Elementary Properties of Positive Concave Mappings with Applications to Network Planning and Optimization

Abstract

This study presents novel methods for computing fixed points of positive concave mappings and for characterizing the existence of fixed points. These methods are particularly important in planning and optimization tasks in wireless networks. For example, previous studies have shown that the feasibility of a network design can be quickly evaluated by computing the fixed point of a concave mapping that is constructed based on many environmental and network control parameters such as the position of base stations, channel conditions, and antenna tilts. To address this and more general problems, given a positive concave mapping, we show two alternative but equivalent ways to construct a matrix that is guaranteed to have spectral radius strictly smaller than one if the mapping has a fixed point. This matrix is then used to build a new mapping that preserves the fixed point of the original positive concave mapping. We show that the standard fixed point iterations using the new mapping converges faster than the standard iterations applied to the original concave mapping. As exemplary applications of the proposed methods, we consider the problems of power and load planning in networks based on the orthogonal frequency division multiple access (OFDMA) technology.

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• Fundamental properties of solutions to utility maximization problems in wireless networks
• The role of asymptotic functions in network optimization and feasibility studies
• (In)Existence of Equilibria for 2-Players, 2-Values Games with Concave Valuations
• Robust Cell-Load Learning with a Small Sample Set
• Resource Optimization with Load Coupling in Multi-cell NOMA
• Improving Resource Efficiency with Partial Resource Muting for Future Wireless Networks
• Spatial Mappings for Planning and Optimization of Cellular Networks