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Journal articles on the topic 'Multi-radio'

Author: Grafiati

Published: 4 June 2021

Last updated: 2 May 2022

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1

Kim, Jong-Duk, and Toung-Kil Kim. "A Study of Multi-Channel Internet Radio Platform." Journal of the Korean Institute of Information and Communication Engineering 14, no. 7 (July 30, 2010): 1723–28. http://dx.doi.org/10.6109/jkiice.2010.14.7.1723.

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2

Han, Bin, Ying Luo, Min Zeng, and Hong Jiang. "Spectrum-Efficient Resource Allocation in Multi-Radio Multi-Hop Cognitive Radio Networks." Sensors 19, no. 20 (October 16, 2019): 4493. http://dx.doi.org/10.3390/s19204493.

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The multi-hop cognitive radio network (CRN) has attracted much attention in industry and academia because of its seamless wireless coverage by forming multi-hop links and high spectrum utilization of cognitive radio (CR) technology. Using multi-slot statistical spectrum status information (SSI), this work investigates the average spectrum efficiency (SE) of a multi-radio multi-hop (MRMH) CRN where each hop is permitted to use different spectra and long-distance hops can reuse the same idle primary user (PU) spectrum. Faced with the modeled SE problem, which is a complex non-convex fractional mixed integer nonlinear programming (MINLP) problem, the optimal spectrum and power allocation for multi-hop links in multi-slot and multi-channel scenarios can be obtained with the proposed successive multi-step convex approximation scheme (SMCA). As shown through computational complexity and simulation analysis, SMCA can obtain an approximate lower bound of the optimal solution for the modeled SE problem with a lower computational cost. Furthermore, some potential relationships between network performance and spectrum idle rate can be easily discussed with SMCA, which can provide some sensible deployment strategies for the MRMH CRN in future multi-slot scenarios.

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3

Chen, Lin, Kaigui Bian, Xiaohu Ge, Wei Chen, Qingsong Ai, and Kehao Wang. "Multi-radio channel rendezvous in cognitive radio networks." IET Communications 13, no. 10 (June 25, 2019): 1433–42. http://dx.doi.org/10.1049/iet-com.2018.5956.

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4

Khan, Tanvir Ahmed, and A. B. M. Alim Al Islam. "Enhancing throughput in multi-radio cognitive radio networks." Wireless Networks 25, no. 7 (August 5, 2019): 4383–402. http://dx.doi.org/10.1007/s11276-019-02103-6.

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5

Wei, Liu. "The Analysis of Single-Radio Mode, Dual-Radio Mode and Multi-Radio Mode WMN’s Capacity." Applied Mechanics and Materials 182-183 (June 2012): 2045–49. http://dx.doi.org/10.4028/www.scientific.net/amm.182-183.2045.

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WMN is the abbreviations of Wireless mesh networks. Along with the evolution of WMN, there appears single-radio mode WMN ,dual-radio mode WMN ,multi-radio mode WMN and their mixed mode WMN. Single-radio mode WMN network has the lowest capacity and the lowest cost, dual-radio and multi-radio mode WMN are better than single-radio mode WMN, multi-radio mode WMN has the largest bandwidth and flexibility, and has obtained the large-scale application.

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6

Mack, K. H., U. Klein, C. P. O'Dea, and A. G. Willis. "Multi-frequency radio continuum mapping of giant radio galaxies." Astronomy and Astrophysics Supplement Series 123, no. 3 (June 1997): 423–44. http://dx.doi.org/10.1051/aas:1997166.

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7

Orlov, V. V., O. A. Lytvynenko, and V. V, Galanin. "MULTI-FREQUENCY RADIO INTERFEROMETRY ALGORITHM." Odessa Astronomical Publications 32 (October 27, 2019): 100–102. http://dx.doi.org/10.18524/1810-4215.2019.32.181776.

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8

Sigle, Rolf, Oliver Blume, Lutz Ewe, and Wieslawa Wajda. "Multi-radio infrastructure for 4G." Bell Labs Technical Journal 13, no. 4 (February 25, 2009): 257–76. http://dx.doi.org/10.1002/bltj.20348.

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9

Kloeck, Clemens, Holger Jaekel, and Friedrich Jondral. "Multi-Agent Radio Resource Allocation." Mobile Networks and Applications 11, no. 6 (December 2006): 813–24. http://dx.doi.org/10.1007/s11036-006-0051-4.

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10

Fokin, G. "Modeling multi-beam radio channel." Telecom IT 9, no. 1 (March 31, 2021): 59–78. http://dx.doi.org/10.31854/2307-1303-2021-9-1-59-78.

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In this work, a simulation model of a radio channel with fading is implemented for use in research of the multipath channel, as well as for assessing the noise immunity of transmission, recep-tion and processing systems in modern and future mobile communication and radio access networks. Formalization of mathematical models of a radio channel with fading, including the Rayleigh amplitude distribution, uniform phase distribution and a given Doppler spectrum, made it possible to visualize the time-frequency and probabilistic characteristics of a radio channel with fading. The implementation of the procedures for delaying and attenuating copies of signals in a multipath radio channel made it pos-sible to reproduce scenarios of flat and frequency selective fading, which are widely used in practice in assessing the noise immunity of signals with given frequency and time characteristics.

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11

Krainy, V., and A. Semenov. "Creation of 3-D Object Radio Images Using Multi-Frequency Multi-static Radio-hologram." Radiooptics Scientific Journal 16, no. 05 (September 3, 2016): 1–10. http://dx.doi.org/10.7463/rdopt.0516.0848109.

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12

Zhong, Xiaoxiong, Yang Qin, and Li Li. "Capacity Analysis in Multi-Radio Multi-Channel Cognitive Radio Networks: A Small World Perspective." Wireless Personal Communications 79, no. 3 (August 3, 2014): 2209–25. http://dx.doi.org/10.1007/s11277-014-1981-y.

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13

Zeng, Kai, Zhenyu Yang, and Wenjing Lou. "Opportunistic Routing in Multi-Radio Multi-Channel Multi-Hop Wireless Networks." IEEE Transactions on Wireless Communications 9, no. 11 (November 2010): 3512–21. http://dx.doi.org/10.1109/twc.2010.092410.100118.

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14

Campolo, Claudia, Lin Cheng, Christoph Sommer, and Hsin-Mu (Michael) Tsai. "Special Issue on Multi-radio, Multi-technology, Multi-system Vehicular Communications." Computer Communications 93 (November 2016): 1–2. http://dx.doi.org/10.1016/j.comcom.2016.09.003.

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15

Nonchev, Stanislav, and Mikko Valkama. "ADVANCED RADIO RESOURCE MANAGEMENT FOR MULTI ANTENNA PACKET RADIO SYSTEMS." International Journal of Wireless & Mobile Networks 2, no. 2 (May 10, 2010): 1–14. http://dx.doi.org/10.5121/ijwmn.2010.2201.

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16

Lin, Tzu-Hsiang, Guu-Chang Yang, and Wing C. Kwong. "A Homogeneous Multi-Radio Rendezvous Algorithm for Cognitive Radio Networks." IEEE Communications Letters 23, no. 4 (April 2019): 736–39. http://dx.doi.org/10.1109/lcomm.2019.2903458.

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17

P.L, Shreenidhi, Ranganath H R, Puttamadappa C, and Basavaraju T G. "Dynamic Channel Allocation Technique for Distributed Multi-radio Multichannel Multi-path Routing Protocol in Wireless Mesh Networks." International Journal of Engineering Research 3, no. 12 (December 1, 2014): 730–36. http://dx.doi.org/10.17950/ijer/v3s12/1205.

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18

Rando, Gaetano. "Multi-Lingual Radio in South Australia." Media Information Australia 35, no. 1 (February 1985): 41–48. http://dx.doi.org/10.1177/1329878x8503500108.

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19

Shue, Ming‐Jeng. "Multi‐functional radio/wire stethoscopic apparatus." Journal of the Acoustical Society of America 84, no. 5 (November 1988): 1968. http://dx.doi.org/10.1121/1.397079.

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20

Miu, Allen, Hari Balakrishnan, and Can Emre Koksal. "Multi-radio diversity in wireless networks." Wireless Networks 13, no. 6 (October 23, 2006): 779–98. http://dx.doi.org/10.1007/s11276-006-9854-2.

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21

Sidi, Moshe, and Israel Cidon. "A Multi-station packet-radio network." Performance Evaluation 8, no. 1 (February 1988): 65–72. http://dx.doi.org/10.1016/0166-5316(88)90013-2.

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22

Li, Ming, Sergio Salinas, Pan Li, Xiaoxia Huang, Yuguang Fang, and Savo Glisic. "Optimal Scheduling for Multi-Radio Multi-Channel Multi-Hop Cognitive Cellular Networks." IEEE Transactions on Mobile Computing 14, no. 1 (January 1, 2015): 139–54. http://dx.doi.org/10.1109/tmc.2014.2314107.

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23

Farzinvash, Leili, and Mehdi Dehghan. "Multi-rate multicast routing in multi-gateway multi-channel multi-radio wireless mesh networks." Journal of Network and Computer Applications 40 (April 2014): 46–60. http://dx.doi.org/10.1016/j.jnca.2013.08.009.

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24

Bhutto, Zuhaibuddin, Jun-Hyuk Park, and Wonyong Yoon. "Characterizing Multi-radio Energy Consumption in Cellular/Wi-Fi Smartphones." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 6 (December 1, 2016): 2920. http://dx.doi.org/10.11591/ijece.v6i6.11916.

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<p>Cellular networks evolved to meet the ever increasing traffic demand by way of offloading mobile traffic to Wi-Fi network elements. Exploiting multi-radio interfaces on a smartphone has recently been examined with regards to heterogeneous bandwidth aggregation and radio switching. However, how a smartphone consumes its energy in driving cellular and Wi-Fi multi-radio interfaces, is not well understood. In this paper, we revealed the energy consumption behavior of 3G cellular and Wi-Fi multi-radio operations of a smartphone. We modified smartphone’s firmware to enable multi-radios operations simultaneously and we performed extensive measurements of multi-radio energy consumption in a real commercial network. From the measured data set, we established a realistic multi-radio energy consumption model and it gave 98% stability from the derived coefficients.</p>

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25

Bhutto, Zuhaibuddin, Jun-Hyuk Park, and Wonyong Yoon. "Characterizing Multi-radio Energy Consumption in Cellular/Wi-Fi Smartphones." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 6 (December 1, 2016): 2920. http://dx.doi.org/10.11591/ijece.v6i6.pp2920-2930.

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<p>Cellular networks evolved to meet the ever increasing traffic demand by way of offloading mobile traffic to Wi-Fi network elements. Exploiting multi-radio interfaces on a smartphone has recently been examined with regards to heterogeneous bandwidth aggregation and radio switching. However, how a smartphone consumes its energy in driving cellular and Wi-Fi multi-radio interfaces, is not well understood. In this paper, we revealed the energy consumption behavior of 3G cellular and Wi-Fi multi-radio operations of a smartphone. We modified smartphone’s firmware to enable multi-radios operations simultaneously and we performed extensive measurements of multi-radio energy consumption in a real commercial network. From the measured data set, we established a realistic multi-radio energy consumption model and it gave 98% stability from the derived coefficients.</p>

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26

Shin, Jung-Chae, Seung-Hwa Min, Ho-Shin Cho, and Youn-Seon Jang. "Efficient Radio Resource Allocation for Cognitive Radio Based Multi-hop Systems." Journal of Korean Institute of Communications and Information Sciences 37, no. 5A (May 30, 2012): 325–38. http://dx.doi.org/10.7840/kics.2012.37a.5.325.

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27

Chao, Chih-Min, Chia-Tsun Chen, and Hsin-Chung Huang. "An adjustable channel hopping algorithm for multi-radio cognitive radio networks." Computer Networks 170 (April 2020): 107107. http://dx.doi.org/10.1016/j.comnet.2020.107107.

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28

Islam, Md Tahidul, Sithamparanathan Kandeepan, and Robin J. Evans. "Multi-Radio Based Rendezvous Technique for Heterogeneous Cognitive Radio Sensor Network." Sensors 21, no. 9 (April 24, 2021): 2997. http://dx.doi.org/10.3390/s21092997.

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In a distributed cognitive radio (CR) sensor network, transmission and reception on vacant channels require cognitive radio nodes to achieve rendezvous. Because of the lack of adequate assistance from the network environment, such as the central controller and other nodes, assisted rendezvous for distributed CR is inefficient in a dynamic network. As a result, non-assisted blind rendezvous, which is unaware of its counterpart node, has recently led to a lot of interest in the research arena. In this paper, we study a channel rendezvous method based on prime number theory and propose a new multi-radio-based technique for non-assisted rendezvous with the blind and heterogeneous condition. The required time and the optimal number of radios for the guaranteed rendezvous are calculated using probability-based measurement. Analytical expressions for probabilistic guaranteed rendezvous conditions are derived and verified by Monte Carlo simulation. In addition, the maximum time to rendezvous (MTTR) is derived in closed form using statistical and probabilistic analysis. Under different channel conditions, our proposed solution leads to a substantial time reduction for guaranteed rendezvous. For the sake of over-performance of our proposed system, the simulation outcome is compared to a recently proposed heterogeneous and blind rendezvous method. The Matlab simulation results show that our proposed system’s MTTR gains range from 11% to over 95% for various parametric values of the system model.

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29

Varatharajan, R., Angelin Peace Preethi, Gunasekaran Manogaran, Priyan Malarvizhi Kumar, and Revathi Sundarasekar. "Stealthy attack detection in multi-channel multi-radio wireless networks." Multimedia Tools and Applications 77, no. 14 (March 28, 2018): 18503–26. http://dx.doi.org/10.1007/s11042-018-5866-z.

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30

Alabady, Salah Abdulghani, and Mohd Fadzli Mohd Salleh. "Wireless Network Coding for Multi Radio Multi Channel Mesh Networks." Wireless Personal Communications 106, no. 3 (March 9, 2019): 1629–47. http://dx.doi.org/10.1007/s11277-019-06233-0.

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31

Pan, Cunhua, Jiangzhou Wang, Wence Zhang, Bo Du, and Ming Chen. "Power Minimization in Multi-Band Multi-Antenna Cognitive Radio Networks." IEEE Transactions on Wireless Communications 13, no. 9 (September 2014): 5056–69. http://dx.doi.org/10.1109/twc.2014.2329296.

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32

Song, Min, Jun Wang, Kai Xing, and E. Park. "Interference-aware broadcasting in multi-radio multi-channel mesh networks." IEEE Transactions on Wireless Communications 7, no. 12 (December 2008): 5473–81. http://dx.doi.org/10.1109/t-wc.2008.071433.

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33

Liu, Tehuang, and Wanjiun Liao. "Multicast Routing in Multi-Radio Multi-Channel Wireless Mesh Networks." IEEE Transactions on Wireless Communications 9, no. 10 (October 2010): 3031–39. http://dx.doi.org/10.1109/twc.2010.082310.090568.

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34

Wan, Pengjun, and Zhi-Guo Wan. "Maximizing Networking Capacity in Multi-Channel Multi-Radio Wireless Networks." Journal of Computer Science and Technology 29, no. 5 (September 2014): 901–9. http://dx.doi.org/10.1007/s11390-014-1477-y.

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35

Mao, XuFei, Xiang-Yang Li, and GuoJun Dai. "Flow admission control for multi-channel multi-radio wireless networks." Wireless Networks 17, no. 3 (December 25, 2010): 779–96. http://dx.doi.org/10.1007/s11276-010-0314-7.

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36

Deng, Zhongliang, Xiaoyi Yu, Wenliang Lin, Ke Wang, Hao Liu, Lei Gu, Yang Liu, and Xiaojuan Ma. "A Multi-Beam Satellite Cooperative Transmission Scheme Based on Resources Optimization and Packets Segmentation." Electronics 10, no. 22 (November 18, 2021): 2841. http://dx.doi.org/10.3390/electronics10222841.

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Multi-beam satellite communication systems are promising architectures in the future. A packet is transmitted by multi-satellite and multi-beam cooperatively, which can provide efficient spectrum utilization, improve system throughput, and guarantee Quality of Services (QoS). In multi-beam satellite communication systems, multi-layer and multi-dimensional radio resources change dynamically, which leads to the discontinuity of optimal resources and the lack of mapping balance between packets and radio resources. To deal with these problems, we propose a cross-layer and cross-dimension radio resources optimization model based on the weighted discrete firefly algorithm and an adaptive packet segmentation scheme based on the irregular gradient algorithm. The cross-layer and cross-dimension radio resources optimization model based on the weighted discrete firefly algorithm simulates cross-layer and cross-dimension optimization for the high-dynamic and multi-dimensional radio resources by considering the channel state information (CSI) and QoS in the multi-beam satellite communication system. The optimal resources are taken as the weight of irregular gradient algorithm to segment packets and map packets to radio resources, which can realize the mapping balance between packets and radio resources and ensure the efficiency and reliability of communication. The simulations show that the new transmission scheme improves the normalized system throughput and user satisfaction index by 18.7% and 6.2%, respectively.

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37

P.L,, Shreenidhi, and Puttamadappa C. "Distributed Efficient Channel Allocation Technique for Multi-Radio Multichannel Interference-aware Multi-path Routing Protocol in Wireless Mesh Networks." International Journal of Engineering Research 4, no. 8 (August 1, 2015): 426–32. http://dx.doi.org/10.17950/ijer/v4s8/805.

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38

Feng, Wei, Jiannong Cao, Chisheng Zhang, Jun Zhang, and Qin Xin. "Coordination of multi-link spectrum handoff in multi-radio multi-hop cognitive networks." Journal of Parallel and Distributed Computing 72, no. 4 (April 2012): 613–25. http://dx.doi.org/10.1016/j.jpdc.2011.11.004.

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39

Sasikumar, Silpa, and Preeti Kharb. "Looking at radio-quiet AGN with radio polarimetry." Acta Astrophysica Taurica 3, no. 1 (March 14, 2022): 17–22. http://dx.doi.org/10.31059/aat.vol3.iss1.pp17-22.

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The dominant radio emission mechanism in radio-quiet quasars (RQQs) is an open question. Primary contenders include: low-power radio jets, winds, star-formation and coronal emission. Our work suggests that radio polarization and emission-line studies can help to distinguish between these scenarios and determine the primary contributor. Our multi-frequency, multi-scale radio polarization study has revealed a composite jet and "wind" radio outflow in the radio-intermediate quasar, III Zw 2, as well as in the BALQSO, Mrk 231. Our radio polarization study in conjunction with the [O III] emission-line study of five type 2 RQQs have provided insights on the interplay of jets/winds and emission-line gas. These sources reveal an anti-correlation between polarized radio emission and [O III] emission. This is similar to that observed in some radio-loud active galactic nuclei (AGN) in the literature and suggests that the radio emission could be depolarized by the emission-line gas. Overall, our work suggests that a close interaction between the radio outflow and the surrounding gaseous environment is likely to be responsible for their stunted form in RQ and RI AGN.

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40

Parvin, S., and T. Fujii. "Radio environment aware stable routing scheme for multi-hop cognitive radio network." IET Networks 1, no. 4 (December 1, 2012): 207–16. http://dx.doi.org/10.1049/iet-net.2012.0103.

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41

Blundell, Katherine M., and Mark Lacy. "A multi-radio-frequency study of the radio-quiet quasar E1821+643." Monthly Notices of the Royal Astronomical Society 274, no. 1 (May 1995): L9—L13. http://dx.doi.org/10.1093/mnras/274.1.l9.

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42

Chang, Yeh-Cheng, Cheng-Shang Chang, and Jang-Ping Sheu. "An Enhanced Fast Multi-Radio Rendezvous Algorithm in Heterogeneous Cognitive Radio Networks." IEEE Transactions on Cognitive Communications and Networking 4, no. 4 (December 2018): 847–59. http://dx.doi.org/10.1109/tccn.2018.2871208.

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43

Wu, Hsin-Te, and Mu-Yen Chen. "A multi-function wearable radio transceiver device based on radio communication technology." Computers & Electrical Engineering 91 (May 2021): 107062. http://dx.doi.org/10.1016/j.compeleceng.2021.107062.

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44

Eie, Sujin, Toshio Terasawa, Takuya Akahori, Tomoaki Oyama, Tomoya Hirota, Yoshinori Yonekura, Teruaki Enoto, et al. "Multi-frequency radio observations of the radio-loud magnetar XTE J1810−197." Publications of the Astronomical Society of Japan 73, no. 6 (November 2, 2021): 1563–74. http://dx.doi.org/10.1093/pasj/psab098.

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Abstract We report on the multi-frequency multi-epoch radio observations of the magnetar XTE J1810−197, which exhibited a radio outburst from 2018 December after its 10-year quiescent period. We performed quasi-simultaneous observations with VERA (22 GHz), Hitachi (6.9 GHz and 8.4 GHz), Kashima (2.3 GHz), and Iitate (0.3 GHz) radio telescopes located in Japan to trace the variability of the magnetar radio pulsations during the observing period from 2018 December 13 to 2019 June 12. The pulse width becomes narrower as the observing frequency goes higher, analogous to the general profile narrowing behavior of ordinary pulsars. When assuming a simple power law in the range of 2.3 GHz and 8.7 GHz, the radio spectrum of the magnetar goes steeper with the average spectral index 〈α〉 ≈ −0.85 for the first four months. The wide-band radio spectra gathered from our observations and the literature suggest that XTE J1810−197 would have a double-peaked spectrum with a valley point in 22–150 GHz, where the first spectral peak implies a gigahertz-peaked spectrum (GPS) feature with a peak at a few GHz. The GPS and the high-frequency peak have been identified in the spectra of other radio-loud magnetars, thus they may be intrinsic features that can give a new insight to the understanding of various emission mechanisms and the surrounding environments of radio magnetars. Our study emphasizes the importance of simultaneous long-term broad-band observations toward radio-loud magnetars to capture the puzzling spectral features and establish a link to other types of neutron stars.

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45

Czumaj, Artur, and Peter Davies. "Leader election in multi-hop radio networks." Theoretical Computer Science 792 (November 2019): 2–11. http://dx.doi.org/10.1016/j.tcs.2019.02.027.

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46

Diet, Antoine M., Nicolas Ribière-Tharaud, Martine Villegas, and Geneviève Baudoin. "Front-end HPA/antenna for multi-radio." International Journal of Microwave and Wireless Technologies 4, no. 5 (May 1, 2012): 483–93. http://dx.doi.org/10.1017/s1759078712000372.

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This paper focuses on multi-radio front-end transmitter, a function implied by cognitive radio (0.5–6 GHz). S and C bands standards (wireless local and metropolitan area networks) present a challenge, due to the signal modulation schemes (orthogonal frequency division multiplex (OFDM)/WCDMA, wideband code division multiple access) dynamic (tens of dBs), driving us to a mandatory transmitter linearization. The idea is to provide frequency, flexibility, and average power control of a multi-radio high-efficiency front end for such signals (polar/envelope elimination and restoration (EER) structure). The study implies antennas design and average power control demonstration. Based on a switched mode power amplifier (PA), a discrete detuning is possible to adapt the PA at both “WiMAX” and “Wifi5” frequencies. This architecture amplifies signals with amplitude information. This is coded here by the ΣΔ/PWM (pulse width modulation) technique, to present a constant envelope signal. The amplitude information is restored by a pass-band radio frequency (RF) filter. The antenna can be designed with a notch, to reduce the filtering constraints (selectivity and standards coexistences) and to help in the restoration of amplitude information. Average power control is illustrated by voltage supply variation and results are a possible dynamic of 9.5 dB. To complete the analysis, the simulation of the propagation channel, including antennas, with CST (free space, line of sight) is imported under AGILENT-ADS.

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47

Angelakis, E., L. Fuhrmann, I. Myserlis, J. A. Zensus, I. Nestoras, V. Karamanavis, N. Marchili, T. P. Krichbaum, A. Kraus, and J. P. Rachen. "F-GAMMA: Multi-frequency radio monitoring ofFermiblazars." Astronomy & Astrophysics 626 (June 2019): A60. http://dx.doi.org/10.1051/0004-6361/201834363.

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Context. The advent of theFermigamma-ray space telescope with its superb sensitivity, energy range, and unprecedented capability to monitor the entire 4πsky within less than 2–3 h, introduced a new standard in time domain gamma-ray astronomy. Among several breakthroughs,Fermihas – for the first time – made it possible to investigate, with high cadence, the variability of the broadband spectral energy distribution (SED), especially for active galactic nuclei (AGN). This is necessary for understanding the emission and variability mechanisms in such systems. To explore this new avenue of extragalactic physics theFermi-GST AGN Multi-frequency Monitoring Alliance (F-GAMMA) programme undertook the task of conducting nearly monthly, broadband radio monitoring of selected blazars, which is the dominant population of the extragalactic gamma-ray sky, from January 2007 to January 2015. In this work we release all the multi-frequency light curves from 2.64 to 43 GHz and first order derivative data products after all necessary post-measurement corrections and quality checks.Aims. Along with the demanding task to provide the radio part of the broadband SED in monthly intervals, the F-GAMMA programme was also driven by a series of well-defined fundamental questions immediately relevant to blazar physics. On the basis of the monthly sampled radio SEDs, the F-GAMMA aimed at quantifying and understanding the possible multiband correlation and multi-frequency radio variability, spectral evolution and the associated emission, absorption and variability mechanisms. The location of the gamma-ray production site and the correspondence of structural evolution to radio variability have been among the fundamental aims of the programme. Finally, the programme sought to explore the characteristics and dynamics of the multi-frequency radio linear and circular polarisation.Methods. The F-GAMMA ran two main and tightly coordinated observing programmes. The Effelsberg 100 m telescope programme monitoring 2.64, 4.85, 8.35, 10.45, 14.6, 23.05, 32, and 43 GHz, and the IRAM 30 m telescope programme observing at 86.2, 142.3, and 228.9 GHz. The nominal cadence was one month for a total of roughly 60 blazars and targets of opportunity. In a less regular manner the F-GAMMA programme also ran an occasional monitoring with the APEX 12 m telescope at 345 GHz. We only present the Effelsberg dataset in this paper. The higher frequencies data are released elsewhere.Results. The current release includes 155 sources that have been observed at least once by the F-GAMMA programme. That is, the initial sample, the revised sample after the firstFermirelease, targets of opportunity, and sources observed in collaboration with a monitoring programme following up onPlancksatellite observations. For all these sources we release all the quality-checked Effelsberg multi-frequency light curves. The suite of post-measurement corrections and flagging and a thorough system diagnostic study and error analysis is discussed as an assessment of the data reliability. We also release data products such as flux density moments and spectral indices. The effective cadence after the quality flagging is around one radio SED every 1.3 months. The coherence of each radio SED is around 40 min.Conclusions. The released dataset includes more than 3 × 104measurements for some 155 sources over a broad range of frequencies from 2.64 GHz to 43 GHz obtained between 2007 and 2015. The median fractional error at the lowest frequencies (2.64–10.45 GHz) is below 2%. At the highest frequencies (14.6–43 GHz) with limiting factor of the atmospheric conditions, the errors range from 3% to 9%, respectively.

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Kuo, V., and R. Fitch. "Scalable multi-radio communication in modular robots." Robotics and Autonomous Systems 62, no. 7 (July 2014): 1034–46. http://dx.doi.org/10.1016/j.robot.2013.08.007.

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Galluzzi, Vincenzo, and Marcella Massardi. "The polarimetric multi-frequency radio sources properties." International Journal of Modern Physics D 25, no. 11 (October 2016): 1640005. http://dx.doi.org/10.1142/s0218271816400058.

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The polarization properties of extragalactic radio sources at frequencies higher than [Formula: see text]GHz are still poorly constrained. However, their characterization would provide invaluable information about the physics of the emission processes and is crucial to estimate their contamination as foregrounds of the polarized Cosmic Microwave Background (CMB) angular power spectrum on scales [Formula: see text]arcmin. In this contribution, after summarizing the state-of-the-art of polarimetric observations in the millimetric wavelength bands, we present our observations of a complete sample of 53 sources with [Formula: see text]mJy carried out with the Australia Telescope Compact Array (ACTA) between [Formula: see text] and [Formula: see text]GHz. The analysis clearly shows that polarization properties cannot be simply inferred from total intensity ones, as the spectral behaviors of the two signals are typically different.

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Ramanathan, S., and Errol L. Lloyd. "Scheduling algorithms for multi-hop radio networks." ACM SIGCOMM Computer Communication Review 22, no. 4 (October 1992): 211–22. http://dx.doi.org/10.1145/144191.144283.

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