Abstract:

The rate of information transmission in wireless communication has dramatically evolved over the last decade. However, due to multipath propagation, the data rate is not constant, even though a reasonably stable data rate is essential for effective wireless transmission. Historically, various fading system models have been employed to analyze and demonstrate the dynamics of remote communication channels. Recent research focuses on SISO wireless communication systems operating under Rician fading conditions. By employing small-limit argument approximations, researchers can evaluate channel capacity with greater accuracy, particularly in scenarios characterized by low signal-to-noise ratios (LSNR). This approach facilitates the development of analytical methods for calculating channel capacities, offering valuable insights into system performance under challenging conditions. The analysis delves into how channel capacity responds to variations in real-time signal-to-noise ratio (SNR), also known as instantaneous SNR, the Rician factor, and the overall power of fading. This comprehensive examination provides new perspectives on the performance of wireless communication systems under these conditions. The SISO model also considers the impact of the Rician factor and the overall power of Rician fading. According to the research, the capacity of the channel increases significantly with the rise of real-time SNR when using the small-limit argument approximation. Additionally, the study explores the highest possible channel capacity for the proposed system under this approximation.