clustering techniques enhanced with smart network selection solutions could highly benefit the QoS and QoE in IoT. As the current studies for WSNs are conducted either in homogeneous or low level heterogeneous networks, they are not ideal or even not able to function in highly dynamic IoT systems with a large range of user scenarios. Moreover, when 5G is finally realized, the problem will become more complex than that in traditional simplified WSNs. Several challenges related to applying clustering techniques to IoT in 5G environment are presented and discussed.

On Transform Domain Communication Systems under Spectrum Sensing Mismatch: A Deterministic Analysis

Towards the era of mobile Internet and the Internet of Things (IoT), numerous sensors and devices are being introduced and interconnected. To support such an amount of data traffic, traditional wireless communication technologies are facing challenges both in terms of the increasing shortage of spectrum resources and massive multiple access. The transform-domain communication system (TDCS) is considered as an alternative multiple access system, where 5G and mobile IoT are mainly focused. However, previous studies about TDCS are under the assumption that the transceiver has the global spectrum information, without the consideration of spectrum sensing mismatch (SSM). In this paper, we present the deterministic analysis of TDCS systems under arbitrary given spectrum sensing scenarios, especially the influence of the SSM pattern to the signal to noise ratio (SNR) performance. Simulation results show that arbitrary SSM pattern can lead to inferior bit error rate (BER) performance.

ULMAP: Ultralightweight NFC Mutual Authentication Protocol with Pseudonyms in the Tag for IoT in 5G

As one of the core techniques in 5G, the Internet of Things (IoT) is increasingly attracting people’s attention. Meanwhile, as an important part of IoT, the Near Field Communication (NFC) is widely used on mobile devices and makes it possible to take advantage of NFC system to complete mobile payment and merchandise information reading. But with the development of NFC, its problems are increasingly exposed, especially the security and privacy of authentication. Many NFC authentication protocols have been proposed for that, some of them only improve the function and performance without considering the security and privacy, and most of the protocols are heavyweight. In order to overcome these problems, this paper proposes an ultralightweight mutual authentication protocol, named ULMAP. ULMAP only uses Bit and XOR operations to complete the mutual authentication and prevent the denial of service (DoS) attack. In addition, it uses subkey and subindex number into its key update process to achieve the forward security. The most important thing is that the computation and storage overhead of ULMAP are few. Compared with some traditional schemes, our scheme is lightweight, economical, practical, and easy to protect against synchronization attack.

Dynamic Compressive Sensing-Based Multi-User Detection for Uplink Grant-Free NOMA

Non-orthogonal multiple access (NOMA) can support more users than OMA techniques using the same wireless resources, which is expected to support massive connectivity for Internet of Things in 5G. Furthermore, in order to reduce the transmission latency and signaling overhead, grant-free transmission is highly expected in the uplink NOMA systems, where user activity has to be detected. In this letter, by exploiting the temporal correlation of active user sets, we propose a dynamic compressive sensing (DCS)-based multi-user detection (MUD) to realize both user activity and data detection in several continuous time slots. In particular, as the temporal correlation of the active user sets between adjacent time slots exists, we can use the estimated active user set in the current time slot as the prior information to estimate the active user set in the next time slot. Simulation results show that the proposed DCS-based MUD can achieve much better performance than that of the conventional CS-based MUD in NOMA systems.

Enabling Massive IoT in 5G and Beyond Systems: PHY Radio Frame Design Considerations

The parameters of physical layer radio frame for 5th generation (5G) mobile cellular systems are expected to be flexibly configured to cope with diverse requirements of different scenarios and services. This paper presents a frame structure and design, which is specifically targeting Internet of Things (IoT) provision in 5G wireless communication systems. We design a suitable radio numerology to support the typical characteristics, that is, massive connection density and small and bursty packet transmissions with the constraint of low-cost and low complexity operation of IoT devices. We also elaborate on the design of parameters for random access channel enabling massive connection requests by IoT devices to support the required connection density. The proposed design is validated by link level simulation results to show that the proposed numerology can cope with transceiver imperfections and channel impairments. Furthermore, the results are also presented to show the impact of different values of guard band on system performance using different subcarrier spacing sizes for data and random access channels, which show the effectiveness of the selected waveform and guard bandwidth. Finally, we present system-level simulation results that validate the proposed design under realistic cell deployments and inter-cell interference conditions.

Smart Channel Sounder for 5G IoT: From Wireless Big Data to Active Communication

Internet-of-Things (IoT) will connect billions of smart devices and generate inundant data through prominent solutions, such as machine type communication. The Third Generation Partnership Project has launched the corresponding standards for multiple heterogeneous wireless smart devices in the long term evolution (LTE)/LTE-advanced. In the forthcoming years, the valuable information hidden in the deluge of data will be extracted and utilized in every field to improve quality and efficiency. However, the bottleneck of realizing this magnificent vista of future intelligent lives lies in how to satisfy the practical demands to transmit huge data volume through efficient wireless communication in diverse scenarios. Herein, multi-scenario wireless communication triggers critical problems in wireless channel modeling and soundings for 5G IoT, which by far, are understudied. In this paper, we introduce a general wireless channel model and its multiple up-to-date corresponding channel sounding methods for future 5G IoT green wireless communication. Through adopting the perspective of wireless big data excavation, the smart channel sounder transforms the traditional passive wireless communication scheme into an active expectation-guaranteed wireless communication scheme, which helps achieve efficient and green communication. To demonstrate the validity and efficiency of this smart sounder scheme, we make a compatible prototype testified in multiple scenarios. The multiple real-scenario experiments demonstrate that the smart sounder can function effectively, especially in those scenarios where traditional channel state information is not available or imperfect.

Enabling the IoT Machine Age With 5G: Machine-Type Multicast Services for Innovative Real-Time Applications

The Internet of Things (IoT) will shortly be undergoing a major transformation from a sensor-driven paradigm to one that is heavily complemented by actuators, drones, and robots. The real-time situational awareness of such active systems requires sensed data to be transmitted in the uplink to edge-cloud, processed, and control instructions transmitted in the downlink. Since many of these applications will be mission critical, the most suitable connectivity family will be cellular due to the availability of licensed spectrum able to protect the offered communications service. However, while much focus in the past was on the uplink of machine-type communications, little attention has been paid to the end-to-end reliability, latency, and energy consumption comprising both up and downlinks. To address this gap, in this paper, we focus on the definition, design, and analysis of machine-type multicast service (MtMS). We discuss the different procedures that need to be redesigned for MtMS and we derive the most appropriate design drivers by analyzing different performance indicators, such as scalability, reliability, latency, and energy consumption. We also discuss the open issues to be considered in future research aimed at enhancing the capabilities of MtMS to support a wide variety of 5G IoT use cases.

5G internet of things [Editor's Note

Many of the applications and use cases that drive the requirements and capabilities of 5G are about end-to-end communication between devices. In order to distinguish them from the more human-centric wireless applications such as mobile telephony and mobile broadband, these applications are often labeled machine-type communication (MTC) or more broadly as the Internet of Things (IoT). Improved provisioning, device management, and service enablement will bring a wider range of potential IoT applications. Some predictions forecast that there will be 15 billion connected MTC devices by 2021, a nearly 40 fold increase over the number of currently deployed MTC devices. Although spanning a wide range of different applications, IoT can be divided into two main categories, massive MTC and critical MTC, depending on their characteristics and requirements. Each brings its own challenges and requirements for standardization. To create a truly networked society requires market driven standardization and the deployment of standardized technology for 5G IoT devices, networks, and software.

Device-to-Device Communications for 5G Internet of Things

The proliferation of heterogeneous devices connected through large-scale networks is a clear sign that the vision of the Internet of Things (IoT) is getting closer to becoming a reality. Many researchers and experts in the field share the opinion that the next-to-come fifth generation (5G) cellular systems will be a strong boost for the IoT deployment. Device-to- Device (D2D) appears as a key communication paradigm to support heterogeneous objects interconnection and to guarantee important benefits. In this paper, we thoroughly discuss the added-value features introduced by cellular/noncellular D2D communications and its potential in efficiently fulfilling IoT requirements in 5G networks. State-of-the-art solutions, enabling radio technologies, and current standardization activities for D2D communications are surveyed and their pros and cons with reference to manifold IoT use cases pointed out. Future research directions are then presented towards a fully converged 5G IoT ecosystem.