Channel Capacity Based on Near Field Ultra Large-scale MIMO

With the increasing development of wireless communication technology, near field ultra large-scale MIMO (Multiple-Input Multiple-Output) technology is becoming more and more critical in improving channel capacity. Traditional MIMO has problems such as insufficient channel capacity and signal-to-noise ratio. In this article, the SWOMP (Stagewise Weak Orthogonal Matching Pursuit) algorithm was used to precisely obtain near field channel state information, and the XL-MIMO (Extremely Large-scale MIMO) near field communication model was constructed through uplink time division duplex. The antenna array was designed in combination with the frequency modulation mode to achieve accurate channel capacity estimation. Empirical evidence showed that compared with traditional algorithms, the channel capacity of this method could reach $1614.11 \mathrm{bit} / \mathrm{s} / \mathrm{Hz}$ at a distance of $\mathbf{1 0}$ meters, and the signal-to-noise ratio could reach 9.41 dB, which effectively improves communication performance and is of great significance to the development of communication systems.