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In this study, the performance of intelligent reflecting surfaces (IRSs) with a discrete phase shift strategy is examined in multiple-antenna systems. Considering the IRS network overhead, the achievable rate model is newly designed to evaluate the practical IRS system performance. Finding the optimal resolution of the IRS discrete phase shifts and a corresponding phase shift vector is an NP-hard combinatorial problem with an extremely large search complexity. Recognizing the performance trade-off between the IRS passive beamforming gain and IRS signaling overheads, the incremental search method is proposed to present the optimal resolution of the IRS discrete phase shift. Moreover, two low-complexity sub-algorithms are suggested to obtain the IRS discrete phase shift vector during the incremental search algorithms. The proposed incremental search-based discrete phase shift method can efficiently obtain the optimal resolution of the IRS discrete phase shift that maximizes the overhead-aware achievable rate. Simulation results show that the discrete phase shift with the incremental search method outperforms the conventional analog phase shift by choosing the optimal resolution of the IRS discrete phase shift. Furthermore, the cumulative distribution function comparison shows the superiority of the proposed method over the entire coverage area. Specifically, it is shown that more than 20 % of coverage extension can be accomplished by deploying IRS with the proposed method. [ABSTRACT FROM AUTHOR]

A new frame synchronization technique based on convolutional neural network (CNN) is proposed for synchronized networks. To estimate the exact packet arrival time, the receiver typically uses the correlator between the received signal and the preamble or pilot in front of the transmitted packet. The conventional frame synchronization technique searches the correlation peak within the time window. In contrast, the proposed method utilizes a CNN to find the packet arrival time. Specifically, in the proposed method, the 1D correlator output is converted into a 2D matrix by reshaping, and the resulting signal is inputted to the proposed 4-layer CNN classifier. Then, the CNN predicts the packet arrival time. To verify the frame synchronization performance, computer simulation is performed for two channel models: additive white Gaussian noise and fading channels. Simulation results show that the proposed CNN-based synchronization method outperforms the conventional correlation-based technique by 2 dB . [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicle (UAV) plays a paramount role in various fields, such as military, aerospace, reconnaissance, agriculture, and many more. The development and implementation of these devices have become vital in terms of usability and reachability. Unfortunately, as they become widespread and their demand grows, they are becoming more and more vulnerable to several security attacks, including, but not limited to, jamming, information leakage, and spoofing. In order to cope with such attacks and security threats, a proper design of robust security protocols is indispensable. Although several pieces of research have been carried out with this regard, there are still research gaps, particularly concerning UAV-to-UAV secure communication, support for perfect forward secrecy, and provision of non-repudiation. Especially in a military scenario, it is essential to solve these gaps. In this paper, we studied the security prerequisites of the UAV communication protocol, specifically in the military setting. More importantly, a security protocol (with two sub-protocols), that serves in securing the communication between UAVs, and between a UAV and a Ground Control Station, is proposed. This protocol, apart from the common security requirements, achieves perfect forward secrecy and non-repudiation, which are essential to a secure military communication. The proposed protocol is formally and thoroughly verified by using the BAN-logic (Burrow-Abadi-Needham logic) and Scyther tool, followed by performance evaluation and implementation of the protocol on a real UAV. From the security and performance evaluation, it is indicated that the proposed protocol is superior compared to other related protocols while meeting confidentiality, integrity, mutual authentication, non-repudiation, perfect forward secrecy, perfect backward secrecy, response to DoS (Denial of Service) attacks, man-in-the-middle protection, and D2D (Drone-to-Drone) security. [ABSTRACT FROM AUTHOR]

Wireless sensors are becoming essential in machine-type communications and Internet of Things. As the key performance metrics, the spectral efficiency as well as the energy efficiency have been considered while determining the effectiveness of sensor networks. In this paper, we present several power-splitting solutions to maximize the average harvested energy under a rate constraint when both the information and power are transmitted through the same wireless channel to a sensor (i.e., a receiver). More specifically, we first designed the optimal dynamic power-splitting policy, which decides the optimal fractional power of the received signal used for energy harvesting at the receiver. As effective solutions, we proposed two types of single-threshold-based power-splitting policies, namely, Policies I and II, which decide to switch between energy harvesting and information decoding by comparing the received signal power with some given thresholds. Additionally, we performed asymptotic analysis for a large number of packets along with practical statistics-based policies. Consequently, we demonstrated the effectiveness of the proposed power-splitting solutions in terms of the rate–energy trade-off. [ABSTRACT FROM AUTHOR]

Localization has been extensively studied owing to its huge potential in various areas, such as Internet of Things, 5G, and unmanned aerial vehicle services. Its wide applications include home automation, advanced production automation, and unmanned vehicle control. In this study, we propose a novel localization method that utilizes convolutional neural network (CNN) and ultra-wideband (UWB) signals. A localization problem is converted to a regression problem with the proposed CNN, in which the ranging and positioning phases are integrated. By integrating the ranging and positioning phases, the proposed CNN estimates the location of UWB transmitter directly without any additional step. To integrate both phases of localization, a simple-yet efficient input image generation method is proposed. In the proposed input image generation method, three oversampled two-dimensional input images are generated from the three received UWB signals and they are provided to the designed CNN through the three channels, which are represented by red-, green-, and blue-color channels, respectively. The proposed CNN-based localization system then estimates the location of the UWB transmitter directly using the three-channel image as an input of the CNN. Simulation results verify that the proposed CNN-based localization method outperforms the traditional threshold-based and existing CNN-based methods. Also, it is observed that the proposed method performs well under an asymmetric environment, unlike the existing method. [ABSTRACT FROM AUTHOR]

The security in vehicular ad hoc networks (VANETs) has become a large consideration in safeguarding growing applications and intelligent transport systems. A group signature, a popular authentication approach for VANETs, can be implemented to protect vehicular communications against malicious users. However, the issue of securely distributing group keys to fast-moving vehicular nodes arises. The growing size of the certificate revocation list (CRL) has provided the corresponding complication in its management and distribution in VANETs. In this paper, an efficient key management protocol for group signature based authentication is proposed. A group is extended to a domain with various roadside units forming a hierarchical topology. Our proposed scheme provides a secure method to deliver group keys to vehicular nodes, ensuring the security requirements. Similarly, through utilizing the two Bloom filters in our hierarchical topology, an efficient and scalable vehicle revocation mechanism can be achieved that can minimize the CRL size. Our experiment results demonstrate a scalable, efficient, and secure key distribution scheme in vehicular networking. Moreover, an effective CRL management mechanism can be accomplished using the hierarchical topology. [ABSTRACT FROM AUTHOR]

In this paper, a power control method is proposed for a buffer-aided relay node (RN) to enhance the energy efficiency of the RN system. By virtue of a buffer, the RN can reserve the data at the buffer when the the channel gain between an RN and a destination node (DN) is weaker than that between SN and RN. The RN then opportunistically forward the reserved data in the buffer according to channel condition between the RN and the DN. By exploiting the buffer, RN reduces transmit power when it reduces the transmit data rate and reserve the data in the buffer. Therefore, without any total throughput reduction, the power consumption of RN can be reduced, resulting in the energy efficiency (EE) improvement of the RN system. Furthermore, for the power control, we devise a simple power control method based on a two-dimensional surface fitting model of an optimal transmit power of RN. The proposed RN power control method is readily and locally implementable at the RN, and it can significantly improve EE of the RN compared to the fixed power control method and the spectral efficiency based method as verified by the rigorous numerical results. [ABSTRACT FROM AUTHOR]

To meet the diverse industrial and market demands, the International Telecommunication Union (ITU) has classified the fifth-generation (5G) into ultra-reliable low latency communications (URLLC), enhanced mobile broadband (eMBB), and massive machine-type communications (mMTC). Researchers conducted studies to achieve the implementation of the mentioned distributions efficiently, within the available spectrum. This paper aims to highlight the importance of URLLC in accordance with the approaching era of technology and industry requirements. While highlighting a few implementation issues of URLLC, concerns for the Internet of things (IoT) devices that depend on the low latency and reliable communications of URLLC are also addressed. In this paper, the recent progress of 3rd Generation Partnership Project (3GPP) standardization and the implementation of URLLC are included. Finally, the research areas that are open for further investigation in URLLC implementation are highlighted, and efficient implementation of URLLC is discussed. [ABSTRACT FROM AUTHOR]

This article presented a compact and high gain antenna with reconfigurable polarization based on two inverted-V dipoles fabricated in a crossed configuration, and with a common planar reflector. The proposed antenna could generate four different types of polarizations, such as vertical polarization (VP), horizontal polarization (HP), right-hand circular polarization (RHCP), and left-hand circular polarization (LHCP). A pair of inverted-V dipoles drove the polarization diversity, where each dipole had an integrated matching circuit and a microstrip balun. Using a crossed inverted-V configuration with a ground plane as the common reflector, we could achieve compactness in size, high directivity, and a wider beamwidth than a normal dipole antenna. To verify the performance of the proposed antenna, we fabricated a sub-6GHz antenna with a Taconic TLX-9 substrate, which had a relative permittivity of 2.5. The proposed antenna showed a measured 10-dB impedance bandwidth of 752 MHz (5.376 GHz to 6.128 GHz). The peak gains for the VP, HP, RHCP and LHCP operations at 5.8 GHz were about 5.2 dBi, 4.61 dBi, 5.25 dBic, and 5.51 dBic, respectively. In addition, the half-power beamwidth (HPBW) for all the polarizations were greater than 78° in the operation band. [ABSTRACT FROM AUTHOR]

In this paper, we consider a 2 × 2 space-time line coded (STLC) system having two-transmit and two-receive antennas. To improve the secrecy rate of the STLC system, in which an illegitimate receiver eavesdrops the information delivered from the STLC transmitter to the STLC receiver, we propose an artificial noise (AN) injection method. By exploiting the STLC structure, a novel AN for the STLC is designed and its optimal power loading factor is derived. Numerical results verify that the proposed secure STLC systems with the designed AN injection and the power control method can significantly improve the secrecy rate compared to the conventional STLC systems. It is observed that the proposed method is more effective if there is a significant gap between the main-channel and the eavesdropper-channel gains. [ABSTRACT FROM AUTHOR]

In this paper, a support vector machine (SVM) technique has been applied to an antenna allocation system with multiple antennas in multiuser downlink communications. Here, only the channel magnitude information is available at the transmitter. Thus, a subset of transmit antennas that can reduce multiuser interference is selected based on such partial channel state information to support multiple users. For training, we generate the feature vectors by fully utilizing the characteristics of the interference-limited setup in the multiuser downlink system and determine the corresponding class label by evaluating a key performance indicator, i.e., sum rate in multiuser communications. Using test channels, we evaluate the performance of our antenna allocation system invoking the SVM-based allocation and optimization-based allocation, in terms of sum-rate performance and computational complexity. Rigorous testing allowed for a comparison of a SVM algorithm design between one-vs-one (OVO) and one-vs-all (OVA) strategies and a kernel function: (i) OVA is preferable to OVO since OVA can achieve almost the same sum rate as OVO with significantly reduced computational complexity, (ii) a Gaussian function is a good choice as the kernel function for the SVM, and (iii) the variance (kernel scale) and penalty parameter (box constraint) of an SVM kernel function are determined by 21.56 and 7.67, respectively. Further simulation results revealed that the designed SVM-based approach can remarkably reduce the time complexity compared to a traditional optimization-based approach, at the cost of marginal sum rate degradation. Our proposed framework offers some important insights for intelligently combining machine learning techniques and multiuser wireless communications. [ABSTRACT FROM AUTHOR]