You can find a short description on Wikipedia: https://en.wikipedia.org/wiki/MIMO#Mathematical_description

If you want to learn the topic in detail, I recommend Chapter 3 in my book "Introduction to Multiple Antenna Communications and Reconfigurable Surfaces" which you can download here:

Book Introduction to Multiple Antenna Communications and Reconfig...

The channel capacity of a MIMO antenna, which represents the maximum achievable data rate for reliable communication, can be calculated using various methods depending on the specific details and desired level of accuracy. Here are two main approaches:

1. Theoretical Formula:

The theoretical formula for MIMO channel capacity, derived by Telatar in 1999, is:

C = sum(log2(1 + λi/σ^2))

where:

• C is the channel capacity in bits/s/Hz
• λi are the eigenvalues of the channel covariance matrix (obtained from the channel matrix H)
• σ^2 is the noise variance

This formula provides the upper limit of achievable capacity under ideal conditions and can be helpful for comparing different MIMO configurations. However, it requires knowledge of the complete channel matrix, which might not be readily available in practical scenarios.

2. Numerical Methods:

For more practical calculations, especially when dealing with complex channel environments or limited information, numerical methods are often employed. Here are some common techniques:

• Monte Carlo simulations: This method involves generating a large number of random channel realizations and estimating the average channel capacity based on the theoretical formula for each realization. It's computationally expensive but provides statistically accurate results.
• Water-filling algorithm: This iterative algorithm optimizes power allocation across different subchannels within the MIMO system to maximize the overall channel capacity. It's efficient and widely used in practical MIMO systems.
• Software tools: Various software tools and libraries are available for MIMO channel analysis and capacity calculations. These tools often integrate various methods and offer user-friendly interfaces for specific applications.

Choosing the most suitable method depends on factors like the available information about the channel, desired accuracy level, and computational resources.

Additional factors to consider:

• Number of antennas: Increasing the number of antennas on both transmit and receive sides generally leads to higher channel capacity.
• Channel conditions: Fading, interference, and other channel impairments can significantly impact the achievable capacity.
• Coding scheme: The employed coding scheme plays a crucial role in achieving reliable communication at a given channel capacity.

Varaprasad Kudumu did you calculate it?