科研进展

Statistical Multiplexing Gain Analysis of Centralized Open Radio Access Networks with Limited Cells and Heterogeneous Traffics(刘亚锋等)

发布时间:2025-07-03

Centralized open radio access networks (O-RANs) aggregate computing resources of multiple cells to improve resource utilization and achieve statistical multiplexing gain (SMG), i.e., the ratio of the number of deployed resources (DepR) for distributed radio access network (D-RAN) to that for O-RAN. SMG of O-RAN has been investigated with infinite number of cells with homogeneous bursty-temporal traffic features. However, in practice, the number of cells is limited, and in the era of Internet of Things (IoT), cells with heterogeneous bursty-temporal traffics (het-traffics), should be considered. This paper analyzes the SMG of O-RAN with limited het-traffic cells. First of all, given traffic models of het-traffic cells following different bursty lognormal distribution and periodic time-varying features, required resources (ReqR) for D-RAN can be derived. Then, to obtain the distribution of ReqR for O-RAN with limited het-traffic cells, a Gaussian mixture model (GMM) based resource distribution approximation (GMM-RDA) is proposed. Thus SMG can be obtained for any given service rate. In simulations, the effectiveness of GMM-RDA is verified by Kolmogorov-Smirnov (K-S) test, and the accuracy of achieved SMG can be up to 99.7%, which is about 33% higher than that obtained by the law of large numbers (LLN) for infinite cells. Moreover, het-traffic cells resulting from service diversification can enhance SMG in O-RAN by 34.7%.


Authors:

Lu Wang

    National Key Laboratory of Transient Impact,Beijing 102202,China.

    No. 208 Research Institute of China Ordnance Industries,Beijing 102202,China.

    State Key Lab of Processors, Institute of Computing Technology,Chinese Academy of Sciences, Beijing 100190,China.

    Email: wanglu01@ict.ac.cn


Yiqing Zhou

    University of Chinese Academy of Sciences,Beijing 100049,China.

    State Key Lab of Processors,Institute of Computing Technology,Chinese Academy of Sciences,Beijing 100190,China.

    Beijing Key Laboratory of Mobile Computing and Pervasive Device,Beijing 100190,China.

    Email:zhouyiqing@ict.ac.cn


Ya-Feng Liu

    State Key Laboratory of Scientific and Engineering Computing.

    Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China

    Email: yafliu@lsec.cc.ac.cn


Ling Liu

University of Chinese Academy of Sciences,Beijing 100049,China.

State Key Lab of Processors,Institute of Computing Technology,Chinese Academy of Sciences,Beijing 100190,China.

Beijing Key Laboratory of Mobile Computing and Pervasive Device,Beijing 100190,China

Email: liuling@ict.ac.cn


Ningzhe Shi

University of Chinese Academy of Sciences,Beijing 100049,China.

State Key Lab of Processors,Institute of Computing Technology,Chinese Academy of Sciences,Beijing 100190,China.

Beijing Key Laboratory of Mobile Computing and Pervasive Device,Beijing 100190,China

Email: shiningzhe21b@ict.ac.cn


Lin Tian

    Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China.

    Nanjing Institute of InforSuperBahn, Nanjing 211100, China.

    University of Chinese Academy of Sciences, Beijing 100049, China.

    Email: tianlindd@ict.ac.cn


Jinglin Shi

University of Chinese Academy of Sciences,Beijing 100049,China.

State Key Lab of Processors,Institute of Computing Technology,Chinese Academy of Sciences,Beijing 100190,China.

Beijing Key Laboratory of Mobile Computing and Pervasive Device,Beijing 100190,China

Email:sjl@ict.ac.c


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