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Journal articles on the topic 'Allocation des ressources radios'

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Author: Grafiati
Published: 25 May 2024

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1

Chung, J. M., C. H. Kim, J. H. Park, J. Shin, and D. Kim. "Optimal channel allocation for cognitive radios." Electronics Letters 46, no. 11 (2010): 802. http://dx.doi.org/10.1049/el.2010.0829.

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2

Prabhjot Kaur, Moin Uddin, and Arun Khosla. "Adaptive Bandwidth Allocation Scheme for Cognitive Radios." International Journal of Advancements in Computing Technology 2, no. 2 (June 30, 2010): 35–41. http://dx.doi.org/10.4156/ijact.vol2.issue2.3.

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3

Balassa, Bela. "Politiques agricoles et allocation internationale des ressources." Économie rurale 189, no. 1 (1989): 22–28. http://dx.doi.org/10.3406/ecoru.1989.3948.

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4

Yang, Zhou, Wenqian Jiang, and Gang Li. "Resource Allocation for Green Cognitive Radios: Energy Efficiency Maximization." Wireless Communications and Mobile Computing 2018 (July 5, 2018): 1–16. http://dx.doi.org/10.1155/2018/1327030.

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Green cognitive radios are promising in future wireless communications due to high energy efficiency. Energy efficiency maximization problems are formulated in delay-insensitive green cognitive radio and delay-sensitive green cognitive radio. The optimal resource allocation strategies for delay-insensitive green cognitive radio and delay-sensitive green cognitive radio are designed to maximize the energy efficiency of the secondary user. The peak interference power and the average/peak transmit power constraints are considered. Two algorithms based on the proposed resource allocation strategies are proposed to solve the formulated problems. Simulation results show that the maximum energy efficiency of the secondary user achieved under the average transmit power constraint is higher than that achieved under the peak transmit power constraint. It is shown that the design of green cognitive radio should take the tradeoff between its complexity and its achievable maximum energy efficiency into consideration.
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5

Kim, Seung-Jun, Nasim Yahya Soltani, and Georgios B. Giannakis. "Resource Allocation for OFDMA Cognitive Radios Under Channel Uncertainty." IEEE Transactions on Wireless Communications 12, no. 7 (July 2013): 3578–87. http://dx.doi.org/10.1109/twc.2013.062413.121892.

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6

Bazerque, Juan-Andrés, and Georgios B. Giannakis. "Distributed Scheduling and Resource Allocation for Cognitive OFDMA Radios." Mobile Networks and Applications 13, no. 5 (July 23, 2008): 452–62. http://dx.doi.org/10.1007/s11036-008-0083-z.

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7

Luo, Rong-hua, and Zhen Yang. "Stackelberg Game-based Distributed Power Allocation Algorithm in Cognitive Radios." Journal of Electronics & Information Technology 32, no. 12 (January 25, 2011): 2964–69. http://dx.doi.org/10.3724/sp.j.1146.2010.00374.

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8

Azmat, Freeha, Yunfei Chen, and Nigel Stocks. "Bio-inspired collaborative spectrum sensing and allocation for cognitive radios." IET Communications 9, no. 16 (November 5, 2015): 1949–59. http://dx.doi.org/10.1049/iet-com.2014.0769.

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9

Liu, Yicong, Muhammad Iqbal, Muhammad Naeem, Alagan Anpalagan, and N. N. Qadri. "Resource Allocation in Hospital Networks Based on Green Cognitive Radios." Wireless Personal Communications 85, no. 3 (June 30, 2015): 1487–507. http://dx.doi.org/10.1007/s11277-015-2852-x.

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10

Jian Tang, R. Hincapie, Guoliang Xue, Weiyi Zhang, and R. Bustamante. "Fair Bandwidth Allocation in Wireless Mesh Networks With Cognitive Radios." IEEE Transactions on Vehicular Technology 59, no. 3 (March 2010): 1487–96. http://dx.doi.org/10.1109/tvt.2009.2038478.

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11

Hung, Nguyen Manh. "L’efficacité économique du mode d’allocation des ressources naturelles." Articles 51, no. 3 (July 15, 2009): 405–19. http://dx.doi.org/10.7202/800630ar.

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Abstract In this paper, the decentralized economic allocation of a common property resource is fully characterized in a dynamic framework. Because of the externalities involved, this mode of allocation is shown to be inefficient. The extent and the causes of this inefficiency are discussed, with special emphasis on a kind of externality herein called the "appropriability". Finally, economic policies involving taxation, subsidy and user charge which purpose to bring about the social optimum are pointed out.
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12

Audibert, Gérard, Hélène Gebel, and Michel Hasselmann. "Allocation de ressources médicales rares : enjeux éthiques et citoyens." Revue française d'éthique appliquée N° 12, no. 1 (June 13, 2022): 171–82. http://dx.doi.org/10.3917/rfeap.012.0171.

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13

NGUYEN, Thanh-Tung, and Insoo KOO. "Distortion-Aware Dynamic Channel Allocation for Multimedia Users in Cognitive Radios." IEICE Transactions on Communications E97.B, no. 12 (2014): 2790–99. http://dx.doi.org/10.1587/transcom.e97.b.2790.

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14

Lopez-Ramos, Luis M., Antonio G. Marques, and Javier Ramos. "Jointly Optimal Sensing and Resource Allocation for Multiuser Interweave Cognitive Radios." IEEE Transactions on Wireless Communications 13, no. 11 (November 2014): 5954–67. http://dx.doi.org/10.1109/twc.2014.2347273.

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15

Alabbasi, Abdulrahman, Zouheir Rezki, and Basem Shihada. "Energy Efficient Resource Allocation for Cognitive Radios: A Generalized Sensing Analysis." IEEE Transactions on Wireless Communications 14, no. 5 (May 2015): 2455–69. http://dx.doi.org/10.1109/twc.2014.2387161.

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16

Ghosh, Amiotosh, and Walaa Hamouda. "Cross-Layer Antenna Selection and Channel Allocation for MIMO Cognitive Radios." IEEE Transactions on Wireless Communications 10, no. 11 (November 2011): 3666–74. http://dx.doi.org/10.1109/twc.2011.080611.100912.

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17

Gamel, Claude. "Comment financer l'allocation universelle? La stratégie de Van Parijs (1995) en question." Recherches économiques de Louvain 70, no. 3 (2004): 287–315. http://dx.doi.org/10.1017/s0770451800010769.

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RésuméDans l'ouvrage que Van Parijs a consacré en 1995 aux fondements philosophiques et économiques du projet d'allocation universelle, le chapitre IV est dédié au problème du financement « soutenable » d'une telle mesure. Les « rentes d'emploi » y sont présentées comme un troisième type de ressources susceptibles d'élargir l'assiette fiscale du financement, à côté des « ressources externes » et des « ressources internes » des individus. Les difficultés d'exploitation de telles rentes légitiment l'exploration d'une stratégie alternative de financement fondée sur la flexibilité « walrassienne » des salaires, laquelle permet de réduire une certaine contradiction entre l'acceptation par Van Parijs de rentes de situation liées à l'emploi et sa volonté ultérieure (chapitre VI) d'« optimiser » le capitalisme. Incidemment, la différence réelle entre allocation universelle et impôt négatif sur le revenu est aussi réexaminée.
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18

Yu, Heejung. "Optimal primary pilot power allocation and secondary channel sensing in cognitive radios." IET Communications 10, no. 5 (March 24, 2016): 487–94. http://dx.doi.org/10.1049/iet-com.2015.0646.

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19

Illanko, Kandasamy, Muhammad Naeem, Alagan Anpalagan, and Dimitrios Androutsos. "Energy-Efficient Frequency and Power Allocation for Cognitive Radios in Television Systems." IEEE Systems Journal 10, no. 1 (March 2016): 313–24. http://dx.doi.org/10.1109/jsyst.2015.2393834.

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20

Yudaninggar, Kartika Sari. "Reformulasi Regulasi Radio Komunitas di Indonesia." POPULIKA 7, no. 1 (January 10, 2019): 94–107. http://dx.doi.org/10.37631/populika.v7i1.30.

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Community Radio (CR) in Indonesia has emerged as a media that able to disseminate information to audience. Since this function can not be fullfiled by both private and public radios, CR is important for audience especially for those who lives in remote or even blank spot area. However, Government regulation on CR is feared to deprive the existence of CR. The regulation ranging from limitation of frequency allocation, criteria on coverage area and limited emmitance strength compare to public and private radios. This imply that the Government has never supported the existence of Community Radio. Government and Indonesia Broadcasting Commistion (KPI), as the powerful bodies, ought to reevaluate broadcasting regulation especially on Community Radio. Reformulation on the regulation is needed to maximilize the function of CR in Indonesia as independent media and to support democratization in the broadcasting system in Indonesia.
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21

Sauner-Leroy, Jacques-Bernard. "Allocation de ressources, avantage concurrentiel et performance des petites et moyennes entreprises de l’industrie manufacturière française." Revue internationale P.M.E. 15, no. 1 (February 16, 2012): 65–85. http://dx.doi.org/10.7202/1008801ar.

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L’analyse des liens entre la possession de un ou plusieurs avantages concurrentiels et la performance des firmes est un domaine qui a déjà été assez largement abordé dans la littérature de management stratégique. Certains de ces travaux ont cherché plus précisément à mettre en évidence des modes de combinaisons de ressources conduisant à la réalisation de niveaux de performance élevés. Toutefois, leurs champs d’investigation sont demeurés le plus souvent restreints à des domaines d’activité spécifiques, de sorte que les résultats auxquels ils aboutissent ne peuvent être généralisés. Partant de ce constat et s’appuyant sur le modèle de « ressources de base » qui apparaît comme le corpus théorique le plus complet sur cette question, l’objet de cette étude est de mettre en évidence, à partir de l’exploitation de 3049 enquêtes issues de la base de données de la Banque de France sur les comportements économiques et financiers des PME de l’industrie manufacturière française, des profils types de combinaison de ressources et de création d’avantages concurrentiels et de les comparer sur plusieurs critères de performance. Pour ce faire, une analyse typologique est menée. Elle conduit à la mise en évidence de six stratégies types de combinaisons de ressources associées à des avantages concurrentiels différents. Les résultats des tests effectués sur les comparaisons de performance entre ces six groupes indiquent que les entreprises qui obtiennent les meilleurs résultats sont celles qui adoptent un positionnement concurrentiel différencié fondé sur une approche qui situe le client au cœur de leur stratégie et qui utilisent principalement la fonction marketing comme support de création de leurs avantages compétitifs.
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22

Nkengne, Patrick, and Léonie Marin. "L’allocation des ressources enseignantes en Afrique subsaharienne francophone : pour une meilleure équité des systèmes éducatifs." Éducation et francophonie 45, no. 3 (May 28, 2018): 35–60. http://dx.doi.org/10.7202/1046416ar.

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Les pays d’Afrique subsaharienne souffrent d’un manque de personnel enseignant, et la forte augmentation de la population d’âge scolaire montre que le problème persistera. Il devient donc crucial pour ces pays d’optimiser l’utilisation de leurs ressources enseignantes en poste en s’assurant qu’elles sont équitablement allouées aux écoles. Or, jusqu’à quel point la répartition des enseignantes et des enseignants entre les écoles d’Afrique subsaharienne est-elle équitable? Comment peut-on améliorer cette allocation? Pour répondre à ces questions, cette étude s’appuie sur deux indicateurs, soit le ratio élèves/maître et le degré d’aléa dans l’allocation des ressources enseignantes aux écoles (1-R2), ainsi que sur des informations recueillies grâce à un « questionnaire pays » auquel ont répondu des acteurs clés des ministères de l’Éducation de pays d’Afrique subsaharienne. Nous avons ainsi eu recours à une approche quantitative et qualitative pour apprécier la situation des pays étudiés relativement à l’allocation des ressources enseignantes aux écoles, mais également pour comprendre les écarts observés en vue d’envisager des remédiations. Un constat majeur se dégage de cette étude : peu de pays francophones d’Afrique subsaharienne parviennent à une allocation équitable de leurs enseignants aux établissements. Le recrutement sur poste et l’automatisation de certains aspects de la gestion du personnel enseignant sont des solutions à considérer.
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23

Huang, Xiaoge, Baltasar Beferull-Lozano, and Carmen Botella. "Quasi-Nash Equilibria for Non-Convex Distributed Power Allocation Games in Cognitive Radios." IEEE Transactions on Wireless Communications 12, no. 7 (July 2013): 3326–37. http://dx.doi.org/10.1109/twc.2013.060413.121158.

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24

Dong In Kim, Long Bao Le, and Ekram Hossain. "Joint rate and power allocation for cognitive radios in dynamic spectrum access environment." IEEE Transactions on Wireless Communications 7, no. 12 (December 2008): 5517–27. http://dx.doi.org/10.1109/t-wc.2008.071465.

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25

Kaur, Prabhjot, Arun Khosla, and Khosla Uddin. "Markovian Queuing Model for Dynamic Spectrum Allocation in Centralized Architecture for Cognitive Radios." International Journal of Engineering and Technology 3, no. 1 (2011): 96–101. http://dx.doi.org/10.7763/ijet.2011.v3.206.

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26

Jayati, Ari Endang, Wahyu Minarti, and Sri Heranurweni. "Analisa Teknis Penetapan Kanal Frekuensi Radio Untuk Lembaga Penyiaran Radio Komunitas Wilayah Kabupaten Batang." Jurnal ELTIKOM 5, no. 2 (September 10, 2021): 73–80. http://dx.doi.org/10.31961/eltikom.v5i2.361.

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The radio frequency spectrum constitutes a limited and strategic natural resource with high economic value, so it must be managed effectively and efficiently to obtain optimal benefits by observing national and international legal principles. Radio Community Broadcasting Institution uses limited frequency allocation in three channels, namely, in the frequency channels 202 (107.7 MHz), 203 (107.8 MHz), and 204 (107.9 MHz), with limited transmit power and area coverage. The problem in this research is the frequency overlap with other community radios in an area. The issue raised is whether it is possible to establish a new community radio in the Batang Regency area by paying attention to existing radios that have licenses in districts/cities that are in the area directly adjacent to Batang Regency by considering the limited allocation of radio frequency channels community, without the occurrence of radio frequency interference with other community radios. The purpose of this research is to solve these problems. It is necessary to have a policy in determining radio frequency users to get good quality radio broadcast reception. The method used is to analyze the frequency determination technique based on the interference analysis on other community broadcasters. By using the Radio Mobile Software for frequency repetition simulation, in this research, the results show that Batang FM Community Radio does not allow to get frequency channels for community radio operations. After all, it interferes with the Service Area of ​​Soneta FM Radio in Pekalongan City because it does not meet the requirements for determining the frequency channel = Eu> NF, namely the Nuisance Field (NF) value of 109.7 dB is greater than the Minimum Usable Field strength (Eu) of 66 dB. In comparison, Limpung FM Radio gets radio frequency on channel 203 (frequency 107.8 MHz) because it meets the requirements for determining the frequency channel = Eu> NF, namely the Minimum Usable Field strength (Eu) 66 dB greater than the Nuisance Field (NF) of 55.7 dB.
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27

Destexhe, Alain. "Crise économique et financement de la santé." Politique africaine 28, no. 1 (1987): 53–64. http://dx.doi.org/10.3406/polaf.1987.5131.

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La santé a une dimension économique et la crise actuelle appelle une révision des stratégies sanitaires, dans le sens d’une meilleure allocation des ressources. On se trouve devant une alternative cruelle : ou des services gratuits accessibles à tous mais démunis de tout, ou des services partiellement payants susceptibles de fournir un minimum de prestations.
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28

Kaarthik, K., P. T. Sivagurunathan, and S. Sivaranjani. "A REVIEW ON SPECTRUM SENSING METHODS FOR COGNITIVE RADIO NETWORKS." JOURNAL OF ADVANCES IN CHEMISTRY 12, no. 18 (November 16, 2016): 5053–57. http://dx.doi.org/10.24297/jac.v12i18.5380.

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In Wireless Communication, Radio Spectrum is doing a vital role; for the future need it should use efficient. The existing system, it is not possible to use it efficiently where the allocation of spectrum is done based on fixed spectrum access (FSA) policy. Several surveys prove that it show the way to inefficient use of spectrum. An innovative technique is needed for spectrum utilization effectively. Using Dynamic spectrum access (DSA) policy, available spectrum can be exploited. Cognitive radio arises to be an attractive solution which introduces opportunistic usage of the frequency bands that are not commonly occupied by licensed users. Cognitive radios promote open spectrum allocation which is a clear departure from habitual command and control allocation process for radio spectrum usage. In short, it permits the formation of “infrastructure-less” joint network clusters which is called Cognitive Radio Networks (CRN). Conversely the spectrum sensing techniques are needed to detect free spectrum. In this paper, different spectrum sensing techniques are analyzed.
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29

Zhou, Fuhui, Zan Li, Jiangbo Si, Boyang Liu, and Haiyan Huang. "Optimal power allocation for multiple input single output cognitive radios with antenna selection strategies." IET Communications 9, no. 10 (July 2, 2015): 1337–45. http://dx.doi.org/10.1049/iet-com.2014.0939.

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30

Guo, Songtao, Chuangyin Dang, and Xiaofeng Liao. "Distributed resource allocation with fairness for cognitive radios in wireless mobile ad hoc networks." Wireless Networks 17, no. 6 (June 19, 2011): 1493–512. http://dx.doi.org/10.1007/s11276-011-0360-9.

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31

Eghbali, Amir, Håkan Johansson, Per Löwenborg, and Heinz G. Göckler. "Dynamic Frequency-Band Reallocation and Allocation: from Satellite-Based Communication Systems to Cognitive Radios." Journal of Signal Processing Systems 62, no. 2 (February 21, 2009): 187–203. http://dx.doi.org/10.1007/s11265-009-0348-1.

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32

Shiung, David, Ya-Yin Yang, and Chu-Sing Yang. "Transmit Power Allocation for Cognitive Radios Under Rate Protection Constraints: A Signal Coverage Approach." IEEE Transactions on Vehicular Technology 62, no. 8 (October 2013): 3685–99. http://dx.doi.org/10.1109/tvt.2013.2257907.

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33

Etner, Johanna. "Allocation optimale des ressources et préférences à la Selden-Kreps et Porteus." Revue économique 49, no. 4 (1998): 967–87. http://dx.doi.org/10.3406/reco.1998.410026.

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34

Etner, Johanna. "Allocation optimale des ressources et préférences à la Selden-Kreps et Porteus." Revue économique 49, no. 4 (July 1998): 967. http://dx.doi.org/10.2307/3502604.

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35

Lajoie, Andrée. "La macro-allocation des ressources et le droit aux services de santé." Revue de droit. Université de Sherbrooke 20, no. 2 (1990): 231–48. http://dx.doi.org/10.17118/11143/13554.

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36

Etner, Johanna. "Allocation optimale des ressources et préférences à la Selden-Kreps et Porteus." Revue économique 49, no. 4 (July 1, 1998): 967–87. http://dx.doi.org/10.3917/reco.p1998.49n4.0967.

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37

M, Anusha, Srikanth Vemuru, and T. Gunasekhar. "Transmission protocols in Cognitive Radio Mesh Networks." International Journal of Electrical and Computer Engineering (IJECE) 5, no. 6 (December 1, 2015): 1446. http://dx.doi.org/10.11591/ijece.v5i6.pp1446-1451.

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A Cognitive Radio (CR) is a radio that can adjust its transmission limit based on available spectrum in its operational surroundings. Cognitive Radio Network (CRN) is made up of both the licensed users and unlicensed users with CR enable and disabled radios. CR’S supports to access dynamic spectrum and supports secondary user to access underutilized spectrum efficiently, which was allocated to primary users. In CRN’S most of the research was done on spectrum allocation, spectrum sensing and spectrum sharing. In this literature, we present various Medium Access (MAC) protocols of CRN’S. This study would provide an excellent study of MAC strategies.
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38

Silva, Francisco S. S., Andson M. Balieiro, Francisco F. de Mendoça, Kelvin L. Dias, and Paulo Guarda. "A Conformance Testing Methodology and System for Cognitive Radios." Wireless Communications and Mobile Computing 2021 (January 29, 2021): 1–15. http://dx.doi.org/10.1155/2021/8869104.

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The fifth generation (5G) of mobile networks has started its operation in some countries and is aimed at meeting demands beyond the current system capabilities such as the huge amount of connected devices from IoT applications (e.g., smart cities), explosive growth of high-speed mobile data traffic (e.g., ultrahigh definition video streaming), and ultrareliable and low latency communication (e.g., autonomous vehicle). To attend to these needs, the electromagnetic spectrum must be made available, but the static spectrum allocation policy has caused a spectrum shortage and impaired the employment/expansion of the wireless systems. To overcome this issue, the dynamic spectrum access (DSA) has been promoted in 5G/6G networks, which is enabled by the cognitive radio (CR) technology. Although diverse mechanisms have been developed to tackle the challenges that emerge in different CR layers/functionalities, a standardized testing methodology and system for CR is still immature. Existing standards or methodologies and systems for CR only focus on the definition of network technologies (e.g., IEEE 802.22 and IEEE 802.11af), performance evaluation of CR algorithms/mechanisms, or definition of the device cognition level via performance results or psychometric approaches, not covering systems/methodologies to verify if the device meets the CR capabilities and regulatory policies, neglecting the conformance testing. In this respect, this paper proposes a flexible methodology and system for CR conformance testing under two perspectives, functionalities and limits. We instantiate it by using the Universal Software Radio Peripheral (USRP) software-defined radio platform and present a proof-of-concept with a conformance metric. The results show the feasibility of our proposal.
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39

Bakht, Khush, Furqan Jameel, Zain Ali, Wali Ullah Khan, Imran Khan, Guftaar Ahmad Sardar Sidhu, and Jeong Woo Lee. "Power Allocation and User Assignment Scheme for beyond 5G Heterogeneous Networks." Wireless Communications and Mobile Computing 2019 (November 16, 2019): 1–11. http://dx.doi.org/10.1155/2019/2472783.

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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.
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40

Musavian, Leila, and Tho Le-Ngoc. "QoS-based power allocation for cognitive radios with AMC and ARQ in Nakagami-mfading channels." Transactions on Emerging Telecommunications Technologies 27, no. 2 (August 11, 2014): 266–77. http://dx.doi.org/10.1002/ett.2853.

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41

Bergeron, Richard. "La restructuration de l’habitat au Burkina-Faso : un moyen pour la révolution." I. Politiques d’État et stratégies de survie : l’enjeu du logement, no. 17 (December 18, 2015): 43–53. http://dx.doi.org/10.7202/1034367ar.

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Un des moyens d’implanter la révolution au Burkina-Faso (ancienne Haute-Volta) a consisté à restructurer les secteurs d’habitat spontané de la capitale, Ouagadougou, où loge 60 % de la population. Pour résoudre les problèmes d’habitat des couches populaires, le régime burkinabé a misé sur une approche collective au logement, visant à faire émerger une conscience collective de l’habitat. Mais des blocages ont empêché sa stratégie de se réaliser : blocages au point de vue de l’interprétation des objectifs par les résidants, blocages liés à l’ampleur des ressources humaines, techniques et logistiques nécessaires à l’entreprise, mauvaise allocation des ressources, gaspillage. Plus fondamentalement, c’est le projet collectif d’habitat, l’émergence d’une conscience collective de l’habitat, qui risque de ne pouvoir se réaliser : qu’adviendra-t-il de la révolution burkinabé si elle devait échouer sur une composante aussi critique de sa stratégie ?
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42

Gougeon, Patrick. "Assurance et diversification." L'Actualité économique 63, no. 2-3 (January 27, 2009): 187–99. http://dx.doi.org/10.7202/601417ar.

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Résumé Le domaine du risk management se limite traditionnellement aux risques purs, par opposition aux risques spéculatifs qui proviennent des aléas du marché. L’objectif de cet article est de mettre en évidence la perte d’efficience qui peut résulter d’une gestion cloisonnée et indépendante de ces deux catégories de risques. Nous proposons un modèle global, inspiré de l’approche portefeuille, au sein duquel différents types d’actions influençant le niveau de risque de la firme sont envisagées simultanément : allocation des ressources entre plusieurs activités, choix d’une structure financière, achat d’assurance. Ce modèle permet d’étudier les arbitrages entre les différentes modalité de réduction du risque. Des conclusions précises sont énoncées, elles concernent principalement la détermination du budget assurances et son allocation.
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43

Zhang, Er Qing, Si Xing Yin, Liang Yin, and Shu Fang Li. "Energy-Efficient Power Allocation for OFDM-Based Cognitive Radio Networks with Imperfect Spectrum Sensing." Advanced Materials Research 846-847 (November 2013): 635–42. http://dx.doi.org/10.4028/www.scientific.net/amr.846-847.635.

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With the rapid development of wireless network technologies and proliferation of related services such as multimedia applications, demands for wireless spectrum resources keep rising. Cognitive radio (CR) is a novel approach for better utilization of the scarce, already packed but highly underutilized radio spectrum. Meanwhile, exclusive functionalities such as spectrum sensing make energy efficiency (EE) a crucial issue in Cognitive Radios (CRs). In this paper, we focus on the energy-efficient power allocation for OFDM-based CRs with imperfect spectrum sensing. The EE maximization for secondary users (SUs) is formulated as a nonlinear fractional programming problem taking into account imperfect spectrum sensing such as miss detection and false alarm. Then by transforming the original problem into a parameter programming, the optimal power allocation is derived with the bisection search (BS) method and dual decomposition method (DDM). Simulation results illustrate the significant performance improvement of our scheme compared to an existing one with objective of maximizing system throughput rather than EE.
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44

Jagannath, Jithin. "Framework for Federated Learning and Edge Deployment of Real-Time Reinforcement Learning Decision Engine on Software Defined Radio." Proceedings of the AAAI Symposium Series 3, no. 1 (May 20, 2024): 304. http://dx.doi.org/10.1609/aaaiss.v3i1.31218.

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Machine learning promises to empower dynamic resource allocation requirements of Next Generation (NextG) wireless networks including 6G and tactical networks. Recently, we have seen the impact machine learning can make on various aspects of wireless networks. Yet, in most cases, the progress has been limited to simulations and/or relies on large processing units to run the decision engines as opposed to deploying it on the radio at the edge. While relying on simulations for rapid and efficient training of deep reinforcement learning (DRL) may be necessary, it is key to mitigate the sim-real gap while trying to improve the generalization capability. To mitigate these challenges, we developed the Marconi-Rosenblatt Framework for Intelligent Networks (MR-iNet Gym), an open-source architecture designed for accelerating the deployment of novel DRL for NextG wireless networks. To demonstrate its impact, we tackled the problem of distributed frequency and power allocation while emphasizing the generalization capability of DRL decision engine. The end-to-end solution was implemented on the GPU-embedded software-defined radio and validated using over-the-air evaluation. To the best of our knowledge, these were the first instances that established the feasibility of deploying DRL for optimized distributed resource allocation for next-generation of GPU-embedded radios.
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45

MOKHEFI, Amine, and Mohamed AMRANI. "Accroître l'efficacité du marché financier algérien et révision de la politique financière Une option pour sortir de l’économie d’endettement." Dirassat Journal Economic Issue 7, no. 3 (September 1, 2016): 423–33. http://dx.doi.org/10.34118/djei.v7i3.515.

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Le marché financier algérien a pris beaucoup d’ampleur au cours de ces dernières années. Bien que certains facteurs limitent la portée de son évolution, le marché est devenu un moyen de financement qui s’affirme comme le canal par excellence pour une meilleure allocation des ressources. Cette recherche a pour objet de présenter un reflet fidèle de l’évolution du marché financier algérien à travers ses compartiments, ses acteurs et aussi les différentes réformes qui ont été émises. L’accent est mis sur les limites qui continuent à influer sur son développement.
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46

Tlouyamma, Joseph, and Mthulisi Velempini. "Channel Selection Algorithm Optimized for Improved Performance in Cognitive Radio Networks." Wireless Personal Communications 119, no. 4 (April 26, 2021): 3161–78. http://dx.doi.org/10.1007/s11277-021-08392-5.

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AbstractA major concern in the recent past was the traditional static spectrum allocation which gave rise to spectrum underutilization and scarcity in wireless networks. In an attempt to solve this challenge, cognitive radios technology was proposed. It allows a spectrum to be accessed dynamically by Cognitive radio users or secondary users (SU). Dynamic access can efficiently be achieved by making necessary adjustment to some Medium access control (MAC) layer functionalities such as sensing and channel allocation. MAC protocols play a central role in scheduling sensing periods and channel allocation which ensure that the interference is reduced to a tolerable level. In order to improve the accuracy of sensing algorithm, necessary adjustments should be made at MAC layer. Sensing delays and errors are major challenges in the design of a more accurate spectrum sensing algorithm. This study focuses on designing a channel selection algorithm to efficiently utilize the spectrum. Channels are ordered and grouped to allow faster discovery of channel access opportunities. The ordering is based on descending order of channel’s idling probabilities. Grouping of channels ensured that channels are sensed simultaneously. These two techniques greatly reduce delays and maximized throughput of SU. Hence, Extended Generalized Predictive Channel Selection Algorithm, a proposed scheme has significantly performed better than its counterpart (Generalized Predictive Channel Selection Algorithm). Matlab simulation tool was used to simulate and plot the results of the proposed channel selection algorithm.
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47

Alnabelsi, Sharhabeel H., Haythem A. Bany Salameh, and Zaid M. Albataineh. "Dynamic resource allocation for opportunistic software-defined IoT networks: stochastic optimization framework." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 4 (August 1, 2020): 3854. http://dx.doi.org/10.11591/ijece.v10i4.pp3854-3861.

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Several wireless technologies have recently emerged to enable efficient and scalable internet-of-things (IoT) networking. Cognitive radio (CR) technology, enabled by software-defined radios, is considered one of the main IoT-enabling technologies that can provide opportunistic wireless access to a large number of connected IoT devices. An important challenge in this domain is how to dynamically enable IoT transmissions while achieving efficient spectrum usage with a minimum total power consumption under interference and traffic demand uncertainty. Toward this end, we propose a dynamic bandwidth/channel/power allocation algorithm that aims at maximizing the overall network’s throughput while selecting the set of power resulting in the minimum total transmission power. This problem can be formulated as a two-stage binary linear stochastic programming. Because the interference over different channels is a continuous random variable and noting that the interference statistics are highly correlated, a suboptimal sampling solution is proposed. Our proposed algorithm is an adaptive algorithm that is to be periodically conducted over time to consider the changes of the channel and interference conditions. Numerical results indicate that our proposed algorithm significantly increases the number of simultaneous IoT transmissions compared to a typical algorithm, and hence, the achieved throughput is improved.
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48

Rekhissa, Hajer Ben, Cecile Belleudy, and Philippe Bessaguet. "Energy Efficient Resource Allocation for M2M Devices in LTE/LTE-A." Sensors 19, no. 24 (December 4, 2019): 5337. http://dx.doi.org/10.3390/s19245337.

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Machine-to-machine (M2M) communication consists of the communication between intelligent devices without human intervention. Long term evolution (LTE) and Long-term evolution-advanced (LTE-A) cellular networks technologies are excellent candidates to support M2M communication as they offer high data rates, low latencies, high capacities and more flexibility. However, M2M communication over LTE/LTE-A networks faces some challenges. One of these challenges is the management of resource radios especially on the uplink. LTE schedulers should be able to meet the needs of M2M devices, such as power management and the support of large number of devices, in addition to handling both human-to-human (H2H) and M2M communications. Motivated by the fundamental requirement of extending the battery lives of M2M devices and managing an LTE network system, including both M2M devices and H2H users, in this paper, two channel-aware scheduling algorithms on the uplink are proposed. Both of them consider the coexistence of H2H and M2M communications and aim to reduce energy consumption in M2M devices. The first algorithm, called FDPS-carrier-by-carrier modified (CBC-M), takes into account channel quality and power consumption while allocating radio resources. Our second algorithm, recursive maximum expansion modified (RME-M), offers a balance between delay requirement and energy consumption. Depending on the system requirements, RME-M considers both channel quality and system deadlines in an adjustable manner according to M2M devices needs. Simulation results show that the proposed schedulers outperform the round-robin scheduler in terms of energy efficiency and have better cell spectral efficiency.
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Othman, Nurzati Iwani, Ahmad Fadzil Ismail, Khairayu Badron, Wahidah Hashim, and Sofia Pinardi. "Improvements for Uplink Long Term Evolution (UL-LTE) in Heterogeneous Network using Dynamic Spectrum Allocation Technique." International journal of Computer Networks & Communications 14, no. 6 (November 30, 2022): 20–35. http://dx.doi.org/10.5121/ijcnc.2022.14602.

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Several interference mitigation strategies can be used in LTE networks to meet the consumers' increasing need for faster data speeds. Dynamic Spectrum Allocation (DSA), which maintains spectrum in a converged radio system and distributes it across all participating radio terminals, is one of the most promising solutions. However, the fundamental obstacle to achieving increased network capacities is increased inter-cell interference. The aim of this paper is to analyse the effectiveness of a newly proposed DSA technique by comparing its bit error rate (BER) and throughput (TP) with a typical uplink LTE configuration. To maximise throughput in a heterogeneous network, the suggested DSA technique utilises the Nash Bargaining Solution (NBS) scheme, a cooperative game theory that could correlate with the bit error rate. The software tool GNU Radio, which offers signal-processing blocks to develop softwaredefined radios and signal-processing systems, was used to create the setups. After the simulations were performed, the BER values were recorded and compared, while the TP values were established and computed appropriately. According to the results, the uplink (UL-LTE) architecture with DSA has an improved TP and a lower BER value. As a result, spectral efficiency can also be improved.
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50

Mathad, K., and M. Math. "Inference and performance aware multi-channel scheduling and routing scheme with call admission control in wireless mesh networks." International Journal on Information Technologies and Security 15, no. 1 (March 1, 2023): 15–26. http://dx.doi.org/10.59035/xuys3831.

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As wireless mesh networks have been deployed in the urban area, dynamic channel allocation is more challengeable because co-located wireless mediums are likely to be tuned to the same channels and may interfere with communication. Further, existing model doesn’t consider reutilizing routing resource. This paper presents an efficient scheduling and routing model considering an external interference and routing resource reutilization for multi-channel wireless mesh networks. Each mesh node uses a novel technique to estimate the usage status of all the channels within its interference range and assigns channels dynamically to radios to minimize interference within the mesh network and between the mesh network and collocated wireless networks. Simulation results demonstrate that our proposed algorithm can improve the network throughput, reduce packet failure rate and consume more energy while transmission substantially compared to other algorithms by removing the interference overestimation problem and assigning channels aggressively with priority.
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