基于AI算法的5G無線通信設(shè)備能耗建模方法研究
2023年電子技術(shù)應(yīng)用第4期
陸赟,,丁薇,王梓丞,,尹以雁,,楊丹,,呂沛錦,楊曉康
(中國移動通信集團(tuán)云南有限公司,,云南 昆明 650000)
摘要: 基于5G網(wǎng)管系統(tǒng)中可采集到的大量能耗,、性能指標(biāo)和基站配置數(shù)據(jù),利用機(jī)器學(xué)習(xí)算法對現(xiàn)網(wǎng)主流AAU設(shè)備建立能耗測算模型,,并對模型的準(zhǔn)確性進(jìn)行驗(yàn)證,。測試結(jié)果表明,利用該方案對現(xiàn)網(wǎng)幾款主流AAU設(shè)備建立的能耗測算模型精度都達(dá)到97%以上,,充分證明該能耗建模方法具有很高的實(shí)用性和推廣價(jià)值,。
中圖分類號:TN925+.1
文獻(xiàn)標(biāo)志碼:A
DOI: 10.16157/j.issn.0258-7998.223378
中文引用格式: 陸赟,丁薇,,王梓丞,,等. 基于AI算法的5G無線通信設(shè)備能耗建模方法研究[J]. 電子技術(shù)應(yīng)用,2023,,49(4):7-10.
英文引用格式: Lu Yun,Ding Wei,,Wang Zicheng,,et al. Research on energy consumption modeling method for 5G wireless communication equipment based on AI algorithm[J]. Application of Electronic Technique,2023,,49(4):7-10.
文獻(xiàn)標(biāo)志碼:A
DOI: 10.16157/j.issn.0258-7998.223378
中文引用格式: 陸赟,丁薇,,王梓丞,,等. 基于AI算法的5G無線通信設(shè)備能耗建模方法研究[J]. 電子技術(shù)應(yīng)用,2023,,49(4):7-10.
英文引用格式: Lu Yun,Ding Wei,,Wang Zicheng,,et al. Research on energy consumption modeling method for 5G wireless communication equipment based on AI algorithm[J]. Application of Electronic Technique,2023,,49(4):7-10.
Research on energy consumption modeling method for 5G wireless communication equipment based on AI algorithm
Lu Yun,,Ding Wei,Wang Zicheng,,Yin Yiyan,,Yang Dan,Lv Peijin,,Yang Xiaokang
(China Mobile Communications Group Yunnan Co.,, Ltd., Kunming 650000,, China)
Abstract: Based on a large amount of energy consumption, performance indicators and base station configuration data that can be collected in the 5G network management system, this paper uses machine learning algorithms to establish an energy consumption calculation model for common AAU equipment on the existing network, and verifies the accuracy of the model. The test results show that the accuracy of the energy consumption calculation models established by this scheme for several common AAU devices in the existing network has reached more than 97%, which fully proves that the energy consumption modeling method has high practicability and promotion value.
Key words : 5G base station,;AAU energy consumption;modeling,;machine learning algorithms
0 引言
隨著5G移動通信系統(tǒng)的大規(guī)模部署,,網(wǎng)絡(luò)提供更快的速率、更大的容量和更廣泛的連接的同時(shí),,通信設(shè)備功耗問題給網(wǎng)絡(luò)建設(shè)和運(yùn)維帶來了極大的困擾,。一方面,由于5G使用的頻率更高,,這使得所需要的5G基站數(shù)量相比4G更多,;另一方面,,由于5G天線采用更高的天線收發(fā)通道數(shù),5G單站功耗是4G單站的2~4倍,。為了方便對基站能耗進(jìn)行評估,,需要構(gòu)建5G基站無線主設(shè)備能耗模型,從而精確測算基站在承載不同業(yè)務(wù)負(fù)荷時(shí)的合理能耗范圍,,以此定位現(xiàn)網(wǎng)運(yùn)行的低能效設(shè)備,,識別設(shè)備的能耗異常問題,對推動5G基站節(jié)能減排工作的開展有較大的意義,。
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作者信息:
陸赟,,丁薇,王梓丞,,尹以雁,,楊丹,呂沛錦,,楊曉康
(中國移動通信集團(tuán)云南有限公司,,云南 昆明 650000)
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