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Автор: Grafiati
Опубліковано: 6 вересня 2023

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1

Zhao, Lindong, Lei Wang, Xuguang Zhang, and Bin Kang. "Social-Aware Cooperative Video Distribution via SVC Streaming Multicast." Wireless Communications and Mobile Computing 2018 (October 25, 2018): 1–9. http://dx.doi.org/10.1155/2018/9315357.

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Анотація:
Scalable Video Coding (SVC) streaming multicast is considered as a promising solution to cope with video traffic overload and multicast channel differences. To solve the challenge of delivering high-definition SVC streaming over burst-loss prone channels, we propose a social-aware cooperative SVC streaming multicast scheme. The proposed scheme is the first attempt to enable D2D cooperation for SVC streaming multicast to conquer the burst-loss, and one salient feature of it is that it takes fully into account the hierarchical encoding structure of SVC in scheduling cooperation. By using our scheme, users form groups to share video packets among each other to restore incomplete enhancement layers. Specifically, a cooperative group formation method is designed to stimulate effective cooperation, based on coalitional game theory; and an optimal D2D links scheduling scheme is devised to maximize the total decoded enhancement layers, based on potential game theory. Extensive simulations using real video traces corroborate that the proposed scheme leads to a significant gain on the received video quality.
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2

Weizhao Wang, Xiang-Yang Li, Yu Wang, and Zheng Sun. "Designing Multicast Protocols for Non-Cooperative Networks." IEEE Journal on Selected Areas in Communications 26, no. 7 (September 2008): 1238–49. http://dx.doi.org/10.1109/jsac.2008.080920.

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3

Binglai Niu, Hai Jiang, and H. V. Zhao. "A Cooperative Multicast Strategy in Wireless Networks." IEEE Transactions on Vehicular Technology 59, no. 6 (July 2010): 3136–43. http://dx.doi.org/10.1109/tvt.2010.2046431.

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4

Zhu, Yun, Jie Gao, Xue Qiong Zhang, and Fan Wang. "Outage Probability Analysis for Opportunistic Network-Coded Cooperative Multicast Transmission in Clustered Wireless Sensor Networks." Advanced Materials Research 756-759 (September 2013): 1418–22. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.1418.

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Cluster-based protocols attempt to solve this problem by load balancing within the cluster and rotating the job of cluster head every few rounds in wireless sensor networks. In this paper, we derive the formulation of the outage probability for opportunistic network-coded cooperative multicast schemes. Simulation results show that our approach can remarkably improve the performance of outage probability than direct multicast.
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5

CHEN, L., L. JIN, F. HE, H. CHENG, and L. WU. "Dynamic Network Selection for Multicast Services in Wireless Cooperative Networks." IEICE Transactions on Communications E91-B, no. 10 (October 1, 2008): 3069–76. http://dx.doi.org/10.1093/ietcom/e91-b.10.3069.

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6

Wu, Fei, Cunqing Hua, Hangguan Shan, and Aiping Huang. "Cooperative multicast with moving window network coding in wireless networks." Ad Hoc Networks 25 (February 2015): 213–27. http://dx.doi.org/10.1016/j.adhoc.2014.10.011.

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7

Yang, Bin, Yulong Shen, Xiaohong Jiang, and Tarik Taleb. "Generalized Cooperative Multicast in Mobile Ad Hoc Networks." IEEE Transactions on Vehicular Technology 67, no. 3 (March 2018): 2631–43. http://dx.doi.org/10.1109/tvt.2017.2771286.

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8

Zhu, Yun, Jie Gao, Lin Zhang, and Shao Lan Sun. "System Modeling for Opportunistic Network-Coded Cooperative Multicast Transmission in Clustered Wireless Sensor Networks." Advanced Materials Research 756-759 (September 2013): 1413–17. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.1413.

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Анотація:
Wireless sensor networks are formed by connected sensors that each have the ability to collect, process, and store environmental information as well as communicate with others via inter-sensor wireless communication. The many-to-one communication pattern used by sensor nodes in most of the data gathering applications leads to such unbalanced energy consumption. Cluster-based protocols attempt to solve this problem by load balancing within the cluster and rotating the job of cluster head every few rounds. In this paper, in order to achieve efficient utilization of wireless resources, we propose an opportunistic network-coded cooperative multicast scheme, which can select appropriate relays by synthetically considering location and instantaneous channel state information to improve the network performance than direct multicast with non additional power consumption.
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9

Zhang, Guopeng, Kun Yang, Qingsong Hu, Peng Liu, and Enjie Ding. "Bargaining Game Theoretic Framework for Stimulating Cooperation in Wireless Cooperative Multicast Networks." IEEE Communications Letters 16, no. 2 (February 2012): 208–11. http://dx.doi.org/10.1109/lcomm.2011.112311.111518.

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10

Marabissi, Dania, Giulio Bartoli, Romano Fantacci, and Luigia Micciullo. "Energy efficient cooperative multicast beamforming in ultra dense networks." IET Communications 12, no. 5 (March 20, 2018): 573–78. http://dx.doi.org/10.1049/iet-com.2017.0618.

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11

Xu, Wenjun, Shengyu Li, Yue Xu, and Xuehong Lin. "Underlaid-D2D-assisted cooperative multicast based on social networks." Peer-to-Peer Networking and Applications 9, no. 5 (April 24, 2015): 923–35. http://dx.doi.org/10.1007/s12083-015-0348-9.

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12

Zhu, Xiangming, Chunxiao Jiang, Liuguo Yin, Linling Kuang, Ning Ge, and Jianhua Lu. "Cooperative Multigroup Multicast Transmission in Integrated Terrestrial-Satellite Networks." IEEE Journal on Selected Areas in Communications 36, no. 5 (May 2018): 981–92. http://dx.doi.org/10.1109/jsac.2018.2832780.

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13

Oh, Taegeun, and Sanghoon Lee. "Cooperative and joint video multicast over MIMO–OFDM networks." Digital Signal Processing 33 (October 2014): 98–115. http://dx.doi.org/10.1016/j.dsp.2014.06.015.

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14

Yuan, Peiyan, Ming Li, Shuhong Li, Chunhong Liu, and Xiaoyan Zhao. "Maximizing the Capacity of Edge Networks with Multicasting." Applied Sciences 13, no. 14 (July 21, 2023): 8424. http://dx.doi.org/10.3390/app13148424.

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Анотація:
Edge networks employ local computing and caching resources to process data, thus alleviating the bandwidth pressure on backbone networks and improve users’ quality of experience. System capacity is one of the key metrics to evaluate the performance of edge networks. However, maximizing system capacity in edge scenarios faces challenges due to the dynamical user sessions and the changing content popularity. This study reports on the influence of multicast communication on the capacity of edge caching networks. When large amounts of content are requested simultaneously or over a short period, one-to-one unicast transmission will consume copious network resources due to repetitious transmission. To solve this problem, this study used the one-to-many multicast scheme to realize cooperative transmission between edge servers. First, multiple copies of the content are distributed to multiple small base stations (SBSs) based on the content’s popularity and the SBSs’ cache sizes. Second, a multicast tree is constructed by using, as the root node, the SBS that stores the content. Third, the content is transmitted along the path of the multicast tree to each end-user. Finally, a simulation platform is constructed to analyze the performance of the two transmission schemes. The results of simulating on edge caching networks show that multicast communication responds well to users’ requests even when the requested content requires sudden transmission, is highly popular or is requested often within short time. This system’s capacity has been significantly improved compared to the classical methods.
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15

Xu, Cao Cao. "Studying Sensor Networks and Multicast Algorithms with TACKY." Advanced Materials Research 989-994 (July 2014): 2093–96. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.2093.

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The refinement of gigabit switches is an unproven challenge. In fact, few biologists would disagree with the refinement of lambda calculus, which embodies the intuitive principles of networking. We explore a novel framework for the synthesis of the producer-consumer problem (TACKY), which we use to show that the foremost cooperative algorithm for the synthesis of operating systems by Sun et al. is Turing complete.
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16

HUANG, Mengjie, Gang FENG, and Yide ZHANG. "Cooperative Loss Recovery for Reliable Multicast in Ad Hoc Networks." International Journal of Communications, Network and System Sciences 03, no. 01 (2010): 72–78. http://dx.doi.org/10.4236/ijcns.2010.31010.

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17

Yang, Long, Qiang Ni, Lu Lv, Jian Chen, Xuan Xue, Hailin Zhang, and Hai Jiang. "Cooperative Non-Orthogonal Layered Multicast Multiple Access for Heterogeneous Networks." IEEE Transactions on Communications 67, no. 2 (February 2019): 1148–65. http://dx.doi.org/10.1109/tcomm.2018.2874239.

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18

Uddin, Mohammad Faisal, Chadi Assi, and Ali Ghrayeb. "Joint Relay Assignment and Power Allocation for Multicast Cooperative Networks." IEEE Communications Letters 16, no. 3 (March 2012): 368–71. http://dx.doi.org/10.1109/lcomm.2012.012412.112327.

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19

Xie, Xianzhong, Bo Rong, Tao Zhang, and Weijia Lei. "Improving physical layer multicast by cooperative communications in heterogeneous networks." IEEE Wireless Communications 18, no. 3 (June 2011): 58–63. http://dx.doi.org/10.1109/mwc.2011.5876501.

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20

Xia, Zicheng, Jiawei Yan, and Yuan Liu. "Cooperative Content Delivery in Multicast Multihop Device-to-Device Networks." IEEE Access 5 (2017): 6314–24. http://dx.doi.org/10.1109/access.2017.2672996.

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21

Mehrizi, Sajad, and Behrad Mahboobi. "Cooperative MIMO relay beamforming in overloaded DS/CDMA multicast networks." IET Communications 11, no. 3 (February 16, 2017): 344–54. http://dx.doi.org/10.1049/iet-com.2016.0610.

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22

Baghban Karimi, Ouldooz, Jiangchuan Liu, and Zongpeng Li. "Multicast with cooperative gateways in multi-channel wireless mesh networks." Ad Hoc Networks 13 (February 2014): 170–80. http://dx.doi.org/10.1016/j.adhoc.2011.10.002.

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23

Lee, I.-Ta, Guann-Long Chiou, and Shun-Ren Yang. "A cooperative multicast routing protocol for mobile ad hoc networks." Computer Networks 55, no. 10 (July 2011): 2407–24. http://dx.doi.org/10.1016/j.comnet.2011.03.019.

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24

Song, Liubin, Youyun Xu, Wei Xie, and Jiang Yu. "A distributed cooperative multicast scheduling strategy in IEEE 802.11 networks." Journal of Electronics (China) 28, no. 3 (May 2011): 334–40. http://dx.doi.org/10.1007/s11767-011-0569-x.

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25

Zhang, Guopeng, Zuyan Wang, Jie Gu, Kun Yang, and Peng Liu. "Performance Analysis of Two Cooperative Multicast Schemes in Cellular Networks." Wireless Personal Communications 95, no. 2 (October 24, 2016): 1317–31. http://dx.doi.org/10.1007/s11277-016-3831-6.

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26

Chen, Lei, Hongyu Wang, and Fanglin Niu. "Cooperative Resource Allocation in Multicast Networks for Outage Probability Minimization." International Journal of Wireless Information Networks 22, no. 1 (December 27, 2014): 1–9. http://dx.doi.org/10.1007/s10776-014-0258-4.

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27

Chekuri, C., J. Chuzhoy, L. Lewin-Eytan, J. Naor, and A. Orda. "Non-Cooperative Multicast and Facility Location Games." IEEE Journal on Selected Areas in Communications 25, no. 6 (August 2007): 1193–206. http://dx.doi.org/10.1109/jsac.2007.070813.

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28

Wang, Xiumin, Jin Wang, and Shukui Zhang. "Network Coded Wireless Cooperative Multicast with Minimum Transmission Cost." International Journal of Distributed Sensor Networks 8, no. 10 (October 1, 2012): 614206. http://dx.doi.org/10.1155/2012/614206.

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Анотація:
We study multicasting over wireless lossy links. Instead of downloading all the data from the source node, we allow the destination nodes themselves to locally exchange the packets, as local communication within a cluster achieves higher packet reception probability with less transmission cost. However, when shall we stop the transmission from the source node? If the source stops too early, the destination nodes locally cannot reconstruct all the original packets, while if the source stops too late, the benefit of cooperative data exchange cannot be fully exploited. In this paper, we propose a network coded hybrid source and cooperative exchange scheme to determine when to stop the source sending and start the exchange process, so as to minimize the total transmission cost. For the case when the clusters are predefined, we derive the expected total transmission cost with our hybrid scheme. Our theoretical results show that under a special condition, the source node should keep sending the packets until all the destinations get the complete information. For the case when the clusters are not predefined, we propose a cluster division algorithm such that the destination nodes within each cluster can conduct data exchange locally with energy efficiency. Finally, simulation results demonstrate the effectiveness of the proposed scheme.
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29

BILÒ, VITTORIO. "THE PRICE OF NASH EQUILIBRIA IN MULTICAST TRANSMISSION GAMES." Journal of Interconnection Networks 11, no. 03n04 (September 2010): 97–120. http://dx.doi.org/10.1142/s0219265910002751.

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Анотація:
We consider the problem of sharing the cost of multicast transmissions in non-cooperative undirected networks where a set of receivers R wants to be connected to a common source s. The set of choices available to each receiver r ∈ R is represented by the set of all (s, r)-paths in the network. Given the choices performed by all the receivers, a public known cost sharing method determines the cost share to be charged to each of them. Receivers are selfish agents aiming to obtain the transmission at the minimum cost share and their interactions create a non-cooperative game. Devising cost sharing methods yielding games whose price of anarchy (price of stability), defined as the worst-case (best-case) ratio between the cost of a Nash equilibrium and that of an optimal solution, is not too high is thus of fundamental importance in non-cooperative network design. Moreover, since cost sharing games naturally arise in socio-economical contests, it is convenient for a cost sharing method to meet some constraining properties. In this paper, we first define several such properties and analyze their impact on the prices of anarchy and stability. We also reconsider all the methods known so far by classifying them according to which properties they satisfy and giving the first non-trivial lower bounds on their price of stability. Finally, we propose a new method, namely the free-riders method, which admits a polynomial time algorithm for computing a pure Nash equilibrium whose cost is at most twice the optimal one. Some of the ideas characterizing our approach have been independently proposed in Ref. 10.
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30

Yang, Bin, Zhenqiang Wu, Yulong Shen, Xiaohong Jiang, and Shikai Shen. "On delay performance study for cooperative multicast MANETs." Ad Hoc Networks 102 (May 2020): 102117. http://dx.doi.org/10.1016/j.adhoc.2020.102117.

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31

Huang, Meng-jie, Gang Feng, and Yi-de Zhang. "CoreRM: Cooperative Loss Recovery for Reliable Multicast in Ad hoc Networks." Journal of Electronics & Information Technology 32, no. 9 (December 2, 2010): 2065–71. http://dx.doi.org/10.3724/sp.j.1146.2009.01054.

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32

Almasaeid, Hisham M., and Ahmed E. Kamal. "Exploiting Multichannel Diversity for Cooperative Multicast in Cognitive Radio Mesh Networks." IEEE/ACM Transactions on Networking 22, no. 3 (June 2014): 770–83. http://dx.doi.org/10.1109/tnet.2013.2258035.

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33

He, Bingtao, Jian Chen, Yonghong Kuo, and Long Yang. "Cooperative jamming for energy harvesting multicast networks with an untrusted relay." IET Communications 11, no. 13 (September 7, 2017): 2058–65. http://dx.doi.org/10.1049/iet-com.2016.1338.

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34

Mehdipour Chari, Kaveh, and Mohammad Ghanbari. "Application Layer Energy-Efficient Scalable Video Cooperative Multicast in Cellular Networks." Wireless Personal Communications 112, no. 4 (February 6, 2020): 2503–17. http://dx.doi.org/10.1007/s11277-020-07161-0.

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35

Zhang, Zhengquan, Zheng Ma, Yue Xiao, Ming Xiao, George K. Karagiannidis, and Pingzhi Fan. "Non-Orthogonal Multiple Access for Cooperative Multicast Millimeter Wave Wireless Networks." IEEE Journal on Selected Areas in Communications 35, no. 8 (August 2017): 1794–808. http://dx.doi.org/10.1109/jsac.2017.2710918.

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36

LI, Jun, and Wen CHEN. "Physical Layer Network Coding for Wireless Cooperative Multicast Flows." IEICE Transactions on Communications E92-B, no. 8 (2009): 2559–67. http://dx.doi.org/10.1587/transcom.e92.b.2559.

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37

Zhang, Yibo, Xiaoxiang Wang, Dongyu Wang, Yufang Zhang, and Yanwen Lan. "Analysis and Design of SCMA-Based Hybrid Unicast-Multicast Relay-Assisted Networks." Sensors 19, no. 2 (January 15, 2019): 329. http://dx.doi.org/10.3390/s19020329.

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Анотація:
This paper studies a multi-user network model based on sparse code multiple access (SCMA), where both unicast and multicast services are considered. In the direct transmission scheme, the communication between the base station (BS) and the users is completed with one stage, in which the relay is inexistent. In the two-stage cooperative transmission scheme, any number of relays are placed to improve the reliability of wireless communication system. The BS broadcasts the requested message to users and relays in the first stage, and the successful relays forward the message to unsuccessful users in the second stage. To characterize the performance of these two schemes, we derive the exact and approximate expressions of average outage probability. Furthermore, to take full advantage of the cooperative diversity, an optimal power allocation and relay location strategy in the high signal-to-noise ratio (SNR) regime is studied. The outage probability reaches the minimum value when the first stage occupies half of the total energy consumed. Simulation and analysis results are presented to demonstrate the performance of these two schemes. The results show that the two-stage cooperative scheme effectively reduce the average outage probability in SCMA network, especially in the high SNR region.
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38

Fortino, Giancarlo, Carlo Mastroianni, and Wilma Russo. "Cooperative control of multicast-based streaming on-demand systems." Future Generation Computer Systems 21, no. 5 (May 2005): 823–39. http://dx.doi.org/10.1016/j.future.2004.08.002.

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39

Yang, Mengkun, and Zongming Fei. "A cooperative failure detection mechanism for overlay multicast." Journal of Parallel and Distributed Computing 67, no. 6 (June 2007): 635–47. http://dx.doi.org/10.1016/j.jpdc.2007.03.002.

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40

Han, Dairu, Wenhe Liao, Haixia Peng, Huaqing Wu, Wen Wu, and Xuemin Shen. "Joint Cache Placement and Cooperative Multicast Beamforming in Integrated Satellite-Terrestrial Networks." IEEE Transactions on Vehicular Technology 71, no. 3 (March 2022): 3131–43. http://dx.doi.org/10.1109/tvt.2021.3138898.

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41

Hwang, Duckdong, Phuc Chau, Jitae Shin, and Tae-Jin Lee. "Two cooperative multicast schemes of scalable video in relay-based cellular networks." IET Communications 9, no. 7 (May 7, 2015): 982–89. http://dx.doi.org/10.1049/iet-com.2014.0915.

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42

Hou, Fen, Lin X. Cai, Pin-Han Ho, Xuemin Shen, and Junshan Zhang. "A cooperative multicast scheduling scheme for multimedia services in IEEE 802.16 networks." IEEE Transactions on Wireless Communications 8, no. 3 (March 2009): 1508–19. http://dx.doi.org/10.1109/twc.2009.080417.

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43

Zhang, GuoPeng, Peng Liu, and EnJie Ding. "Pareto optimal time-frequency resource allocation for selfish wireless cooperative multicast networks." Science China Information Sciences 56, no. 12 (November 24, 2012): 1–8. http://dx.doi.org/10.1007/s11432-012-4617-4.

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44

Li, Suo Ping, Yong Qiang Zhou, and Yong Zhou. "Delay and energy efficiency analysis of multicast cooperative ARQ over wireless networks." Acta Informatica 51, no. 1 (January 8, 2014): 51–60. http://dx.doi.org/10.1007/s00236-013-0192-4.

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45

Hu, Jie, Lie-Liang Yang, and Lajos Hanzo. "Distributed Multistage Cooperative-Social-Multicast-Aided Content Dissemination in Random Mobile Networks." IEEE Transactions on Vehicular Technology 64, no. 7 (July 2015): 3075–89. http://dx.doi.org/10.1109/tvt.2014.2354295.

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46

Hao, Hao, Changqiao Xu, Lujie Zhong, and Dapeng Oliver Wu. "Stochastic Cooperative Optimization for Multicast Scheduling in Heterogeneous and Green 5G Networks." IEEE Transactions on Green Communications and Networking 4, no. 3 (September 2020): 903–13. http://dx.doi.org/10.1109/tgcn.2020.2981459.

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47

Li, Jheng-Sian, Jyh-Horng Wen, Chung-Hua Chiang, and Chien-Erh Weng. "Performance on Multiple Pilot-Based Grouping Methods in Satellite-Terrestrial Cooperative Wireless Networks." Electronics 11, no. 3 (January 30, 2022): 430. http://dx.doi.org/10.3390/electronics11030430.

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Анотація:
The grouping method is an efficient transmitting strategy in a spatial diversity system. In this paper, relay-based grouping methods in satellite terrestrial cooperative wireless networks are proposed. The proposed methods focus on finding out the best two signals received from relay stations in a user’s neighborhood and use the advantage of space diversity to overcome the effect of channel fading. A grouping method, called the pilot-based grouping method was proposed in our previous work. In order to improve the grouping success rate and the channel capacity, a modified grouping method is proposed. In addition, for a single relay the modified grouping method can achieve better results than the pilot-based grouping method. In the end, several analysis strategies of the grouping method for multimedia broadcast and multicast services in satellite terrestrial cooperative networks are proposed. The simulation results show the performance improvement and the system evaluation for different quality of services in the demanded relay-based cooperative networks. The proposed modified grouping methods can be widespread in any relay-based cooperative networks.
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48

Yang, Long, Jian Chen, Yonghong Kuo, and Hailin Zhang. "Outage Performance of DF-Based Cooperative Multicast in Spectrum-Sharing Cognitive Relay Networks." IEEE Communications Letters 18, no. 7 (July 2014): 1250–53. http://dx.doi.org/10.1109/lcomm.2014.2327631.

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Bo Rong and Abdelhakim Hafid. "Cooperative Multicast for Mobile IPTV Over Wireless Mesh Networks: The Relay-Selection Study." IEEE Transactions on Vehicular Technology 59, no. 5 (2010): 2207–18. http://dx.doi.org/10.1109/tvt.2010.2042630.

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