On-demand Physical Layer Cooperation

Principal investigator (UCLA): Suhas Diggavi (UCLA), Christina Fragouli (UCLA), Ayfer Ozgur (Stanford)

Sponsor: National Science Foundation (NSF) Project Award #: 1514531

CIF:Medium:Collaborative Research:An Information-theoretic approach to nanopore sequencing

Project timeline: 2015-2019

Project synopsis: Wireless access is fast becoming the primary portal to the Internet, causing an exponentially rising demand for wireless data. This has pushed current wireless systems to their limits, despite significant investment in infrastructure to meet the ever-growing demands. Physical layer cooperation can enable near-optimal usage of the available wireless bandwidth.

This proposal fundamentally rethinks physical-layer cooperation by introducing an on-demand approach to wireless cooperation. It can be argued that the success of the (wired) Internet was made possible by its on-demand operation, using adaptation, local knowledge, feedback and a best-effort service model. Notably, the success of many peer-to-peer network protocols is closely tied to on-demand information propagation and adaptation of the network. The broad goal of this proposal is to bring this philosophy to wireless networks, enabling near-optimal usage of the wireless network bandwidth within the complexity constraints of implementable systems. This project aims to complement the theoretical work with proof-of-concept deployments on software radio testbeds, and also engage industry partners to impact next-generation wireless network designs. The project also promotes training of research engineers, through a plan to establish a unique inter-university education and research program, which will include joint and collaborative student advising and curricular development.

The underlying assumption of most network information theory works is that one can build architectures which tightly coordinate the estimation and sharing of information about the wireless channels, the user requirements and the network topology, at a very fast time-scale, without impacting the performance (rates, error). That is, the cost of learning the very dynamic network state is not accounted for. Another implicit assumption is complete network usage, that all available relays in a wireless network are used, with no adaptation to user demand. This can be very wasteful in many situations, and again, the cost of unnecessarily using relays is not accounted for. The many breakthrough ideas based on these assumptions have advanced a collective understanding, but bringing physical layer cooperation techniques closer to practical networks requires additional steps to move beyond these assumptions. This project puts together a program that develops the theoretical foundations and practice of an on-demand network operation, that dispenses with these assumptions. This entails operating specific subsets of the network relays (sub-networks) that fulfill target rates, as opposed to using all network relays to achieve the best possible performance. This project constructs a theoretical understanding of how to select, adapt and operate these sub-networks on demand, by using accountable partial network knowledge and using feedback mechanisms to enhance signal adaptation to the unknown. The theoretical formulations are tightly coupled to implementable protocols that will be validated in test beds.