Also, the fundamentals of massive MIMO have been presented in.
In related reports, an overview of MIMO channel propagation models, including an extensive description of modern signal processing techniques for single-user and multiuser systems, is presented in. Similarly, a detailed description of propagation channel modeling is discussed in, and a thorough review of propagation measurements, parameterization, and model validation is presented in. Rappaport presents an overview of the radio propagation channel, and an introduction to the wireless channel model and channel statistics is given in. This is because MIMO technology has promising capabilities to achieving the desired high data rates and very high network reliability, thereby enhancing the quality of service (QoS) for mobile subscribers to sustain their vast data-hungry applications. Also, several research works have proposed the deployment of multiple antennas, also known as MIMO, as a candidate technology.
It also emphasized that massive MIMO can deliver remarkable improvements in spectral and energy efficiencies. The monograph covers critical areas such as spatial signal processing, channel estimation, power, and spatial resource allocation. Toward this end, the concept of cellular networks and ways to improve spectral efficiency with practical examples are proposed in. To achieve high gains in spectral, energy, and hardware efficiency in wireless communication systems, the deployment of multiple input multiple output (MIMO) technology presents enormous potentials as a leading candidate. Currently, wireless network service improvements require the aggressive deployment of dense access points to increase the spectral efficiency (SE) and energy efficiency (EE). The widespread adoption of these devices places a stringent requirement on the existing wireless network infrastructure to be strengthened in terms of robustness, capacity, and coverage to meet the rapidly growing mobile services demands. Over the last decade, the use of wireless communication devices and applications has increased exponentially. Finally, we present the recent 3GPP-based 3D channel model, the transitioning from 2D to 3D channel modeling, discuss open issues, and highlight vital lessons learned for future research exploration in MIMO communication systems. Additionally, we examined the strengths and limitations of the existing channel models and discussed model design, development, parameterization, implementation, and validation. The standardized models provide a unified framework for modern radio propagation architecture, advanced signal processing, and cutting-edge multiple access techniques. The analytical models show the statistical features of the MIMO channel with respect to the measured data. The physical models describe the MIMO channel using physical parameters. First, we present the general MIMO channel model and identified three major MIMO channel models, viz., the physical, analytical, and standardized models. This article presents a detailed survey of MIMO channel models in wireless communication systems. A key technology used to improve SE substantially is the multiple input multiple output (MIMO) technique. A major barometer used to gauge the performance of a wireless communication system is the spectral efficiency (SE) of its communication channels. Consequently, this has led to the aggressive use of the available propagation channels to fulfill the minimum quality of service (QoS) requirement. The field of wireless communication networks has witnessed a dramatic change over the last decade due to sophisticated technologies deployed to satisfy various demands peculiar to different data-intensive wireless applications.