Very large MIMO systems use arrays with significantly more antennas than current systems, enabling unprecedented performance in terms of data rate and link reliability. The performance of MIMO systems depends on the number of transmit and receive antennas, with more antennas providing more degrees of freedom in the propagation channel. In quasi-static channels, the reliability of a point-to-point MIMO link scales with the number of antennas, while in rapidly varying channels, the achievable rate scales with the minimum of the number of transmit and receive antennas. Multiuser systems benefit from the ability to transmit simultaneously to multiple users and schedule them efficiently. The challenges of MIMO include increased hardware complexity, signal processing complexity, and energy consumption. Very large MIMO systems require a large number of antennas, which increases the physical space needed and the power consumption. However, very large MIMO systems can significantly reduce power consumption by distributing the power among many antennas. The system can also be made highly robust, as the failure of a few antennas does not significantly affect the overall performance. Very large MIMO systems have the potential to achieve high data rates and improve system performance under the same regulatory power constraints. They can also reduce energy consumption, which is a growing concern for cellular base stations. Additionally, very large MIMO systems can eliminate the need for expensive and bulky components like large coaxial cables. The large-number-of-antennas regime has been of academic interest, but recent research has shown that practical system aspects in this regime are important. For example, a time-division multiplexing cellular system with very large MIMO can support over 40 single-antenna users with high throughput. The asymptotics of random matrix theory play a significant role in very large MIMO systems, leading to deterministic behavior and well-conditioned matrices. The performance of very large MIMO systems is influenced by the number of antennas, the propagation environment, and the channel properties. The system can achieve high data rates when the number of antennas is large and the propagation environment is favorable. However, the system is limited by interference and the need for accurate channel state information. The use of time-reversal techniques can focus power to a specific point in space, improving system performance. Very large MIMO systems also have implications for antenna design and propagation. The performance of the system depends on the antenna array's ability to exploit the propagation environment. The number of antennas and their spacing affect the system's performance, with more antennas and better spacing leading to improved performance. However, the system is limited by the physical constraints of the antenna array and the propagation environment. The paper discusses the information-theoretic performance limits of very large MIMO systems, the practical algorithms used in these systems, and the influence of channel properties on system performance. It also addresses the practical constraints on antenna arrangements and the challenges of implementing very large MIMO systems. The paper concludes that very large MIMO systems have the potential to significantly improve system performance and reduce energy consumption, but they alsoVery large MIMO systems use arrays with significantly more antennas than current systems, enabling unprecedented performance in terms of data rate and link reliability. The performance of MIMO systems depends on the number of transmit and receive antennas, with more antennas providing more degrees of freedom in the propagation channel. In quasi-static channels, the reliability of a point-to-point MIMO link scales with the number of antennas, while in rapidly varying channels, the achievable rate scales with the minimum of the number of transmit and receive antennas. Multiuser systems benefit from the ability to transmit simultaneously to multiple users and schedule them efficiently. The challenges of MIMO include increased hardware complexity, signal processing complexity, and energy consumption. Very large MIMO systems require a large number of antennas, which increases the physical space needed and the power consumption. However, very large MIMO systems can significantly reduce power consumption by distributing the power among many antennas. The system can also be made highly robust, as the failure of a few antennas does not significantly affect the overall performance. Very large MIMO systems have the potential to achieve high data rates and improve system performance under the same regulatory power constraints. They can also reduce energy consumption, which is a growing concern for cellular base stations. Additionally, very large MIMO systems can eliminate the need for expensive and bulky components like large coaxial cables. The large-number-of-antennas regime has been of academic interest, but recent research has shown that practical system aspects in this regime are important. For example, a time-division multiplexing cellular system with very large MIMO can support over 40 single-antenna users with high throughput. The asymptotics of random matrix theory play a significant role in very large MIMO systems, leading to deterministic behavior and well-conditioned matrices. The performance of very large MIMO systems is influenced by the number of antennas, the propagation environment, and the channel properties. The system can achieve high data rates when the number of antennas is large and the propagation environment is favorable. However, the system is limited by interference and the need for accurate channel state information. The use of time-reversal techniques can focus power to a specific point in space, improving system performance. Very large MIMO systems also have implications for antenna design and propagation. The performance of the system depends on the antenna array's ability to exploit the propagation environment. The number of antennas and their spacing affect the system's performance, with more antennas and better spacing leading to improved performance. However, the system is limited by the physical constraints of the antenna array and the propagation environment. The paper discusses the information-theoretic performance limits of very large MIMO systems, the practical algorithms used in these systems, and the influence of channel properties on system performance. It also addresses the practical constraints on antenna arrangements and the challenges of implementing very large MIMO systems. The paper concludes that very large MIMO systems have the potential to significantly improve system performance and reduce energy consumption, but they also