R. Yu, G. Xue, M. Bennis, X. Chen and Z. Han, "HSDRAN: Hierarchical Software-Defined Radio Access Network for Distributed Optimization," in IEEE Transactions on Vehicular Technology, vol. 67, no. 9, pp. 8623-8636, Sept. 2018. doi: 10.1109/TVT.2017.2691735
HSDRAN : hierarchical software-defined radio access network for distributed optimization
|Author:||Yu, Ruozhou1; Xue, Guoliang1; Bennis, Mehdi2;|
1Arizona State University, Tempe, AZ 85287, USA
2University of Oulu, Oulu 90014, Finland
3VTT Technical Research Centre of Finland, Oulu 90570, Finland
4University of Houston, Houston, TX 77004 USA
|Online Access:||PDF Full Text (PDF, 0.9 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe202002246188
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2020-02-24
The drastic growth of mobile traffic greatly challenges the capacity of mobile infrastructures. Dense deployment of low-power small cells helps alleviate the congestion in the radio access network, yet it also introduces large complexity for network management. Software-defined radio access network has been proposed to tackle the added complexity. However, existing software-defined solutions rely on a fully centralized control plane to make decisions for the whole network, which greatly limits the scalability and responsiveness of the control plane. In this paper, we propose a hierarchical software-defined radio access network architecture. The proposed architecture leverages the hierarchical structure of radio access networks, deploying additional local controllers near the network edge. Utilizing the intrinsic locality in radio access networks, it offloads control tasks from the central controller to local controllers with limited overhead introduced. Under the architecture, a distributed optimization framework is proposed, and a typical optimization problem is studied to illustrate the effectiveness of the proposed architecture and framework. Both analysis and experiments validate that the proposed architecture and framework can improve the network objective during the optimization, meanwhile balancing load and improving scalability and responsiveness.
IEEE transactions on vehicular technology
|Pages:||8623 - 8636|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work was supported in part by the NSF Grants 1646607, 1547201, 1456921, 1443917, 1405121, 1457262, and 1461886, and in part by the TEKES Grants 2364/31/2014 and 2368/31/2014.
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