Spectral clustering-based energy-efficient resource allocation algorithm in heterogeneous cellular ultra-dense network
In order to solve problems of high power consumption, spectrum shortage and low energy efficiency in the ultra-intensive 5G mobile communication scenario, a resource allocation algorithm based on the maximum energy efficiency for the two-layer heterogeneous cellular non-orthogonal multiple access ne...
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| Format: | Article |
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Editorial Department of Journal on Communications
2021-07-01
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| Series: | Tongxin xuebao |
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| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021141/ |
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| author | Xue WANG Jing LIU Jiani SUN Jizhen ZHANG Zhihong QIAN |
| author_facet | Xue WANG Jing LIU Jiani SUN Jizhen ZHANG Zhihong QIAN |
| author_sort | Xue WANG |
| collection | DOAJ |
| description | In order to solve problems of high power consumption, spectrum shortage and low energy efficiency in the ultra-intensive 5G mobile communication scenario, a resource allocation algorithm based on the maximum energy efficiency for the two-layer heterogeneous cellular non-orthogonal multiple access network was proposed.The original NP-hard optimization problem on the downlink communication link of ultra-dense scene was divided into two subproblem, such as frequency resource allocation and power allocation, which became a deterministic constraint optimization problem.The frequency resource allocation scheme of different user groups was obtained by using base station clustering based on the improved k-means algorithm and users grouping based on spectral clustering algorithm.The fraction of energy efficiency optimization was transformed into a solvable continuous convex optimization problem and power distribution was realized by Dinkelbach method, and the Lagrange multiplier iterative algorithm, respectively.Jointly optimize system energy efficiency in terms of base station clustering, user grouping, resource block allocation and power allocation, which minimized the inter-cluster interference and intra-cluster interference of the base station efficiently.The simulation results show that the proposed algorithm is better on energy efficiency and computational efficiency compared with existing algorithms. |
| format | Article |
| id | doaj-art-3bafd698cdbb4ad9ad8d3d3418a7e351 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2021-07-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-3bafd698cdbb4ad9ad8d3d3418a7e3512025-01-14T07:22:34ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2021-07-014216217559744135Spectral clustering-based energy-efficient resource allocation algorithm in heterogeneous cellular ultra-dense networkXue WANGJing LIUJiani SUNJizhen ZHANGZhihong QIANIn order to solve problems of high power consumption, spectrum shortage and low energy efficiency in the ultra-intensive 5G mobile communication scenario, a resource allocation algorithm based on the maximum energy efficiency for the two-layer heterogeneous cellular non-orthogonal multiple access network was proposed.The original NP-hard optimization problem on the downlink communication link of ultra-dense scene was divided into two subproblem, such as frequency resource allocation and power allocation, which became a deterministic constraint optimization problem.The frequency resource allocation scheme of different user groups was obtained by using base station clustering based on the improved k-means algorithm and users grouping based on spectral clustering algorithm.The fraction of energy efficiency optimization was transformed into a solvable continuous convex optimization problem and power distribution was realized by Dinkelbach method, and the Lagrange multiplier iterative algorithm, respectively.Jointly optimize system energy efficiency in terms of base station clustering, user grouping, resource block allocation and power allocation, which minimized the inter-cluster interference and intra-cluster interference of the base station efficiently.The simulation results show that the proposed algorithm is better on energy efficiency and computational efficiency compared with existing algorithms.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021141/heterogeneous networkresource allocationpower allocationenergy efficiency |
| spellingShingle | Xue WANG Jing LIU Jiani SUN Jizhen ZHANG Zhihong QIAN Spectral clustering-based energy-efficient resource allocation algorithm in heterogeneous cellular ultra-dense network Tongxin xuebao heterogeneous network resource allocation power allocation energy efficiency |
| title | Spectral clustering-based energy-efficient resource allocation algorithm in heterogeneous cellular ultra-dense network |
| title_full | Spectral clustering-based energy-efficient resource allocation algorithm in heterogeneous cellular ultra-dense network |
| title_fullStr | Spectral clustering-based energy-efficient resource allocation algorithm in heterogeneous cellular ultra-dense network |
| title_full_unstemmed | Spectral clustering-based energy-efficient resource allocation algorithm in heterogeneous cellular ultra-dense network |
| title_short | Spectral clustering-based energy-efficient resource allocation algorithm in heterogeneous cellular ultra-dense network |
| title_sort | spectral clustering based energy efficient resource allocation algorithm in heterogeneous cellular ultra dense network |
| topic | heterogeneous network resource allocation power allocation energy efficiency |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021141/ |
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