Cloud Radio Access Networks

Project Description

Next-generation wireless cellular systems are expected to undergo a radical paradigm shift, which is akin to the revolution brought forth by clouding computing in computer networks. As cloud computing prescribes the physical separation of user-centric data input/output and remote computing, cloud radio access networks (C-RANs) separate distributed and localized radio transmission/reception units from centralized information processing nodes.

In a basic C-RAN, radio units (RUs), such as macro-, pico- and home-base stations, provide the wireless interface between the operator’s network and the mobile devices. However, unlike in conventional cellular systems, the RUs do not implement the information processing functionalities needed to encode and decode information on the wireless channel. Instead, information processing is carried out remotely within the “cloud” of the operator’s network. This migration of computing to the cloud is enabled by a network of backhaul links that connect the radio units both among themselves and to control units (CUs) within the cloud.

The centralization of information processing afforded by C-RANs enables effective interference management at the geographical scale covered by the distributed radio units. This in turn promises to be a key component of the solution to the so called “spectrum crunch” problem.  However, the main roadblock to the realization of the mentioned promises of C-RANs hinges on the effective integration of the wireless interface provided by the radio units with the backhaul network that links the radio units and information processing nodes within the cloud.  The goal of this research is to investigate advanced integration strategies based on network information theoretic principles.

People

Faculty: Osvaldo Simeone

Post-Doc: Seok-Hwan Park

Visiting Student: Jinkyu Kang (KAIST)

Collaborators: Shlomo Shamai (Technion), Onur Sahin (InterDigital), Joonhyuk Kang

(KAIST)

Support

InterDigital, Vienna Science and Technology Fund