Efficient Discrete Rate Assignment and Power Optimization in Optical Communication Systems Following the Gaussian Noise Model
Computationally efficient heuristics for solving the discrete-rate capacity optimization problem for optical fiber communication systems are investigated. In the Gaussian noise nonlinearity model regime, this class of problem is an NP-hard mixed integer convex problem. The proposed heuristic minimiz...
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| Autor*in: |
Roberts, Ian [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Journal of lightwave technology - New York, NY : IEEE, 1983, 35(2017), 20, Seite 4425-4437 |
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| Übergeordnetes Werk: |
volume:35 ; year:2017 ; number:20 ; pages:4425-4437 |
| Links: |
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| DOI / URN: |
10.1109/JLT.2017.2744624 |
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OLC1997802392 |
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| 520 | |a Computationally efficient heuristics for solving the discrete-rate capacity optimization problem for optical fiber communication systems are investigated. In the Gaussian noise nonlinearity model regime, this class of problem is an NP-hard mixed integer convex problem. The proposed heuristic minimizes the number of calls required to solve the computationally intensive problem of determining the feasibility of proposed discrete rate allocations. In a live system, optimization using this algorithm minimizes the number of potential discrete rate allocations tested for feasibility while additional discrete system capacity is extracted. In exemplary point-to-point links at 50 Gbaud with 50 Gb/s rate steps, the mean lost capacity per modem is reduced from 24.5 Gb/s with truncation to 7.95 Gb/s with discrete-rate optimization. With 25 Gb/s rate steps, the mean lost capacity is reduced from 12.3 Gb/s to 2.07 Gb/s. An unbiased metric is proposed to extend the capacity optimization objective from point-to-point links to mesh networks. A gain of 13% in distance-times-capacity metric is obtained from discrete-rate optimization with 50 Gb/s rate steps, and a 7.5% gain is obtained with 25 Gb/s rate steps. | ||
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10.1109/JLT.2017.2744624 doi PQ20171228 (DE-627)OLC1997802392 (DE-599)GBVOLC1997802392 (PRQ)i650-e7269543cf3aea3dd5f706c7d452f8ff746ccdaada775d34d900cd6e6ae9195e0 (KEY)0124889820170000035002004425efficientdiscreterateassignmentandpoweroptimizatio DE-627 ger DE-627 rakwb eng 530 600 620 DE-600 Roberts, Ian verfasserin aut Efficient Discrete Rate Assignment and Power Optimization in Optical Communication Systems Following the Gaussian Noise Model 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Computationally efficient heuristics for solving the discrete-rate capacity optimization problem for optical fiber communication systems are investigated. In the Gaussian noise nonlinearity model regime, this class of problem is an NP-hard mixed integer convex problem. The proposed heuristic minimizes the number of calls required to solve the computationally intensive problem of determining the feasibility of proposed discrete rate allocations. In a live system, optimization using this algorithm minimizes the number of potential discrete rate allocations tested for feasibility while additional discrete system capacity is extracted. In exemplary point-to-point links at 50 Gbaud with 50 Gb/s rate steps, the mean lost capacity per modem is reduced from 24.5 Gb/s with truncation to 7.95 Gb/s with discrete-rate optimization. With 25 Gb/s rate steps, the mean lost capacity is reduced from 12.3 Gb/s to 2.07 Gb/s. An unbiased metric is proposed to extend the capacity optimization objective from point-to-point links to mesh networks. A gain of 13% in distance-times-capacity metric is obtained from discrete-rate optimization with 50 Gb/s rate steps, and a 7.5% gain is obtained with 25 Gb/s rate steps. Measurement Resource management gaussian noise model Encoding Signal to noise ratio Discrete capacity optimization optical communications network optimization Gaussian noise Optimization Optical noise Kahn, Joseph M oth Enthalten in Journal of lightwave technology New York, NY : IEEE, 1983 35(2017), 20, Seite 4425-4437 (DE-627)129620882 (DE-600)246121-3 (DE-576)015127214 0733-8724 nnns volume:35 year:2017 number:20 pages:4425-4437 http://dx.doi.org/10.1109/JLT.2017.2744624 Volltext http://ieeexplore.ieee.org/document/8016579 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-PHY GBV_ILN_70 GBV_ILN_185 AR 35 2017 20 4425-4437 |
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10.1109/JLT.2017.2744624 doi PQ20171228 (DE-627)OLC1997802392 (DE-599)GBVOLC1997802392 (PRQ)i650-e7269543cf3aea3dd5f706c7d452f8ff746ccdaada775d34d900cd6e6ae9195e0 (KEY)0124889820170000035002004425efficientdiscreterateassignmentandpoweroptimizatio DE-627 ger DE-627 rakwb eng 530 600 620 DE-600 Roberts, Ian verfasserin aut Efficient Discrete Rate Assignment and Power Optimization in Optical Communication Systems Following the Gaussian Noise Model 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Computationally efficient heuristics for solving the discrete-rate capacity optimization problem for optical fiber communication systems are investigated. In the Gaussian noise nonlinearity model regime, this class of problem is an NP-hard mixed integer convex problem. The proposed heuristic minimizes the number of calls required to solve the computationally intensive problem of determining the feasibility of proposed discrete rate allocations. In a live system, optimization using this algorithm minimizes the number of potential discrete rate allocations tested for feasibility while additional discrete system capacity is extracted. In exemplary point-to-point links at 50 Gbaud with 50 Gb/s rate steps, the mean lost capacity per modem is reduced from 24.5 Gb/s with truncation to 7.95 Gb/s with discrete-rate optimization. With 25 Gb/s rate steps, the mean lost capacity is reduced from 12.3 Gb/s to 2.07 Gb/s. An unbiased metric is proposed to extend the capacity optimization objective from point-to-point links to mesh networks. A gain of 13% in distance-times-capacity metric is obtained from discrete-rate optimization with 50 Gb/s rate steps, and a 7.5% gain is obtained with 25 Gb/s rate steps. Measurement Resource management gaussian noise model Encoding Signal to noise ratio Discrete capacity optimization optical communications network optimization Gaussian noise Optimization Optical noise Kahn, Joseph M oth Enthalten in Journal of lightwave technology New York, NY : IEEE, 1983 35(2017), 20, Seite 4425-4437 (DE-627)129620882 (DE-600)246121-3 (DE-576)015127214 0733-8724 nnns volume:35 year:2017 number:20 pages:4425-4437 http://dx.doi.org/10.1109/JLT.2017.2744624 Volltext http://ieeexplore.ieee.org/document/8016579 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-PHY GBV_ILN_70 GBV_ILN_185 AR 35 2017 20 4425-4437 |
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10.1109/JLT.2017.2744624 doi PQ20171228 (DE-627)OLC1997802392 (DE-599)GBVOLC1997802392 (PRQ)i650-e7269543cf3aea3dd5f706c7d452f8ff746ccdaada775d34d900cd6e6ae9195e0 (KEY)0124889820170000035002004425efficientdiscreterateassignmentandpoweroptimizatio DE-627 ger DE-627 rakwb eng 530 600 620 DE-600 Roberts, Ian verfasserin aut Efficient Discrete Rate Assignment and Power Optimization in Optical Communication Systems Following the Gaussian Noise Model 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Computationally efficient heuristics for solving the discrete-rate capacity optimization problem for optical fiber communication systems are investigated. In the Gaussian noise nonlinearity model regime, this class of problem is an NP-hard mixed integer convex problem. The proposed heuristic minimizes the number of calls required to solve the computationally intensive problem of determining the feasibility of proposed discrete rate allocations. In a live system, optimization using this algorithm minimizes the number of potential discrete rate allocations tested for feasibility while additional discrete system capacity is extracted. In exemplary point-to-point links at 50 Gbaud with 50 Gb/s rate steps, the mean lost capacity per modem is reduced from 24.5 Gb/s with truncation to 7.95 Gb/s with discrete-rate optimization. With 25 Gb/s rate steps, the mean lost capacity is reduced from 12.3 Gb/s to 2.07 Gb/s. An unbiased metric is proposed to extend the capacity optimization objective from point-to-point links to mesh networks. A gain of 13% in distance-times-capacity metric is obtained from discrete-rate optimization with 50 Gb/s rate steps, and a 7.5% gain is obtained with 25 Gb/s rate steps. Measurement Resource management gaussian noise model Encoding Signal to noise ratio Discrete capacity optimization optical communications network optimization Gaussian noise Optimization Optical noise Kahn, Joseph M oth Enthalten in Journal of lightwave technology New York, NY : IEEE, 1983 35(2017), 20, Seite 4425-4437 (DE-627)129620882 (DE-600)246121-3 (DE-576)015127214 0733-8724 nnns volume:35 year:2017 number:20 pages:4425-4437 http://dx.doi.org/10.1109/JLT.2017.2744624 Volltext http://ieeexplore.ieee.org/document/8016579 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-PHY GBV_ILN_70 GBV_ILN_185 AR 35 2017 20 4425-4437 |
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10.1109/JLT.2017.2744624 doi PQ20171228 (DE-627)OLC1997802392 (DE-599)GBVOLC1997802392 (PRQ)i650-e7269543cf3aea3dd5f706c7d452f8ff746ccdaada775d34d900cd6e6ae9195e0 (KEY)0124889820170000035002004425efficientdiscreterateassignmentandpoweroptimizatio DE-627 ger DE-627 rakwb eng 530 600 620 DE-600 Roberts, Ian verfasserin aut Efficient Discrete Rate Assignment and Power Optimization in Optical Communication Systems Following the Gaussian Noise Model 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Computationally efficient heuristics for solving the discrete-rate capacity optimization problem for optical fiber communication systems are investigated. In the Gaussian noise nonlinearity model regime, this class of problem is an NP-hard mixed integer convex problem. The proposed heuristic minimizes the number of calls required to solve the computationally intensive problem of determining the feasibility of proposed discrete rate allocations. In a live system, optimization using this algorithm minimizes the number of potential discrete rate allocations tested for feasibility while additional discrete system capacity is extracted. In exemplary point-to-point links at 50 Gbaud with 50 Gb/s rate steps, the mean lost capacity per modem is reduced from 24.5 Gb/s with truncation to 7.95 Gb/s with discrete-rate optimization. With 25 Gb/s rate steps, the mean lost capacity is reduced from 12.3 Gb/s to 2.07 Gb/s. An unbiased metric is proposed to extend the capacity optimization objective from point-to-point links to mesh networks. A gain of 13% in distance-times-capacity metric is obtained from discrete-rate optimization with 50 Gb/s rate steps, and a 7.5% gain is obtained with 25 Gb/s rate steps. Measurement Resource management gaussian noise model Encoding Signal to noise ratio Discrete capacity optimization optical communications network optimization Gaussian noise Optimization Optical noise Kahn, Joseph M oth Enthalten in Journal of lightwave technology New York, NY : IEEE, 1983 35(2017), 20, Seite 4425-4437 (DE-627)129620882 (DE-600)246121-3 (DE-576)015127214 0733-8724 nnns volume:35 year:2017 number:20 pages:4425-4437 http://dx.doi.org/10.1109/JLT.2017.2744624 Volltext http://ieeexplore.ieee.org/document/8016579 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-PHY GBV_ILN_70 GBV_ILN_185 AR 35 2017 20 4425-4437 |
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10.1109/JLT.2017.2744624 doi PQ20171228 (DE-627)OLC1997802392 (DE-599)GBVOLC1997802392 (PRQ)i650-e7269543cf3aea3dd5f706c7d452f8ff746ccdaada775d34d900cd6e6ae9195e0 (KEY)0124889820170000035002004425efficientdiscreterateassignmentandpoweroptimizatio DE-627 ger DE-627 rakwb eng 530 600 620 DE-600 Roberts, Ian verfasserin aut Efficient Discrete Rate Assignment and Power Optimization in Optical Communication Systems Following the Gaussian Noise Model 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Computationally efficient heuristics for solving the discrete-rate capacity optimization problem for optical fiber communication systems are investigated. In the Gaussian noise nonlinearity model regime, this class of problem is an NP-hard mixed integer convex problem. The proposed heuristic minimizes the number of calls required to solve the computationally intensive problem of determining the feasibility of proposed discrete rate allocations. In a live system, optimization using this algorithm minimizes the number of potential discrete rate allocations tested for feasibility while additional discrete system capacity is extracted. In exemplary point-to-point links at 50 Gbaud with 50 Gb/s rate steps, the mean lost capacity per modem is reduced from 24.5 Gb/s with truncation to 7.95 Gb/s with discrete-rate optimization. With 25 Gb/s rate steps, the mean lost capacity is reduced from 12.3 Gb/s to 2.07 Gb/s. An unbiased metric is proposed to extend the capacity optimization objective from point-to-point links to mesh networks. A gain of 13% in distance-times-capacity metric is obtained from discrete-rate optimization with 50 Gb/s rate steps, and a 7.5% gain is obtained with 25 Gb/s rate steps. Measurement Resource management gaussian noise model Encoding Signal to noise ratio Discrete capacity optimization optical communications network optimization Gaussian noise Optimization Optical noise Kahn, Joseph M oth Enthalten in Journal of lightwave technology New York, NY : IEEE, 1983 35(2017), 20, Seite 4425-4437 (DE-627)129620882 (DE-600)246121-3 (DE-576)015127214 0733-8724 nnns volume:35 year:2017 number:20 pages:4425-4437 http://dx.doi.org/10.1109/JLT.2017.2744624 Volltext http://ieeexplore.ieee.org/document/8016579 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-PHY GBV_ILN_70 GBV_ILN_185 AR 35 2017 20 4425-4437 |
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Efficient Discrete Rate Assignment and Power Optimization in Optical Communication Systems Following the Gaussian Noise Model |
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Efficient Discrete Rate Assignment and Power Optimization in Optical Communication Systems Following the Gaussian Noise Model |
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Roberts, Ian |
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efficient discrete rate assignment and power optimization in optical communication systems following the gaussian noise model |
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Efficient Discrete Rate Assignment and Power Optimization in Optical Communication Systems Following the Gaussian Noise Model |
| abstract |
Computationally efficient heuristics for solving the discrete-rate capacity optimization problem for optical fiber communication systems are investigated. In the Gaussian noise nonlinearity model regime, this class of problem is an NP-hard mixed integer convex problem. The proposed heuristic minimizes the number of calls required to solve the computationally intensive problem of determining the feasibility of proposed discrete rate allocations. In a live system, optimization using this algorithm minimizes the number of potential discrete rate allocations tested for feasibility while additional discrete system capacity is extracted. In exemplary point-to-point links at 50 Gbaud with 50 Gb/s rate steps, the mean lost capacity per modem is reduced from 24.5 Gb/s with truncation to 7.95 Gb/s with discrete-rate optimization. With 25 Gb/s rate steps, the mean lost capacity is reduced from 12.3 Gb/s to 2.07 Gb/s. An unbiased metric is proposed to extend the capacity optimization objective from point-to-point links to mesh networks. A gain of 13% in distance-times-capacity metric is obtained from discrete-rate optimization with 50 Gb/s rate steps, and a 7.5% gain is obtained with 25 Gb/s rate steps. |
| abstractGer |
Computationally efficient heuristics for solving the discrete-rate capacity optimization problem for optical fiber communication systems are investigated. In the Gaussian noise nonlinearity model regime, this class of problem is an NP-hard mixed integer convex problem. The proposed heuristic minimizes the number of calls required to solve the computationally intensive problem of determining the feasibility of proposed discrete rate allocations. In a live system, optimization using this algorithm minimizes the number of potential discrete rate allocations tested for feasibility while additional discrete system capacity is extracted. In exemplary point-to-point links at 50 Gbaud with 50 Gb/s rate steps, the mean lost capacity per modem is reduced from 24.5 Gb/s with truncation to 7.95 Gb/s with discrete-rate optimization. With 25 Gb/s rate steps, the mean lost capacity is reduced from 12.3 Gb/s to 2.07 Gb/s. An unbiased metric is proposed to extend the capacity optimization objective from point-to-point links to mesh networks. A gain of 13% in distance-times-capacity metric is obtained from discrete-rate optimization with 50 Gb/s rate steps, and a 7.5% gain is obtained with 25 Gb/s rate steps. |
| abstract_unstemmed |
Computationally efficient heuristics for solving the discrete-rate capacity optimization problem for optical fiber communication systems are investigated. In the Gaussian noise nonlinearity model regime, this class of problem is an NP-hard mixed integer convex problem. The proposed heuristic minimizes the number of calls required to solve the computationally intensive problem of determining the feasibility of proposed discrete rate allocations. In a live system, optimization using this algorithm minimizes the number of potential discrete rate allocations tested for feasibility while additional discrete system capacity is extracted. In exemplary point-to-point links at 50 Gbaud with 50 Gb/s rate steps, the mean lost capacity per modem is reduced from 24.5 Gb/s with truncation to 7.95 Gb/s with discrete-rate optimization. With 25 Gb/s rate steps, the mean lost capacity is reduced from 12.3 Gb/s to 2.07 Gb/s. An unbiased metric is proposed to extend the capacity optimization objective from point-to-point links to mesh networks. A gain of 13% in distance-times-capacity metric is obtained from discrete-rate optimization with 50 Gb/s rate steps, and a 7.5% gain is obtained with 25 Gb/s rate steps. |
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Efficient Discrete Rate Assignment and Power Optimization in Optical Communication Systems Following the Gaussian Noise Model |
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