This article is a tutorial on using genetic algorithms to optimize antenna and scattering patterns. Genetic algorithms are "global" numerical-optimization methods, patterned after the natural processes of genetic recombination and evolution. The algorithms encode each parameter into binary sequences, called a gene, and a set of genes is a chromosome. These chromosomes undergo natural selection, mating, and mutation, to arrive at the final optimal solution. After providing a detailed explanation of how a genetic algorithm works, and a listing of a MATLAB code, the article presents three examples. These examples demonstrate how to optimize antenna patterns and backscattering radar-cross-section patterns. Finally, additional details about algorithm design are given. >

Introduction to Genetic Algorithms in Electromagnetics

Providing seamless connectivity to unmanned aerial vehicle user equipment (UAV-UE) is very challenging due to the encountered line-of-sight interference and reduced gains of down-tilted base station (BS) antennas. For instance, as the altitude of UAV-UEs increases, their cell association and handover procedure become driven by the side-lobes of the BS antennas. In this paper, the performance of cellular-connected UAV-UEs is studied under 3D practical antenna configurations. Two scenarios are studied: scenarios with static, hovering UAV-UEs and scenarios with mobile UAV-UEs. For both scenarios, the UAV-UE coverage probability is characterized as a function of the system parameters. The effects of the number of antenna elements on the UAV-UE coverage probability and handover rate of mobile UAV-UEs are then investigated. Results reveal that the UAV-UE coverage probability under a practical antenna pattern is worse than that under a simple antenna model. Moreover, vertically-mobile UAV-UEs are susceptible to attitude handover due to consecutive crossings of the nulls and peaks of the antenna side-lobes.

Performance Analysis of Mobile Cellular-Connected Drones under Practical Antenna Configurations

Implementation of an improved chaotic encryption algorithm for real-time embedded systems by using a 32-bit microcontroller

The increasing demand in 5G wireless systems has brought significant improvement in transmission speed with lower latency, especially in ultra-dense networks. The demand of privacy and security are becoming more critical in such large scale wireless networks. Different from traditional encryption methods, in this paper, we discussed the physical layer security features in large scale social networks. The opportunities in large scale social networks are summarized in physical, link and upper layer using the cross layer optimization, traditional physical layer security will meet new problems pending to be tackled. Also, we summarized the challenges due to some ideal considerations: the detection of wire-tap users, the utilization of high dynamic range and the information exchanging in cross layer design.

Physical Layer Security in 5G Based Large Scale Social Networks: Opportunities and Challenges

Cognitive radio networks (CRNs) are an emerging paradigm for next generation wireless communication systems allowing for more efficient radio spectrum utilization. In order to harness the full potential that CRNs may offer, many challenges and problems need to be overcome and addressed. One of the critical questions is the performance of secondary networks under primary user activity constraints. In this respect, queueing assumes a primary role in characterizing the delay, throughput and other performance metrics for secondary users, which in turn has implications for resource allocation, medium access control and quality of service provisioning. This survey presents an overview and classification of the various queueing models and techniques which have been proposed in the literature in the context of CRNs. Furthermore, open problems, future research directions and further potential applications related to queueing for CRNs are identified.

Queueing Models for Cognitive Radio Networks: A Survey

Two techniques are proposed for improving the accuracy of localization estimation in indoor visible light communication systems, namely, averaging and Kalman filtering with averaging schemes. In the averaging technique, the receiver position is estimated using the received signal strength (RSS) indication method multiple times (e.g., N samples), and the acquired estimations are averaged over all samples. To further improve the localization, the Kalman filtering algorithm is adopted to estimate the received power over N samples, followed by applying the RSS technique on the average received power. The proposed techniques are analyzed mathematically, considering the effects of both line-of-sight (LOS) and first-reflection from non-LOS propagations. The performance of the proposed techniques is determined by evaluating the positioning errors in a typical room. The results are compared to that of the traditional RSS system. Simulation results reveal that an improvement of about 33.3% in the average positioning error is achievable when using the averaging scheme as compared to that of the traditional RSS scheme. This improvement increases to 72.2% when adopting the proposed Kalman filtering scheme.

Improving the visible light communication localization system using Kalman filtering with averaging

A Kalman filter (KF) is employed for estimating a VLC channel. Two modulation techniques; asymmetrically clipped optical-orthogonal frequency-division multiplexing (ACO-OFDM) and direct current optical-orthogonal frequency-division multiplexing (DCO-OFDM) are applied. The results show that KF estimator outperforms other traditional estimators for both modulation techniques.

Kalman Filtering for VLC Channel Estimation of ACO-OFDM Systems

This paper focuses on improving the traffic system for Intelligent Transportation System (ITS) by using an imaging receiver instead of photodiode as a single receiver. Here, two simple traffic models have been proposed and analyzed in order to optimize the design characteristics such as signal to noise ratio, required power, received information, bit error rate, and modulation technique. First, a standalone visible light communication (VLC) with different modulation techniques is considered. The On–OFF Keying, L-Pulse Position Modulation (L-PPM), and Inverse L-Pulse Position Modulation (I-L-PPM) are investigated. Then, a hybrid communication system utilizing VLC and radio frequency (RF) is proposed for position-based services. The VLC/RF system combines the benefits of both systems and offers long distance transmission which is an important concern in ITS and in order to improve the link reliability in infrastructure to vehicle communications. This means that the probability of having a communication link between the transmitter and receiver is maintained without interruption. Then, the performance is finally evaluated. The obtained simulation results show a considerable increase in the received information using the proposed hybrid VLC/RF system compared to a VLC system.

An efficient hybrid visible light communication/radio frequency system for vehicular applications

Internet of Things (IoT) is a novel paradigm which allows many smart devices to be connected to the Internet. The rapid growth of IoT opened the door for many challenges. Security is the major challenge among those. Traditional solutions cannot keep-up with the attackers being more and more smart and powerful. Moving Target Defense (MTD) deploys mechanisms and strategies which are diverse and change over time to prevent the system vulnerabilities from being exploited. In this paper, we exploit the surrounding mobile devices as computational resources to establish virtual IoT modules acting as fake and real sensors and gateways. The proposed management framework “Hlo‘I’” dynamically changes the role of the module to continuously confuse the attacker. Virtual gateways can either be a relay to a static gateway, or a part of the fake IoT network relying fake traffic from the fake virtual sensors. Results showed the effectiveness and efficiency of the proposed system to secure IoT networks.

Honeypot-like Moving-target Defense for secure IoT Operation

Internet of Things (IoT) depicts an intelligent future, where any IoT-based devices having a sensorial and computing capabilities to interact with each other. Recently, we are living in the area of internet and rapidly moving towards a smart planet where devices are capable to be connected to each other. Cooperative ad-hoc vehicle systems are the main driving force for the actualization of IoT-based concept. Vehicular Ad-hoc Network (VANET) is considered as a promising platform for the intelligent wireless communication system. This paper presents and analyzes the tradeoffs between the security and reliability of the IoT-based VANET system in the presence of eavesdropping attacks using smart vehicle relays based on opportunistic relay selection (ORS) scheme. Then, the optimization of the distance between the source (S), destination (D), and Eavesdropper (E) is illustrated in details, showing the effect of this parameter on the IoT-based network. In order to improve the SRT, we quantify the attainable SRT improvement with variable distances between IoT-based nodes. It is shown that given the maximum tolerable Intercept Probability (IP), the Outage Probability (OP) of our proposed model approaches zero for Ge → ∞, where Ge is distance ratio between S — E via the vehicle relay (R).

Amr Mokhtar

Papers

Improving the visible light communication localization system using Kalman filtering with averaging

Kalman Filtering for VLC Channel Estimation of ACO-OFDM Systems

An efficient hybrid visible light communication/radio frequency system for vehicular applications

Honeypot-like Moving-target Defense for secure IoT Operation

Security versus reliability study for power-limited mobile IoT devices