Efficient Evaluation of Massive MIMO Channel Capacity

Massive multiple-input multiple-output (MIMO) is a key promising technology for 5G wireless networks that allows significant increase in spectral and energy efficiency without increasing the spectrum and/or the number of cell sites. However, the computational time and resources required to rigorously analyze the capacity offered by a base station (BS) equipped with a large number of antenna elements increase with the increase of the number of antenna elements in the array. In this paper, we present a novel approximation approach for modeling large microstrip antenna arrays in BSs of massive MIMO systems. The approach subdivides an M x N array into columns, rows, rectangular, or square subarrays, each consisting of a group of elements. The coupling is rigorously taken into account within each subarray, but it is ignored between subarrays, using just an array factor instead. Results are demonstrated for an 8x8 = 64 element patch array. It is shown that the difference in the capacity evaluated using rigorous electromagnetic simulations and the proposed approach is less than 0.79% using the 2 x (8 x 4) approach for both the suburban macrocell model of the Extended Spatial Channel Model (SCME/suburban macro cell (SMa)) outdoor propagation model and three-dimensional independent identically distributed model with a significant reduction of 44% and 50%, respectively, in computational time as compared to the full-wave antenna array modeling approach.