It is widely recognized that one of the factors that are going to yield the most significant capacity increase in wireless networks is spatial reuse of radio resources through dense deployment of radio access points. This leads to the development of small cell networks where different size cells, e.g. macro cells, picocells, femtocells, relays, coexist under the same standard. Of course, dense deployment is able to unravel its potential benefits only provided that interference is properly managed. In this paper, we propose an algorithm able to perform cell association and radio resource allocation jointly, in order to maximize the sum rate in a MIMO (interference) network. Cell selection is inherently a combinatorial problem. To deal with the nonconvexity, we introduce a suitably chosen convex relaxation of the objective function and develop a fast algorithm converging to a locally optimal solution of the nonconvex problem. © 2014 IEEE.
Joint cell selection and radio resource allocation in MIMO small cell networks via successive convex approximation / Sardellitti, S.; Scutari, G.; Barbarossa, S.. - (2014), pp. 850-854. (Intervento presentato al convegno 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 tenutosi a Florence; italy) [10.1109/ICASSP.2014.6853717].
Joint cell selection and radio resource allocation in MIMO small cell networks via successive convex approximation
Sardellitti S.;Barbarossa S.
2014
Abstract
It is widely recognized that one of the factors that are going to yield the most significant capacity increase in wireless networks is spatial reuse of radio resources through dense deployment of radio access points. This leads to the development of small cell networks where different size cells, e.g. macro cells, picocells, femtocells, relays, coexist under the same standard. Of course, dense deployment is able to unravel its potential benefits only provided that interference is properly managed. In this paper, we propose an algorithm able to perform cell association and radio resource allocation jointly, in order to maximize the sum rate in a MIMO (interference) network. Cell selection is inherently a combinatorial problem. To deal with the nonconvexity, we introduce a suitably chosen convex relaxation of the objective function and develop a fast algorithm converging to a locally optimal solution of the nonconvex problem. © 2014 IEEE.File | Dimensione | Formato | |
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