The Experts below are selected from a list of 300 Experts worldwide ranked by ideXlab platform
Yuefeng Ji - One of the best experts on this subject based on the ideXlab platform.
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Resource Allocation Optimization for Time and Wavelength Division Multiplexing Passive Optical Network Enabled Mobile Fronthaul With Bitrate-Variable Compressed Common Public Radio Interface
Journal of Optical Communications and Networking, 2016Co-Authors: Gang Wang, Rentao Gu, Yuefeng JiAbstract:© 2016 Optical Society of America. Recently, a cloud radio access network (C-RAN) has been proposed as a Candidate Architecture for fifth-generation mobile communication. Fronthaul is a new segment in C-RAN. In this paper, we investigate the algorithms for resource allocation in time and wavelength division multiplexing passive optical network enabled front-haul. We formulate an integer nonlinear programming (INLP) model, considering the operation mode of the small cell. A heuristic method is also proposed based on an adaptive parallel genetic algorithm (GA). Three optimization objectives are considered when we implement the resource allocation schemes in the fronthaul: 1) minimize the total number of used wavelengths, 2) minimize the load imbalance of the fronthaul, and 3) minimize the amount of traffic influenced by fronthaul virtual topology change. The results show that INLP and adaptive parallel GA have good performance for resource allocation in the fronthaul. Wavelength resources can be significantly saved in different load scenarios, so that the load difference can be minimized with minimal topology adjustment. Furthermore, the adaptive parallel GA obtains more efficient resource allocation than the traditional GA with much less running time, which makes it applicable for the large-scale fronthaul network optimization with fast convergence.
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Resource allocation optimization for time and wavelength division multiplexing passive optical network enabled mobile fronthaul with bitrate-variable compressed common public radio interface
IEEE OSA Journal of Optical Communications and Networking, 2016Co-Authors: Gang Wang, Rentao Gu, Yuefeng JiAbstract:Recently, a cloud radio access network (C-RAN) has been proposed as a Candidate Architecture for fifth-generation mobile communication. Fronthaul is a new segment in C-RAN. In this paper, we investigate the algorithms for resource allocation in time and wavelength division multiplexing passive optical network enabled front-haul. We formulate an integer nonlinear programming (INLP) model, considering the operation mode of the small cell. A heuristic method is also proposed based on an adaptive parallel genetic algorithm (GA). Three optimization objectives are considered when we implement the resource allocation schemes in the fronthaul: 1) minimize the total number of used wavelengths, 2) minimize the load imbalance of the fronthaul, and 3) minimize the amount of traffic influenced by fronthaul virtual topology change. The results show that INLP and adaptive parallel GA have good performance for resource allocation in the fronthaul. Wavelength resources can be significantly saved in different load scenarios, so that the load difference can be minimized with minimal topology adjustment. Furthermore, the adaptive parallel GA obtains more efficient resource allocation than the traditional GA with much less running time, which makes it applicable for the large-scale fronthaul network optimization with fast convergence.
Gang Wang - One of the best experts on this subject based on the ideXlab platform.
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Resource Allocation Optimization for Time and Wavelength Division Multiplexing Passive Optical Network Enabled Mobile Fronthaul With Bitrate-Variable Compressed Common Public Radio Interface
Journal of Optical Communications and Networking, 2016Co-Authors: Gang Wang, Rentao Gu, Yuefeng JiAbstract:© 2016 Optical Society of America. Recently, a cloud radio access network (C-RAN) has been proposed as a Candidate Architecture for fifth-generation mobile communication. Fronthaul is a new segment in C-RAN. In this paper, we investigate the algorithms for resource allocation in time and wavelength division multiplexing passive optical network enabled front-haul. We formulate an integer nonlinear programming (INLP) model, considering the operation mode of the small cell. A heuristic method is also proposed based on an adaptive parallel genetic algorithm (GA). Three optimization objectives are considered when we implement the resource allocation schemes in the fronthaul: 1) minimize the total number of used wavelengths, 2) minimize the load imbalance of the fronthaul, and 3) minimize the amount of traffic influenced by fronthaul virtual topology change. The results show that INLP and adaptive parallel GA have good performance for resource allocation in the fronthaul. Wavelength resources can be significantly saved in different load scenarios, so that the load difference can be minimized with minimal topology adjustment. Furthermore, the adaptive parallel GA obtains more efficient resource allocation than the traditional GA with much less running time, which makes it applicable for the large-scale fronthaul network optimization with fast convergence.
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Resource allocation optimization for time and wavelength division multiplexing passive optical network enabled mobile fronthaul with bitrate-variable compressed common public radio interface
IEEE OSA Journal of Optical Communications and Networking, 2016Co-Authors: Gang Wang, Rentao Gu, Yuefeng JiAbstract:Recently, a cloud radio access network (C-RAN) has been proposed as a Candidate Architecture for fifth-generation mobile communication. Fronthaul is a new segment in C-RAN. In this paper, we investigate the algorithms for resource allocation in time and wavelength division multiplexing passive optical network enabled front-haul. We formulate an integer nonlinear programming (INLP) model, considering the operation mode of the small cell. A heuristic method is also proposed based on an adaptive parallel genetic algorithm (GA). Three optimization objectives are considered when we implement the resource allocation schemes in the fronthaul: 1) minimize the total number of used wavelengths, 2) minimize the load imbalance of the fronthaul, and 3) minimize the amount of traffic influenced by fronthaul virtual topology change. The results show that INLP and adaptive parallel GA have good performance for resource allocation in the fronthaul. Wavelength resources can be significantly saved in different load scenarios, so that the load difference can be minimized with minimal topology adjustment. Furthermore, the adaptive parallel GA obtains more efficient resource allocation than the traditional GA with much less running time, which makes it applicable for the large-scale fronthaul network optimization with fast convergence.
Rentao Gu - One of the best experts on this subject based on the ideXlab platform.
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Resource Allocation Optimization for Time and Wavelength Division Multiplexing Passive Optical Network Enabled Mobile Fronthaul With Bitrate-Variable Compressed Common Public Radio Interface
Journal of Optical Communications and Networking, 2016Co-Authors: Gang Wang, Rentao Gu, Yuefeng JiAbstract:© 2016 Optical Society of America. Recently, a cloud radio access network (C-RAN) has been proposed as a Candidate Architecture for fifth-generation mobile communication. Fronthaul is a new segment in C-RAN. In this paper, we investigate the algorithms for resource allocation in time and wavelength division multiplexing passive optical network enabled front-haul. We formulate an integer nonlinear programming (INLP) model, considering the operation mode of the small cell. A heuristic method is also proposed based on an adaptive parallel genetic algorithm (GA). Three optimization objectives are considered when we implement the resource allocation schemes in the fronthaul: 1) minimize the total number of used wavelengths, 2) minimize the load imbalance of the fronthaul, and 3) minimize the amount of traffic influenced by fronthaul virtual topology change. The results show that INLP and adaptive parallel GA have good performance for resource allocation in the fronthaul. Wavelength resources can be significantly saved in different load scenarios, so that the load difference can be minimized with minimal topology adjustment. Furthermore, the adaptive parallel GA obtains more efficient resource allocation than the traditional GA with much less running time, which makes it applicable for the large-scale fronthaul network optimization with fast convergence.
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Resource allocation optimization for time and wavelength division multiplexing passive optical network enabled mobile fronthaul with bitrate-variable compressed common public radio interface
IEEE OSA Journal of Optical Communications and Networking, 2016Co-Authors: Gang Wang, Rentao Gu, Yuefeng JiAbstract:Recently, a cloud radio access network (C-RAN) has been proposed as a Candidate Architecture for fifth-generation mobile communication. Fronthaul is a new segment in C-RAN. In this paper, we investigate the algorithms for resource allocation in time and wavelength division multiplexing passive optical network enabled front-haul. We formulate an integer nonlinear programming (INLP) model, considering the operation mode of the small cell. A heuristic method is also proposed based on an adaptive parallel genetic algorithm (GA). Three optimization objectives are considered when we implement the resource allocation schemes in the fronthaul: 1) minimize the total number of used wavelengths, 2) minimize the load imbalance of the fronthaul, and 3) minimize the amount of traffic influenced by fronthaul virtual topology change. The results show that INLP and adaptive parallel GA have good performance for resource allocation in the fronthaul. Wavelength resources can be significantly saved in different load scenarios, so that the load difference can be minimized with minimal topology adjustment. Furthermore, the adaptive parallel GA obtains more efficient resource allocation than the traditional GA with much less running time, which makes it applicable for the large-scale fronthaul network optimization with fast convergence.
Cristiano Bonato Both - One of the best experts on this subject based on the ideXlab platform.
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Design considerations for software-defined wireless networking in heterogeneous cloud radio access networks
Journal of Internet Services and Applications, 2017Co-Authors: Marcelo A. Marotta, Juliano Araujo Wickboldt, Maicon Kist, Lisandro Zambenedetti Granville, Juergen Rochol, Cristiano Bonato BothAbstract:The fifth generation (5G) cellular infrastructure is envisaged as a dense and heterogeneous deployment of small cells overlapping with existing macrocells in the Radio Access Network (RAN). Densification and heterogeneity, however, pose new challenges such as dealing with interference, accommodating massive signaling traffic, and managing increased energy consumption. Heterogeneous Cloud Radio Access Networks (H-CRAN) emerges as a Candidate Architecture for a sustainable deployment of 5G. In addition, the application of SDN concepts to wireless environments motivated recent research in the so-called Software-Defined Wireless Networking (SDWN). In this article, we discuss how SDWN can support the development of a flexible, programmable, and sustainable infrastructure for 5G. We also present a case study based on SDWN to perform frequency assignment, interference, and handover control in an H-CRAN environment. Results allow the establishment of a tradeoff between wireless communication capacity gains and signaling overhead added by the employment of SDWN concepts to H-CRAN.
E. Corbel - One of the best experts on this subject based on the ideXlab platform.
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hybrid satellite terrestrial mobile network for 4g Candidate Architecture and space segment dimensioning
2008 4th Advanced Satellite Mobile Systems, 2008Co-Authors: E. Corbel, Isabelle Buret, J.-d. Gayrard, Giovanni E. Corazza, A BoleaalamanacAbstract:The great effort that is devoted to the definition of the '4G' highlights the need for the MSS ecosystem to explore the opportunity to include satellite into the paradigm of '4G' networks of networks. Satellites may appear as a way to 'fill the holes' of the terrestrial coverage thus offering global mobility to end user. We consider here two missions to be delivered over Europe : an interactive broadcast mission and a two-way broadband mission, both targeting handset, vehicular and nomadic terminals. Firstly a general discussion and a Candidate hybrid satellite and terrestrial network Architecture is proposed for low- frequency bands under CGC (Complementary Ground Component) license. Secondly the dimensioning of the space segment for both missions is presented. The paper stresses the demand for satellites with large antennas and high amplified power. It also briefly touches on the required adaptation of the 4G air interfaces to the satellite constraints. In addition it shows that the system capacity is mainly driven by the spectrum resource.
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Hybrid Satellite & Terrestrial Mobile Network for 4G : Candidate Architecture and Space Segment Dimensioning
2008 4th Advanced Satellite Mobile Systems, 2008Co-Authors: E. Corbel, Isabelle Buret, J.-d. Gayrard, Giovanni E. Corazza, Ana Bolea-alamanacAbstract:The great effort that is devoted to the definition of the '4G' highlights the need for the MSS ecosystem to explore the opportunity to include satellite into the paradigm of '4G' networks of networks. Satellites may appear as a way to 'fill the holes' of the terrestrial coverage thus offering global mobility to end user. We consider here two missions to be delivered over Europe : an interactive broadcast mission and a two-way broadband mission, both targeting handset, vehicular and nomadic terminals. Firstly a general discussion and a Candidate hybrid satellite and terrestrial network Architecture is proposed for low- frequency bands under CGC (Complementary Ground Component) license. Secondly the dimensioning of the space segment for both missions is presented. The paper stresses the demand for satellites with large antennas and high amplified power. It also briefly touches on the required adaptation of the 4G air interfaces to the satellite constraints. In addition it shows that the system capacity is mainly driven by the spectrum resource.
