Stochastic Geometry Analysis of Multi-Antenna Wireless Networks
This book presents a unified framework for the tractable analysis of large-scale, multi-antenna wireless networks using stochastic geometry. This mathematical analysis is essential for assessing and understanding the performance of complicated multi-antenna networks, which are one of the foundations of 5G and beyond networks to meet the ever-increasing demands for network capacity. Describing the salient properties of the framework, which makes the analysis of multi-antenna networks comparable to that of their single-antenna counterparts, the book discusses effective design approaches that do not require complex system-level simulations. It also includes various application examples with different multi-antenna network models to illustrate the framework’s effectiveness.
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actual antenna pattern ad hoc networks analysis of multi-antenna analytical framework analytical results approximation beamforming cellular networks channel Commun Corollary cosine antenna pattern coverage improvement coverage probability denoted deploying derived directional antenna directional antenna arrays downlink energy efficiency expression function gamma distributed given HetNets hoc networks homogeneous PPP IEEE IEEE Trans increases J.G. Andrews Laplace transform Lemma link reliability log-Laplace transform lower bound lower triangular Toeplitz mm-wave ad hoc mm-wave cellular networks mm-wave networks multi-antenna networks multi-antenna wireless networks multiuser network model network performance number of antennas optimal BS density outage probability parameter performance analysis point process Poisson power series precoding Proof Proposition random Rayleigh fading Sect signal power gain simulation single-antenna networks SINR SIR coverage probability small cell networks spatial spectral efficiency stochastic geometry techniques Theorem Toeplitz matrix tractable triangular Toeplitz matrix typical receiver typical user Wirel Zhang