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The role of asymptotic functions in network optimization and feasibility studies

: Cavalcante, R.L.G.; Stanczak, S.


Institute of Electrical and Electronics Engineers -IEEE-; IEEE Signal Processing Society:
IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017. Proceedings : November 14-16, 2017, Montreal, Quebec, Canada
Piscataway, NJ: IEEE, 2018
ISBN: 978-1-5090-5990-4
ISBN: 978-1-5090-5989-8
ISBN: 978-1-5090-5991-1
Global Conference on Signal and Information Processing (GlobalSIP) <5, 2017, Montréal>
Conference Paper
Fraunhofer HHI ()

Solutions to network optimization problems have greatly benefited from developments in nonlinear analysis, and, in particular, from developments in convex optimization. A key concept that has made convex and nonconvex analysis an important tool in science and engineering is the notion of asymptotic function, which is often hidden in many influential studies on nonlinear analysis and related fields. Therefore, we can also expect that asymptotic functions are deeply connected to many results in the wireless domain, even though they are rarely mentioned in the wireless literature. In this study, we show connections of this type. By doing so, we explain many properties of centralized and distributed solutions to wireless resource allocation problems within a unified framework, and we also generalize and unify existing approaches to feasibility analysis of network designs. In particular, we show sufficient and necessary conditions for mappings widely used in wireless communication problems (more precisely, the class of standard interference mappings) to have a fixed point. Furthermore, we derive fundamental bounds on the utility and the energy efficiency that can be achieved by solving a large family of max-min utility optimization problems in wireless networks.