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Feature Selection (FS) is critically important for optimising the performance of Intrusion Detection Systems (IDSs) used in Wireless Sensor Networks (WSNs). However, selecting an optimal number of relevant features from massive IDS data sets has been an ongoing FS research problem. Many approaches use Machine Learning (ML), such as nature-inspired population-based and Differential Evolution (DE)-based algorithms for FS. However, the main drawback of DE is that it has a premature convergence issue, which leads to false convergence. In this paper, a novel mutation strategy is proposed to alleviate premature convergence and to develop a modified DE-based FS algorithm called DE with maturity extension (DE-ME). The novel mutation is achieved by changing the mutation factor in the DE/rnd/1 based on K-Nearest Neighbour (KNN) as the most efficient implementation without adding further complexity to the design process. The proposed DE-ME algorithm improves the FS operation with significant performance improvements in terms of overcoming premature convergence and increasing accuracy for selection. The DE-ME algorithm was used to select the most effective features from 41 features in the Network Security Laboratory Knowledge Discovery in Databases (NSL-KDD) dataset. The accuracy of DE-ME is high at 99.66 %, its False Positive Rate (FPR) is low at 0.464 %, and the true positive rate (TPR) achieved is 99.80 %. In addition, the number of features selected by DE-ME is 6 out of 41 features in the dataset.

Reconfigurable intelligent surface (RIS) has emerged as a promising technology for supporting sixth-generation (6G) wireless communication systems. RIS intelligently manages signal reflection properties to enhance signal strength and quality at the receiver. RIS devices are inherently passive, requiring minimal power to perform signal manipulation. Through signal path optimization, interference and transmit power reduction, RIS advances energy efficiency. This aligns with the eco-friendly goals of 6G. However, efficient optimization in RIS-aided networks plays a crucial role in fully unlocking the potential of RIS. Additionally, performance evaluation of RIS-aided systems contributes to understanding optimal configurations and design guidelines for real-world RIS deployments. Despite the contributions from performance evaluation and optimization, RIS confronts various design constraints that demand innovative approaches to optimization and evaluation of their performances. Implementing RIS poses challenges in optimizing configurations for dynamic environments, handling computational complexity in large-scale systems, and adapting to changing wireless conditions. This work provides a comprehensive and in-depth survey of the state-of-the-art in joint optimization designs and performance evaluation for RIS-aided wireless systems. Furthermore, we identify areas that require further investigation to facilitate future research in addressing the existing gaps in knowledge. Finally, the survey discusses promising future research directions that include exploring optimization techniques ensuring global optima with computational efficiency, investigating analytical approaches for accurate network performance assessment under diverse conditions, advancing multi-objective joint optimization, developing application-specific integrated performance metrics, examining the joint impact of relevant RIS design parameters, investigating adaptive quantization schemes, and exploring reliable channel state estimation techniques that are resilient against dynamic environments, noise, interference, and delays.

The deployment of the millimeter (mmWave) frequency spectrum by fifth-generation (5G) device-to-device (D2D) wireless networks is anticipated to meet the growing demands for increased capacity. The antenna is regarded of as an important determinant that guarantees the maximum performance of wireless communication. This paper presents a low-profile magneto-electric (ME) dipole antenna for 5G mmWave D2D communication. A single-element quasi-loop radiator was designed to excite horizontal polarization, and a coaxial probe was used to produce vertical polarization. Subsequently, the structure of the radiator was transformed into a two-element quasi-loop antenna to achieve an omnidirectional radiation pattern with relatively enhanced gain. A coaxially fed T-junction microstrip element was implemented to equally distribute the signal between the two quasi-loop radiators and attain proper impedance matching. Furthermore, a pair of shorting pins was introduced into the two-element design to maintain the circularly polarized (CP) radiation. The finest values of the axial ratio and |S11| were derived by rigorously optimizing all the geometry parameters. Both single-element and two-element quasi-loop antennas were fabricated and characterized experimentally on the air substrate. The advantage of avoiding a physical substrate is to realize a wide bandwidth, circumvent dielectric losses, and ascertain the maximum gain. The measured and simulated results agree thoroughly with each other. Stable in-band CP radiation were accomplished, thus confirming an appropriate field vector combination from the coaxial probe and the radiator. The finalized antenna engaged an area of ~ 7.6 λ 0 2 for operation at 23.9–30.0 GHz with an axial ratio 5 dBic.

Wireless sensor networks (WSNs) are a major part of the telecommunications sector. WSN is applied in many aspects, including surveillance battlefields, patient medical monitoring, building automation, traffic control, environmental monitoring, and building intrusion monitoring. The WSN is made up of a vast number of sensor nodes, which are interconnected through a network. However, despite the growing usage of applications that rely on WSNs, they continue to suffer from restrictions, such as security issues and limited characteristics due to low memory and calculation power. Security issues lead to a lack of communication between sensors, wasting more energy. The need for efficient solutions has increased, especially with the rise of the Internet of Things, which relies on the effectiveness of WSNs. This review focuses on security issues by reviewing and addressing diverse types of WSN assaults that happened on each layer of the WSN that were published in security issues in the previous 3 years. As a consequence, this paper gives a taxonomy of security threats for each layer and different algorithmic solutions that numerous researchers who seek to counter this attack have explored. This study also presents a framework for constructing an intrusion detection system in the WSN by emphasising the drawbacks of each approach suggested by researchers to defend against specific forms of assault. In order to diminish the impact of this attack, this summary shows which attacks the majority of researchers have dealt with as well as which ones they have not yet addressed in their academic work.

A simple arrangement of wheel-shaped copper microstrip antenna is presented for operation in the 24 GHz frequency band. In this structure, a coaxial feed probe was utilized to generate vertical polarization, and a wheel-shaped microstrip with four coupling arms was used to produce horizontal polarization. An antenna comprising of two copper sheets assembled between the air-substrate was manufactured and characterized experimentally. The measured and simulated values are in close compliance with each other. A stable in-band omnidirectional radiation patterns were achieved thereby ensuring a proper combination of the field vectors from the feed probe and the radiating arms. The antenna occupied an overall footprint of 8 mm to fruitfully realize −10 dB impedance bandwidth >3 GHz and radiation efficiency of ~100%. In the operating frequency band from 22.5 to 25.7 GHz, axial ratio

In order to pursue rapid development of the new generation of wireless communication systems and elevate their security and efficiency, this paper proposes a novel scheme for automatic dual determination of modulation types and signal to noise ratios (SNR) for next generations of wireless communication systems, fifth-generation (5G) and beyond. The proposed scheme adopts unique signatures depicted in two-dimensional asynchronously sampled in-phase-quadrature amplitudes' histograms (2D-ASIQHs)-based images and applies the support vector machines (SVMs) tool. Along with the estimation of the instantaneous SNR values over 0-35 dB range, the determination of nine modulation types that belong to different modulation categories i.e., phase-shift keying (Binary-PSK, Quadrature-PSK, and 8-PSK), amplitude-shift keying (2-ASK and 4-ASK) and quadrature-amplitude modulation (4-QAM, 16-QAM, 32-QAM, and 64-QAM) could be achieved by this scheme. The application of this scheme has been simulated using a channel model that is impaired by additive white Gaussian noise (AWGN) and Rayleigh fading, covering a broad range of SNRs of 0-35 dB. The performance of this dual-determination scheme shows high modulation recognition accuracy and low mean SNR estimation error. Therefore, it can be a better alternative for designers of next generation wireless communication systems.

This paper presents a low-complexity technique for simultaneous determination of modulation types and signal-to-noise ratios (SNRs) in wireless communication systems. The proposed approach exploits the extracted features of patterns observed in signals’ asynchronous amplitudes histograms, for the simultaneous determination of these quantities using support vector machine. Features extraction has been performed by a well-known technique called principal component analysis which is used to extract the most significant features before being supplied to the artificial intelligent system. Simulations for three commonly-used modulation types have been conducted under real-world channel conditions. The results conclude that the presented approach can accurately identify the modulation types with 99.83% accuracy despite the existence of real-world channel impairments. Furthermore, the algorithm is capable of SNRs estimation over a broad range of 0–30 dB with average estimation error of 0.79 dB. The proposed paper exploits the simplicity of generating asynchronous amplitudes histograms to enable cost-effective and reduced-complexity implementation in cognitive wireless systems.