DAS - Distributed antenna systems are a popular deployment strategy for increasing the coverage of mobile cellular as well as WLANs in large settings such as convention/exhibition centers, enterprises, stadiums, hospitals, etc. However, instead of simply using them as extended transmitters, these DAS systems can also be intelligently leveraged to perform a multitude of wireless transmission strategies, ranging from simple broadcast to more sophisticated network MIMO - the configuration of such strategies being orchestrated from a central controller. Such software-defined wireless access networks are critical to delivering enhanced user experience for mobile services and applications. In this project, we have designed and implemented a C-RAN system that can effectively cater to users with varying channel conditions (static and mobile users, network dynamics, etc.) by appropriately tailoring their transmission strategies, thereby resulting in a superior quality of mobile experience.

Software-defined Mobile Networks - In a cloud-driven radio access network (C-RAN), the processing of all the cells is moved to a central processing entity (cloud), while the remote ends only serves as simple radio transmission/reception units. Interestingly, this creates a new "front-haul" network (between the central processor and remote radio units) that is uniqie to C-RANs. Unlike wired networks, where software-defined networking (SDN) is related to configuring routes on the fly, the notion of "software-defined, reconfigurable" front-hauls is even more powerful in C-RANs - the configurations directly map to different wireless transmission strategies on the access network, as well as also affect the usage of computing resources in the cloud. Given this duplex effect on both the access network and the cloud, we introduce the notion of a "reconfigurable" or "software-defined" front-haul for C-RANs and show that adapting them to network traffic conditions and dynamics is critical to the success of the entire C-RAN, delivering both improved user performance  as well as cost and energy reduction for operators.