mm‐Wave micro‐wave integrated Sub‐RAN for CRAN performance enhancement

Analysis of mmWave Performance

Coverage Enhancement for mmWave Communications using Passive Reflectors

Millimeter wave (mmWave) technology is expected to dominate the future 5G networks mainly due to large spectrum available at these frequencies. However, coverage deteriorates significantly at mmWave frequencies due to higher path loss, especially for the non-line-of-sight (NLOS) scenarios. In this work, we explore the use of passive reflectors for improving mmWave signal coverage in NLOS indoor...

Repository CRAN

Repository CRAN

Title Distributions to be used for GAMLSS modelling. Description This package contains the distributions for GAMLSS modelling.

Deep Reinforcement Learning for Improving Downlink mmWave Communication Performance

We propose a method to improve the DL SINR for a single cell indoor base station operating in the millimeter wave frequency range using deep reinforcement learning. In this paper, we use the deep-Q reinforcement learning models to arrive at optimal sequences of actions to improve the cellular network SINR value from a starting to a feasible target value. While deep reinforcement learning has be...