Browsing by Author "Abdullah, Qazwan"

Now showing 1 - 4 of 4

Citation - Scopus: 2
A Compact Size 5g Hairpin Bandpass Filter With Multilayer Coupled Line
(TECH SCIENCE PRESS, 2021) Abdullah, Qazwan; Aydoğdu, Ömer; Salh, Adeeb; Farah, Nabil; Talib, Hairul Nizam; Sadeq, Taha; Saif, Abdu
The multilayer structure is a promising technique used to minimize the size of planar microstrip filters. In the flexible design and incorporation of other microwave components, multilayer band-pass filter results in better and enhanced dimensions. This paper introduces a microstrip fifth-generation (5G) low-frequency band of 2.52-2.65 GHz using a parallel-coupled line (PCL) Bandpass filter and multilayer (ML) hairpin Bandpass filter. The targeted four-pole resonator has a center frequency of 2.585 GHz with a bandwidth of 130 MHz. The filters are designed with a 0.1 dB passband ripple with a Chebyshev response. The hairpin-line offers compact filter design structures. Theoretically, they can be obtained by bending half-wavelength resonator resonators with parallel couplings into a U shape. The proposed configuration of the parallel-coupled line resonator is used to design the ML band-pass filter. The FR4 substrate with a dielectric constant (epsilon(r)) of 4.3 and 1.6 mm thickness was used. A comparative analysis between the simulated insertion loss and the reflection coefficient of substrates RO3003 and FR4 was performed to validate the efficiency of the proposed filter design. Simulation of PCL filter is accomplished using computer simulation technology (CST) and an advanced design system (ADS) software. The PCL Bandpass filter was experimentally validated and a total tally between simulation results and measured results were achieved demonstrating a well-measured reflection coefficient. The simulated results obtained by the hairpin ML bandpass filter show that the circuit performs well in terms of Scattering(S) parameters and the filter size is significantly reduced.
Citation - WoS: 12
Citation - Scopus: 21
Investigation of the Computational Burden Effects of Self-Tuning Fuzzy Logic Speed Controller of Induction Motor Drives With Different Rules Sizes
(Ieee-Inst Electrical Electronics Engineers Inc, 2021) Farah, Nabil; Talib, Md Hairul Nizam; İbrahim, Zülkifilie; Abdullah, Qazwan; Aydoğdu, Ömer; Azri, Maaspaliza; Isa, Zainuddin Mat
Fuzzy Logic Controller (FLC) as speed controller is preferred in many AC machine drives, due to its ability to handle model non-linearity, speed variations and parameters change. Additionally, Self-Tuning FLC (ST-FLC) is a modified FLC controller to overcome the issues associated with a fixed parameter FLC and to avoid performance degradation of the machine drive. It can update the FLC parameters in accordance to any variation, changes or disturbances that may occur to the drive system. However, FLC system requires huge computation capacity which increases the computational burden of the overall machine drive system and may result in poor performance. This research proposed a simple ST-FLC mechanism to tune the main FLC speed controller. Three different rule-size of FLC (9, 25, and 49) rules are implemented with ST-FLC mechanism based Induction Motor (IM) drive. Performance comparison of the three different rule-size based ST-FLC is conducted based on simulation and experimental analysis. In addition, a computational effort is technically analyzed and compared for the three different rule-size. In the experiment, ST-FLC with less number of rules (9-rules) shows superior performance, lower sampling and lower computational efforts compared to ST-FLC with higher rule-size (25, 49) rules.
Citation - WoS: 15
Citation - Scopus: 20
Low Computational Complexity for Optimizing Energy Efficiency in Mm-Wave Hybrid Precoding System for 5g
(Ieee-Inst Electrical Electronics Engineers Inc, 2022) Salh, Adeb; Audah, Lukman; Abdullah, Qazwan; Aydoğdu, Ömer; Alhartomi, Mohammed A.; Alsamhi, Saeed Hamood; Shah, Nor Shahida M.
Millimeter-wave (mm-wave) communication is the spectral frontier to meet the anticipated significant volume of high data traffic processing in next-generation systems. The primary challenges in mm-wave can be overcome by reducing complexity and power consumption by large antenna arrays for massive multiple-input multiple-output (mMIMO) systems. However, the circuit power consumption is expected to increase rapidly. The precoding in mm-wave mMIMO systems cannot be successfully achieved at baseband using digital precoders, owing to the high cost and power consumption of signal mixers and analog-to-digital converters. Nevertheless, hybrid analog-digital precoders are considered a cost-effective solution. In this work, we introduce a novel method for optimizing energy efficiency (EE) in the upper-bound multiuser (MU) - mMIMO system and the cost efficiency of quantized hybrid precoding (HP) design. We propose effective alternating minimization algorithms based on the zero gradient method to establish fully-connected structures (FCSs) and partially-connected structures (PCSs). In the alternating minimization algorithms, low complexity is proposed by enforcing an orthogonal constraint on the digital precoders to realize the joint optimization of computational complexity and communication power. Therefore, the alternating minimization algorithm enhances HP by improving the performance of the FCS through advanced phase extraction, which involves high complexity. Meanwhile, the alternating minimization algorithm develops a PCS to achieve low complexity using HP. The simulation results demonstrate that the proposed algorithm for MU - mMIMO systems improves EE. The power-saving ratio is also enhanced for PCS and FCS by 48.3% and 17.12%, respectively.
Citation - WoS: 1
Citation - Scopus: 2
Sustainability and Latency Reduction Through Federated Learning-Powered Digital Twins in Iot Devices
(Ieee, 2024) Abdullah, Qazwan; Salh, Adeb; Ahmed, Mustafa Sami; Shah, Nor Shahida Mohd; Aydogdu, Omer; Hussain, Ghasan Ali
The rapid advancement of emerging technologies and the Internet of Things (IoT), including the evolution of Digital Twins (DT), necessitates an accelerated pace in the Beyond Fifth Generation (B5G). This is crucial to establish widespread wireless access by ensuring resilient and immediate wireless connectivity within the real network environment. This article uses edge networks and DTs with blockchain technology. Ensuring robust real-time data processing while providing a scalable and secure solution is the aim. Bridging the gap between digital systems and physical edge networks is the goal. In this research, we bridge the gap between physical edge networks and digital systems by introducing Networks with Digital Twin Edges (NDITE), which combine digital twins and edge networks. Next, we propose a blockchain-driven federated learning method in NDITE to improve data privacy and communication security. We schedule relaying users and manage bandwidth resources using DT-powered Deep Reinforcement Learning (DRL) to increase efficiency. According to the simulation results, the suggested DRL agent-based DT can minimize the weighted cost of transmission policy of edge computing strategies and choose 47.5% of computing tasks to be completed locally with 1 MHz of bandwidth. It can also exploit the optimal policy.