Analysis of Demodulation Efficiency and Complexity Using Non-Gaussian Approximation in Massive MIMO Systems

The use of a large number of antennas (Massive MIMO systems) provides immense advantages to modern communication systems in achieving a high data rate, spectral efficiency, and large number of concurrently connected users. However, the increase in the number of antennas leads to high computational complexity of the demodulation algorithms, and the problem is aggravated if higher order modulation schemes are used. As a result, new demodulation algorithms with good interference immunity characteristics and acceptable computational complexity should be synthesized for practical implementation in Massive MIMO systems. An approach was proposed earlier for applying a non-Gaussian approximation of the a priori distribution of the estimated parameters and a modified Newton method for demodulation in communication systems with a large number of antennas. Here, the interference immunity of the proposed demodulation algorithm is examined for a different number of antennas and different modulation orders and its computational complexity is evaluated. Comparison of the characteristics of the proposed demodulation algorithm with the popular MMSE and K-best algorithms confirms the effectiveness of proposed non-Gaussian approximation approach in combination with the modified Newton method for demodulation in Massive MIMO systems.