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 × 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 8 × 8 = 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 × (8 × 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.