Optimization of NOMA Downlink Network Parameters under Harvesting Energy Strategy Using Multi-Objective GWO
Non-orthogonal multiple access technique (NOMA) is based on the principle of sharing the same physical resource, over several power levels, where user’s signals are transmitted by using the superposition-coding scheme at the transmitter and these users signals are decoded by the receiver by means of...
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| Format: | Article |
| Language: | English |
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Spolecnost pro radioelektronicke inzenyrstvi
2023-12-01
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| Series: | Radioengineering |
| Subjects: | |
| Online Access: | https://www.radioeng.cz/fulltexts/2023/23_04_0492_0501.pdf |
| _version_ | 1797392291224092672 |
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| author | F. Titel M. Belattar |
| author_facet | F. Titel M. Belattar |
| author_sort | F. Titel |
| collection | DOAJ |
| description | Non-orthogonal multiple access technique (NOMA) is based on the principle of sharing the same physical resource, over several power levels, where user’s signals are transmitted by using the superposition-coding scheme at the transmitter and these users signals are decoded by the receiver by means of successive interference cancellation technique (SIC). In this work, performance of NOMA Downlink network under Rayleigh fading distribution is studied, in the power domain where a power beacon (PB) is used to help a base station (BS) to serve distant users, by Wireless Power Transfer (WPT). The harvested energy permits by the BS, supports information signal transmission to NOMA users. This concept can be an effective way to power Internet of Things (IoT) devices, reduce battery dependency, and promote energy sustainability and may be used in SWIPT systems and vehicular networks. To improve the key performance indicators of the system expressed by the outage performance of NOMA users and system throughput, a Multi-Objective Grey Wolf Optimizer algorithm (MOGWO) is used to find optimal values of several influencing parameters. These parameters are partition time expressing the harvesting energy time, the power conversion factor and power allocation coefficients. |
| first_indexed | 2024-03-08T23:46:05Z |
| format | Article |
| id | doaj.art-e08d848edbff4497b3b8469c750e7edf |
| institution | Directory Open Access Journal |
| issn | 1210-2512 |
| language | English |
| last_indexed | 2024-03-08T23:46:05Z |
| publishDate | 2023-12-01 |
| publisher | Spolecnost pro radioelektronicke inzenyrstvi |
| record_format | Article |
| series | Radioengineering |
| spelling | doaj.art-e08d848edbff4497b3b8469c750e7edf2023-12-13T22:27:59ZengSpolecnost pro radioelektronicke inzenyrstviRadioengineering1210-25122023-12-01324492501Optimization of NOMA Downlink Network Parameters under Harvesting Energy Strategy Using Multi-Objective GWOF. TitelM. BelattarNon-orthogonal multiple access technique (NOMA) is based on the principle of sharing the same physical resource, over several power levels, where user’s signals are transmitted by using the superposition-coding scheme at the transmitter and these users signals are decoded by the receiver by means of successive interference cancellation technique (SIC). In this work, performance of NOMA Downlink network under Rayleigh fading distribution is studied, in the power domain where a power beacon (PB) is used to help a base station (BS) to serve distant users, by Wireless Power Transfer (WPT). The harvested energy permits by the BS, supports information signal transmission to NOMA users. This concept can be an effective way to power Internet of Things (IoT) devices, reduce battery dependency, and promote energy sustainability and may be used in SWIPT systems and vehicular networks. To improve the key performance indicators of the system expressed by the outage performance of NOMA users and system throughput, a Multi-Objective Grey Wolf Optimizer algorithm (MOGWO) is used to find optimal values of several influencing parameters. These parameters are partition time expressing the harvesting energy time, the power conversion factor and power allocation coefficients.https://www.radioeng.cz/fulltexts/2023/23_04_0492_0501.pdfbase stationoutage probabilitypower beaconthroughputwireless power transfermulti-objective optimizationgrey wolf optimizer (gwo)multi-objective grey wolf optimizer (mogwo)pareto optimal solutions |
| spellingShingle | F. Titel M. Belattar Optimization of NOMA Downlink Network Parameters under Harvesting Energy Strategy Using Multi-Objective GWO Radioengineering base station outage probability power beacon throughput wireless power transfer multi-objective optimization grey wolf optimizer (gwo) multi-objective grey wolf optimizer (mogwo) pareto optimal solutions |
| title | Optimization of NOMA Downlink Network Parameters under Harvesting Energy Strategy Using Multi-Objective GWO |
| title_full | Optimization of NOMA Downlink Network Parameters under Harvesting Energy Strategy Using Multi-Objective GWO |
| title_fullStr | Optimization of NOMA Downlink Network Parameters under Harvesting Energy Strategy Using Multi-Objective GWO |
| title_full_unstemmed | Optimization of NOMA Downlink Network Parameters under Harvesting Energy Strategy Using Multi-Objective GWO |
| title_short | Optimization of NOMA Downlink Network Parameters under Harvesting Energy Strategy Using Multi-Objective GWO |
| title_sort | optimization of noma downlink network parameters under harvesting energy strategy using multi objective gwo |
| topic | base station outage probability power beacon throughput wireless power transfer multi-objective optimization grey wolf optimizer (gwo) multi-objective grey wolf optimizer (mogwo) pareto optimal solutions |
| url | https://www.radioeng.cz/fulltexts/2023/23_04_0492_0501.pdf |
| work_keys_str_mv | AT ftitel optimizationofnomadownlinknetworkparametersunderharvestingenergystrategyusingmultiobjectivegwo AT mbelattar optimizationofnomadownlinknetworkparametersunderharvestingenergystrategyusingmultiobjectivegwo |