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Today’s Radio Access Networks (RANs) face: Increasing capacity needs vs. falling revenues per user. Large base stations deployments of high costs
(CAPEX/OPEX) and power consumption. Resources dimensioned for peak traffic loads. Large fibre availability in urban areas.
[GSMA, The Mobile Economy 2013]
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60% network costs come from RAN (site rental, energy, maintenance). still, traffic varies strongly geographically and temporally (20% of BS carry 50% traffic, while 50% of BSs generate 10% revenue). in Orange France LTE backhaul, 86% of sites (in blue) within 10 km of central offices (in green). Central offices are connected up to 28 sites.
The Mobile Cloud Networking (MCN) project aims to extend the cloud computing paradigm to communication networks, leading to efficient resources’ exploitation.
MCN aims at offering RAN-as-a-Service (RANaaS): Cloud-based, on-demand, elastic, adaptable to load
In Cloud-RAN (C-RAN), base stations are split into: Remote Radio Head (RRH), a hardware component. Base Band Unit (BBU), software-based.
RRHs and BBUs are linked by an optical fronthaul. Aims fast, cost- and energy-efficient deployments.
BBUs
RRHs
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cheap and small RRHs in almost infrastructure-less sites, with all the digital processing being elastically supported by cloud-based data-centres 1/3 roll-out time Reduction of 15% CAPEX and 50% OPEX 71% energy saving
Currently, BBUs run on custom dedicated hardware platforms.
RANaaS aims to extend C-RAN by: Taking advantage of general purpose platforms. Integrating virtualisation and the cloud paradigms. Using shared computation, storage and networking
BBU has various dimensions and dependencies, characterised by diferent processing loads.
Processing in BBU
Downlink Uplink
PHY
MAC
Usage characteristics – number of users – traffic profile
System characteristics – Bandwidth [MHz] – Modulation and Coding
Scheme (MCS) – number of antennas.
BBU
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leading to expect different processing requirements for downlink and uplink at the eNB. Common for all users: (e.g., OFDM signal generation) per user: (e.g., modulation and coding).
Virtual Machine (VM) – e.g., KVM: Virtualisation infrastructure that emulates a physical
computing environment (guest). Managed by a hypervisor running on top of the
infrastructure (host).
Virtualisation Environment (VE) – e.g., LXC and Docker: No hardware emulation nor hypervisor (containers). Bare metal performance characteristics, relying on OS’s
Results for a different machine settings. KVM is unpredictable, even RT! LXC/Docker performance shall be similar to RTLinux.
BBU Processing Distribution (2)
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RT-OAI: kernel is low latency and OAI process is prioritised Example processing times at the UL eNB for BW=20MHz, MCS=16 UL is most time consuming (decoding)
LXC/Docker proved to provide a bar metal performance: Exploit native Linux Features. Does not require a hypervisor. Lightweigth, lower overhead and potentially better
performance. LXC/Docker ecosystem: Growing popularity, promising! Integration with OpenStack.
Limitation: Does not support multi-OS. Require support from the host OS.
Based on a Heat orchestration Template (HoT), Heat orchestrator uses OpenStack control plane to build Heat stack, a composite environment (web services, HSS, EPC and eNB). LXC provides a VE in OpenStack. environment.
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Resource provisioning: Uses HoT to call Nova, Glance and Neutron to build the heat stack OpenStack has drives for KVM, LXC, Docker, etc. configurable for the user LXC provides a VE in Openstack. LXC builds a container in the OS where components’ images are put. OpenStack deploys it, creating dedicated directories, and starts the containers. Binaries in the container are natively executed in the kernel by the host.
RANaaS aims to integrate virtualisation and cloud paradigms.
C-RAN software-based base-stations (BBUs) have critical processing requirements.
The feasibility to run a single BBU on a GPP platform was evaluated using OAI LTE base station emulator: BBU processing has multiple dependencies, the heaviest
being uplink decoding. LXC and Docker are lightweight virtualization
environments that outperform KVM. A prototype of RANaaS was presented, based on Heat,
OpenStack and Linux Containers. It is a promising approach.