Gestion d'interférence pour les réseaux favorables à l'environnement

Brief description of project

Achieving efficient wireless communications is widely believed to be pivotal in advancing important milestones in societies that value information and the environment.  Such networks though, in the presence of a large number of users, can become an enormous environmental burden, given the massive amounts of power that is required both for transmitting signals as well as for supporting the intense computational process that take place.  It has been well established that in such large networks, interference between nodes is a central bottleneck - which together with algorithmic complexity, take up the lion's share of the power costs.  The main volume of research in reducing multiuser interference has up to date focused on specifically exploring novel interference management techniques in settings that are simplistic, under very simplifying and extreme assumptions on the amount of channel knowledge at the nodes, and in the absence of considerations regarding implementation complexity which can often be entirely prohibitive.

There are two major aspects that clearly set the IMAGE-NET project apart from the existing volume of prior research.  The first aspect is that we take a unifying view of interference and complexity, which allows us to consider interference management solutions under strict delay and complexity constraints.  This approach is imperative given that a large fraction of the current state of art in interference management is far from being practically implementable.  The second aspect that sets this proposal apart is that we adopt a unifying view of the different methods of interference management, each defined by varying degrees of channel knowledge at the interfering nodes, as well as by varying capabilities of the different nodes.  At the two extremes of this spectrum lie powerful but impractical interference alignment solutions that often require astronomical complexity, and on the other extreme lie very rare instances were simple linear solutions result in optimal interference management. We view these jointly.  These differentiating aspects help us provide both theoretical tools for analysis-and-optimization in wireless networks of interfering users, as well as help us provide clear breakthroughs towards computationally efficient implementation of the novel interference management methods.

To achieve this objective we focus on specific key subareas. The first relates to the fundamental tradeoff between interference management and feedback quality, and seeks to understand the behavior of interference management schemes under varying degrees of channel state information at the transmitter (CSIT), i.e., under reduced and imperfect CSIT. Another major aspect corresponds to how such CSIT can be properly and efficiently disseminated in large networks. Thirdly we will also search for a unified view by studying the fundamental tradeoff between performance-delay-complexity in interference networks, and then proceed to propose algorithms that are properly designed to meet this tradeoff.


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Image-Net ANR Project.