CU placement over a reconfigurable wireless fronthaul in 5G networks with functional splits

Davit Harutyunyan, Roberto Riggio, Slawomir Kuklinski and Toufik Ahmed

International Journal of Network Management, 2020, vol. 30, issue 1

Abstract: Mobile network operators are currently facing a tremendous increase in the level of data traffic. Although cell size reduction is one of the most common ways used to accommodate such traffic demand, densely deployed small cells also dramatically increase the level of intercell interference. By centralizing baseband signal processing at powerful computing infrastructures, called centralized unit (CU) pools, cloud radio access network (C‐RAN) enables advanced coordination algorithms to be employed in dense small cell networks. In C‐RAN, due to stringent bandwidth and latency requirements at the fronthaul links, the optical fiber, thanks to its bandwidth and latency characteristics, continues to be the most prevalent fronthaul medium option. Nevertheless, the optical fiber is one of the fronthaul options, while C‐RAN (physical layer radio frequency [PHY‐RF] split) is one of the functional splits that can be defined each coming with different fronthaul requirements. In this paper, we formulate and solve a dynamic CU placement problem for mobile networks as an integer linear programming (ILP) problem. In the considered network, CU pools are placed at the edges of the network, and a reconfigurable millimeter wave (MMW) wireless fronthaul links are used in order to provide decentralized units (DUs) with connectivity. We study the impact of different functional splits on the placement cost and on the acceptance ratio using different substrate networks. Lastly, we propose and evaluate a CU placement heuristic algorithm using a numerical simulator. The results reveal that the optimal functional split selection can lead to significant resource utilization benefits in the RAN.

Date: 2020
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https://doi.org/10.1002/nem.2086

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Persistent link: https://EconPapers.repec.org/RePEc:wly:intnem:v:30:y:2020:i:1:n:e2086

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