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Annonce

5 novembre 2019

[Master 2] Energy-aware partitioning for C-RAN architecture


Catégorie : Stagiaire


Contacts : Matthieu Gautier (matthieu.gautier@irisa.fr) and Robin Gerzaguet (robin.gerzaguet@irisa.fr)

Keyword: FPGA, SDR, C-RAN

Programmation skills: VHDL, C language, Linux, Vivado tools

 

1 Context

Cloud Radio Access Networks (C-RANs) have been introduced to reduce the cost of base station deployment and management [1][2]. C-RAN approach is often viewed as an architectural evolution of the distributed base station concept, which allows separating the physical location of the remote radio head (RRH) from the digital baseband unit (BBU). This helps to facilitate coordination between potentially interfering base station systems but also it allows sharing between resources of different base stations. C-RAN approach has the potential to decrease cost, energy and power consumption compared to traditional approaches and is therefore expected to be widely adopted by 5G systems. However, one of the main challenges is to determine how to separate the processing between the base station and the cloud. The RRH/BU partitioning may be different from a RRH to another. Moreover, this functional partitioning can be redistributed among time, depending on several criteria related to energy consumption, network congestion, latency and throughput. It forces to envision adaptive base station capable to cope with various configurations. It also spotlights the importance of the so-called orchestrator which is in charge of the dynamic RRH-BBU split.

2 Internship goals

In order to evaluate the efficiency of the RRH/BBU partitioning, accurate models for energy consumption, throughput and latency both at the RRH and the BBU must be proposed. Moreover, different hardware targets of the process must be considered. These models will help the orchestrator, which chooses the partitioning, for rapid prototyping. For the internship, models will be defined by considering three partitionings: from full centralized (no processing in the RRH) to full processing in the RRH, with an intermediate partitioning with few processing in the RRH (e.g. synchronization).

To this aim, the goal of the internship is to implement a basic physical layer to emulate a cellular network (e.g. FSK-like and OFDM-like) in both software core (i.e. CPU) and hardware core (i.e. FPGA). The transceiver architecture will rely on the latest generation of Software Defined Radios, ADALM-PLUTO and USRP-E310, allowing fast sampling up to 160 Msamples/s over a wide frequency range (70 MHz-6 GHz) [3]. From this, performance evaluation and dynamic reconfigurations of the C-RAN-based network will be assessed.

The internship will focus on the following steps:

- Implementing functional blocks in both software and hardware using VIVADO design suit,

- Validating network behavior with various functional splits between RRH and BBU with ADALM-PLUTO and USRP- 310 cores,

- Evaluating performance (in terms of throughput, latency and energy consumption) for different RRH-BBU splits.

References

[1] A. Checko and et al., “Cloud RAN for Mobile Networks; A Technology Overview,” IEEE Communications Surveys Tutorials, 2015.

[2] S. Barbarossa, S. Sardellitti, and P. D. Lorenzo, “Communicating While Computing: Distributed mobile cloud computing over 5G heterogeneous networks,” IEEE Signal Processing Magazine, 2014.

[3] Ettus Research, “Universal Software radio platform (USRP),” 2017. https://www.ettus.com/product/details/E310-KIT.

 

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