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The papers in this special section focus on advances in security and privacy techniques in emerging wireless networks.

Relay has been a promising technique for extending the coverage area of a cellular network without incurring additional cost for wired backhaul. With this merit, relay technology has been widely considered for developing and deploying cellular networks such as IEEE 802.16j WiMAX and 3GPP LTE-Advanced. As a natural consequence, standardization for relay support is now being conducted in the 3GPP 5G

The Internet of Things (IoT) is an emerging technology whose popularity and use cases grow with every passing day. Although the domain of IoT has proven to be transformative, as the deployment size of the network increases, it becomes a huge challenge to secure such a large number of heterogeneous devices connected by a complex network having a variety of access protocols. Software defined networking

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

Nowadays, the development of the Internet of Things (IoT) has received much attention from both industry and academia. Sensors and devices connected to the IoT network can conveniently gather and collect information for further usage and analysis by IoT users. However, a large quantity of data produced by IoT devices contain sensitive information, which leads to many challenging security issues in

Data sharing among connected and autonomous vehicles without any protection will cause private information leakage. Simply encrypting data introduces a heavy overhead; most importantly, when encrypted data (ciphertext) is decrypted on a vehicle, the receiver will be fully aware of the sender's data, implying potential data leakage. To tackle these issues, we propose an edge-assisted privacy-preserving

LBSs have been prospering over recent years. Although many LPPMs are proposed to solve specific problems under certain settings, it is still hard to satisfy the different demands of users due to the diverse requirements for quality of service (QoS) and privacy preservation. In this article, we propose an adaptive scheme to achieve fine-grained QoS for privacy-aware users in LBSs. Specifically, we construct

Deploying blockchain in IoT is an effective way to address traditional security issues. However, existing approaches have two major limitations: since the blockchain itself is subject to attacks, including selfish mining, double spending, and distributed denial of service attacks, IoT smart devices are also vulnerable once hackers successfully invade blockchain systems; due to the heterogeneity and

A reputation management scheme plays a critical role for secure communications in vehicular networks. However, due to the limited wireless communication in the past few years, the existing solutions fail to capture the current high-performance network communication provided by the 5G network. As a result, the attributes of security and efficiency can hardly be satisfied at the same time. In this article

Outlier detection in the Internet of Things (IoT) is an essential challenge issue studied in numerous fields, including fraud monitoring, intrusion detection, secure localization, trust management, and so on. Conventional outlier detection technologies cannot be used directly in IoT due to the open nature of wireless communication as well as the resource-constrained characteristics of end nodes. Therefore

Wireless communication is the most important carrier for covert channels because increasing security threats have made covert channels an alternative to transmitting confidential information in untrusted wireless communications. As a solution for next-generation mobile communication, voice over LTE (VoLTE) is developed using a high-speed packet-switched core network to provide high-quality end-to-end

Authentication is the most pervasive means for developers to protect users' private data against attacks while using mobile applications. Incorrect implementations of authentication make users' accounts vulnerable to several attacks such as eavesdropping attacks, reply attacks, and man-inthe- middle attacks, and thus break the first line of defense in securing mobile services. To solve this problem

Mobile social applications have been widely used by Internet users. Users can efficiently acquire many kinds of information and share their statuses by various social platforms. However, when a user intends to share information through the user's social applications, the user can set the access permission only before the information is posted. Once the information is posted, it is completely beyond

In this article, we introduce a novel deception strategy inspired by the "Borrowing Arrows with Thatched Boats" strategy, one of the most famous military tactics in history, in order to defeat reactive jamming attacks for low-power IoT networks. Our proposed strategy allows resource-constrained IoT devices to be able to defeat powerful reactive jammers by leveraging their own jamming signals. More

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In an increasingly interconnected world, the demand for smartphones, tablets, and other wireless devices in the IoT has surged over the last few years. This high demand has increased mobile data usage and wireless communication, resulting in an explosion of traffic demand in the limited 2.4 GHz frequency band. This traffic demand and the limitations of existing wireless devices operating in the same

Artificial intelligence (AI)-driven fog computing (FC) and its emerging role in vehicular networks is playing a remarkable role in revolutionizing daily human lives. Fog radio access networks are accommodating billions of Internet of Things devices for real-time interactive applications at high reliability. One of the critical challenges in today's vehicular networks is the lack of standard wireless

The rise of big data and AI boosts the development of future wireless networks. However, due to the high cost of data offloading and model training, it is challenging to implement network intelligence based on the existing centralized learning strategies, especially at the edge of networks. To provide a feasible solution, a paradigm of federated learning- enabled intelligent F-RANs is proposed, which

The rapid development of wireless communication technology and smart devices has made the traditional cloud-based Internet of Things architecture unable to meet the stringent requirements of 5G mobile communication networks. In order to realize high-reliability and low-latency communication for 5G, F-RANs have become a potential evolution path. However, F-RANs still face several challenges regrading

Recently, fog-computing-based radio access networks (F-RANs) have been conceptualized to provide high quality of experience (QoE) for adaptive bit rate (ABR) streaming, where additional computing capacity is supplemented on fog nodes to facilitate complicated cross-layer optimization (i.e., joint bit rate selection and radio resource allocation). However, finding an optimal global solution with acceptable

With the advent of 5G wireless communication systems, multimedia data is predicted to grow rapidly in the near future. As a result, the large amount of multimedia data puts huge pressure on wireless communication, which poses a huge challenge to network capacity. Multimedia data (image/ video) intelligent compression is an effective way to increase the network capacity and improve the user's QoE. The

Fog computing has emerged as a unifying platform to provide computing, communication, and storage for a variety of mobile applications. That helps achieve high bandwidth, high intelligence, low latency, and low energy consumption in handling massive networking devices and emerging rich multimedia services in 5G networks. Current prominence and future promises are changing from the Internet of Things

Industrial robots are widely adopted in modern industries, including automobile manufacturing, warehousing, and so on. The industrial robot with cellular network connection will be more flexible and intelligent than that without a network connection or with a conventional industrial communication network connection (e.g., fieldbus, real-time Ethernet, and WiFi). This is seen as the direction of development

F-RAN is regarded as a promising paradigm for mobile networks to alleviate the unprecedented traffic pressures and meet quality of service requirements of various 5G services with great flexibility. To make F-RAN work in a reliable, efficient, and smart way, AI-enabled F-RAN could be innovative in a number of directions: computing task offloading, resource management, dynamic beam selection, cross-layer

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The articles in this special section provide a comprehensive overview on the recent development of the intelligent radio. The advances in wireless communications have continuously been pushing the limit of radio technologies. Nowadays, radio networks can provide extremely high data rate, ultra-low latency, and high reliability to serve communication needs of sectors that could not be imagined before

In this article, we present a pathway to intelligent radio. After briefly reviewing the CR enabling techniques developed in the past couple of decades, we introduce the recent advances on ML in communications, especially those that can be applied to CR straightforwardly. Then we discuss those AI techniques that have been specifically designed to make spectrum sensing and spectrum access intelligent

5G wireless communication networks are currently being deployed, and B5G networks are expected to be developed over the next decade. AI technologies and, in particular, ML have the potential to efficiently solve the unstructured and seemingly intractable problems by involving large amounts of data that need to be dealt with in B5G. This article studies how AI and ML can be leveraged for the design

Assigning bands of the wireless spectrum as resources to users is a common problem in wireless networks. Typically, frequency bands were assumed to be available in a stable manner. Nevertheless, in recent scenarios where wireless networks may be deployed in unknown environments, spectrum competition is considered, making it uncertain whether a frequency band is available at all or at what quality.

License-assisted access (LAA) to unlicensed spectrum is a potential solution to improve the resource availability and system scalability of 5G/ B5G networks. Challenges arise from coexistence between LAA and incumbent systems, especially the ubiquitous IEEE 802.11 WiFi systems. This article demonstrates that the coexistence can be substantially improved by leveraging learning-based clustering of small

The explosive growth of wireless devices and data rate demands makes spectrum scarcity a serious problem. A promising solution is to employ OSA, which enables SUs to seek and opportunistically exploit the underutilized spectrum without interrupting the data transmission of PUs. However, the real-world implementation of OSA still faces several critical challenges including lack of global information

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Spectrum sensing, which helps to resolve the coexistence issue and optimize spectrum efficiency, plays an important role in future wireless communication systems. However, the upcoming 5G communication involves diversified scenarios with different characteristics and diverse requirements. This tendency makes it difficult for spectrum sensing methods to flexibly serve various applications while maintaining

Integrated satellite-terrestrial networks (ISTNs) toward beyond fifth-generation (B5G) wireless systems benefiting from both satellite and terrestrial systems can achieve all-time seamless and broad coverage. Considering the scarcity of frequency resources and intense satellite-terrestrial cochannel interference, intelligent resource allocation with high spectrum efficiency and low co-channel interference

Deep learning is a branch of machine learning that learns the high-level abstraction of data in a layered structure. Since its invention, it has been successfully applied in many image and speech processing applications. The success of deep learning depends on how big the data size is. Recently, the number of smart sensors and the Internet of Things have increased exponentially. This, in turn, has

Beamforming is evidently a core technology in recent generations of mobile communication networks. Nevertheless, an iterative process is typically required to optimize the parameters, making it ill-placed for real-time implementation due to high complexity and computational delay. Heuristic solutions such as zero-forcing are simpler but at the expense of performance loss. Alternatively, DL is well

The upcoming Internet of Things and fifth generation communications are expected to support short package transmissions with low complexity and low energy consumption, which motivates applications of noncoherent communications. First, we review the design methods for noncoherent communications based on two statistical schemes, that is, maximum likelihood (ML) decoding and energy-based decoding, which

5G wireless network technology will not only significantly increase bandwidth but also introduce new features such as mMTC and URLLC. However, high request latency will remain a challenging problem even with 5G due to the massive requests generated by an increasing number of devices that require long travel distances to the services deployed in cloud centers. By pushing the services closer to the edge

In this work, we propose a new deep imitation learning (DIL)-driven edge-cloud computation offloading framework for MEC networks. A key objective for the framework is to minimize the offloading cost in time-varying network environments through optimal behavioral cloning. Specifically, we first introduce our computation offloading model for MEC in detail. Then we make fine-grained offloading decisions

Caching content on mobile devices reduces not only the transmission of backhaul links but also the latency of content acquisition. However, in the existing caching schemes, the joint effect of the caching-aware indicator of users and content dimensions on the caching strategy is not considered. Thus, how to learn fine-grained caching- aware indicators and design caching schemes are still challenging

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The 5G Phase-2 and beyond wireless systems will focus more on vertical applications such as autonomous driving and the Industrial Internet of Things, many of which are categorized as uRLLC. In this article, an alternative view of uRLLC is presented, information latency, measuring the distortion of information resulting from time lag of its acquisition process, which is more relevant than conventional

Unmanned aerial vehicles (UAVs) can be powerful Internet of Things components to execute sensing tasks over the next-generation cellular networks, which are generally referred to as the cellular Internet of UAVs. However, due to the high mobility of UAVs and shadowing in airto-ground channels, UAVs operate in a dynamic and uncertain environment. Therefore, UAVs need to improve the quality of service

MmWave communication suffers from severe path loss due to high frequency and is sensitive to blockages because of high penetration loss, especially in mobile communication scenarios. It highly depends on line-of-sight channels and narrow beams, and thus efficient beam tracking and beam alignment are necessary techniques to maintain robust communication links, in which tracking user mobility lays the

Radio FD has emerged as an attractive technique capable of doubling the spectral efficiency over half duplex. However, for signal reception, an FD node needs to suppress its transmitter's signals quite significantly. In point to point communication systems, these transmitter signals are termed self-interference. When working with an FD mobile network, the self-interference problem becomes much more

Unmanned aerial vehicle (UAV)-enabled communication networks are promising in the fifth and beyond wireless communication systems. In this paper, we shed light on three UAV-enabled mobile edge computing (MEC) architectures. Those architectures have been receiving ever increasing research attention for improving computation performance and decreasing execution latency by integrating UAV into MEC networks

VLC performs the dual-functions of communication and lighting and will play an important role in next-generation wireless communications. Proper multiple access methods should be identified for VLC in multi-user scenarios. This article proposes a VLC-CDMA system using OCCs, which are unipolar codes with a multiple sub-codes structure. OCCs offer good autocorrelation and cross-correlation functions

The practical development of WUSN would benefit numerous applications, including online infrastructure monitoring, earthquake warning systems, and agricultural automation. However, state-of- the-art RF electromagnetic wireless systems are ineffective for communicating through-soil, due to extreme signal path losses from absorption and scattering in soil, even though the typical data requirements for

IoT provides ubiquitous connectivity and pervasive intelligence. Challenges arise from the data-intensive applications pertaining to IoT. The major contribution of this article is a new asymptotically optimal, fully decentralized, real-time framework which seamlessly integrates wireless computation offloading and fog computing in IoT networks with random traffic variations over space and time. Other

With the explosive growth of data traffic over wireless access networks, the use of the millimeter- wave band becomes inevitable due to the spectrum scarcity in lower frequencies and the availability of large chunks of underutilized spectrum in this band. The rapid evolution of wireless technologies and co-existence of legacy and emerging wireless infrastructures are leading to complex network operation