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نتیجه جستجو - Cognitive Radio

تعداد مقالات یافته شده: 29
ردیف عنوان نوع
1 An efficient radio-frequency spectrum utilization technique for cognitive radio networks
یک تکنیک کارآمد استفاده از طیف فرکانس رادیویی برای شبکه‌های رادیویی شناختی-2022
Cognitive radio (CR) is a rising technology that unlocks the doors for radio spectrum scarcity problem, which is of great concern nowadays among the researchers at various levels. CR enables to unlicensed users or secondary users (SUs) to access the primary channels when licenced users or primary users (PUs) are not using these channels. Two fundamental access methods namely overlay and underlay are very popular in utilizing the free available channels or the white spaces. Various hybrid access methods have been proposed and recommended by many researchers to further enhance the radio spectrum utilization. Of course hybrid access methods are the better ways to deal this spectrum scarcity problem, but a comprehensive and directed effort is required to optimize the modality of these methods. This work proposes a Markov chain based hybrid access method named as Hybrid Spectrum Utilization Technique (HSUT), which tries to maximize the radio spectrum utilization by enhancing the PU’s detection probability. This work also analyzes the performance of the HSUT and results obtained through OMNeT++ simulator are very encouraging. At last, this work also compares the performance of the HSUT with the overlay, underlay, Hybrid-P1 (Dhurandher et al., 2021), and the Hybrid-P2 (Dhurandher et al., 2021) access methods.
keywords: Cognitive radio | White spaces | Hybrid access | Markov chain | OMNeT++
مقاله انگلیسی
2 Robust congestion control in cognitive radio network using event-triggered sliding mode based on reaching laws
کنترل تراکم قوی در شبکه رادیویی شناختی با استفاده از حالت کشویی ناشی از رویداد بر اساس دستیابی به قوانین-2020
In a band-limited spectrum, an increase in requests for various services of wireless applications is a matter of apprehension. To fulfill the expectations of immense wireless users, effective management and efficient use of the band-limited spectrum is highly desired. Cognitive Radio emerges as a solution to the problem of spectrum scarcity by opportunistically sharing the spectrum among licensed and unlicensed users. A careful balance of spectrum usage among different priority class users must be ensured to avoid network congestion. A robust congestion controller with three different reaching laws has been studied in this work for optimal spectrum utilization in Cognitive Radio Network. The sliding mode controller, which is eminent for its robustness and disturbance rejection capabilities has been combined with a novel dynamic event-triggering scheme to reduce energy expenses and computational complexities. The controller adequacy has been supported by simulations.
مقاله انگلیسی
3 Secondary User Experience-oriented Resource Allocation in AI-empowered Cognitive Radio Networks Using Deep Neuroevolution
تخصیص منابع کاربر گرا ثانویه در شبکه های رادیویی شناختی دارای هوش مصنوعی با استفاده از تکامل عصبی عمیق-2020
Secondary user (SU)-experience-oriented resource allocation (RA) will become increasingly important in cognitive radio networks (CRNs) in future wireless networks. For efficient real-time processes, cognitive radios (CRs) are usually combined with artificial intelligence (AI) to improve better adaptation and intelligent RA. However, deep learning (DL), which is a key AI strategy with remarkable capabilities towards advancing this vision, has several built-in limitations. Firstly, the most successful DL applications require training with large amounts of data; secondly, they assume that the data samples to be independent, while in CRNs one typically encounters sequences of highly correlated states. To circumvent this issue, this paper introduces a deep neuroevolution (DNE) technique for dynamic RA. Using this technique, a stable learning framework was achieved by introducing the phenotypic plasticity of transmission rates and delay constraints inside a multi-layer perceptron (MLP). The stability of SU satisfaction as they increased in number was achieved at 36 SUs, which is a 13.3% decrease from when they were only 6 SUs in the CRN for all learning mechanisms.
Keywords: Secondary user | Artificial intelligence| Cognitive radio networks | Ant colony optimization | Logistic regression | Multilayer perceptron | Deep Q-network | Deep neuroevolution
مقاله انگلیسی
4 IEC 61850 based energy management system using plug-in electric vehicles and distributed generators during emergencies
IEC 61850 سیستم مدیریت انرژی مبتنی بر IEC با استفاده از وسایل نقلیه الکتریکی پلاگین و ژنراتور توزیع شده در مواقع اضطراری-2020
During emergencies, alternative power system operation that utilizes local assets to energize local loads will change the face of the situation. While distributed generators (DGs) such as PV or wind turbines can be utilized for generation, plug-in electric vehicles (PEVs) can act as mobile generators. Different strategies for forming dynamic and networked microgrids utilizing the local generation during emergencies have been widely proposed in literature. However, the underlying communication required for optimal formation of dynamic microgrids and energy management during emergencies is not discussed. Addressing this gap, this paper develops a communication- based energy management system for emergency cases based on IEC 61850 standard. The IEC 61850 based communication modeling provides interoperability and serves for plug-and-play purposes. Furthermore, for establishing communication during emergencies the concept of Cognitive Radio (CR) is proposed in this scheme. Simulation results show the feasibility of modeling and acceptability of its performance.
Keywords: Emergency | Microgrid | Plugged in Electric Vehicle (PEV) | Vehicle-to-grid (V2G) | IEC 61850 and Communication modeling
مقاله انگلیسی
5 A Reinforcement Learning based evolutionary multi-objective optimization algorithm for spectrum allocation in Cognitive Radio networks
یک الگوریتم بهینه سازی چند هدفه تکاملی مبتنی بر یادگیری تقویتی برای تخصیص طیف در شبکه های رادیویی شناختی-2020
To cope up with drastically increasing demand for radio resources lead to raise a challenge to the wireless community. The limited radio spectrum and fixed spectrum allocation strategy have become a bottleneck for various wireless communication. Cognitive Radio (CR) technology along with potential benefits of machine learning has attracted substantial research interest especially in the context of spectrum management. However, a variety of performance attributes as objectives draw attention during the technological preparations for spectrum management such as higher spectral efficiency, lower latency, higher network capacity, and better energy efficiency as these objectives are often conflicting with each other. Hence, this paper addresses the spectrum allocation problem concerning network capacity and spectrum efficiency as conflicting objectives and model the scenario as a multiobjective optimization problem in CR networks. An improved version of the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) which combines the feature of evolutionary algorithm and machine learning called Non-dominated Sorting Genetic Algorithm based on Reinforcement Learning (NSGARL) is proposed which incorporates a self-tuning parameter approach to handle multiple conflicting objectives. The numerical findings validate the effectiveness of the proposed algorithm through the Pareto optimal set and obtain optimal solution efficiently to satisfy various requirements of spectrum allocation in CR networks.
Keywords: Cognitive Radio (CR) networks | Multi-objective optimization | NSGA-II | NSGA-RL | Reinforcement learning | Spectrum allocation
مقاله انگلیسی
6 AI-Enhanced Cooperative Spectrum Sensing for Non-Orthogonal Multiple Access
سنجش طیف تعاونی تقویت شده هوش مصنوعی برای دسترسی چندگانه غیر متعامد-2020
Many state-of-the-art techniques are leveraged to improve spectral efficiency, of which cognitive radio and multiple access are the most promising ones. In cognitive radio communications, spectrum sensing is the most fundamental part, whose accuracy has a significant impact on spectrum utilization. Furthermore, due to the complex radio environment, multiple-user CSS has been proposed as a refined solution. NOMA, as an essential technique in 5G, holds great promise in improving spectral efficiency and carrying massive connectivity. In this article, we propose a novel CSS framework for NOMA to further improve the spectral efficiency. Considering the complicated physical layer implementations of NOMA, we introduce an AI based solution to cooperatively sense the spectrum with a nice accuracy rate and acceptable complexity. Numerical results validate the effectiveness of our proposed solution.
مقاله انگلیسی
7 ساخت مجموعه قالب همبند کارا با حداکثر طول عمر در شبکه های رادیویی شناختی
سال انتشار: 2019 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 15
مجموعه قالب همبند (CDS)، معرف فناوری طرح ریزی ستون مجازی در شبکه های بی سیم است و نقش مهمی در برنامه های بی سیم مانند پخش برنامه، مسیریابی و غیره دارد. در شبکه های رادیویی شناختی به علت فعالیت های تصادفی کاربران اولیه (PU ها) ، طول عمر و کارایی دو شاخص مهم در اندازه گیری الگوریتم های CDS می باشد. با این حال، بهترین کار در الگوریتم های موجود در ساخت CDS در CRN ها، نادیده گرفتن اثربخشی اجرا در مقابل طول عمر است. در این مقاله، یک الگوریتم توزیع چهار فازی برای به حداکثر رساندن طول عمر CDS با تضمین کارایی الگوریتم ارائه شد. الگوریتم پیشنهادی در زمانبندی O (N3 log N) متوقف می شود که بیشتر از O (N4) موثر است.
کليدواژه: مجموعه قالب همبند | شبکه های رادیویی شناختی | حداکثر طول عمر | الگوریتم توزیع شده
مقاله ترجمه شده
8 Privacy-preserving aggregation for cooperative spectrum sensing
تجمیع حفظ حریم خصوصی برای سنجش طیف تعاونی-2019
Cognitive radio technology has been proposed as a promising way to alleviate spectrum scarcity. In cognitive radio networks, cooperative spectrum sensing is an effective approach to improve spectrum-estimation accuracy. In this approach, a fusion center (FC) outsources sensing tasks to secondary users (SUs), and aggregates sensing reports provided by SUs to estimate spectrum availability. However, as sensing reports are highly correlated to SUs’ real locations, revealing sensing reports to an untrusted FC may incur a serious privacy threat for SUs. In this paper, we propose an efficient scheme that allows the FC to learn desired statistics from a group of SUs without compromising individual privacy. Moreover, the FC is still able to compute the sum over the remaining SUs when some SUs fail to submit their reports. Besides, to ensure secure communication in cooperative spectrum sensing, the proposed scheme verifies the legitimacy of SUs by utilizing the elliptic curve cryptography technique. The results of security analysis show that the proposed scheme achieves the combined objectives of privacy preservation, authentication, fault tolerance, and resistance to various types of attacks. Performance evaluation results demonstrate the feasibility and practicality of the proposed scheme.
Keywords: Cognitive radio networks | Cooperative spectrum sensing | Privacy preservation | Authentication | Fault tolerance | Elliptic curve cryptography
مقاله انگلیسی
9 An efficient privacy-preserving protocol for database-driven cognitive radio networks
یک پروتکل موثر برای حفظ حریم خصوصی برای شبکه های رادیویی شناختی محور از پایگاه داده-2019
Cognitive radio is regarded as a promising technology for remedying spectrum shortage and improving spectrum utilization. However, database-driven cognitive radio networks (CRNs) are vulnerable to a series of security attacks and privacy threats, especially the privacy breach of secondary users (SUs). In this paper, we propose an efficient privacy-preserving protocol to protect the identity and trajectory privacy of each SU and to prevent the database (DB) from tracing any SU. Besides, this paper also aims at improving the efficiency of authentication and channel allocation to offer the best connectivity to SUs wherever they are and at any time. Taking advantage of the elliptic curve cryptography technique, our protocol achieves the mutual authentication between SUs and base stations (BSs), which enhances the security of CRNs communication. Based on channel pre-allocation to BSs, our protocol reduces the latency of obtaining available channels for SUs. Moreover, our protocol exploits reputation to motivate SUs to be honest and thus increases the utilization of the limited spectrum resources. The results of security analysis show that our protocol provides strong privacy preservation for SUs that the DB cannot get the entire trajectory of any SU, even the DB colludes with all BSs. Furthermore, the results also show that the proposed protocol can resist various types of attacks. The results of performance evaluation indicate the efficiency of the proposed privacy-preserving protocol.
Keywords: Cognitive radio networks | Privacy-preserving | Authentication | Elliptic curve cryptography | Reputation
مقاله انگلیسی
10 Securing Cognitive Radio Networks using blockchains
ایمن سازی شبکه های رادیویی شناختی با استفاده از بلاکچین -2019
Due to the increase in industrial applications of Internet of Things (IoT), number of internet connected devices have been increased accordingly. This has resulted in big challenges in terms of accessibility, scalability, connectivity and adaptability. IoT is capable of creating connections between devices on wireless medium but the utilization of scarce spectrum in efficient manner for the establishment of these connections is the biggest concern. To accommodate spectrum allocation problem different radio technologies are being utilized. One of the most efficient technique being used is cognitive radio, which dynamically allocate the unlicensed spectrum for IoT applications. Spectrum sensing being the fundamental component of Cognitive Radio Network (CRN) is threatened by security attacks. Process of spectrum sensing is disturbed by the malicious user (MU) which attacks the primary signal detection and affects the accuracy of sensing outcome. The presence of such MU in system, sending false sensing data can degrade the performance of cognitive radios. Therefore, in this article a blockchain based method is proposed for the MU detection in network. By using this method an MU can easily be discriminated from a reliable user through cryptographic keys. The efficiency of the proposed mechanism is analyzed through proper simulations using MATLAB. Consequently, this mechanism can be deployed for the validation of participating users in the process of spectrum sensing in CRN for IoTs.
Keywords: Spectrum sensing | Cognitive Radio Networks | Blockchains | Malicious user detection
مقاله انگلیسی
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