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IRS-enabled NOMA communication systems:A network architecture primer with future trends and challenges

Digital Communications and Networks 2024年第5期10卷 1503-1528页

作者： Haleema Sadia Ahmad Kamal Hassan Ziaul Haq Abbas Ghulam Abbas Muhammad Waqas Zhu Han Faculty of Electrical Engineering and Telecommunications and Networking(TeleCoN)Research Center Ghulam Ishaq Khan Institute of Engineering and Technology(GIKI)Topi 23640Pakistan Faculty of Computer Science and Engineering GIKITopi 23640Pakistan Department of Computer Engineering College of Information TechnologyUniversity of Bahrain32028Bahrain School of Engineering Edith Cowan UniversityPerth WA6027Australia Department of Electrical and Computer Engineering University of HoustonHoustonTX 77004USA Department of Computer Science and Engineering Kyung Hee UniversitySeoul 446-701South Korea

Non-Orthogonal Multiple Access(NOMA)has already proven to be an effective multiple access scheme for5th Generation(5G)wireless *** provides improved performance in terms of system throughput,spectral efficiency,fairness,and energy efficiency(EE).However,in conventional NOMA networks,performance degradation still exists because of the stochastic behavior of wireless *** combat this challenge,the concept of Intelligent Reflecting Surface(IRS)has risen to prominence as a low-cost intelligent solution for Beyond 5G(B5G)*** this paper,a modeling primer based on the integration of these two cutting-edge technologies,i.e.,IRS and NOMA,for B5G wireless networks is *** in-depth comparative analysis of IRS-assisted Power Domain(PD)-NOMA networks is provided through 3-fold ***,a primer is presented on the system architecture of IRS-enabled multiple-configuration PD-NOMA systems,and parallels are drawn with conventional network configurations,i.e.,conventional NOMA,Orthogonal Multiple Access(OMA),and IRS-assisted OMA *** by this,a comparative analysis of these network configurations is showcased in terms of significant performance metrics,namely,individual users'achievable rate,sum rate,ergodic rate,EE,and outage ***,for multi-antenna IRS-enabled NOMA networks,we exploit the active Beamforming(BF)technique by employing a greedy algorithm using a state-of-the-art branch-reduceand-bound(BRB)*** optimality of the BRB algorithm is presented by comparing it with benchmark BF techniques,i.e.,minimum-mean-square-error,zero-forcing-BF,and ***,we present an outlook on future envisioned NOMA networks,aided by IRSs,i.e.,with a variety of potential applications for 6G wireless *** work presents a generic performance assessment toolkit for wireless networks,focusing on IRS-assisted NOMA *** comparative analysis provides a solid foundation for the dev

关键词： Intelligent reflecting surface Non-orthogonal multiple access 6G Beamforming Sum rate Energy efficiency

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Iterative Segmentation and Propagation Based Interactive Video Object Segmentation

Iterative Segmentation and Propagation Based Interactive Vid...

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2023 International Conference on Algorithm, Imaging Processing, and Machine Vision, AIPMV 2023

作者： Luo, Sihan Yang, Sizhe Yuan, Xia School of Computer Science and Engineering Nanjing University of Science and Technology Jiangsu Nanjing China School of Information and Software Engineering University of Electronic Science and Technology of China Sichuan Chengdu China

ISBN: (纸本)9781510672444

Interactive video object segmentation (iVOS), which aims to efficiently produce high-quality segmentation masks of the target object in a video with user interactions. Recently, numerous works are proposed to advance the task of iVOS. However, their usages on user intent are limited. First, typical modules usually try to direct generate the segmentation without any further exploration on the input interaction, which misses valuable information. Second, recent iVOS approaches also do not consider the raw interactive information. As a result, the final segmentation results will be poisoned by the erroneous information given by the previous round’s segmentation masks. To solve the aforementioned weaknesses, in this paper, an Iterative Segmentation and Propagation based iVOS method is proposed to conduct better user intent exploration, namely ISP. ISP directly models user intent into the PGI2M module and TP module. Specifically, ISP first extracts a coarse-grained segmentation mask by analyzing the user’s input. Subsequently, this mask is used as a prior to aid the PGI2M module. Secondly, ISP presents a new interaction-driven self-attention module to recall the user’s intent in the TP module. Extensive experiments on two public datasets show the superiority of ISP over existing methods. © 2024 SPIE.

关键词： Iterative methods

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Nondestructive detection and classification of impurities-containing seed cotton based on hyperspectral imaging and one-dimensional convolutional neural network

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Digital Communications and Networks 2025年第2期11卷 308-316页

作者： Yeqi Fei Zhenye Li Tingting Zhu Zengtao Chen Chao Ni College of Mechanical and Electronic Engineering Nanjing Forestry UniversityNanjing 210037China School of Intelligent Manufacturing Nanjing University of Science and Technology ZiJin CollegeNanjing 210046China Department of Mechanical Engineering University of AlbertaEdmonton AB T6G 1H9Canada

The cleanliness of seed cotton plays a critical role in the pre-treatment of cotton textiles,and the removal of impurity during the harvesting process directly determines the quality and market value of cotton *** fusing band combination optimization with deep learning,this study aims to achieve more efficient and accurate detection of film impurities in seed cotton on the production *** applying hyperspectral imaging and a one-dimensional deep learning algorithm,we detect and classify impurities in seed cotton after *** main categories detected include pure cotton,conveyor belt,film covering seed cotton,and film adhered to the conveyor *** proposed method achieves an impurity detection rate of 99.698%.To further ensure the feasibility and practical application potential of this strategy,we compare our results against existing mainstream *** addition,the model shows excellent recognition performance on pseudo-color images of real *** a processing time of 11.764μs per pixel from experimental data,it shows a much improved speed requirement while maintaining the accuracy of real production *** strategy provides an accurate and efficient method for removing impurities during cotton processing.

关键词： Seed cotton Film impurity Hyperspectral imaging Band optimization Classification

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Leveraging Network Slicing in SDNs for Handling Application Failures

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2024年第4期51卷 409-421页

作者： Lokesh, Bommareddy Rajagopalan, Narendran School of Computer Science and Engineering VIT-AP University Andhra Pradesh Amaravati522237 India Department of Computer Science and Engineering National Institute of Technology Puducherry Karaikal609609 India

Unlike traditional networks, Software-defined networks (SDNs) provide an overall view and centralized control of all the devices in the network. SDNs enable the network administrator to implement the network policy by programming applications on top of the SDN controller using generic APIs. One or more controller instances can be deployed to administer the data flow by maintaining unified control of the entire network. The controller is expected to respond quickly to queries from forwarding devices. Presuming quick responses from the controller while enforcing a complex security mechanism is unreasonable. In this paper, the authors propose a unique, adaptive, lightweight, yet efficient technique called ISOLATOR to mitigate the effect of insider attacks and malfunctioning of distributed applications in an SDN-enabled cloud. The proposed security application upon detecting any suspicious activity by a virtual machine, isolates it by removing the interface to its respective shared network and reconnects it through a restricted network operating in a highly selective mode. By subjecting the data traffic to deep packet inspection, the restricted network searches for a match with a known worm pattern. The application is programmed for the OpenDayLight controller and the results show a significant improvement in identifying malicious activities with minimal latency and computational cost. © (2024), (International Association of Engineers). All Rights Reserved.

关键词： Controllers

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Highly Reliable Multilayer Encryption Scheme With Constellation Shaping Based on Joint Index Modulation

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Journal of Lightwave technology 2025年第12期43卷 5689-5698页

作者： Zhu, Dongxu Liu, Bo Ren, Jianxin Mao, Yaya Song, Xiumin Chen, Shuaidong Zhao, Lilong Yin, Mengtong Dai, Wei Chen, Guoqing Cai, Junjie Institute of Optics and Electronics Nanjing University of Information Science & Technology Nanjing210044 China State Key Laboratory Cultivation Base of Atmospheric Optoelectronic Detection and Information Fusion Nanjing University of Information Science & Technology Nanjing210044 China Jiangsu International Joint Laboratory for Meteorological Photonics and Optoelectronic Detection Nanjing University of Information Science & Technology Nanjing210044 China Jiangsu Engineering Research Center for Intelligent Optoelectronic Sensing Technology of Atmosphere Nanjing University of Information Science & Technology Nanjing210044 China Beijing University of Posts and Telecommunications Beijing100876 China Department of Electronic Engineering Tsinghua University Beijing100084 China

This paper proposes a highly reliable multilayer encryption scheme with constellation shaping based on joint index modulation. Multilayer encryption is used to ensure the security of the scheme. We utilize the 3D-Zhang chaotic system to realize the multidimensional perturbation of bits, subcarriers, and symbols of the original signal. The key information is masked with the signal using joint index modulation (JIM). The cooperative transmission of the initial value of the chaotic system is realized through the position information of the silent subcarriers and the constellation modes of the corresponding subcarriers. The scheme interleaves the initial values of the two chaotic systems to encode them as index bits, realizing the first layer of masked keys. Additional constellation shaping is achieved by optimizing the index mapping rules and changing the distribution of constellation points in the center and in the dual mode. The rotational encryption of the constellation is realized using a one-dimensional sinusoidal chaotic system after the completion of JIM, and the second layer of spherical shell masking of the key information is completed. The experimental implementation demonstrates the successful transmission of a 14 Gb/s 3D-JIM -8QAM signal over a 2 km weakly coupled seven-core fiber. Results confirm that the multi-layer encryption approach ensures secure signal transmission even under partial key leakage, without introducing degradation to the system's transmission performance. Compared to a random constellation distribution, the optimized index mapping scheme provides a coding gain of 0.75 dB at an FEC (Forward Error Correction) threshold of 3.8×10-3. The proposed scheme achieves error-free key transmission, with a bit error rate (BER) consistently maintained at 0. Notably, even minor key misalignments result in a BER of 0.5, facilitating timely key updates. The scheme boasts a vast key space of 10150, effectively resisting brute-force attacks. Due to its hi

关键词： Forward error correction

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Obstacle detection method based on point cloud registration and target reduction processing Efficient detection of vehicle obstacles 4

Obstacle detection method based on point cloud registration ...

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4th International Conference on Machine Learning and computer Application, ICMLCA 2023

作者： Pi, Dawei Guan, Lei Wang, Hongliang Department of Vehicle Engineering Nanjing University of Science and Technology Nanjing China

ISBN: (数字)9781510680265

ISBN: (纸本)9781510680258

Obstacle detection systems serve as a linchpin in ensuring the safety of autonomous vehicles. While contemporary detection techniques grapple with intricate results, diminished efficiency, and substantial computational burdens, our research introduces a groundbreaking method anchored in point cloud registration and target reduction for areas with obstructions. This approach not only facilitates high-precision positioning but also expedites the process of obstacle detection, a cornerstone for the subsequent navigation and obstacle evasion tasks in intelligent vehicles. Initially, we harness the power of NDT registration to achieve meticulous positioning. Subsequent stages involve refining the detection landscape by filtering out non-road obstacles using our innovative target reduction process and then employing advanced clustering techniques to pinpoint obstacles. We've validated our approach using the comprehensive Mulran dataset. Both qualitative and quantitative assessments underscore the method's robustness, reliability, and superior effectiveness. Experimental outcomes compellingly demonstrate that our newly proposed obstacle detection framework considerably elevates both operational efficiency and accuracy, paving the way for safer and smarter autonomous driving. © 2024 SPIE.

关键词： Efficiency

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Distributed Population-Based Simultaneous Perturbation Stochastic Approximation for Fine-Tuning Large Language Models 21st

Distributed Population-Based Simultaneous Perturbation Stoch...

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21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024

作者： Tan, Yajing Huang, Yuwei Duan, Qiqi Yang, Yijun Shi, Yuhui Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China

ISBN: (纸本)9789819601219

Very recently, a memory-efficient version (called MeZO) of simultaneous perturbation stochastic approximation (SPSA), one well-established zeroth-order optimizer from the automatic control community, has shown competitive fine-tuning performance on large language models (LLMs) with billions of weights under the limited memory of a single GPU, which often hinders the direct usage of the standard backpropagation (BP) update. Furthermore, population-based evolutionary methods (such as evolution strategies from OpenAI and population-based training from DeepMind) have shown a promising direction to improving and scaling up various large-scale AI systems via efficiently utilizing increasingly available distributed computing resources, owing to their relatively simple yet efficient data and control flows. In this paper, we propose a population-based SPSA for fine-tuning LLMs with non-differentiable objective functions. Specifically, our proposed method combines the desirable exploration ability of distributed population-based evolutionary methods with the powerful exploitation ability of SPSA in the modern distributed computing environment wherein the efficient implementation of BP is still challenging because of its complex dependencies in forward-pass and backward-pass information flows. Simulation experiments on a set of challenging (non-differentiable) natural language process tasks empirically validate the potential of our method on fine-tuning even in a relatively small-scale distributed computing scenario. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Stochastic systems

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A Novel Lightweight Image Encryption Scheme

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computers, Materials & Continua 2023年第4期75卷 2137-2153页

作者： Rawia Abdulla Mohammed Maisa’a Abid Ali Khodher Ashwak Alabaichi Department of Computer Science University of TechnologyBaghdadIraq Department of Biomedical Engineering University of KerbalaKerbalaIraq

Encryption algorithms are one of the methods to protect dataduring its transmission through an unsafe transmission medium. But encryptionmethods need a lot of time during encryption and decryption, so itis necessary to find encryption algorithms that consume little time whilepreserving the security of the data. In this paper, more than one algorithmwas combined to obtain high security with a short implementation time. Achaotic system, DNA computing, and Salsa20 were combined. A proposed5D chaos system was used to generate more robust keys in a Salsa algorithmand DNA computing. Also, the confusion is performed using a new *** proposed chaos system achieves three positive Lyapunov *** results demonstrate of the proposed scheme has a sufficient peak signalto-noise ratio, a low correlation, and a large key space. These factors makeit more efficient than its classical counterpart and can resist statistical anddifferential attacks. The number of changing pixel rates (NPCR) and theunified averaged changed intensity (UACI) values were 0.99710 and UACI33.68. The entropy oscillates from 7.9965 to 7.9982 for the tested encryptedimages. The suggested approach is resistant to heavy attacks and takes lesstime to execute than previously discussed methods, making it an efficient,lightweight image encryption scheme. The method provides lower correlationcoefficients than other methods, another indicator of an efficient imageencryption system. Even though the proposed scheme has useful applicationsin image transmission, it still requires profound improvement in implementingthe high-intelligence scheme and verifying its feasibility on devices with theInternet of Things (IoT) enabled.

关键词： Chaotic system lightweight confusion diffusion encryption Salsa20

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A Novel Diversified API Recommendation for Power System Sensors 17

A Novel Diversified API Recommendation for Power System Sens...

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IEEE Congress on Cybermatics: 17th IEEE International Conference on Internet of Things, iThings 2024, 20th IEEE International Conference on Green Computing and Communications, GreenCom 2024, 17th IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2024, 10th IEEE International Conference on Smart Data, SmartData 2024

作者： Zhu, Minhao Gu, Huanhuan Che, Xun Chen, Jingfei Zhao, Qian Liu, Fan Zheng, Yu Nari Group Corporation Nanjing China Nanjing University of Science and Technology School of Cyber Science and Engineering Nanjing China Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing China Guodian Nanjing Automation Co. Ltd. Nanjing China

ISBN: (纸本)9798350351637

The collaborative interaction between power systems and the Internet of Things (IoT) is strengthening, with IoT devices facilitating real-time monitoring and governance of the power grid, pushing power systems to the next frontier: the smart grid. Nevertheless, the reliance of power systems on a vast array of IoT devices, each with its unique API, makes the development of a unified smart grid software solution extremely complex. Most existing research focuses on accuracy in recommendations, thus neglecting users' needs for functional diversity. To address this issue, we propose a diversified API recommendation approach that suggests a variety of functional APIs from power system sensors to users. We start by converting API labels into feature vectors based on a pre-trained language model and calculate the similarity between APIs through clustering. Subsequently, we construct an API graph to model the functional similarity relationships between APIs. Finally, we generate a minimum weighted tree to obtain a combination of APIs that meets the requirements and ensures diversity. We demonstrate the advantages of our proposed method in terms of diversity through a case study. © 2024 IEEE.

关键词： Power systems computer aided design

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Scheduling Bi-Objective Lot-Streaming Hybrid Flow Shops with Consistent Sublots via an Enhanced Artificial Bee Colony Algorithm

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Complex System Modeling and Simulation 2025年第1期5卷 46-67页

作者： Benxue Lu Kaizhou Gao Peiyong Duan Adam Slowik School of Computer Science Liaocheng UniversityLiaocheng 252000China Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China School of Information and Automation Engineering Qilu University of TechnologyJinan 250353China Department of Electronics and Computer Science Koszalin University of TechnologyKoszalin 75-453Poland

This work addresses bi-objective hybrid flow shop scheduling problems considering consistent sublots(Bi-HFSP_CS).The objectives are to minimize the makespan and total energy ***,the Bi-HFSP_CS is formalized,followed by the establishment of a mathematical ***,enhanced version of the artificial bee colony(ABC)algorithms is proposed for tackling the Bi-HFSP_***,fourteen local search operators are employed to search for better *** different Q-learning tactics are developed to embed into the ABC algorithm to guide the selection of operators throughout the iteration ***,the proposed tactics are assessed for their efficacy through a comparison of the ABC algorithm,its three variants,and three effective algorithms in resolving 95 instances of 35 different *** experimental results and analysis showcase that the enhanced ABC algorithm combined with Q-learning(QABC1)demonstrates as the top performer for solving concerned *** study introduces a novel approach to solve the Bi-HFSP_CS and illustrates its efficacy and superior competitive strength,offering beneficial perspectives for exploration and research in relevant domains.

关键词： hybrid flow shop scheduling Q-learning lot streaming local search

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