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Joint optimization for secure ambient backscatter communication in NOMA-enabled IoT networks

Digital Communications and Networks 2023年第1期9卷 264-269页

作者： Wali Ullah Khan Furqan Jameel Asim Ihsan Omer Waqar manzoor ahmed Interdisciplinary Centre for Security Reliability and Trust(SnT)/SigComUniversity of LuxembourgLuxembourg Department of Communications and Networking Aalto University02150EspooFinland Department of Communication and Information Engineering Shanghai Jiao Tong UniversityShanghai200240China Department of Engineering Thompson Rivers University(TRU)British Columbia(BC)Canada College of Computer Science and Technology Qingdao UniversityQingdao266071China

Non-Orthogonal Multiple Access(NOMA)has emerged as a novel air interface technology for massive connectivity in Sixth-Generation(6G)*** recent integration of NOMA in Backscatter Communication(BC)has triggered significant research interest due to its applications in low-powered Internet of Things(IoT)***,the link security aspect of these networks has not been well *** article provides a new optimization framework for improving the physical layer security of the NOMA ambient BC *** system model takes into account the simultaneous operation of NOMA IoT users and the Backscatter Node(BN)in the presence of multiple EavesDroppers(EDs).The EDs in the surrounding area can overhear the communication of Base Station(BS)and BN due to the wireless broadcast ***,the chief aim is to enhance link security by optimizing the BN reflection coefficient and BS transmit *** gauge the performance of the proposed scheme,we also present the suboptimal NOMA and conventional orthogonal multiple access as benchmark *** Carlo simulation results demonstrate the superiority of the NOMA BC scheme over the pure NOMA scheme without the BC and conventional orthogonal multiple access schemes in terms of system secrecy rate.

关键词： 6G Non-orthogonal multiple access Ambient backscatter communication Internet-of-things Joint optimization Physical layer security

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Performance Analysis in Cloud Radio Access Networks:User-Centralized Coordination Approach

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China Communications 2015年第11期12卷 12-23页

作者： Munzali ahmed Abana SUN Yaohua manzoor ahmed Lukman A.Olawoyin LI Yong Key Laboratory of Universal Wireless Communication Ministry of EducationBeijing University of Posts and Telecommunications Wireless Communication Center Beijing University of Posts and Telecommunications

The cloud radio access network(C-RAN) has recently been proposed as an important component of the next generation wireless networks providing opportunities for improving both spectral and energy effi ciencies. The performance of this network structure is however constrained by severe inter-cell interference due to the limited capacity of fronthaul between the radio remote heads(RRH) and the base band unit(BBU) pool. To achieve performance improvement taking full advantage of centralized processing capabilities of C-RANs,a set of RRHs can jointly transmit data to the same UE for improved spectral effi ciency. In this paper,a user centralized joint coordinated transmission(UC-JCT) scheme is put forth to investigate the downlink performance of C-RANs. The most important benefit the proposed strategy is the ability to translate what would have been the most dominant interfering sources to usable signal leading to a signifi cantly improved performance. Stochastic geometry is utilized to model the randomness of RRH location and provides a reliable performance analysis. We derive an analytical expression for the closed integral form of the coverage probability of a typical UE. Simulation results confirm the accuracy of our analysis and demonstrate that significant performance gain can be achieved from the proposed coordination schemes.

关键词： cloud radio access network poisson point process coverage probability joint coordinated transmission baseband unit

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Deep reinforcement learning based computation offloading and resource allocation for low-latency fog radio access networks

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Intelligent and Converged Networks 2020年第3期1卷 243-257页

作者： G.M.Shafiqur Rahman Tian Dang manzoor ahmed Key Laboratory of Universal Wireless Communications(Ministry of Education) Beijing University of Posts and TelecommunicationsBeijing 100876China

Fog Radio Access Networks(F-RANs)have been considered a groundbreaking technique to support the services of Internet of Things by leveraging edge caching and edge ***,the current contributions in computation offloading and resource allocation are inefficient;moreover,they merely consider the static communication mode,and the increasing demand for low latency services and high throughput poses tremendous challenges in F-RANs.A joint problem of mode selection,resource allocation,and power allocation is formulated to minimize latency under various *** propose a Deep Reinforcement Learning(DRL)based joint computation offloading and resource allocation scheme that achieves a suboptimal solution in *** core idea of the proposal is that the DRL controller intelligently decides whether to process the generated computation task locally at the device level or offload the task to a fog access point or cloud server and allocates an optimal amount of computation and power resources on the basis of the serving *** results show that the proposed approach significantly minimizes latency and increases throughput in the system.

关键词： fog radio access networks computation offloading mode selection resource allocation distributed computation low latency deep reinforcement learning

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Enhancing Data Forwarding Efficiency in SIoT with Multidimensional Social Relations

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Computers, Materials & Continua 2024年第1期78卷 1095-1113页

作者： Fang Xu Songhao Jiang Yi Ma manzoor ahmed Zenggang Xiong Yuanlin Lyu School of Computer and Information Science Hubei Engineering UniversityXiaogan432000China School of Computer Science and Information Engineering Hubei UniversityWuhan430062China Artificial Intelligence Industrial Technology Research Institute Hubei Engineering UniversityXiaogan432000China

Effective data communication is a crucial aspect of the Social Internet of Things(SIoT)and continues to be a significant research *** paper proposes a data forwarding algorithm based on Multidimensional Social Relations(MSRR)in SIoT to solve this *** proposed algorithm separates message forwarding into intra-and cross-community forwarding by analyzing interest traits and social connections among *** new metrics are defined:the intensity of node social relationships,node activity,and community *** the community,messages are sent by determining which node is most similar to the sender by weighing the strength of social connections and node *** a node performs cross-community forwarding,the message is forwarded to the most reasonable relay community by measuring the node activity and the connection between *** proposed algorithm was compared to three existing routing algorithms in simulation *** indicate that the proposed algorithmsubstantially improves message delivery efficiency while lessening network overhead and enhancing connectivity and coordination in the SIoT context.

关键词： SIoT data forwarding social attributes social relations community

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Primitives towards verifiable computation： a survey

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Frontiers of Computer Science 2018年第3期12卷 451-478页

作者： Haseeb AHMAD Licheng WANG Haibo HONG Jing LI Hassan DAWOOD manzoor ahmed Yixian YANG State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Computer Science and Information Engineering Zhejiang Gongshang University Hangzhou 310018 China Department of Computer Engineering University of Engineering and Technology Taxila 47050 Pakistan Future Internet & Communication Lab Department of Electronic Engineering Tsinghua University Beijing 100084 China

Verifiable computation （VC） paradigm has got the captivation that in real term is highlighted by the concept of third party computation. In more explicate terms, VC allows resource constrained clients/organizations to securely outsource expensive computations to untrusted service providers, while acquiring the publicly or privately verifiable results. Many mainstream solutions have been proposed to address the diverse problems within the VC domain. Some of them imposed assumptions over performed computations, while the others took advantage of interactivity /non-interactivity, zero knowledge proofs, and arguments. Further proposals utilized the powers of probabilistic checkable or computationally sound proofs. In this survey, we present a chronological study and classify the VC proposals based on their adopted domains. First, we provide a broader overview of the theoretical advancements while critically analyzing them. Subsequently, we present a comprehensive view of their utilization in the state of the art VC approaches. Moreover, a brief overview of recent proof based VC systems is also presented that lifted up the VC domain to the verge of practicality. We use the presented study and reviewed resuits to identify the similarities and alterations, modifications, and hybridization of different approaches, while comparing their advantages and reporting their overheads. Finally, we discuss implementation of such VC based systems, their applications, and the likely future directions.

关键词： verifiable computation cloud computation interactive non-interactive zero knowledge probabilisticcheckable proofs computationally sound proofs

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Generating Type 2 Trapezoidal Fuzzy Membership Function Using Genetic Tuning

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Computers, Materials & Continua 2022年第4期71卷 717-734页

作者： Siti Hajar Khairuddin Mohd Hilmi Hasan Emilia Akashah P.Akhir manzoor ahmed Hashmani Centre for Research in Data Science Department of Computer and Information SciencesUniversiti Teknologi PETRONASPerakMalaysia

Fuzzy inference system(FIS)is a process of fuzzy logic reasoning to produce the output based on fuzzified *** system starts with identifying input from data,applying the fuzziness to input using membership functions(MF),generating fuzzy rules for the fuzzy sets and obtaining the *** are several types of input MFs which can be introduced in FIS,commonly chosen based on the type of real data,sensitivity of certain rule implied and computational *** paper focuses on the construction of interval type 2(IT2)trapezoidal shape MF from fuzzy C Means(FCM)that is used for fuzzification process of mamdani *** the process,upper MF(UMF)and lower MF(LMF)of the MF need to be identified to get the range of the footprint of uncertainty(FOU).This paper proposes Genetic tuning process,which is a part of genetic algorithm(GA),to adjust parameters in order to improve the behavior of existing system,especially to enhance the accuracy of the system *** novel process is a hybrid approach which produces Genetic Fuzzy System(GFS)that helps to enhance fuzzy classification problems and *** approach provides a new method for the construction and tuning process of the IT2 MF,based on the FCM *** result is compared to Gaussian shape IT2 MF and trapezoid IT2 MF generated by the classic GA *** is shown that the proposed approach is able to outperform the mentioned benchmarked *** work implies a wider range of IT2 MF types,constructed based on FCM outcomes,and an optimum generation of the FOU so that it can be implemented in practical applications such as prediction,analytics and rule-based solutions.

关键词： Fuzzy inference system membership function genetic tuning lateral adjustment trapezoidal MF fuzzy C means

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A Hybrid Feature Selection Framework for Predicting Students Performance

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Computers, Materials & Continua 2022年第1期70卷 1893-1920页

作者： Maryam Zaffar manzoor ahmed Hashmani Raja Habib KS Quraishi Muhammad Irfan Samar Alqhtani Mohammed Hamdi High Performance Cloud Computing(HPC3) Department of Computer and Information SciencesUniversiti Teknologi PETRONAS32610SeriIskandarMalaysia Department of Computer Science and Information Technology University of LahorePakistan Department of Process Engineering Pakistan Institute of Engineering&Applied SciencesNiloreIslamabadPakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia College of Computer Science and Information Systems Najran University61441NajranSaudi Arabia

Student performance prediction helps the educational stakeholders to take proactive decisions and make interventions,for the improvement of quality of education and to meet the dynamic needs of *** selection of features for student’s performance prediction not only plays significant role in increasing prediction accuracy,but also helps in building the strategic plans for the improvement of students’academic *** are different feature selection algorithms for predicting the performance of students,however the studies reported in the literature claim that there are different pros and cons of existing feature selection algorithms in selection of optimal *** this paper,a hybrid feature selection framework(using feature-fusion)is designed to identify the significant features and associated features with target class,to predict the performance of *** main goal of the proposed hybrid feature selection is not only to improve the prediction accuracy,but also to identify optimal features for building productive strategies for the improvement in students’academic *** key difference between proposed hybrid feature selection framework and existing hybrid feature selection framework,is two level feature fusion technique,with the utilization of cosine-based ***,according to the results reported in existing literature,cosine similarity is considered as the best similarity measure among existing similarity *** proposed hybrid feature selection is validated on four benchmark datasets with variations in number of features and number of *** validated results confirm that the proposed hybrid feature selection framework performs better than the existing hybrid feature selection framework,existing feature selection algorithms in terms of accuracy,f-measure,recall,and *** reported in presented paper show that the proposed approach gives more than 90%accuracy on benchmark dataset that is better tha

关键词： Educational data mining feature selection hybrid feature selection

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Combined Effect of Concept Drift and Class Imbalance on Model Performance During Stream Classification

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Computers, Materials & Continua 2023年第4期75卷 1827-1845页

作者： Abdul Sattar Palli Jafreezal Jaafar manzoor ahmed Hashmani Heitor Murilo Gomes Aeshah Alsughayyir Abdul Rehman Gilal Department of Computer and Information Sciences Universiti Teknologi PETRONAS(UTP)Seri Iskandar32610Malaysia Centre for Research in Data Science UTPPerak32610Malaysia High Performance Cloud Computing Centre(HPC3) UTPPerak32610Malaysia School of Engineering and Computer Science Victoria University of WellingtonWellington6012New Zealand AI Institute University of Waikato WellingtonHamilton3240New Zealand Anti-Narcotics Force Ministry of Narcotics ControlIslamabad46000Pakistan College of Computer Science and Engineering Taibah UniversityMadinah42353Saudi Arabia

Every application in a smart city environment like the smart grid,health monitoring, security, and surveillance generates non-stationary datastreams. Due to such nature, the statistical properties of data changes overtime, leading to class imbalance and concept drift issues. Both these issuescause model performance degradation. Most of the current work has beenfocused on developing an ensemble strategy by training a new classifier on thelatest data to resolve the issue. These techniques suffer while training the newclassifier if the data is imbalanced. Also, the class imbalance ratio may changegreatly from one input stream to another, making the problem more *** existing solutions proposed for addressing the combined issue of classimbalance and concept drift are lacking in understating of correlation of oneproblem with the other. This work studies the association between conceptdrift and class imbalance ratio and then demonstrates how changes in classimbalance ratio along with concept drift affect the classifier’s *** analyzed the effect of both the issues on minority and majority classesindividually. To do this, we conducted experiments on benchmark datasetsusing state-of-the-art classifiers especially designed for data stream ***, recall, F1 score, and geometric mean were used to measure theperformance. Our findings show that when both class imbalance and conceptdrift problems occur together the performance can decrease up to 15%. Ourresults also show that the increase in the imbalance ratio can cause a 10% to15% decrease in the precision scores of both minority and majority *** study findings may help in designing intelligent and adaptive solutionsthat can cope with the challenges of non-stationary data streams like conceptdrift and class imbalance.

关键词： Classification data streams class imbalance concept drift class imbalance ratio

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X-Band Power Amplifier for Next Generation Networks Based on MESFET

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China Communications 2017年第4期14卷 11-19页

作者： Muhammad Saad Khan Hongxin Zhang Fan Zhang Sulman Shahzad Rahat Ullah Sajid Ali Qasim Ali Arain manzoor ahmed School of Electronic Engineering Beijing University of Posts and Telecommunications (BUPT) Beijing 100876 China Beijing Key Laboratory of Work Safety Intelligent Monitoring Beijing University of Posts and Telecommunications Beijing 100876 china College of Information Science and Electrical Engineering Zhejiang University Hangzhou Zhejiang 310027china Electrical Engineering Department University College of Engineering & Technology Bahauddin Zakariya University Multan Pakistan State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing 100876 China Department of Coxnputer Science D.G. Khan Campus. University of Education Lahore Pakistan Future lnternet & Communication Lab (FIB) Department of Electronic Engineering Tsinghua University Beijing 100084 China

Advanced wireless standards of communication like 3GPP and LTE are becoming more and more efficient and with this evolution of communication systems mobile equipment is also become smaller and smaller. Power amplifier designing has become a very crucial task in this era where efficiency and size are the main concern of any designer. In this paper we have design and analyzed X-band Class E Metal-semiconductor field effect transistor(MESFET) based Power Amplifier. This device targets the devices which use OFDM technique to improve their spectral efficiency for the next generation communication systems. Microstrip lines are used to achieve small size for our design instead of lumped components. Load Pull measurements are used to get MESFET input and output impedances optimum values. For linear and non linear operation small signal mathematical model of the design is used. To reduce thermal losses FR4 substrate is used to increase PA efficiency. Our designs shows small values of input and output return loss of about-22.3d B and-23.716 d B achieving a high gain of about25.6 d B respectively, with PAE of about 30 % having stability factor greater than 1 and 21.894 d Bm of output power.

关键词： MESFET X-band power amplifier advance design system PAE LTE

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基于QMix的车辆云计算资源动态分配方法

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计算机工程 2022年第11期48卷 284-290,298页

作者：刘金石 manzoor ahmed 林青青岛大学计算机科学技术学院山东青岛266071

城市交通智能化和通信技术的进步会产生大量基于车辆的应用,但目前车辆有限的计算资源无法满足车辆应用的计算需求与延迟性约束。车辆云(VC)可以高效地调度资源,从而显著降低任务请求的延迟与传输成本。针对VC环境下任务卸载与计算资源... 详细信息

城市交通智能化和通信技术的进步会产生大量基于车辆的应用,但目前车辆有限的计算资源无法满足车辆应用的计算需求与延迟性约束。车辆云(VC)可以高效地调度资源,从而显著降低任务请求的延迟与传输成本。针对VC环境下任务卸载与计算资源分配问题,提出一个考虑异质车辆和异质任务的计计资源分配算法。对到达的任务构建M/M/1队列模型与计算模型,并定义一个效用函数以最大化系统整体效用。针对环境中车辆地理分布的高度动态系统变化,提出基于双时间尺度的二次资源分配机制(SRA),使用两个不同时间尺度的资源分配决策动作,对其分别构建部分可观测马尔可夫决策过程。两个决策动作通过执行各自的策略获得的奖励进行连接,将问题建模为两层计算资源分配问题。在此基础上提出基于二次资源分配机制的多智能体算法SRA-QMix求解最优策略。仿真结果表明,与深度确定性策略梯度算法对比,该算法的整体效用值和任务完成率分别提高了70%、6%,对于QMix和MADDPG算法分别应用SRA后的任务完成率分别提高了13%与15%,可适用于动态的计算资源分配环境。

关键词：车辆云多智能体强化学习 QMix算法任务卸载排队理论

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