GPU-ENABLED SOFTWARE ENVIRONMENT FOR PERFORMANCE SIMULATION OF SC MACRODIVERSITY SYSTEM WITH TWO MICRODIVERSITY MRC RECEIVERS IN THE PRESENCE OF κ-µ FADING

In this paper, the outage probability (P out ) of the selection combining (SC) macrodiversity (MD) system with two maximal ratio combining (MRC) microdiversity (mD) receivers in Gamma shadowed κ - µ fading environment is investigated. Each mD receiver has L input branches. For this system model, analytical expression for the probability density function (PDF) of the signal to noise ratio (SNR) at the output of the MD SC receiver, and the P out of the MD SC receiver are calculated. The obtained results are graphically presented to accentuate parameters influence to the system performance. Finally, the P out expression is adopted for purpose of quality of service (QoS) estimation inside Graphics Processing Unit (GPU) enabled software simulation environment aiming optimal planning of mobile networks in smart cities making use of deep learning for demand prediction and linear optimization.