The integration of chaos theory and orthogonal moments has gained significant traction in contemporary image analysis. This paper presents a novel approach to image encryption and decryption, leveraging a modified logistic chaotic map and discrete orthogonal moments. The coefficients derived from Charlier polynomials and the image function are utilized to obfuscate the plaintext image. Furthermore, to bolster security measures, the pixel values of the obfuscated image are shuffled employing a modified logistic chaotic map. The encryption key is constructed from the parameters of both the chaotic map and Charlier polynomials, enhancing the robustness of the encryption scheme. Extensive experimental validation is conducted to assess the security of the proposed image encryption algorithm. Results demonstrate a considerable deviation in pixel values following diffusion via Charlier moments’ coefficients. Statistical tests and comprehensive security analyses affirm the resilience of the proposed algorithm against data loss attacks. The experimental result with Pearson correlation coefficient is almost 0, key space is greater than 2^210, and  information entropy can reach 7.8404,  which establish its superior security posture relative to existing algorithms within the domain of image encryption. The findings underscore the efficacy and reliability of the proposed scheme, positioning it as a viable solution for safeguarding sensitive image data in various applications.

The 802.11 ac protocol is widely utilized in local-area-networks with wireless access (WLANs) because of its effective 5GHz networking technology. Several path-loss and link-speed (LS) prediction models have previously been employed to aid in the effective design of 802.11 WLAN systems that predict the received-signal-strength (RSS), and LS between the client and the access-point (AP). However, majority of them fail to account for numerous indoor propagation phenomena that affect signal propagation in complex environments. This includes the shadowing that influences RSS, especially in a network system with multiple moving parts and small-scale fading, where signal reflections, obstacles, and dispersion lead to RSS fluctuations. Therefore, taking into account shadow fading influence in the LS estimation model is critical for enhancing estimation accuracy. Previously, we proposed modification of the simple log-distance model by taking shadowing variables into account which dynamically optimize the RSS and LS estimation precision of the previous model. Though our modified model outperforms the prior model, the model’s accuracy has not been evaluated in comparison to a wide range of other mathematical models. In this paper, we present the performance investigation of various estimation models for RSS and LS estimations of 802.11ac WLANs under various scenarios and analysis their performance accuracy by considering several statistical error models.  To test its relative effectiveness the proposed modified model's performance is also compared against two existing machine learning (ML) approaches. To calculate the models parameters including shadowing factor, we first show the experimental results of RSS and LS of the 802.11ac MU-MIMO link. Then, we tune the path-loss exponent, shadowing factors, and other parameters of models by taking into account experimental data. Our estimation results indicate that our modified model is more precise than the other mathematical estimation models and its accuracy is very similar to the random forest (RF) ML model, in an extensive variety of consequences with less error. 

Fifth-generation (5G) wireless communication systems employ millimeter-wave (mm-wave) frequency bands to achieve a very broad spectrum for high data rate transmission. To meet the system requirements, the best design of antenna arrays with superior performance is essential. Thus, in this paper, the design and performance analysis of single element, 2 x 1, and 4 x 1 metamaterial inspired millimeter-wave antenna (MIA) arrays are proposed. The antenna elements are designed using Rogers’ 5880 as a substrate material with a 2.2 dielectric constant and thickness of 0.35 mm to operate at a center frequency of 38 GHz. The simulated design of the single, 2 x 1, and 4 x 1 MIA arrays return loss, bandwidth, gain, voltage standing wave ratio (VSWR), and total efficiency are: -82.95 dB, -67.1 dB, -69.12 dB; 1.971 GHz, 2.278 GHz, 4.704 GHz; 7.36 dBi, 9.11 dBi, 11.4 dBi; 1.001432, 1.0009, 1.0007; and 95.55 %, 94.01 %, 95.87. As compared to other works, improved performance has been achieved by considering the effect of meta-materials on the radiator and at the ground of microstrip patch antennas (MPA). The selected type of meta-materials alters the current distribution of the radiating patch that enhances the fringing fields at the edge of MPAs, which inspires the radiation of antennas and reduces the surface wave loss at the radiators’ ground plane. The proposed MIA antenna arrays have improved upon the drawbacks of traditional MPAs and fulfill the requirements of 5G communication systems.

Millimeter-wave (mm-wave) communication stands as a vital technology for future wireless networks, necessitating efficient beamforming techniques to mitigate significant path loss and harness the extensive mm-wave spectrum. Traditional fully digital beamforming methods are often deemed unfeasible due to the substantial costs and energy requirements, which stem from the need for individual radio frequency (RF) chains for each antenna element particularly in Massive MIMO systems. Hybrid beamforming emerges as a more economical solution, reducing both hardware expenses and energy consumption by utilizing a limited number of RF chains. This paper offers an in-depth evaluation of hybrid beamforming in 5G and beyond mm-wave systems, proposing a new classification framework for various hardware configurations. The research employs a practical approach to compare different strategies, focusing on two main factors: the beam patterns produced with optimal and hybrid weights, and the resulting spectral efficiency, which is a key performance metric. The findings indicate that the beam patterns generated with both optimal and hybrid weights display comparable characteristics, especially for dominant beams. Additionally, the study shows that increasing the number of data streams leads to a significant boost in spectral efficiency, an essential element for enhancing 5G network performance. The systematic comparisons delve into the interactions and trade-offs between these design aspects, highlighting promising candidates for hybrid beamforming in the wireless communication systems of the future.

This paper explores the potential of Ultra-Massive Multiple Input Multiple Output (UM MIMO) systems as a key technology for 6G wireless communications within the Terahertz (THz) frequency band (0.1 – 10 THz). The THz spectrum offers immense capacity and speed advantages but presents significant challenges, such as higher propagation losses and limited coverage range due to atmospheric absorption and signals spreading. The study provides a comprehensive analysis of UM MIMO’s technical performance in overcoming these challenges, focusing on key metrics such as signal propagation, system capacity, and coverage range. Additionally, the research examines the optimization of beam dynamics and spectral efficiency in UM MIMO systems under various wireless channel conditions and precoding techniques. The findings highlight the importance of advanced antenna techniques and adaptive beam management in maximizing the efficiency and viability of 6G THz networks, positioning UM MIMO as a fundamental solution for next-generation wireless communication.