Dense Deployments for Green Networks (DENSE4GREEN)
Dense Deployments for Green Networks
Date du début: 1 juil. 2013,
Date de fin: 30 juin 2015
The exponential growth in demand for higher data rates in wireless networks requires a massive network densification that is neither economically or ecologically viable with the current cellular architectures. This has stimulated an intense research activity in green or energy-efficient cellular networks. In this regard, a promising solution is inspired to the concept of small-cell networks, which is founded on the idea of a very dense and heterogeneous deployment of operator-installed low-cost and low-power base stations connected via a backhaul infrastructure, endowed with multiple antennas, and equipped with cooperative and cognitive technologies. Although promising, this new concept makes the cellular architecture increasingly complex and poses many issues. Interference management is one of the many technical challenges that must be dealt while designing such networks. The objective of this fellowship lies in identifying and posing in the right modeling perspective the theoretical performance of such interference-limited networks and in finding the algorithmic solutions to approach those limits. The methodology of investigation uses many of the mathematical tools that have been recently proved so useful (random matrix theory, cooperative game theory, and stochastic geometry). The research will be conducted in close collaboration with some of the leading experts in the field, thereby ensuring a step-by-step research-through-training activity that from the analysis of the state of the art will guide me towards the objectives of this fellowship. The latter are briefly summarized as follows: 1) To broaden the application of the investigated mathematical tools in order to derive tractable and general models for dense heterogeneous networks; 2) To provide conceptual insights on the design of efficient communication technologies for the deployment of small-cell networks; 3) To understand the energy-efficiency limits of beyond-LTE wireless networks.
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