Showing items 1 - 20 of 210

5G for Vehicular Communications

- Shah, Syed, Ahmed, Ejaz, Imran, Muhammad, Zeadally, Sherali

  • Authors: Shah, Syed , Ahmed, Ejaz , Imran, Muhammad , Zeadally, Sherali
  • Date: 2018
  • Type: Text , Journal article
  • Relation: IEEE Communications Magazine Vol. 56, no. 1 (2018), p. 111-117
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  • Description: 5G is ongoing, and it is an emerging platform that not only aims to augment existing but also introduce a plethora of novel applications that require ultra-reliable low-latency communication. It is a new radio access technology that provides building blocks to retrofit existing platforms (e.g., 2G, 3G, 4G, and WiFi) for greater coverage, accessibility, and higher network density with respect to cells and devices. It implies that 5G aims to satisfy a diverse set of communication requirements of the various stakeholders. Among the stakeholders, vehicles, in particular, will benefit from 5G at both the system and application levels. The authors present a tutorial perspective on vehicular communications using the building blocks provided by 5G. First, we identify and describe key requirements of emerging vehicular communications and assess existing standards to determine their limitations. Then we provide a glimpse of the adopted 5G architecture and identify some of its promising salient features for vehicular communications. Finally, key 5G building blocks (i.e., proximity services, mobile edge computing and network slicing) are explored in the context of vehicular communications, and associated design challenges are highlighted. © 1979-2012 IEEE.

6G wireless systems : a vision, architectural elements, and future directions

- Khan, Latif, Yaqoob, Ibrar, Imran, Muhammad, Han, Zhu, Hong, Choong

  • Authors: Khan, Latif , Yaqoob, Ibrar , Imran, Muhammad , Han, Zhu , Hong, Choong
  • Date: 2020
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 8, no. (2020), p. 147029-147044
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  • Description: Internet of everything (IoE)-based smart services are expected to gain immense popularity in the future, which raises the need for next-generation wireless networks. Although fifth-generation (5G) networks can support various IoE services, they might not be able to completely fulfill the requirements of novel applications. Sixth-generation (6G) wireless systems are envisioned to overcome 5G network limitations. In this article, we explore recent advances made toward enabling 6G systems. We devise a taxonomy based on key enabling technologies, use cases, emerging machine learning schemes, communication technologies, networking technologies, and computing technologies. Furthermore, we identify and discuss open research challenges, such as artificial-intelligence-based adaptive transceivers, intelligent wireless energy harvesting, decentralized and secure business models, intelligent cell-less architecture, and distributed security models. We propose practical guidelines including deep Q-learning and federated learning-based transceivers, blockchain-based secure business models, homomorphic encryption, and distributed-ledger-based authentication schemes to cope with these challenges. Finally, we outline and recommend several future directions. © 2013 IEEE.

A blockchain based privacy-preserving system for electric vehicles through local communication

- Yahaya, Adamu, Javaid, Nadeem, Khalid, Rabiya, Imran, Muhammad, Naseer, Nidal

A blockchain model for fair data sharing in deregulated smart grids

- Samuel, Omaji, Javaid, Nadeem, Awais, Muhammad, Ahmed, Zeeshan, Imran, Muhammad, Guizani, Mohsen

  • Authors: Samuel, Omaji , Javaid, Nadeem , Awais, Muhammad , Ahmed, Zeeshan , Imran, Muhammad , Guizani, Mohsen
  • Date: 2019
  • Type: Text , Conference paper
  • Relation: 2019 IEEE Global Communications Conference, GLOBECOM 2019, Waikoloa 9-13 December 2019
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  • Description: The emergence of smart home appliances has generated a high volume of data on smart meters belonging to different customers. However, customers can not share their data in deregulated smart grids due to privacy concern. Although, these data are important for the service provider in order to provide an efficient service. To encourage the customers' participation, this paper proposes an access control mechanism by fairly compensating customers for their participation in data sharing via blockchain using the concept of differential privacy. We addressed the computational issues of existing ethereum blockchain by proposing a proof of authority consensus protocol through the Pagerank mechanism in order to derive the reputation scores. Experimental results show the efficiency of the proposed model to minimize privacy risk, and maximize aggregator's profit. In addition, gas consumption, as well as the cost of the computational resources, is reduced. © 2019 IEEE.

A blockchain-based decentralized energy management in a P2P trading system

- Khalid, Rabiya, Javaid, Nadeem, Javaid, Sakeena, Imran, Muhammad, Naseer, Nidal

  • Authors: Khalid, Rabiya , Javaid, Nadeem , Javaid, Sakeena , Imran, Muhammad , Naseer, Nidal
  • Date: 2020
  • Type: Text , Conference paper
  • Relation: 2020 IEEE International Conference on Communications, ICC 2020, Dublin, Ireland, 7 to 11 June, IEEE International Conference on Communications Vol. 2020-June
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  • Description: Local energy generation and peer to peer (P2P) energy trading in the local market can reduce energy consumption cost, emission of harmful gases (as renewable energy sources (RESs) are used to generate energy at user's premises) and increase smart grid resilience. In this paper, to implement a hybrid P2P energy trading market, a blockchain-based solution is proposed. A blockchain-based system is fully decentralized and it allows the market members to interact with each other and trade energy without involving any third party. Smart contracts play a very important role in the blockchain-based energy trading market. They contain all the necessary rules for energy trading. We have proposed three smart contracts to implement the hybrid electricity trading market. The market members interact with main smart contract which requests P2P smart contract and prosumer to grid (P2G) smart contract for further processing. The main objectives of this paper are to propose a model to implement an efficient hybrid energy trading market while reducing cost and peak to average ratio (PAR) of electricity. © 2020 IEEE.

A blockchain-based privacy-preserving mechanism with aggregator as common communication point

- Yahaya, Adamu, Javaid, Nadeem, Khalid, Rabiya, Imran, Muhammad, Guizani, Mohsen

  • Authors: Yahaya, Adamu , Javaid, Nadeem , Khalid, Rabiya , Imran, Muhammad , Guizani, Mohsen
  • Date: 2020
  • Type: Text , Conference paper
  • Relation: 2020 IEEE International Conference on Communications, ICC 2020, Dublin, Ireland, 7 to 11 June, IEEE International Conference on Communications Vol. 2020-June
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  • Description: The high penetration of renewable energy resources into the distributed system and their intermittent behavior of the non-dispatchable generation causes issues of demand supply mismatch and serious security and privacy concerned in the system. It is believed that incorporating blockchain will reduce costs, enhance data security, and improve the system efficiency. However, privacy issues are not completely eliminated and can hinder the wide applications of blockchain. In the study, we present a Reputation Based Starvation Free Energy Allocation Policy (Reputation-SFEAP) in a decentralized and distributed blockchain-based energy trading; while keeping Aggregator as Common Communication Point. In addition, Identity-Based encryption (ID-Based encryption) technique is added that improves transactional information privacy. According to the research analysis, it is observed that the proposed system model has optimal and fair energy allocation algorithms, which prevent all the energy users from energy starvation and share the available energy accordingly. Moreover, the incorporated encryption system has greater security-privacy level, which protects passive attacker and disguises attacker from penetration. © 2020 IEEE.

A blockchain-based solution for enhancing security and privacy in smart factory

- Wan, Jafu, Li, Jiapeng, Imran, Muhammad, Li, Di

  • Authors: Wan, Jafu , Li, Jiapeng , Imran, Muhammad , Li, Di
  • Date: 2019
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Industrial Informatics Vol. 15, no. 6 (2019), p. 3652-3660
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  • Description: Through the Industrial Internet of Things (IIoT), a smart factory has entered the booming period. However, as the number of nodes and network size become larger, the traditional IIoT architecture can no longer provide effective support for such enormous system. Therefore, we introduce the Blockchain architecture, which is an emerging scheme for constructing the distributed networks, to reshape the traditional IIoT architecture. First, the major problems of the traditional IIoT architecture are analyzed, and the existing improvements are summarized. Second, we introduce a security and privacy model to help design the Blockchain-based architecture. On this basis, we decompose and reorganize the original IIoT architecture to form a new multicenter partially decentralized architecture. Then, we introduce some relative security technologies to improve and optimize the new architecture. After that we design the data interaction process and the algorithms of the architecture. Finally, we use an automatic production platform to discuss the specific implementation. The experimental results show that the proposed architecture provides better security and privacy protection than the traditional architecture. Thus, the proposed architecture represents a significant improvement of the original architecture, which provides a new direction for the IIoT development. © 2005-2012 IEEE.

A cooperative crowdsensing system based on flying and ground vehicles to control respiratory viral disease outbreaks

- Sahraoui, Yesin, Kerrache, Chaker, Amadeo, Marica, Vegni, Anna, Korichi, Ahmed, Nebhen, Jamel, Imran, Muhammad

  • Authors: Sahraoui, Yesin , Kerrache, Chaker , Amadeo, Marica , Vegni, Anna , Korichi, Ahmed , Nebhen, Jamel , Imran, Muhammad
  • Date: 2022
  • Type: Text , Journal article
  • Relation: Ad Hoc Networks Vol. 124, no. (2022), p.
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  • Description: The massive increase in population density in cities has led to several urban problems, such as an increment of air pollution, traffic congestion, and a faster spread of infectious diseases. With the rapid innovation in the intelligent sensors technology, and its integration into smart vehicles and Unmanned Aerial Vehicles (UAVs), a novel sensing paradigm has been promoted, namely vehicular crowdsensing, which leverages on-board sensors to capture information from the surrounding environment. Collected data are then analyzed to take proper countermeasures. In this paper, we present a smart coordination mechanism between UAVs and ground vehicles (GVs), which sense information like body temperature and breathing rate of people, in order to support a variety of monitoring applications, including discovering the presence of infectious diseases. In our framework, namely GUAVA, aerial and ground vehicles are equipped with GPS devices and thermal cameras to monitor specific geographic areas, detect humans’ vital parameters and, at the same time, discover duplicate data by identifying matching faces in thermal video sequences with the GaussianFace algorithm. The sensing tasks in hard-to-reach places are assigned to UAVs, with the ability to power up wirelessly from the nearest GV and offload the collected monitoring images to it. Simulation results have assessed our proposed framework, showing good performance in terms of distinct Quality of Service (QoS) metrics. © 2021

A cooperative heterogeneous vehicular clustering mechanism for road traffic management

- Ahmad, Iftikhara, Noor, Rafidah, Zaba, Muhammad, Qureshi, Muhammad, Imran, Muhammad, Shoaib, Muhammad

  • Authors: Ahmad, Iftikhara , Noor, Rafidah , Zaba, Muhammad , Qureshi, Muhammad , Imran, Muhammad , Shoaib, Muhammad
  • Date: 2020
  • Type: Text , Journal article
  • Relation: International Journal of Parallel Programming Vol. 48, no. 5 (2020), p. 870-889
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  • Description: The vehicular ad-hoc networks integrates with long-term evolution (LTE) forming a heterogeneous network, capable of providing seamless connectivity, which meets the communication requirements of intelligent transportation systems. However, heterogeneous network-based applications involve LTE resource (data and spectrum) usage cost and must be taken care while developing such a solution. One of the scenarios is the access of the information to/from remote server over the internet via LTE for road traffic management applications. Although clustering of the vehicle is significant to minimize the data and LTE network usage, however, the problem of non-cooperation of the vehicles in clustering process and within a cluster are major issues in sharing costly data acquired from the internet. Because, who and why one (vehicle) should pay the cost is the big question, proliferating the non-cooperative behavior among the cluster members. To solve these issues, strategic game-theoretic based clustering mechanism named as cooperative interest-aware clustering (CIAC) is developed. The proposed CIAC not only balance the cost of usage by controlling non-cooperative behavior among the vehicles within the cluster but at the same time motivate vehicles to participate in the clustering process to share the data and cost as well. It consists of a cluster head selection process based on the strategic game-theoretic approach and a fair-use policy. The implementation results show superiority in performance of our protocol over the existing approaches. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

A critical analysis of mobility management related issues of wireless sensor networks in cyber physical systems

- Al-Muhtadi, Jalal, Qiang, Ma, Zeb, Khan, Chaudhry, Junaid, Imran, Muhammad

  • Authors: Al-Muhtadi, Jalal , Qiang, Ma , Zeb, Khan , Chaudhry, Junaid , Imran, Muhammad
  • Date: 2018
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 6, no. (2018), p. 16363-16376
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  • Description: Mobility management has been a long-standing issue in mobile wireless sensor networks and especially in the context of cyber physical systems its implications are immense. This paper presents a critical analysis of the current approaches to mobility management by evaluating them against a set of criteria which are essentially inherent characteristics of such systems on which these approaches are expected to provide acceptable performance. We summarize these characteristics by using a quadruple set of metrics. Additionally, using this set we classify the various approaches to mobility management that are discussed in this paper. Finally, the paper concludes by reviewing the main findings and providing suggestions that will be helpful to guide future research efforts in the area. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**

A deep learning model based on concatenation approach for the diagnosis of brain tumor

- Noreen, Neelum, Palaniappan, Sellappan, Qayyum, Abdul, Ahmad, Iftikhar, Imran, Muhammad, Shoaib, M.uhammad

  • Authors: Noreen, Neelum , Palaniappan, Sellappan , Qayyum, Abdul , Ahmad, Iftikhar , Imran, Muhammad , Shoaib, M.uhammad
  • Date: 2020
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 8, no. (2020), p. 55135-55144
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  • Description: Brain tumor is a deadly disease and its classification is a challenging task for radiologists because of the heterogeneous nature of the tumor cells. Recently, computer-aided diagnosis-based systems have promised, as an assistive technology, to diagnose the brain tumor, through magnetic resonance imaging (MRI). In recent applications of pre-trained models, normally features are extracted from bottom layers which are different from natural images to medical images. To overcome this problem, this study proposes a method of multi-level features extraction and concatenation for early diagnosis of brain tumor. Two pre-trained deep learning models i.e. Inception-v3 and DensNet201 make this model valid. With the help of these two models, two different scenarios of brain tumor detection and its classification were evaluated. First, the features from different Inception modules were extracted from pre-trained Inception-v3 model and concatenated these features for brain tumor classification. Then, these features were passed to softmax classifier to classify the brain tumor. Second, pre-trained DensNet201 was used to extract features from various DensNet blocks. Then, these features were concatenated and passed to softmax classifier to classify the brain tumor. Both scenarios were evaluated with the help of three-class brain tumor dataset that is available publicly. The proposed method produced 99.34 %, and 99.51% testing accuracies respectively with Inception-v3 and DensNet201 on testing samples and achieved highest performance in the detection of brain tumor. As results indicated, the proposed method based on features concatenation using pre-trained models outperformed as compared to existing state-of-the-art deep learning and machine learning based methods for brain tumor classification. © 2013 IEEE.

A framework and mathematical modeling for the vehicular delay tolerant network routing

- Nasir, Mostofa, Noor, Rafidah, Iftikhar, Mohsin, Imran, Muhammad, Abdul Wahab, Ainuddin, Jabbarpour, Mohammad, Khokhar, R.

  • Authors: Nasir, Mostofa , Noor, Rafidah , Iftikhar, Mohsin , Imran, Muhammad , Abdul Wahab, Ainuddin , Jabbarpour, Mohammad , Khokhar, R.
  • Date: 2016
  • Type: Text , Journal article
  • Relation: Mobile Information Systems Vol. 2016, no. (2016), p.
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  • Description: Vehicular ad hoc networks (VANETs) are getting growing interest as they are expected to play crucial role in making safer, smarter, and more efficient transportation networks. Due to unique characteristics such as sparse topology and intermittent connectivity, Delay Tolerant Network (DTN) routing in VANET becomes an inherent choice and is challenging. However, most of the existing DTN protocols do not accurately discover potential neighbors and, hence, appropriate intermediate nodes for packet transmission. Moreover, these protocols cause unnecessary overhead due to excessive beacon messages. To cope with these challenges, this paper presents a novel framework and an Adaptive Geographical DTN Routing (AGDR) for vehicular DTNs. AGDR exploits node position, current direction, speed, and the predicted direction to carefully select an appropriate intermediate node. Direction indicator light is employed to accurately predict the vehicle future direction so that the forwarding node can relay packets to the desired destination. Simulation experiments confirm the performance supremacy of AGDR compared to contemporary schemes in terms of packet delivery ratio, overhead, and end-to-end delay. Simulation results demonstrate that AGDR improves the packet delivery ratio (5-7%), reduces the overhead (1-5%), and decreases the delay (up to 0.02 ms). Therefore, AGDR improves route stability by reducing the frequency of route failures. © 2016 Mostofa Kamal Nasir et al.

A hybrid computing solution and resource scheduling strategy for edge computing in smart manufacturing

- Li, Xiaomin, Wan, Jiafu, Dai, Hong-Ning, Imran, Muhammad, Xia, Min, Celesti, Antonio

  • Authors: Li, Xiaomin , Wan, Jiafu , Dai, Hong-Ning , Imran, Muhammad , Xia, Min , Celesti, Antonio
  • Date: 2019
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Industrial Informatics Vol. 15, no. 7 (2019), p. 4225-4234
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  • Description: At present, smart manufacturing computing framework has faced many challenges such as the lack of an effective framework of fusing computing historical heritages and resource scheduling strategy to guarantee the low-latency requirement. In this paper, we propose a hybrid computing framework and design an intelligent resource scheduling strategy to fulfill the real-time requirement in smart manufacturing with edge computing support. First, a four-layer computing system in a smart manufacturing environment is provided to support the artificial intelligence task operation with the network perspective. Then, a two-phase algorithm for scheduling the computing resources in the edge layer is designed based on greedy and threshold strategies with latency constraints. Finally, a prototype platform was developed. We conducted experiments on the prototype to evaluate the performance of the proposed framework with a comparison of the traditionally-used methods. The proposed strategies have demonstrated the excellent real-time, satisfaction degree (SD), and energy consumption performance of computing services in smart manufacturing with edge computing. © 2005-2012 IEEE.

A hybrid precoding- and filtering-based uplink MC-LNOMA scheme for 5G cellular networks with reduced PAPR

- Baig, Imran, Farooq, Umer, Ahmed, Ejaz, Imran, Muhammad, Shoaib, Muhammad

  • Authors: Baig, Imran , Farooq, Umer , Ahmed, Ejaz , Imran, Muhammad , Shoaib, Muhammad
  • Date: 2018
  • Type: Text , Journal article
  • Relation: Transactions on Emerging Telecommunications Technologies Vol. 29, no. 10 (2018), p.
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  • Description: Uplink multicarrier localized nonorthogonal multiple access (MC-LNOMA) is a variant of hybrid nonorthogonal multiple access, where subcarrier mapping is performed in localized mode. MC-LNOMA is one of the most prominent emerging schemes and likely to be employed in the forthcoming fifth-generation cellular networks due to its massive connectivity, spectral efficiency, better cell coverage capability, and higher data rate. It may employ orthogonal frequency-division multiple access due to the technical ripeness. However, schemes based on orthogonal frequency-division multiple access all suffer from the high peak-to-average power ratio problem. Therefore, in this paper, a new finite impulse response filter–based discrete cosine transform–precoded uplink MC-LNOMA scheme is presented for peak-to-average power ratio reduction. MATLAB simulations demonstrate the performance supremacy of the proposed scheme compared to contemporary schemes such as discrete cosine transform–precoded uplink MC-LNOMA and nonprecoded uplink MC-LNOMA. © 2018 John Wiley & Sons, Ltd.

A Joint Filtering and Precoding Based Uplink MC-NOMA

- Baig, Imran, Farooq, U., Ul Hasan, N., Zghaibeh, M., Imran, Muhammad

  • Authors: Baig, Imran , Farooq, U. , Ul Hasan, N. , Zghaibeh, M. , Imran, Muhammad
  • Date: 2018
  • Type: Text , Conference paper
  • Relation: 2018 International Symposium on Networks, Computers and Communications, ISNCC 2018, Rome, 19-21 June 2018
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  • Description: Non Orthogonal Multiple Access (NOMA) has become one of the prospective candidates for upcoming 5 th generation Cellular network standard. Multicarrier NOMA (MC-NOMA) is a kind of hybrid NOMA, where, Orthogonal Frequency Division Multiple Access (OFDMA) may be employed to achieve higher capacity. However, MC-NOMA scheme based on OFDMA face the problem of higher Peak-to-Average Power Ratio (PAPR). The high PAPR reduces both energy and spectral efficiency of the MC-NOMA scheme. Therefore, in this paper, a new Finite Impulse Response (FIR) filtering based Zadoff-Chu Matrix Transform (ZCMT) precoded uplink MC-NOMA scheme is presented to reduce higher PAPR. MATLAB® simulations demonstrate that, the proposed filter based ZCMT precoded uplink MC-NOMA scheme outperform the ZCMT precoded uplink MC-NOMA schemes without filtering, uplink Single Carrier NOMA (SC-NOMA) schemes and conventional uplink MC-NOMA schemes available in the literature. © 2018 IEEE.

A joint SLM and precoding based PAPR reduction scheme for 5G UFMC cellular networks

- Baig, Imran, Farooq, Umer, Hasan, Najam, Zghaibeh, Manaf, Arshad, Muhammad, Imran, Muhammad

A lightweight cyber security framework with context-awareness for pervasive computing environments

- Al-Muhtadi, Jalal, Saleem, Kashif, Al-Rabiaah, Sumaya, Imran, Muhammad, Gawanmeh, Amjad, Rodrigues, Joel

  • Authors: Al-Muhtadi, Jalal , Saleem, Kashif , Al-Rabiaah, Sumaya , Imran, Muhammad , Gawanmeh, Amjad , Rodrigues, Joel
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Sustainable Cities and Society Vol. 66, no. (2021), p.
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  • Description: Internet of things (IoT) plays a key role in enabling smart sustainable cities. Pervasive computing over the IoT platform makes life more convenient by embedding sensors based on context-aware computing devices in the physical environment for the ubiquitous availability of computing resources. The sensors gather contextual information from the physical world and transmit it to receivers as per requirements or in case of environmental changes, such as temperature and humidity. However, the combination of dynamic operation and the need to handle sensitive and private data make the pervasive computing environment and IoT devices vulnerable to numerous attacks. Smart environments require a maximum level of safety assurance, such as trusted context producers and customers, which should protect sensitive information from exposure or monitoring. This paper discusses the major cyber threats in smart environments and proposes a novel lightweight security framework that authenticates and maintains the context providers and receivers. The cloud environment is adopted for user authentication at the user layer to implement access control and role assignment. Finally, the proposed security framework is implemented in the IBM cloud platform with six devices to evaluate its efficiency, sustainability, and secure communication. © 2020 Elsevier Ltd

A lightweight federated learning based privacy preserving B5G pandemic response network using unmanned aerial vehicles: A proof-of-concept

- Nasser, Nasser, Fadlullah, Zubair, Fouda, Mostafa, Ali, Asmaa, Imran, Muhammad

  • Authors: Nasser, Nasser , Fadlullah, Zubair , Fouda, Mostafa , Ali, Asmaa , Imran, Muhammad
  • Date: 2022
  • Type: Text , Journal article
  • Relation: Computer Networks Vol. 205, no. (2022), p.
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  • Description: The concept of an intelligent pandemic response network is gaining momentum during the current novel coronavirus disease (COVID-19) era. A heterogeneous communication architecture is essential to facilitate collaborative and intelligent medical analytics in the fifth generation and beyond (B5G) networks to intelligently learn and disseminate pandemic-related information and diagnostic results. However, such a technique raises privacy issues pertaining to the health data of the patients. In this paper, we envision a privacy-preserving pandemic response network using a proof-of-concept, aerial–terrestrial network system serving mobile user entities/equipment (UEs). By leveraging the unmanned aerial vehicles (UAVs), a lightweight federated learning model is proposed to collaboratively yet privately learn medical (e.g., COVID-19) symptoms with high accuracy using the data collected by individual UEs using ambient sensors and wearable devices. An asynchronous weight updating technique is introduced in federated learning to avoid redundant learning and save precious networking as well as computing resources of the UAVs/UEs. A use-case where an Artificial Intelligence (AI)-based model is employed for COVID-19 detection from radiograph images is presented to demonstrate the effectiveness of our proposed approach. © 2021 Elsevier B.V.

A low PAPR universal filtered multi-carrier system for 5G machine type communications

- Baig, Imrana, Farooq, Umer, Hasan, Najam, Zghaibeh, Manafa, Jeoti, Varun, Imran, Muhammad

  • Authors: Baig, Imrana , Farooq, Umer , Hasan, Najam , Zghaibeh, Manafa , Jeoti, Varun , Imran, Muhammad
  • Date: 2019
  • Type: Text , Conference paper
  • Relation: 2019 Wireless Days, WD 2019, Manchester, 24 April to 26 April 2019 Vol. 2019-April
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  • Description: Universal Filtered Multi-Carriers (UFMC) has become one of the favorable modulation systems for upcoming 5G Machine-Type Communications (MTC) communications due to its robustness against multiuser interference, fragmented spectrum suitability and short burst support. However, UFMC systems faces a challenging problem in the form of high Peak-to-Average Power Ratio (PAPR) at the transmitter side. The high PAPR value downplays the efficiency of UFMC transmitter. To counter the high PAPR values, in this work, a new Generalized Chirp-Like Precoding based UFMC (GCL-P-UFMC) system is proposed. The Monte-Carlo simulations of the proposed GCL-P-UFMC system indicate that the proposed system has low PAPR as compared to the conventional UFMC system and the Orthogonal Frequency Division Multiplexing (OFDM) system available in the literature. At a clip rate of 10-3, the proposed system gives on average 30% better PAPR results as compared to the conventional UFMC and OFDM systems. © 2019 IEEE.

A microservice recommendation mechanism based on mobile architecture

- Wang, Ru, Imran, Muhammad, Saleem, Kashif

  • Authors: Wang, Ru , Imran, Muhammad , Saleem, Kashif
  • Date: 2020
  • Type: Text , Journal article
  • Relation: Journal of Network and Computer Applications Vol. 152, no. (2020), p.
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  • Description: The microservice recommendation mechanism, as a key supporting technology for providing users with intelligent and proactive application services, is one of the important research contents in mobile social networks. In this paper, a recommendation mechanism of mobile social network service based on user trajectory, trust network and collaborative filtering algorithm is proposed. The user trajectory prediction model based on Generative Adversarial Network (GAN) is introduced into the process of service recommendation, and combined with trust degree to constitute the 3D service recommendation model of user-service-trajectory prediction. This method improves the accuracy and reliability of service recommendation and avoids the blindness and randomness of service recommendation. The simulation experiments show that the service recommendation algorithm has higher accuracy than the traditional collaborative filtering algorithm. © 2019 Elsevier Ltd