Article
Computer Science, Information Systems
Mahmoud A. Albreem, Khawla A. Alnajjar, Ali J. Almasadeh
Summary: Massive MIMO is a key technology in 5G and beyond 5G communication systems, used to meet high capacity demands. This paper proposes low complexity massive MIMO data detection techniques based on ZF and V-BLAST methods, using approximate matrix inversion techniques and stair matrix initialization to balance performance and complexity. Additionally, a massive MIMO detector based on approximate matrix inversion, stair matrix initialization, and deep learning is presented. Simulation results show significant improvement in performance and notable reduction in computational complexity compared to conventional methods in both simple and real channel scenarios.
Article
Chemistry, Multidisciplinary
Dong Shen, Li Chen, Hao Liang
Summary: Signal detection in massive MIMO systems faces many challenges. This paper proposes a Gauss-Seidel detector based on conjugate gradient and Jacobi iteration, with three initialization options to accelerate algorithm convergence. The suggested scheme outperforms other schemes in terms of bit error rate (BER) and approaches the performance of the MMSE detection algorithm with fewer iterations.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Electrical & Electronic
Juan Jose Murillo-Fuentes, Irene Santos, Jose Carlos Aradillas, Matilde Sanchez-Fernandez
Summary: In this paper, a new iterative detection and decoding algorithm based on expectation propagation for massive MIMO scenarios is proposed. The double-EP approach significantly improves convergence with just double the computational complexity of the LMMSE-based IDD. Additionally, low-complexity DEP detector approaches are developed using Gauss-Seidel and Neumann series methods for approximating the mean and covariance matrix of the posterior.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2021)
Article
Biology
Abida Hussain, Mohana Sundaram Muthuvalu, Ibrahima Faye, Mudasar Zafar, Mustafa Inc, Farkhanda Afzal, Muhammad Sajid Iqbal
Summary: A brain tumor is a rapidly developing and abnormal system where aberrant cells cause the healthy cells to perish. This study presents a mathematical model for brain glioma growth and compares different methods for predicting the growth of glioma cells in treating the brain tumor. The results show that the TSSOR method is faster and more efficient than the TSGS and GS methods, reducing the number of iterations and computational time.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Computer Science, Information Systems
Mahmoud A. Albreem, Wael Salah, Arun Kumar, Mohammed H. Alsharif, Ali Hanafiah Rambe, Muzammil Jusoh, Anthony Ngozichukwuka Uwaechia
Summary: This study examines iterative matrix inversion methods in massive MIMO systems, revealing that conjugate gradient and optimized coordinate descent methods offer the lowest complexity and acceptable performance. Additionally, the Gauss-Seidel method outperforms other detectors in complexity increment, with performance not improving with every iteration. Omega is shown to play a significant role in achieving satisfactory performance in both RI and SOR based detectors.
Article
Multidisciplinary Sciences
Mahmoud A. Albreem
Summary: In this paper, three efficient initialization methods of the AMP-based massive MIMO UL detector are proposed based on iterative methods, namely, the successive overrelaxation, the Gauss-Seidel, and the Jacobi. In addition, a stair matrix is exploited to achieve high convergence rate.
NATIONAL ACADEMY SCIENCE LETTERS-INDIA
(2021)
Article
Mathematics, Applied
Kamsing Nonlaopon, Farooq Ahmed Shah, Khaleel Ahmed, Ghulam Farid
Summary: This article presents a new generalized iterative technique for finding the approximate solution of a system of linear equations Ax = b. The efficiency of the iterative technique is analyzed by implementing it on some examples and comparing it with existing methods. A parameter introduced in the method plays a vital role in achieving better and quicker solutions. Convergence analysis is also examined. The findings of this paper may inspire further research in this area.
Proceedings Paper
Engineering, Electrical & Electronic
Shahriar Shahabuddin, Mahmoud A. Albreem, Mohammad Shahanewaz Shahabuddin, Zaheer Khan, Markku Juntti
Summary: This paper presents a VLSI architecture and FPGA implementation of an iterative detection algorithm based on a stair matrix, which supports massive MIMO systems with high data rate and clock frequency, providing superior error-rate performance compared to most contemporary detectors.
2021 IEEE 12TH LATIN AMERICA SYMPOSIUM ON CIRCUITS AND SYSTEM (LASCAS)
(2021)
Article
Environmental Sciences
S. R. Zhu, L. Z. Wu, T. Ma, S. H. Li
Summary: Richards' equation is widely used in unsaturated flow problems and its numerical solution can be improved by linearization and the use of integral correction method and multistep preconditioner. The proposed improved Gauss-Seidel iterative method (ICMP(m)-GS) demonstrates faster convergence rate, higher calculation efficiency and accuracy compared to traditional methods. The method is validated through examples of unsaturated flow and shows promising results in simulating rainfall infiltration of unsaturated soil slopes.
ENVIRONMENTAL EARTH SCIENCES
(2022)
Article
Mathematics, Applied
Wenxv Ding, Zhihong Liu, Ying Li, Anli Wei, Mingcui Zhang
Summary: In this paper, the Gauss-Seidel and successive over-relaxation iteration methods for quaternion linear systems Ax = b are studied and the structure-preserving algorithms of these methods are obtained. The convergence and computational cost of these iteration methods are discussed and numerical examples are given to demonstrate their efficiency. As an application, two kinds of structure-preserving iterative algorithms are applied to solve elliptic biquaternion linear systems Ax = b.
NUMERICAL ALGORITHMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Shuairun Zhu, Lizhou Wu, Ping Cheng, Jianting Zhou
Summary: A modified Gauss-Seidel iterative method has been developed for solving the problem of rainfall infiltration, showing higher computational efficiency and accuracy compared to traditional methods, with faster convergence rate and higher computation efficiency.
COMPUTERS AND GEOTECHNICS
(2022)
Article
Mathematics, Applied
Alex Bespalov, Daniel Loghin, Rawin Youngnoi
Summary: The stochastic Galerkin finite element method is an efficient numerical solution for linear elliptic partial differential equations with parametric or random inputs, but requires solving large coupled systems of linear equations. Truncation preconditioners for SGFEM were analyzed and shown to be optimal with respect to discretization parameters.
SIAM JOURNAL ON SCIENTIFIC COMPUTING
(2021)
Article
Computer Science, Software Engineering
Zhihao Wang, Yajuan Li, Jianzhen Liu, Weiyin Ma, Chongyang Deng
Summary: We propose a Gauss-Seidel progressive iterative approximation (GS-PIA) method for subdivision surface interpolation. GS-PIA inherits the good properties of progressive iterative approximation (PIA) and has a faster convergence rate than PIA and weighted progressive iterative approximation (W-PIA), does not require computing optimal weights, and preserves the mesh topology.
Article
Engineering, Electrical & Electronic
Chuan Zhang, Zhizhen Wu, Christoph Studer, Zaichen Zhang, Xiaohu You
Summary: This paper proposes an efficient GS-based soft-output data detector and corresponding VLSI architecture for massive MIMO systems, achieving throughput of 732 Mb/s with close-to-MMSE error-rate performance. Optimization methods are used to reduce processing latency and area on the VLSI architecture level. The proposed solution shows advantages in complexity and efficiency over existing designs, especially under challenging propagation conditions.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2021)
Article
Engineering, Electrical & Electronic
Haifeng Yao, Ting Li, Yunchao Song, Wei Ji, Yan Liang, Fei Li
Summary: This paper proposes a model-driven deep learning detector network called Block Gauss-Seidel Network (BGS-Net) based on the Gauss-Seidel iterative method to reduce the complexity in massive MIMO systems. By converting a large matrix inversion to small matrix inversions, BGS-Net achieves lower complexity and good robustness. Improved BGS-Net is able to further enhance the detection performance.
EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING
(2022)
Article
Green & Sustainable Science & Technology
Kanchana Kadirvel, Raju Kannadasan, Mohammed H. Alsharif, Zong Woo Geem
Summary: Electric vehicles are becoming highly preferred in domestic transportation systems due to the increasing demand and cost of fuel. Companies like Tesla, BMW, Audi, and Mercedes have entered the market with their EV offerings. This study proposes an improved interleaved phase-shifted semi-bridgeless boost converter for EV battery charging, which achieves faster charging speed and increased current injection compared to conventional converters.
Review
Robotics
Syed Agha Hassnain Mohsan, Nawaf Qasem Hamood Othman, Yanlong Li, Mohammed H. H. Alsharif, Muhammad Asghar Khan
Summary: Unmanned aerial vehicles (UAVs) or drones are widely used in various fields such as economy, commerce, leisure, military and academics. Despite facing limitations, UAVs show great potential and offer a range of features and capabilities, along with challenges and security issues. This study provides valuable insights into the potentials and characteristics of UAVs, along with future research directions.
INTELLIGENT SERVICE ROBOTICS
(2023)
Article
Energy & Fuels
Manish Kumar Singla, Jyoti Gupta, Mohammed H. Alsharif, Abu Jahid
Summary: This article presents a cost-effective and reliable solution for meeting the energy demands of remote areas through the integration of multiple renewable energy sources. The proposed system aims to reduce dependence on fossil fuels and promote sustainable development by utilizing accessible energy resources in a self-contained microgrid. The study used HOMER software to optimize the combination of energy sources and storage technologies, and identified that the solar PV/fuel cell combination is more cost-effective, reliable, and efficient compared to the solar PV/battery combination. The proposed IHRES model offers a promising solution for meeting energy demands in remote areas while reducing dependence on fossil fuels and promoting sustainable development.
Article
Energy & Fuels
Gopu Venugopal, Arun Kumar Udayakumar, Adhavan Balashanmugham, Mohamad Abou Houran, Faisal Alsaif, Rajvikram Madurai Elavarasan, Kannadasan Raju, Mohammed H. Alsharif
Summary: This article proposes a technique for detecting and categorizing interturn insulation problems in variable-speed motor drives. It combines Salp Swarm Optimization (SSO) with Recurrent Neural Network (RNN) to identify and label the insulation concerns. The proposed technique improves the system precision by simplifying the detection and classification process. The model is implemented in MATLAB/Simulink and various metrics are analyzed for evaluation.
Article
Engineering, Electrical & Electronic
Saeed Abdallah, Zeno Verboven, Mohamed Saad, Mahmoud A. Albreem
Summary: Ambient backscatter communication (AmBC) is a promising technology for low-cost, low-power devices in the Internet-of-Things (IoT) applications. This paper addresses the challenging channel estimation problem for full-duplex multi-antenna AmBC systems. Three solutions are proposed, including a pilot-based maximum likelihood (ML) estimator, a semi-blind estimator based on the expectation maximization (EM) framework, and a semi-blind estimator based on the decision-directed (DD) strategy. Simulations demonstrate the accuracy and performance superiority of the semi-blind estimators compared to the ML estimator.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Article
Chemistry, Analytical
Anupma Gupta, Vipan Kumar, Dinesh Garg, Mohammed H. Alsharif, Abu Jahid
Summary: Terahertz imaging is the most important technique for early-stage breast cancer detection, as it reduces breast cancer-related fatalities and improves quality of life. The choice of the right sensor is crucial for the development of a high-quality THz imaging system.
Article
Green & Sustainable Science & Technology
Dilip Kumar, Yogesh Kumar Chauhan, Ajay Shekhar Pandey, Ankit Kumar Srivastava, Varun Kumar, Faisal Alsaif, Rajvikram Madurai Elavarasan, Md Rabiul Islam, Raju Kannadasan, Mohammed H. Alsharif
Summary: In this paper, a novel hybrid MPPT algorithm called PSO_ML-FSSO was proposed to improve the efficiency and reduce the settling time of solar PV systems. The algorithm was compared with other well-known methods and demonstrated superior performance. The findings highlight the potential of PSO_ML-FSSO for optimizing solar PV systems.
Review
Multidisciplinary Sciences
Mohammed. H. H. Alsharif, Abu Jahid, Anabi Hilary Kelechi, Raju Kannadasan
Summary: The rise of the internet of things has had a significant impact on the economy and environment due to the billions or trillions of interconnected devices. Energy consumption becomes a crucial issue with the use of sensors, and thus, developing energy-efficient and sustainable solutions for IoT is necessary. This article examines energy-efficient practices and strategies for IoT, focusing on four framework principles including M2M communications, WSN, RFID, and microcontroller units and ICs, aiming to contribute to the implementation of eco-sustainable and energy-efficient IoT technologies in the future.
Review
Computer Science, Information Systems
Muhammad Asghar Khan, Neeraj Kumar, Syed Agha Hassnain Mohsan, Wali Ullah Khan, Moustafa M. Nasralla, Mohammed H. Alsharif, Justyna Zywiolek, Insaf Ullah
Summary: Fifth-generation (5G) cellular networks have led to beyond 5G (B5G) networks that can incorporate autonomous services into swarms of unmanned aerial vehicles (UAVs). These networks provide capacity expansion strategies to address massive connectivity issues and ensure high throughput and low latency in extreme or emergency situations. On the other hand, 6G technology integrates AI/ML, IoT, and blockchain to establish reliable, intelligent, secure, and ubiquitous UAV networks, but also poses new challenges for swarm UAVs due to new enabling technologies and unique network design.
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
(2023)
Article
Computer Science, Information Systems
Bikash Ranjan Behera, Sanjeev Kumar Mishra, Mohammed H. Alsharif, Abu Jahid
Summary: Due to the widespread use of low-power embedded devices, research into alternate energy sources is necessary. RF energy is always considered due to its accessibility. A comprehensive study on a reflective-inspired reconfigurable antenna integrated with a rectifier circuit is reported, providing broadband circular polarization and directional radiation. The findings highlight the potential for addressing limitations in RF energy harvesting.
Article
Engineering, Marine
Abdul Razzaq, Syed Agha Hassnain Mohsan, Yanlong Li, Mohammed H. Alsharif
Summary: This study presents an architectural framework and algorithms as a solution for designing and developing an IoUT system. It includes recommendations and forecasts for potential partners in the smart ocean. A case study is implemented to assess the system's usability and agility in exploiting sensor data, executing algorithms, and querying outputs for performance evaluation.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2023)
Review
Chemistry, Analytical
Annisa Anggun Puspitasari, To Truong An, Mohammed H. Alsharif, Byung Moo Lee
Summary: This study is of great significance in applying ML algorithms and their derivatives to optimize emerging 6G technologies and meet the visions and requirements of the 6G network.
Article
Chemistry, Analytical
Anupma Gupta, Vipan Kumar, Shonak Bansal, Mohammed H. Alsharif, Abu Jahid, Ho-Shin Cho
Summary: This study aims to design a compact antenna structure suitable for implantable devices in a wide frequency range, covering various bands such as ISM, WMTS, UWB, and Wi-Fi. The proposed antenna demonstrates superior performance in terms of size, bandwidth, gain, and SAR values compared to existing tri-band implantable antennas.
Article
Engineering, Multidisciplinary
Arun Kumar, Aziz Nanthaamornphong, R. Selvi, J. Venkatesh, Mohammed H. Alsharif, Peerapong Uthansakul, Monthippa Uthansakul
Summary: Smart Hospital will play a key role in improving the quality of healthcare services. Integrating technology with traditional hospitals allows for remote access to medical facilities, saving time and improving efficiency. This research focuses on enhancing power savings, spectral access, latency, and Bit error rate of 5G waveforms, while also examining the role of IoT and AI in smart hospitals.
ALEXANDRIA ENGINEERING JOURNAL
(2023)
Article
Computer Science, Information Systems
Ashish Bagwari, J. Logeshwaran, K. Usha, Kannadasan Raju, Mohammed H. Alsharif, Peerapong Uthansakul, Monthippa Uthansakul
Summary: Industrial wireless sensor networks (WSNs) are popular due to scalability and low cost, but face challenges in energy optimization and network maintenance. Machine Learning techniques are used to create an enhanced energy optimization model, identifying and optimizing node energy consumption and predicting optimal outcomes.
