"Looking into the Future of Wireless Communications: an Overview of the Massive Multiple Input Multiple Output (MIMO) Technology"

The exceptional growth in global demand for wireless traffic has led to the scarcity of the precious resources of the frequency spectrum. All this, combined with the ever-increasing number of connected users and the need for higher speed, better coverage and low latency, has motivated researchers to find effective solutions to improve the spectrum utilization and channel capacity of wireless communication systems. In this thesis, fundamental notions on Radio Spectrum (RS) are provided, introducing the concept of the Cognitive Radio (CR) technology designed to improve the use of spectrum resources. After an overview of cellular network infrastructure and their evolution over time, the main multiple access technologies such as Frequency Division Multiple Access (FDMA), Time Division Multiple Access (TDMA), Code Division Multiple Access (CDMA), Orthogonal Frequency Division Multiple Access (OFDMA) and Beam Division Multiple Access (BDMA) are discussed due to their ability to enable the efficient reuse of the limited spectrum resources. Subsequently, the reasons why Massive Multiple-Input and Multiple-Output (MIMO) technology can be used in current and future cellular networks to improve the communication performance of the systems will be detailed. Continuing this work, a comparison between different wireless scheme configurations, namely Single-Input Single-Output (SISO), Single-Input and Multiple-Output (SIMO), Multiple-Input and Single-Output (MISO) and MIMO, is illustrated, highlighting that the latter is the best among the others because, by adopting multiple antennas on both the transmitter and receiver sides, it allows transmitting and receiving multiple data streams within the same channel in the same time and frequency resources, thus improving throughput for all users and avoiding interference without additional bandwidth or transmission power. Furthermore, the fundamentals of MIMO technology and its main properties, such as diversity, multiplexing, beamforming and precoding, are analyzed. Moving on, a comparison is provided between Single User (SU)-MIMO and Multi User (MU)-MIMO, highlighting how they work and their differences. Finally, Massive MIMO technology is analyzed in this thesis, since it has been proposed as a key enabler for next-generation applications, as it is expected to provide more advantages over other current solutions by using a large number of antennas on both the transmitting and receiving side, thus improving the overall efficiency. In particular, this technology can improve the throughput, capacity, coverage, spectral and energy efficiency of a wireless system using relatively simple processing, together with the advantage of being built using low-cost and low-power components. Despite its potential advantages, this work also summarizes some challenges faced by Massive MIMO implementations such as pilot contamination, channel estimation, precoding, user scheduling, hardware impairments, and signal detection. The integration of Artificial Intelligence (AI) into the Massive MIMO system is presented as a way to solve its various challenges and improve the overall wireless communication system. Finally, examples of different applications based on Massive MIMO that can be useful in people’s daily lives are discussed, as it will be the key technology of any wireless communication standard in the near future.