Internet of Things (IoT) is an emerging domain that promises ubiquitous connection to the Internet, turning common objects into connected devices. The IoT paradigm is changing the way people interact with things around them. It paves the way for creating pervasively connected infrastructures to support innovative services and promises better flexibility and efficiency. Such advantages are attractive not only for consumer applications, but also for the industrial domain. Over the last few years, we have been witnessing the IoT paradigm making its way into the industry marketplace with purposely designed solutions. In this paper, we clarify the concepts of IoT, Industrial IoT, and Industry 4.0. We highlight the opportunities brought in by this paradigm shift as well as the challenges for its realization. In particular, we focus on the challenges associated with the need of energy efficiency, real-time performance, coexistence, interoperability, and security and privacy. We also provide a systematic overview of the state-of-the-art research efforts and potential research directions to solve Industrial IoT challenges.

Industrial Internet of Things: Challenges, Opportunities, and Directions

Device-to-Device (D2D) communication has emerged as a promising technology for optimizing spectral efficiency in future cellular networks. D2D takes advantage of the proximity of communicating devices for efficient utilization of available resources, improving data rates, reducing latency, and increasing system capacity. The research community is actively investigating the D2D paradigm to realize its full potential and enable its smooth integration into the future cellular system architecture. Existing surveys on this paradigm largely focus on interference and resource management. We review recently proposed solutions in over explored and under explored areas in D2D. These solutions include protocols, algorithms, and architectures in D2D. Furthermore, we provide new insights on open issues in these areas. Finally, we discuss potential future research directions.

A Survey of Device-to-Device Communications: Research Issues and Challenges

One of the most engaging challenges for mobile operators today is how to manage the exponential data traffic increase. Mobile data offloading stands out as a promising and low-cost solution to reduce the burden on the cellular network. To make this possible, we need a new hybrid network paradigm that leverages the existence of multiple alternative communication channels. This entails significant modifications in the way data are handled, affecting also the behavior of network protocols. In this paper, we present a comprehensive survey of data offloading techniques in cellular networks and extract the main requirements needed to integrate data offloading capabilities into today's mobile networks. We classify existing strategies into two main categories, according to their requirements in terms of content delivery guarantees: delayed and nondelayed offloading. We overview the technical aspects and discuss the state of the art in each category. Finally, we describe in detail the novel functionalities needed to implement mobile data offloading in the access network, as well as current and future research challenges in the field, with an eye toward the design of hybrid architectures.

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Data Offloading Techniques in Cellular Networks: A Survey

Direct communication between two or more devices without the intervention of a base station, known as device-to-device (D2D) communication, is a promising way to improve performance of cellular networks in terms of spectral and energy efficiency. The D2D communication paradigm has been largely exploited in non-cellular technologies such as Bluetooth or Wi-Fi but it has not yet been fully incorporated into existing cellular networks. In this regard, a new proposal focusing on the integration of D2D communication into LTE-A has been recently approved by the 3GPP standardization community as discussed in this paper. In cellular networks, D2D communication introduces several critical issues, such as interference management and decisions on whether devices should communicate directly or not. In this survey, we provide a thorough overview of the state of the art focusing on D2D communication, especially within 3GPP LTE/LTE-A. First, we provide in-depth classification of papers looking at D2D from several perspectives. Then, papers addressing all major problems and areas related to D2D are presented and approaches proposed in the papers are compared according to selected criteria. On the basis of the surveyed papers, we highlight areas not satisfactorily addressed so far and outline major challenges for future work regarding efficient integration of D2D in cellular networks.

In-Band Device-to-Device Communication in OFDMA Cellular Networks: A Survey and Challenges

The ever-increasing number of resource-constrained machine-type communication (MTC) devices is leading to the critical challenge of fulfilling diverse communication requirements in dynamic and ultra-dense wireless environments. Among different application scenarios that the upcoming 5G and beyond cellular networks are expected to support, such as enhanced mobile broadband (eMBB), massive machine type communications (mMTCs), and ultra-reliable and low latency communications (URLLCs), the mMTC brings the unique technical challenge of supporting a huge number of MTC devices in cellular networks, which is the main focus of this paper. The related challenges include quality of service (QoS) provisioning, handling highly dynamic and sporadic MTC traffic, huge signalling overhead, and radio access network (RAN) congestion. In this regard, this paper aims to identify and analyze the involved technical issues, to review recent advances, to highlight potential solutions and to propose new research directions. First, starting with an overview of mMTC features and QoS provisioning issues, we present the key enablers for mMTC in cellular networks. Along with the highlights on the inefficiency of the legacy random access (RA) procedure in the mMTC scenario, we then present the key features and channel access mechanisms in the emerging cellular IoT standards, namely, LTE-M and narrowband IoT (NB-IoT). Subsequently, we present a framework for the performance analysis of transmission scheduling with the QoS support along with the issues involved in short data packet transmission. Next, we provide a detailed overview of the existing and emerging solutions toward addressing RAN congestion problem, and then identify potential advantages, challenges, and use cases for the applications of emerging machine learning (ML) techniques in ultra-dense cellular networks. Out of several ML techniques, we focus on the application of low-complexity $Q$ -learning approach in the mMTC scenario along with the recent advances toward enhancing its learning performance and convergence. Finally, we discuss some open research challenges and promising future research directions.

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Toward Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions

LPWAN is a type of wireless telecommunication network designed to allow long range communications with relaxed requirements on data rate and latency between the core network and a high-volume of battery-operated devices This article first reviews the leading LPWAN technologies on both unlicensed spectrum (SIGFOX, and LoRa) and licensed spectrum (LTE-M and NB-IoT) Although these technologies differ in many aspects, they do have one thing in common: they all utilize the narrow-band transmission mechanism as a leverage to achieve three fundamental goals, that is, high system capacity, long battery life, and wide coverage This article introduces an effective bandwidth concept that ties these goals together with the transmission bandwidth, such that these contradicting goals are balanced for best overall system performance

Narrowband Wireless Access for Low-Power Massive Internet of Things: A Bandwidth Perspective

This article first reviews the proximity discovery techniques used in most device-to-device communication systems. The associated issues when applied to a cellular network and the potential solutions are then addressed. We propose a unified discovery design for full, partial, and off-network coverage scenarios. We discuss the advantages and disadvantages of packet and signature-based discovery schemes. We present a signature-based discovery design as a conceptual example for cellular applications. Through this example, we demonstrate that a cellular network can benefit from the information provided by the device discovery that a traditional cellular system lacks so that resources, interference, and connection selection can be more efficiently managed under a unified cellular network centric architecture.

Proximity discovery for device-to-device communications over a cellular network

Zadoff-Chu (ZC) sequences have been used as synchronization sequences in modern wireless communication systems, replacing the conventional pseudorandom noise sequences due to their perfect autocorrelation properties. We first study the problem of ambiguity between a timing offset and a frequency offset, which arises when a ZC sequence is used as a synchronization signal. We then show how a frequency offset can impair the timing property of a ZC sequence, causing irreducible timing errors. An analytical framework, particularly the timing spectrum, is developed, which fully characterizes a ZC sequence's timing properties and its fundamental limitations as a time synchronization sequence in the presence of a frequency offset between the transmitter and the receiver. This analytical framework provides a powerful analytical tool for timing signal design and performance analysis of ZC sequences.

Analysis of the Frequency Offset Effect on Zadoff–Chu Sequence Timing Performance

Physical layer control signals in cellular communications serve the purpose of delivering physical layer control messages in a timely fashion to support cell radio resource management and data transmissions between the network and the mobile users. This article describes the evolution of 3GPP LTE in control channel design. The legacy LTE control channels (Release 8) have proven to be well-designed robust channels for signaling physical layer messages. However, emerging wireless communication transmission technologies continue to challenge the traditional design of LTE control channels. We have reached a point where a totally new design of the control channels has to be provided in order for the new transmission features to be introduced into LTE. In this article we first give an overview of the legacy LTE control channel, and present the new challenges. We then describe in depth the new solutions provided by LTE (Release 11). Finally, we address the limitations of the new design, which are recently identified in certain newly-emerging applications, in particular, the machine-type communications. A new round of evolution is hence imperative. New solutions provided by next release of LTE (Release 13) are presented.

The Evolution of LTE Physical Layer Control Channels

Although the development of the next generation (i.e., 5G) of wireless networks is in its initial phase, it is widely agreed that some key technologies will play a vital role in the realization of 5G, such as millimeter waves, massive MIMO, small cells, and new radio air interfaces. Among these, densely deployed small cell networks are believed to be one of the most practical solutions to the 5G promise of truly ubiquitous mobile broadband. However, synchronization between densely deployed small cells is the key to the materialization of the benefits a small cell network promises, and is one of the most challenging issues of small cell networks. In this article, we overview the existing network synchronization techniques and address their limitations in small cell network deployment environments. There are two primary synchronization techniques in today's communication networks. GNSS provides the most accurate synchronization accuracy. However, due to environmental and cost limitations, GNSS may not be available in some small cell deployment scenarios (e.g., indoors). Another synchronization technique is IEEE 1588, the accuracy of which depends highly on backhaul conditions. We therefore study the feasibility of a radio-interface- based solution as a practical alternative to the synchronization problem of a dense small cell network with an application to LTE.

Mao Wang

Papers

Narrowband Wireless Access for Low-Power Massive Internet of Things: A Bandwidth Perspective

Proximity discovery for device-to-device communications over a cellular network

Analysis of the Frequency Offset Effect on Zadoff–Chu Sequence Timing Performance

The Evolution of LTE Physical Layer Control Channels

Network synchronization for dense small cell networks