Mathematical Methods for Wireless Communications

This chapter provides a mathematical background to define a mathematical model of cellular systems, and design and optimize wireless communications. It describes the approximation problems and establishes a solution in vector spaces. The chapter reviews some important matrix factorization. Most matrix computation from original data is not easy to calculate in an explicit way. Matrix factorization (or decomposition) allows us to rephrase some matrix forms in such a way that they can be solved more easily. Various matrix decompositions covered include lower upper decomposition, Cholesky decomposition, QR decomposition, and singular value decomposition. The chapter explains the least square algorithm in the context of a regression problem. Regression analysis is a useful tool for forecasting, error reduction or data analysis.