Abstract:
We are observing a revolution in wireless technology, where the society is demanding new
services, such as smart cities, autonomous vehicles, augmented reality, etc. These challenging
services not only are demanding a vast increase of data rates in the range of 1000 times higher,
but also they are real-time applications with an important delay constraint. Furthermore, an
extraordinary number of different machine-type devices will be connected to the network,
known as Internet of Things (IoT), where they will be transmitting real-time measurements
from different sensors. In this context, the Third Generation Partnership Project (3GPP) has
already developed the new Fifth Generation (5G) of mobile communication systems, which
should be capable of satisfying all the requirements. Hence, 5G will provide three key aspects,
such as: enhanced mobile broad-band (eMBB) services, massive
Area of interest in this work focus on transmitter and receiver RF propagation Channel
estimation best techniques impact analysis with respect to achievable sum rates in Massive
MIMO systems. In addition to study the massive MIMO RF propagation channels estimation
system, the interested in the Channel estimation among different type techniques: Minimum
Mean Square Error (MMSE), Zero Forcing (ZF) and Maximum Ratio Transmission (MRT)
precoding. Theoretically, the precoding is known as Space Division Multiple Access. Each
linear precoding shows the best performance with each signal power regime. For the
comparison between MRT and ZF, MRT gives better performance at low signal to noise ratio
(SNR) while ZF performs better at high SNR. MMSE gives the best channel estimation across
the entire SNR.
