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Journal articles on the topic 'Spectrum efficiency'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Haddad, M., A. Hayar, and M. Debbah. "Spectral efficiency of spectrum-pooling systems." IET Communications 2, no. 6 (2008): 733. http://dx.doi.org/10.1049/iet-com:20070469.

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2

Mück, Markus, and Christophe GAIE. "The Future of Spectrum Management - Conciliating Spectrum Allocation, Spectral Efficiency and Spectrum Monetization." International Journal of Computational Systems Engineering 7, no. 1 (2022): 1. http://dx.doi.org/10.1504/ijcsyse.2022.10054832.

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3

Gaie, Christophe, and Markus Mueck. "The future of spectrum management - conciliating spectrum allocation, spectral efficiency and spectrum monetisation." International Journal of Computational Systems Engineering 7, no. 1 (2022): 1. http://dx.doi.org/10.1504/ijcsyse.2022.131031.

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4

Kim, Taehan, Hyun-Min Park, and Ki Won Sung. "Measurement of Spectrum Utilization Efficiency Considering Spectrum Sharing." Journal of the Korea Contents Association 14, no. 9 (2014): 589–97. http://dx.doi.org/10.5392/jkca.2014.14.09.589.

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5

Vadim Nozdrin. "Economic efficiency of spectrum allocation." ITU Journal on Future and Evolving Technologies 2, no. 1 (2021): 67–76. http://dx.doi.org/10.52953/mwlm5949.

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Spectrum demand is rapidly expanding, driven by the developments of incumbent radio systems, as well as with the requirements of new technologies and market players to get spectrum access. In this regard, one of the fundamental functions of the state spectrum regulator is to create an enabling administrative and legal environment to ensure efficient spectrum use and to mitigate scarcity of this valuable natural resource. This paper analyses the economic value of spectrum use and suggests an extension of the spectrum's traditional technical boundaries, in order to take into consideration energy

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6

Lee, W. C. Y. "Spectrum efficiency in cellular (radio)." IEEE Transactions on Vehicular Technology 38, no. 2 (1989): 69–75. http://dx.doi.org/10.1109/25.61338.

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7

Freyens, Benoît Pierre, and Oleg Yerokhin. "Allocative vs. technical spectrum efficiency." Telecommunications Policy 35, no. 4 (2011): 291–300. http://dx.doi.org/10.1016/j.telpol.2011.02.002.

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8

Ayeni, A. A. "SPATIAL SPECTRUM UTILIZATION EFFICIENCY METRIC FOR SPECTRUM SHARING SYSTEM." International Journal of Digital Information and Wireless Communications 5, no. 1 (2015): 44–51. http://dx.doi.org/10.17781/p001560.

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9

Kim, Youngju, Taehoon Kwon, and Daesik Hong. "Area Spectral Efficiency of Shared Spectrum Hierarchical Cell Structure Networks." IEEE Transactions on Vehicular Technology 59, no. 8 (2010): 4145–51. http://dx.doi.org/10.1109/tvt.2010.2052938.

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10

Qian, Yi. "Spectrum Efficiency and Energy Efficiency in Wireless Communication Networks." IEEE Wireless Communications 27, no. 5 (2020): 2–3. http://dx.doi.org/10.1109/mwc.2020.9241874.

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11

Hathway, Charlotte. "Spectral Efficiency." New Electronics 53, no. 3 (2020): 27–28. http://dx.doi.org/10.12968/s0047-9624(22)61115-5.

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12

Abdul Hameed Ansari. "Optimizing Spectrum Management Using Advanced Spectrum Sensing Techniques." Panamerican Mathematical Journal 35, no. 2s (2024): 610–25. https://doi.org/10.52783/pmj.v35.i2s.2970.

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The management of spectrum through the advanced techniques within cognitive radio networks (CRN) is vital for detecting vacant spectrum in networks. With the spectrum dearth increasingly encountered in wireless communication systems, the utilization of dynamic spectrum access represents an important strategy for resource management efficiency. Spectrum sensing plays an important role in finding free frequency bands, thus making it possible to use secondary users without affecting excessively the primary user's operations. The paper includes different advanced techniques, such as Noise-Resilien

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13

Stavitsky, Alan G., and Tad Odell. "Spectrum Efficiency and the Public Interest." Journal of Broadcasting & Electronic Media 50, no. 4 (2006): 692–702. http://dx.doi.org/10.1207/s15506878jobem5004_7.

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14

Lu, Zhaohua, Xiaodan Zhang, Huahua Xiao, Dengkui Zhu, and Kun Liu. "Inter-cell spectrum efficiency improvement technology." Physical Communication 9 (December 2013): 272–80. http://dx.doi.org/10.1016/j.phycom.2013.04.003.

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15

YANG, Chun-ping, and Dao-ben LI. "High spectrum efficiency channel encoding method." Journal of China Universities of Posts and Telecommunications 16, no. 3 (2009): 30–44. http://dx.doi.org/10.1016/s1005-8885(08)60223-x.

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16

Rosston, Gregory L. "Increasing the Efficiency of Spectrum Allocation." Review of Industrial Organization 45, no. 3 (2014): 221–43. http://dx.doi.org/10.1007/s11151-014-9431-2.

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17

Ahmadinejad, H., and A. Falahati. "Spectral efficiency in non-terrestrial heterogeneous networks with spectrum underlay access." Physical Communication 46 (June 2021): 101313. http://dx.doi.org/10.1016/j.phycom.2021.101313.

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18

Leem, Cha Sik, Sang Won Kim, Chang-Joo Kim, Sung-Chul Kang, and Jaiyong Lee. "Spectral Efficiency of WRAN Spectrum Overlay in the TV White Space." ETRI Journal 30, no. 6 (2008): 871–73. http://dx.doi.org/10.4218/etrij.08.0208.0204.

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19

Pham, Quoc-Viet, and Won-Joo Hwang. "Fairness-Aware Spectral and Energy Efficiency in Spectrum-Sharing Wireless Networks." IEEE Transactions on Vehicular Technology 66, no. 11 (2017): 10207–19. http://dx.doi.org/10.1109/tvt.2017.2717926.

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20

Tachikawa, Shin-Ichi, and Gen Marubayashi. "Spectral efficiency of M-ary/spread spectrum multiple access communication systems." Electronics and Communications in Japan (Part III: Fundamental Electronic Science) 74, no. 5 (1991): 65–77. http://dx.doi.org/10.1002/ecjc.4430740508.

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21

Weiss, T. A., and F. K. Jondral. "Spectrum pooling: an innovative strategy for the enhancement of spectrum efficiency." IEEE Communications Magazine 42, no. 3 (2004): S8–14. http://dx.doi.org/10.1109/mcom.2004.1273768.

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22

Guo, Junhu, Jinyu Wang, Hui Li, and Yuefeng Ji. "A new asymmetric spectrum assignment method to improve spectrum efficiency for spectrum-sliced optical network." Optical Fiber Technology 19, no. 6 (2013): 565–73. http://dx.doi.org/10.1016/j.yofte.2013.09.001.

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23

Gao, Hui, Min Wang, and Tiejun Lv. "Energy Efficiency and Spectrum Efficiency Tradeoff in the D2D-Enabled HetNet." IEEE Transactions on Vehicular Technology 66, no. 11 (2017): 10583–87. http://dx.doi.org/10.1109/tvt.2017.2754424.

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24

Haas, R., and J. C. Belfiore. "Spectrum efficiency limits in mobile cellular systems." IEEE Transactions on Vehicular Technology 45, no. 1 (1996): 33–40. http://dx.doi.org/10.1109/25.481818.

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25

Rysavy, Peter. "Challenges and Considerations in Defining Spectrum Efficiency." Proceedings of the IEEE 102, no. 3 (2014): 386–92. http://dx.doi.org/10.1109/jproc.2014.2301637.

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26

Cramton, Peter. "The Efficiency of the Fcc Spectrum Auctions." Journal of Law and Economics 41, S2 (1998): 727–36. http://dx.doi.org/10.1086/467410.

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27

Goetzendorff, Andor, Martin Bichler, and Jacob K. Goeree. "Synergistic valuations and efficiency in spectrum auctions." Telecommunications Policy 42, no. 1 (2018): 91–105. http://dx.doi.org/10.1016/j.telpol.2017.08.006.

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28

Dorodnyy, Alexander, Valery Shklover, Leonid Braginsky, Christian Hafner, and Juerg Leuthold. "High-efficiency spectrum splitting for solar photovoltaics." Solar Energy Materials and Solar Cells 136 (May 2015): 120–26. http://dx.doi.org/10.1016/j.solmat.2015.01.005.

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29

Murota, K. "Spectrum efficiency of GMSK land mobile radio." IEEE Transactions on Vehicular Technology 34, no. 2 (1985): 69–75. http://dx.doi.org/10.1109/t-vt.1985.24039.

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30

Szu, Harold H. "Matched filter spectrum shaping for light efficiency." Applied Optics 24, no. 10 (1985): 1426. http://dx.doi.org/10.1364/ao.24.001426.

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31

Linnartz, J. P. M. G. "Spectrum efficiency of radio data system (RDS)." IEEE Transactions on Broadcasting 39, no. 3 (1993): 331–34. http://dx.doi.org/10.1109/11.237712.

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32

SUZUKI, S. "Optimum Wavelength Filter Spectrum Response in DWDM Systems for Ultimate Spectral Efficiency." IEICE Transactions on Communications E88-B, no. 9 (2005): 3649–59. http://dx.doi.org/10.1093/ietcom/e88-b.9.3649.

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33

Saha, Rony Kumer. "Countrywide Mobile Spectrum Sharing with Small Indoor Cells for Massive Spectral and Energy Efficiencies in 5G and Beyond Mobile Networks." Energies 12, no. 20 (2019): 3825. http://dx.doi.org/10.3390/en12203825.

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In this paper, we propose a technique to share the licensed spectrums of all mobile network operators (MNOs) of a country with in-building small cells per MNO by exploiting the external wall penetration loss of a building and introducing the time-domain eICIC technique. The proposed technique considers allocating the dedicated spectrum Bop per MNO only its to outdoor macro UEs, whereas the total spectrum of all MNOs of the country Bco to its small cells indoor per building such that technically any small indoor cell of an MNO can have access to Bco instead of merely Bop assigned only to the MN

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34

Shaghluf, Nagwa, and T. Aaron Gulliver. "Spectrum and energy efficiency of cooperative spectrum prediction in cognitive radio networks." Wireless Networks 25, no. 6 (2018): 3265–74. http://dx.doi.org/10.1007/s11276-018-1720-5.

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35

Hassan, Mohamed, Manwinder Singh, Khalid Hamid, et al. "Enhancing NOMA’s Spectrum Efficiency in a 5G Network through Cooperative Spectrum Sharing." Electronics 12, no. 4 (2023): 815. http://dx.doi.org/10.3390/electronics12040815.

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Non-orthogonal multiple access (NOMA) is one of the most effective techniques for meeting the spectrum efficiency (SE) requirements of 5G and beyond networks. This paper presents two novel methods for improving the SE of the downlink (DL) NOMA power domain (PD) integrated with a cooperative cognitive radio network (CCRN) in a 5G network using single-input and single-output (SISO), multiple-input and multiple-output (MIMO), and massive MIMO (M-MIMO) in the same network and in a single cell. In the first method, NOMA users compete for free channels in a competing channel (C-CH) on the CCRN. The

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36

Saha, Rony Kumer. "Realization of Licensed/Unlicensed Spectrum Sharing Using eICIC in Indoor Small Cells for High Spectral and Energy Efficiencies of 5G Networks." Energies 12, no. 14 (2019): 2828. http://dx.doi.org/10.3390/en12142828.

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In this paper, we show how to realize numerous spectrum licensing policies by means of time-domain enhanced inter-cell interference coordination (eICIC) technique to share both the licensed and unlicensed spectrums with small cells in order to address the increasing demand of capacity, spectral efficiency, and energy efficiency of future mobile networks. Small cells are deployed only in 3-dimensional (3D) buildings within a macrocell coverage of a mobile network operator (MNO). We exploit the external wall penetration loss of each building to realize traditional dedicated access, co-primary sh

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37

Soloviov, S. O., I. V. Dziublyk, and V. V. Trokhymchuk. "Bioinformation analysis of rotavirus vaccine efficiency." Farmatsevtychnyi zhurnal, no. 5-6 (February 12, 2019): 97–104. http://dx.doi.org/10.32352/0367-3057.5-6.18.8.

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A couple of studies have shown that viruses cause from 25 to 60% of acute intestinal infections (AII) cases, among which rotaviruses play a leading role in the structure of children's AII of viral etiology. According to the WHO recommendations, vaccination against rotavirus infection should be included into national immunization programs. Due to a wide diversity of circulating rotavirus genotypes, the issue of RVI vaccine efficiency, taking into account the dynamics of the molecular-genetic spectrum of RVI pathogens over time, remains relevant. The aim of the work – мodeling the dynamics

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38

Sathya, K., B. K. AnuPreethi, and V. Vijayaraghavan. "Analysis of Energy Efficiency for Cognitive Radio Networks." Asian Journal of Electrical Sciences 4, no. 2 (2015): 1–3. http://dx.doi.org/10.51983/ajes-2015.4.2.1952.

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CR-based technology aims to combat scarcity in the radio spectrum using dynamic spectrum access (DSA).It improves the performance of spectrum efficiency by allowing secondary users to share the spectrum owned by primary users. In this paper, different techniques have been analyzed to improve the energy efficiency of a CRNs.Gradient based iteration algorithm is used to obtain the Stackelberg equilibrium solution. Water filling factors aided search method deals with the Energy Efficient optimization problem with multiple interference power constraint. Efficient barrier method is used to provide

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39

Jaronde, Pravin, Archana Vyas, and Mahendra Gaikwad. "Spectrum Efficient Cognitive Radio Sensor Network for IoT with Low Energy Consumption." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 11s (2023): 469–79. http://dx.doi.org/10.17762/ijritcc.v11i11s.8176.

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Cognitive Radio Sensor Networks (CRSNs) have emerged as a promising solution for efficient utilization of the limited frequency spectrum. One of the key challenges in CRSNs is achieving spectrum efficiency by avoiding interference and maximizing the use of the available spectrum. Particle Swarm Optimization (PSO) techniques have been widely used to optimize the spectrum allocation and improve the spectrum efficiency of CRSNs. In this paper the study provides an overview of the research on spectrum efficiency in CRSNs using PSO techniques and also discussed the key parameters that affect the sp

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40

Ibrahim, Misbah, Ahmed Al Muyeed Syed, Kundu Babuya Soumik, Mehtanin Khabir Kanij, and Shafiqul Islam Md. "Study on the Absorption and Scattering Efficiencies of the Cadmium Telluride Nanowire." International Journal of Advances in Materials Science and Engineering (IJAMSE) 4, October (2015): 23–29. https://doi.org/10.5281/zenodo.3342035.

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The optical properties of cadmium telluride nanowires have been simulated using the Mie scattering coefficients. It is seen that the absorption efficiency shows multiple peaks along the spectrum due to leaky mode resonance. The nanowires showed strong polarization dependence in smaller radius. Higher angle of incidence showed a suppressing effect on lower valued peaks on absorption efficiency. Scattering efficiency showed peaks at visible spectrum from 30nm to 100nm. Transverse magnetic wave showed a more pronounced effect in scattering than transverse electric wave.

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41

Gmira, Sara, Abdellatif Kobbane, Jalel Ben-Othman, and Mouna El Machkour. "A New Energy Efficiency/Spectrum Efficiency Model for Cooperative Cognitive Radio Network." Mobile Networks and Applications 23, no. 5 (2018): 1436–48. http://dx.doi.org/10.1007/s11036-018-1078-z.

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42

Byun, Hee Sub, and Kwon-Hum Yeon. "Evaluation of the Economic Efficiency of the Spectrum: Focusing on Productive Efficiency." Journal of Korean Institute of Electromagnetic Engineering and Science 33, no. 6 (2022): 477–88. http://dx.doi.org/10.5515/kjkiees.2022.33.6.477.

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43

Li, Feilong, Zhiqiang Li, Guangxia Li, Feihong Dong, and Wei Zhang. "Efficient Wideband Spectrum Sensing with Maximal Spectral Efficiency for LEO Mobile Satellite Systems." Sensors 17, no. 12 (2017): 193. http://dx.doi.org/10.3390/s17010193.

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44

Bystrom, M., and J. W. Modestino. "A general scheme for spectral efficiency evaluation of direct-sequence spread-spectrum systems." IEEE Transactions on Communications 49, no. 7 (2001): 1142–44. http://dx.doi.org/10.1109/26.935152.

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45

Padarthi, Krishna Kishore, Venkata Tarun Mantripragadi, Nitish Panchakshari, and Dr M. V. Nageswara Rao. "Spectral Efficiency Improvement Techniques in OFDM and UFMC." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (2022): 409–17. http://dx.doi.org/10.22214/ijraset.2022.42172.

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Abstract: This article describes about to analyse the spectral efficiency of different modulation techniques in OFDM and UFMC. UFMC is a multi-carrier modulation technique in fifth generation network (5G). In this paper, we review the different modulation techniques in 5G technology and motivate the need of UFMC technique in 5G wireless communication. In 4G OFDM modulation technique, some drawbacks like side band leakages, high Peak to Average Power ratio (PAPR) and spectrum utilization degrades the performance of the system. Another multi carrier technique called Filter Bank Multi carrier (FB

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46

Saha, Rony Kumer. "On Exploiting Millimeter-Wave Spectrum Trading in Countrywide Mobile Network Operators for High Spectral and Energy Efficiencies in 5G/6G Era." Sensors 20, no. 12 (2020): 3495. http://dx.doi.org/10.3390/s20123495.

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In this paper, we propose a dynamic exclusive-use spectrum access (DESA) method to improve the overall licensed millimeter-wave (mmWave) spectrum utilization of all mobile network operators (MNOs) in a country. By exploiting secondary spectrum trading, the proposed DESA method shares partly and exclusively the licensed mmWave spectrum of one MNO to another in a dynamic and on-demand basis for a certain agreement term. We formulate the proposed DESA method for an arbitrary number of MNOs in a country. We then present an iterative algorithm to find the optimal amount of shared spectrum for each

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47

Olanrewaju, B. S. "Survey of Related Technologies for Improved Spectrum Efficiency." IOSR Journal of Engineering 02, no. 11 (2012): 25–33. http://dx.doi.org/10.9790/3021-021122533.

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48

Iyer, Sridhar. "Power-Efficiency Comparison of Spectrum-Efficient Optical Networks." International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems 5, no. 3 (2016): 166. http://dx.doi.org/10.11601/ijates.v5i3.221.

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With steady traffic volume growth in the core networks, it is predicted that the future optical network communication will be constrained mainly by the power consumption. Hence, for future internet sustainability, it will be a mandate to ensure power-efficiency in the optical networks. Two paradigms known to support both, the traffic heterogeneity and high bandwidth requests are the: (i) next generation flexible (or elastic) orthogonal frequency division multiplexing (OFDM) based networks which provide flexible bandwidth allocation per wavelength, and (ii) currently deployed mixed-line-rate (M

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49

Wildman, Steven S., Johannes M. Bauer, and Carol Ting. "Spectrum governance regimes: efficiency properties and policy choices." info 8, no. 2 (2006): 83–96. http://dx.doi.org/10.1108/14636690610653617.

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50

Holland, Oliver, A. Hamid Aghvami, Terence E. Dodgson, and Hanna Bogucka. "Intra-operator dynamic spectrum management for energy efficiency." IEEE Communications Magazine 50, no. 9 (2012): 178–84. http://dx.doi.org/10.1109/mcom.2012.6295730.

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