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Imran Khan; Pakistan Us-Pakistan Center For Advanced Studies In Energy Uet Peshawar; Umair Iqbal. TRNSYS Modeling and Simulation of a Solar-Fuel Hybrid Thermal Power Plant based on a Central Receiver System. International journal of Engineering Works 2021, 8, 139 -142.
AMA StyleImran Khan, Pakistan Us-Pakistan Center For Advanced Studies In Energy Uet Peshawar, Umair Iqbal. TRNSYS Modeling and Simulation of a Solar-Fuel Hybrid Thermal Power Plant based on a Central Receiver System. International journal of Engineering Works. 2021; 8 (04):139-142.
Chicago/Turabian StyleImran Khan; Pakistan Us-Pakistan Center For Advanced Studies In Energy Uet Peshawar; Umair Iqbal. 2021. "TRNSYS Modeling and Simulation of a Solar-Fuel Hybrid Thermal Power Plant based on a Central Receiver System." International journal of Engineering Works 8, no. 04: 139-142.
With the increasing requirements for power system transient stability assessment, the research on power system transient stability assessment theory and methods requires not only qualitative conclusions about system transient stability but also quantitative analysis of stability and even development trends. Judging from the research and development process of this direction at home and abroad in recent years, it is mainly based on the construction of quantitative index models to evaluate its transient stability and development trend. Regarding the construction theories and methods of quantitative index models, a lot of results have been achieved so far. The research ideas mainly focus on two categories: uncertainty analysis methods and deterministic analysis methods. Transient stability analysis is one of the important factors that need to be considered. Therefore, this paper proposed an optimized algorithm based on deep learning for preventive control of the transient stability in power systems. The proposed algorithm accurately fits the generator’s power and transient stability index through a deep belief network (DBN) by unsupervised pre-training and fine-tuning. The non-linear differential–algebraic equation and complex transient stability are determined using the deep neural network. The proposed algorithm minimizes the control cost under the constraints of the contingency by realizing the data-driven acquisition of the optimal preventive control. It also provides an efficient solution to stability and reliability rules with similar safety into the corresponding control model. Simulation results show that the proposed algorithm effectively improved the accuracy and reduces the complexity as compared with existing algorithms.
Qinggang Su; Habib Ullah Khan; Imran Khan; Bong Jun Choi; Falin Wu; Ayman A. Aly. An optimized algorithm for optimal power flow based on deep learning. Energy Reports 2021, 7, 2113 -2124.
AMA StyleQinggang Su, Habib Ullah Khan, Imran Khan, Bong Jun Choi, Falin Wu, Ayman A. Aly. An optimized algorithm for optimal power flow based on deep learning. Energy Reports. 2021; 7 ():2113-2124.
Chicago/Turabian StyleQinggang Su; Habib Ullah Khan; Imran Khan; Bong Jun Choi; Falin Wu; Ayman A. Aly. 2021. "An optimized algorithm for optimal power flow based on deep learning." Energy Reports 7, no. : 2113-2124.
Wireless sensor network barrier coverage plays an important role in intrusion detection. How to construct a robust barrier is a key research issue. For the initial deployment of barriers, with the depletion of node energy, some node dies prematurely, resulting in the existence of more weak points in the barrier. A method of using the re-deployment of mobile nodes to strengthen the barrier is proposed. This method adopts the set-based max-flow algorithm to calculate the number of weak points that can be strengthened and deploys and schedules movable nodes according to the weak situation to strengthen the barrier. The enhanced barrier has better performance and solves the problem of strengthening the weak points of the barrier. Simulation results show that the proposed algorithm can effectively strengthen the barrier and extend the survival time of the barrier, and the complexity of the algorithm is also relatively low.
Omar A. Saraereh; Ashraf Ali; Luae Al-Tarawneh; Imran Khan. A robust approach for barrier-reinforcing in wireless sensor networks. Journal of Parallel and Distributed Computing 2020, 149, 186 -192.
AMA StyleOmar A. Saraereh, Ashraf Ali, Luae Al-Tarawneh, Imran Khan. A robust approach for barrier-reinforcing in wireless sensor networks. Journal of Parallel and Distributed Computing. 2020; 149 ():186-192.
Chicago/Turabian StyleOmar A. Saraereh; Ashraf Ali; Luae Al-Tarawneh; Imran Khan. 2020. "A robust approach for barrier-reinforcing in wireless sensor networks." Journal of Parallel and Distributed Computing 149, no. : 186-192.
Massive multiple-input multiple-output (MIMO) is a backbone technology in the fifth-generation (5G) and beyond 5G (B5G) networks. It enhances performance gain, energy efficiency, and spectral efficiency. Unfortunately, a massive number of antennas need sophisticated processing to detect the transmitted signal. Although a detector based on the maximum likelihood (ML) is optimal, it incurs a high computational complexity, and hence, it is not hardware-friendly. In addition, the conventional linear detectors, such as the minimum mean square error (MMSE), include a matrix inversion, which causes a high computational complexity. As an alternative solution, approximate message passing (AMP) algorithm is proposed for data detection in massive MIMO uplink (UL) detectors. Although the AMP algorithm is converging extremely fast, the convergence is not guaranteed. A good initialization influences the convergence rate and affects the performance substantially together and the complexity. In this paper, we exploit several free-matrix-inversion methods, namely, the successive over-relaxation (SOR), the Gauss–Seidel (GS), and the Jacobi (JA), to initialize the AMP-based massive MIMO UL detector. In other words, hybrid detectors are proposed based on AMP, JA, SOR, and GS with an efficient initialization. Numerical results show that proposed detectors achieve a significant performance enhancement and a large reduction in the computational complexity.
Mahmoud Albreem; Arun Kumar; Mohammed Alsharif; Imran Khan; Bong Choi. Comparative Analysis of Data Detection Techniques for 5G Massive MIMO Systems. Sustainability 2020, 12, 9281 .
AMA StyleMahmoud Albreem, Arun Kumar, Mohammed Alsharif, Imran Khan, Bong Choi. Comparative Analysis of Data Detection Techniques for 5G Massive MIMO Systems. Sustainability. 2020; 12 (21):9281.
Chicago/Turabian StyleMahmoud Albreem; Arun Kumar; Mohammed Alsharif; Imran Khan; Bong Choi. 2020. "Comparative Analysis of Data Detection Techniques for 5G Massive MIMO Systems." Sustainability 12, no. 21: 9281.
Aiming at the problem of optimal power flow in photovoltaic (PV) Inverters, this paper proposes a real-time algorithm for optimal power flow (OPF) in distributed PV inverters with sophisticated communication technologies and measurement. A higher accuracy and computation speed are obtained by proposing a linear, time-varying optimization method, and the objective function and constraints were linearized using the Taylor expansion under the premise of small variable changes during the short control period. By comparing with the constant linearization method, the proposed time-varying linear approximation method is more accurate and efficient. The problems faced by the centralized calculation is overcome by proposing a distributed control method which utilizes the alternating direction method of multipliers. The proposed distributed control method enables the distributed PV inverters to optimize their own power setpoints with only a little information required from neighbor nodes. Case study results demonstrate that the proposed algorithm makes the distributed PV Inverters more efficient and economical than the other methods.
Qais Alsafasfeh; Omar A. Saraereh; Moath Alsafasfeh; Ayman Maqableh; Imran Khan; Bong Jun Choi. An Efficient Algorithm for Power Flow Optimization in PV Inverters Systems. Electric Power Components and Systems 2020, 48, 1362 -1377.
AMA StyleQais Alsafasfeh, Omar A. Saraereh, Moath Alsafasfeh, Ayman Maqableh, Imran Khan, Bong Jun Choi. An Efficient Algorithm for Power Flow Optimization in PV Inverters Systems. Electric Power Components and Systems. 2020; 48 (12-13):1362-1377.
Chicago/Turabian StyleQais Alsafasfeh; Omar A. Saraereh; Moath Alsafasfeh; Ayman Maqableh; Imran Khan; Bong Jun Choi. 2020. "An Efficient Algorithm for Power Flow Optimization in PV Inverters Systems." Electric Power Components and Systems 48, no. 12-13: 1362-1377.
In hostile and remote environments, such as mountains, forests or suburban areas, traditional communications may not be available, especially after a disaster, such as a flood, a forest fire or an earthquake. In these situations, the wireless networks may become congested or completely disrupted and may not be adequate to support the traffic generated by rescuers. It is also considered as the key tool in Corona Virus (COVID-19) battle. Moreover, the conventional approaches with fixed gateways may not work either, and this might lead to decoding errors due to the large distance between mobile nodes and the gateway. To avoid the decoding errors and improve the reliability of the messages, we propose to use intermediate Unmanned Aerial Vehicles (UAVs) to transfer messages from ground-based Long Range (LoRa) nodes to the remote base station (BS). Specifically, this UAV-enabled LoRa architecture is based on the ad hoc WiFi network, wherein, UAVs act as relays for the traffic generated between LoRa nodes and BS. To make the architecture more efficient, a distributed topology control algorithm is also proposed for UAVs. The algorithm is based on virtual spring forces and movement prediction technique that periodically updates the UAV topology to adapt to the movement of the ground-based LoRa nodes that move on the surface. The simulation results show the feasibility of the proposed approach for packet reception rate and average delay quality of service (QoS) metrics. It is observed that the mechanisms implemented in a UAV-enabled LoRa network effectively help to improve the packet reception rate with nominal buffer delays.
Omar A. Saraereh; Amer Alsaraira; Imran Khan; Peerapong Uthansakul. Performance Evaluation of UAV-Enabled LoRa Networks for Disaster Management Applications. Sensors 2020, 20, 2396 .
AMA StyleOmar A. Saraereh, Amer Alsaraira, Imran Khan, Peerapong Uthansakul. Performance Evaluation of UAV-Enabled LoRa Networks for Disaster Management Applications. Sensors. 2020; 20 (8):2396.
Chicago/Turabian StyleOmar A. Saraereh; Amer Alsaraira; Imran Khan; Peerapong Uthansakul. 2020. "Performance Evaluation of UAV-Enabled LoRa Networks for Disaster Management Applications." Sensors 20, no. 8: 2396.
A vehicular adhoc network (VANET) recently emerged in the the Internet of Vehicles (IoV); it involves the computational processing of moving vehicles. Nowadays, IoV has turned into an interesting field of research as vehicles can be equipped with processors, sensors, and communication devices. IoV gives rise to handoff, which involves changing the connection points during the online communication session. This presents a major challenge for which many standardized solutions are recommended. Although there are various proposed techniques and methods to support seamless handover procedure in IoV, there are still some open research issues, such as unavoidable packet loss rate and latency. On the other hand, the emerged concept of edge mobile computing has gained crucial attention by researchers that could help in reducing computational complexities and decreasing communication delay. Hence, this paper specifically studies the handoff challenges in cluster based handoff using new concept of dynamic edge-backup node. The outcomes are evaluated and contrasted with the network mobility method, our proposed technique, and other cluster-based technologies. The results show that coherence in communication during the handoff method can be upgraded, enhanced, and improved utilizing the proposed technique.
Khalid Mahmood Awan; Malik Nadeem; Ali Safaa Sadiq; Abdullah Alghushami; Imran Khan; Khaled Rabie. Smart Handoff Technique for Internet of Vehicles Communication using Dynamic Edge-Backup Node. Electronics 2020, 9, 524 .
AMA StyleKhalid Mahmood Awan, Malik Nadeem, Ali Safaa Sadiq, Abdullah Alghushami, Imran Khan, Khaled Rabie. Smart Handoff Technique for Internet of Vehicles Communication using Dynamic Edge-Backup Node. Electronics. 2020; 9 (3):524.
Chicago/Turabian StyleKhalid Mahmood Awan; Malik Nadeem; Ali Safaa Sadiq; Abdullah Alghushami; Imran Khan; Khaled Rabie. 2020. "Smart Handoff Technique for Internet of Vehicles Communication using Dynamic Edge-Backup Node." Electronics 9, no. 3: 524.
With the surge of ubiquitous demand for high-complexity and quality mobile Internet-of-things (IoT) services, new cooperative relaying paradigms have emerged. Motivated by the long and unpredictable end-to-end communication in relay-aided IoT networks, there is a need to introduce novel modulation schemes for very low bit error rate (BER) communications. In this paper, a practical modulation mapping scheme has been proposed to reduce decoding errors. Specifically, a hybrid automatic repeat request (HARQ) system has been used with an intermediate relay to transfer a message from a source to a destination. The design of modulation mapping has been optimized by first formulating the objective as the quadratic assignment problem. Later, the solution to the mapping problem is provided using an iterative search method. To validate the proposed solution, extensive simulations have been performed in MATLAB. The results show that the proposed solution outperforms the conventional relay retransmission and the heuristic design approaches.
Waleed Shahjehan; Shahid Bashir; Saleem Latteef Mohammed; Ahmed Bashar Fakhri; Adeniyi Adebayo Isaiah; Imran Khan; Peerapong Uthansakul. Efficient Modulation Scheme for Intermediate Relay-Aided IoT Networks. Applied Sciences 2020, 10, 2126 .
AMA StyleWaleed Shahjehan, Shahid Bashir, Saleem Latteef Mohammed, Ahmed Bashar Fakhri, Adeniyi Adebayo Isaiah, Imran Khan, Peerapong Uthansakul. Efficient Modulation Scheme for Intermediate Relay-Aided IoT Networks. Applied Sciences. 2020; 10 (6):2126.
Chicago/Turabian StyleWaleed Shahjehan; Shahid Bashir; Saleem Latteef Mohammed; Ahmed Bashar Fakhri; Adeniyi Adebayo Isaiah; Imran Khan; Peerapong Uthansakul. 2020. "Efficient Modulation Scheme for Intermediate Relay-Aided IoT Networks." Applied Sciences 10, no. 6: 2126.
Heterogeneous networks are rapidly emerging as one of the key enablers of beyond fifth-generation (5G) wireless networks. It is gradually becoming clear to the network operators that existing cellular networks may not be able to support the traffic demands of the future. Thus, there is an upsurge in the interest of efficiently deploying small-cell networks for accommodating a growing number of user equipment (UEs). This work further extends the state-of-the-art by proposing an optimization framework for reducing the power consumption of small-cell base stations (BSs). Specifically, a novel algorithm has been proposed which dynamically switches off the redundant small-cell BSs based on the traffic demands of the network. Due to the dynamicity of the formulated problem, a new UE admission control policy has been presented when the problem becomes infeasible to solve. To validate the effectiveness of the proposed solution, the simulation results are compared with conventional techniques. It is shown that the proposed power control solution outperforms the conventional approaches both in terms of accommodating more UEs and reducing power consumption.
Qais Alsafasfeh; Omar A. Saraereh; Ashraf Ali; Luae Al-Tarawneh; Imran Khan; Adão Silva. Efficient Power Control Framework for Small-Cell Heterogeneous Networks. Sensors 2020, 20, 1467 .
AMA StyleQais Alsafasfeh, Omar A. Saraereh, Ashraf Ali, Luae Al-Tarawneh, Imran Khan, Adão Silva. Efficient Power Control Framework for Small-Cell Heterogeneous Networks. Sensors. 2020; 20 (5):1467.
Chicago/Turabian StyleQais Alsafasfeh; Omar A. Saraereh; Ashraf Ali; Luae Al-Tarawneh; Imran Khan; Adão Silva. 2020. "Efficient Power Control Framework for Small-Cell Heterogeneous Networks." Sensors 20, no. 5: 1467.
As more and more mobile multimedia services are produced, end users are increasingly demanding access to high-speed, low-latency mobile communication networks. Among them, device-to-device (D2D) communication does not need the data to be forwarded through the base station relay but allows the two mobile devices adjacent to each other to establish a direct local link under control of the base station. This flexible communication method reduces the processing bottlenecks and blind spots of the base station and can be widely used in dense user communication scenarios such as transportation systems. Aiming at the problem of high energy consumption and improved quality of service demands by the D2D users, this paper proposes a new scheme to effectively improve the user fairness and satisfaction based on the user grouping into clusters. The main idea is to create the interference graph between the D2D users which is based on the graph coloring theory and constructs the color lists of the D2D users while cellular users’ requirements are guaranteed. Finally, those D2D users who can share the same channel are grouped in the same cluster. Simulation results show that the proposed scheme outperforms the existing schemes and effectively improve system performance.
Raya Majid Alsharfa; Saleem Latteef Mohammed; Sadik Kamel Gharghan; Imran Khan; Bong Jun Choi. Cellular-D2D Resource Allocation Algorithm Based on User Fairness. Electronics 2020, 9, 386 .
AMA StyleRaya Majid Alsharfa, Saleem Latteef Mohammed, Sadik Kamel Gharghan, Imran Khan, Bong Jun Choi. Cellular-D2D Resource Allocation Algorithm Based on User Fairness. Electronics. 2020; 9 (3):386.
Chicago/Turabian StyleRaya Majid Alsharfa; Saleem Latteef Mohammed; Sadik Kamel Gharghan; Imran Khan; Bong Jun Choi. 2020. "Cellular-D2D Resource Allocation Algorithm Based on User Fairness." Electronics 9, no. 3: 386.
High capacity and ultra-reliable vehicular communication are going to be important aspects of beyond 5G communication networks. However, the vehicular communication problem becomes complex at a large scale when vehicles are roaming on the road, while simultaneously communicating with each other. Moreover, at higher frequencies (like 28 GHz), the dynamics of vehicular communication completely shift towards unpredictability and low-reliability. These factors may result in high packet error and a large amount of interference, resulting in regular disruptions in communications. A thorough understanding of performance variations is the key to moving towards the next generation of vehicular networks. With this intent, this article aims to provide a comprehensive interference analysis, wherein the closed-form expressions of packet error probability (PEP) and ergodic capacity are derived. Using the expression of the PEP, diversity analysis is provided which unveils the impact of channel nonlinearities on the performance of interference-constrained vehicular networks. The insights provided here are expected to pave the way for reliable and high capacity vehicular communication networks.
Omar A. Saraereh; Ashraf Ali; Imran Khan; Khaled Rabie. Interference Analysis for Vehicle-to-Vehicle Communications at 28 GHz. Electronics 2020, 9, 262 .
AMA StyleOmar A. Saraereh, Ashraf Ali, Imran Khan, Khaled Rabie. Interference Analysis for Vehicle-to-Vehicle Communications at 28 GHz. Electronics. 2020; 9 (2):262.
Chicago/Turabian StyleOmar A. Saraereh; Ashraf Ali; Imran Khan; Khaled Rabie. 2020. "Interference Analysis for Vehicle-to-Vehicle Communications at 28 GHz." Electronics 9, no. 2: 262.
The Internet-of-things (IoT) has been gradually paving the way for the pervasive connectivity of wireless networks. Due to the ability to connect a number of devices to the Internet, many applications of IoT networks have recently been proposed. Though these applications range from industrial automation to smart homes, healthcare applications are the most critical. Providing reliable connectivity among wearables and other monitoring devices is one of the major tasks of such healthcare networks. The main source of power for such low-powered IoT devices is the batteries, which have a limited lifetime and need to be replaced or recharged periodically. In order to improve their lifecycle, one of the most promising proposals is to harvest energy from the ambient resources in the environment. For this purpose, we designed an energy harvesting protocol that harvests energy from two ambient energy sources, namely radio frequency (RF) at 2.4 GHz and thermal energy. A rectenna is used to harvest RF energy, while the thermoelectric generator (TEG) is employed to harvest human thermal energy. To verify the proposed design, extensive simulations are performed in Green Castalia, which is a framework that is used with the Castalia simulator in OMNeT++. The results show significant improvements in terms of the harvested energy and lifecycle improvement of IoT devices.
Omar A. Saraereh; Amer Alsaraira; Imran Khan; Bong Jun Choi. A Hybrid Energy Harvesting Design for On-Body Internet-of-Things (IoT) Networks. Sensors 2020, 20, 407 .
AMA StyleOmar A. Saraereh, Amer Alsaraira, Imran Khan, Bong Jun Choi. A Hybrid Energy Harvesting Design for On-Body Internet-of-Things (IoT) Networks. Sensors. 2020; 20 (2):407.
Chicago/Turabian StyleOmar A. Saraereh; Amer Alsaraira; Imran Khan; Bong Jun Choi. 2020. "A Hybrid Energy Harvesting Design for On-Body Internet-of-Things (IoT) Networks." Sensors 20, no. 2: 407.
Non-orthogonal multiple access (NOMA) has become the key technology in the future 5G wireless networks. It can achieve multi-user multiplexing in the transmit power domain by allocating different power, which can effectively improve the system capacity and spectral efficiency. Aiming at the problem of high computational complexity and improving system capacity in non-orthogonal multiple access (NOMA) based on orthogonal frequency division multiple access (OFDMA) for 5G wireless cellular networks, this paper proposes an improved low complexity radio resource allocation algorithm for user grouping and power allocation optimization. The optimization model is established with the goal of maximizing system capacity. Through the step-by-step optimization idea, the complex non-convex optimization problem is decomposed into two sub-problems to be solved separately. Firstly, all users are grouped based on the greedy method, and then the power allocation is performed on the sub-carriers of the fixed group. Simulation results show that the proposed algorithm has better system capacity than the existing state-of-the-art algorithms and reduced complexity performance.
Omar A. Saraereh; Amer Alsaraira; Imran Khan; Peerapong Uthansakul. An Efficient Resource Allocation Algorithm for OFDM-Based NOMA in 5G Systems. Electronics 2019, 8, 1399 .
AMA StyleOmar A. Saraereh, Amer Alsaraira, Imran Khan, Peerapong Uthansakul. An Efficient Resource Allocation Algorithm for OFDM-Based NOMA in 5G Systems. Electronics. 2019; 8 (12):1399.
Chicago/Turabian StyleOmar A. Saraereh; Amer Alsaraira; Imran Khan; Peerapong Uthansakul. 2019. "An Efficient Resource Allocation Algorithm for OFDM-Based NOMA in 5G Systems." Electronics 8, no. 12: 1399.
Wireless networks employing millimeter-wave (mmWave) and Massive Multiple-Input Multiple-Output (MIMO) technologies are a key approach to boost network capacity, coverage, and quality of service (QoS) for future communications. They deploy symmetric antennas on a large scale in order to enhance the system throughput and data rate. However, increasing the number of antennas and Radio Frequency (RF) chains results in high computational complexity and more energy requirements. Therefore, to solve these problems, this paper proposes a low-complexity hybrid beamforming scheme for mmWave Massive-MIMO 5G wireless networks. The proposed algorithm is on the basis of alternating the minimum mean square error (Alt-MMSE) hybrid beamforming technique in which the orthogonal properties of the digital matrix were designed, and then the MSE of the transmitted and received signal was reduced. The phase of the analog matrix was obtained from the updated digital matrix. Simulation results showed that the proposed hybrid beamforming algorithm had better performance than existing state-of-the-art algorithms, and similar performance with the optimal digital precoding algorithm.
Saleem Latteef Mohammed; Mohammed H. Alsharif; Sadik Kamel Gharghan; Imran Khan; Mahmoud Albreem. Robust Hybrid Beamforming Scheme for Millimeter-Wave Massive-MIMO 5G Wireless Networks. Symmetry 2019, 11, 1424 .
AMA StyleSaleem Latteef Mohammed, Mohammed H. Alsharif, Sadik Kamel Gharghan, Imran Khan, Mahmoud Albreem. Robust Hybrid Beamforming Scheme for Millimeter-Wave Massive-MIMO 5G Wireless Networks. Symmetry. 2019; 11 (11):1424.
Chicago/Turabian StyleSaleem Latteef Mohammed; Mohammed H. Alsharif; Sadik Kamel Gharghan; Imran Khan; Mahmoud Albreem. 2019. "Robust Hybrid Beamforming Scheme for Millimeter-Wave Massive-MIMO 5G Wireless Networks." Symmetry 11, no. 11: 1424.
The issue of spectrum scarcity in wireless networks is becoming prominent and critical with each passing year. Although several promising solutions have been proposed to provide a solution to spectrum scarcity, most of them have many associated tradeoffs. In this context, one of the emerging ideas relates to the utilization of cognitive radios (CR) for future heterogeneous networks (HetNets). This paper provides a marriage of two promising candidates (i.e., CR and HetNets) for beyond fifth generation (5G) wireless networks. More specifically, a joint power allocation and user assignment solution for the multiuser underlay CR-based HetNets has been proposed and evaluated. To counter the limiting factors in these networks, the individual power of transmitting nodes and interference temperature protection constraints of the primary networks have been considered. An efficient solution is designed from the dual decomposition approach, where the optimal user assignment is obtained for the optimized power allocation at each node. The simulation results validate the superiority of the proposed optimization scheme against conventional baseline techniques.
Khush Bakht; Furqan Jameel; Zain Ali; Wali Ullah Khan; Imran Khan; Guftaar Ahmad Sardar Sidhu; Jeong Woo Lee. Power Allocation and User Assignment Scheme for beyond 5G Heterogeneous Networks. Wireless Communications and Mobile Computing 2019, 2019, 1 -11.
AMA StyleKhush Bakht, Furqan Jameel, Zain Ali, Wali Ullah Khan, Imran Khan, Guftaar Ahmad Sardar Sidhu, Jeong Woo Lee. Power Allocation and User Assignment Scheme for beyond 5G Heterogeneous Networks. Wireless Communications and Mobile Computing. 2019; 2019 ():1-11.
Chicago/Turabian StyleKhush Bakht; Furqan Jameel; Zain Ali; Wali Ullah Khan; Imran Khan; Guftaar Ahmad Sardar Sidhu; Jeong Woo Lee. 2019. "Power Allocation and User Assignment Scheme for beyond 5G Heterogeneous Networks." Wireless Communications and Mobile Computing 2019, no. : 1-11.
In order to solve the problem of interference and spectrum optimization caused by D2D (device-to-device) communication multiplexing uplink channel of heterogeneous cellular networks, the allocation algorithm based on the many-to-one Gale-Shapley (M21GS) algorithm proposed in this paper can effectively solve the resource allocation problem of D2D users multiplexed cellular user channels in heterogeneous cellular network environments. In order to improve the utilization of the wireless spectrum, the algorithm allows multiple D2D users to share the channel resources of one cellular user and maintains the communication service quality of the cellular users and D2D users by setting the signal to interference and noise ratio (SINR) threshold. A D2D user and channel preference list are established based on the implemented system’s capacity to maximize the system total capacity objective function. Finally, we use the Kuhn–Munkres (KM) algorithm to achieve the optimal matching between D2D clusters and cellular channel to maximize the total capacity of D2D users. The MATLAB simulation is used to compare and analyze the total system capacity of the proposed algorithm, the resource allocation algorithm based on the delay acceptance algorithm, the random resource allocation algorithm and the optimal exhaustive search algorithm, and the maximum allowable access for D2D users. The simulation results show that the proposed algorithm has fast convergence and low complexity, and the total capacity is close to the optimal algorithm.
Omar A. Saraereh; Saleem Latteef Mohammed; Imran Khan; Khaled Rabie; Sofeine Affess; Khan. An Efficient Resource Allocation Algorithm for Device-To-Device Communications. Applied Sciences 2019, 9, 3816 .
AMA StyleOmar A. Saraereh, Saleem Latteef Mohammed, Imran Khan, Khaled Rabie, Sofeine Affess, Khan. An Efficient Resource Allocation Algorithm for Device-To-Device Communications. Applied Sciences. 2019; 9 (18):3816.
Chicago/Turabian StyleOmar A. Saraereh; Saleem Latteef Mohammed; Imran Khan; Khaled Rabie; Sofeine Affess; Khan. 2019. "An Efficient Resource Allocation Algorithm for Device-To-Device Communications." Applied Sciences 9, no. 18: 3816.
Symmetrical precoding and algorithms play a vital role in the field of wireless communications and cellular networks. This paper proposed a low-complexity hybrid precoding algorithm for mmWave massive multiple-input multiple-output (MIMO) systems. The traditional orthogonal matching pursuit (OMP) has a large complexity, as it requires matrix inversion and known candidate matrices. Therefore, we propose a bird swarm algorithm (BSA) based matrix-inversion bypass (MIB) OMP (BSAMIBOMP) algorithm which has the feature to quickly search the BSA global optimum value. It only directly finds the array response vector multiplied by the residual inner product, so it does not require the candidate’s matrices. Moreover, it deploys the Banachiewicz–Schur generalized inverse of the partitioned matrix to decompose the high-dimensional matrix into low-dimensional in order to avoid the need for a matrix inversion operation. The simulation results show that the proposed algorithm effectively improves the bit error rate (BER), spectral efficiency (SE), complexity, and energy efficiency of the mmWave massive MIMO system as compared with the existing OMP hybrid and SDRAltMin algorithm without any matrix inversion and known candidate matrix information requirement.
Imran Khan; Shagufta Henna; Nasreen Anjum; Aduwati Sali; Jonathan Rodrigues; Yousaf Khan; Muhammad Irfan Khattak; Farhan Altaf. An Efficient Precoding Algorithm for mmWave Massive MIMO Systems. Symmetry 2019, 11, 1099 .
AMA StyleImran Khan, Shagufta Henna, Nasreen Anjum, Aduwati Sali, Jonathan Rodrigues, Yousaf Khan, Muhammad Irfan Khattak, Farhan Altaf. An Efficient Precoding Algorithm for mmWave Massive MIMO Systems. Symmetry. 2019; 11 (9):1099.
Chicago/Turabian StyleImran Khan; Shagufta Henna; Nasreen Anjum; Aduwati Sali; Jonathan Rodrigues; Yousaf Khan; Muhammad Irfan Khattak; Farhan Altaf. 2019. "An Efficient Precoding Algorithm for mmWave Massive MIMO Systems." Symmetry 11, no. 9: 1099.
Aiming at the problem of high computational complexity due to a large number of antennas deployed in mmWave massive multiple-input multiple-output (MIMO) communication systems, this paper proposes an efficient algorithm for optimizing beam control vectors with low computational complexity based on codebooks for millimeter-wave massive MIMO systems with split sub-arrays hybrid beamforming architecture. A bidirectional method is adopted on the beam control vector of each antenna sub-array both at the transmitter and receiver, which utilizes the idea of interference alignment (IA) and alternating optimization. The simulation results show that the proposed algorithm has low computational complexity, fast convergence, and improved spectral efficiency as compared with the state-of-the-art algorithms.
Salem Alemaishat; Omar A. Saraereh; Imran Khan; Sophene H. Affes; Xingwang Li; Jeong Woo Lee. An Efficient Precoding Scheme for Millimeter-Wave Massive MIMO Systems. Electronics 2019, 8, 927 .
AMA StyleSalem Alemaishat, Omar A. Saraereh, Imran Khan, Sophene H. Affes, Xingwang Li, Jeong Woo Lee. An Efficient Precoding Scheme for Millimeter-Wave Massive MIMO Systems. Electronics. 2019; 8 (9):927.
Chicago/Turabian StyleSalem Alemaishat; Omar A. Saraereh; Imran Khan; Sophene H. Affes; Xingwang Li; Jeong Woo Lee. 2019. "An Efficient Precoding Scheme for Millimeter-Wave Massive MIMO Systems." Electronics 8, no. 9: 927.
Channel state information (CSI) feedback in massive MIMO systems is too large due to large pilot overhead. It is due to the large channel matrix dimension which depends on the number of base station (BS) antennas and consumes the majority of scarce radio resources. To solve this problem, we proposed a scheme for efficient CSI acquisition and reduced pilot overhead. It is based on the separation mechanism for the channel matrix. The spatial correlation among multiuser channel matrices in the virtual angular domain is utilized to split the channel matrix. Then, the two parts of the matrix are estimated by deploying the compressed sensing (CS) techniques. This scheme is novel in the sense that the user equipment (UE) directly transmits the received symbols from the BS to the BS, so a joint CSI recovery is performed at the BS. Simulation results show that the proposed channel estimation scheme effectively estimates the channel with reduced pilot overhead and improved performance as compared with the state-of-the-art schemes.
Imran Khan; Joel J. P. C. Rodrigues; Jalal Al-Muhtadi; Muhammad Irfan Khattak; Yousaf Khan; Farhan Altaf; Seyed Sajad Mirjavadi; Bong Jun Choi. A Robust Channel Estimation Scheme for 5G Massive MIMO Systems. Wireless Communications and Mobile Computing 2019, 2019, 1 -8.
AMA StyleImran Khan, Joel J. P. C. Rodrigues, Jalal Al-Muhtadi, Muhammad Irfan Khattak, Yousaf Khan, Farhan Altaf, Seyed Sajad Mirjavadi, Bong Jun Choi. A Robust Channel Estimation Scheme for 5G Massive MIMO Systems. Wireless Communications and Mobile Computing. 2019; 2019 ():1-8.
Chicago/Turabian StyleImran Khan; Joel J. P. C. Rodrigues; Jalal Al-Muhtadi; Muhammad Irfan Khattak; Yousaf Khan; Farhan Altaf; Seyed Sajad Mirjavadi; Bong Jun Choi. 2019. "A Robust Channel Estimation Scheme for 5G Massive MIMO Systems." Wireless Communications and Mobile Computing 2019, no. : 1-8.
In this paper, we present a joint power allocation and adaptive link selection protocol for an orthogonal frequency division multiplexing (OFDM)-based network consists of one source node i.e., base station (BS), one destination node i.e., (MU) and a buffer aided decode and forward (DF) relay node. Our objective is to maximize the average throughput of the system via power loading over different subcarriers at source and relay nodes. A separate power budget is assumed at each transmitting node to make the system more practical. In order to form our solution more tractable, a decomposition framework is implemented to solve the mixed integer optimization problem. Further, less complex suboptimal approaches have also been presented and simulation results are provided to endorse the efficiency of our designed algorithms.
Tayyaba Jabeen; Zain Ali; Wali Ullah Khan; Furqan Jameel; Imran Khan; Guftaar Ahmad Sardar Sidhu; Bong Jun Choi. Joint Power Allocation and Link Selection for Multi-Carrier Buffer Aided Relay Network. Electronics 2019, 8, 686 .
AMA StyleTayyaba Jabeen, Zain Ali, Wali Ullah Khan, Furqan Jameel, Imran Khan, Guftaar Ahmad Sardar Sidhu, Bong Jun Choi. Joint Power Allocation and Link Selection for Multi-Carrier Buffer Aided Relay Network. Electronics. 2019; 8 (6):686.
Chicago/Turabian StyleTayyaba Jabeen; Zain Ali; Wali Ullah Khan; Furqan Jameel; Imran Khan; Guftaar Ahmad Sardar Sidhu; Bong Jun Choi. 2019. "Joint Power Allocation and Link Selection for Multi-Carrier Buffer Aided Relay Network." Electronics 8, no. 6: 686.