IMPROVING NOISE IMMUNITY AND INCREASING DATA TRANSMISSION SPEED IN WI-FI NETWORKS

Abstract

Wireless communication systems, including computer Wi-Fi networks, are currently undergoing intensive development. The radio communication channels of such systems are subject to a complex of interference and distortion. To improve such parameters as performance and interference resistance, especially in conditions of dense use of a rather limited frequency channel, there is a need to improve existing methods and create fundamentally new ones. The purpose of the article is to review the methods of information transmission in modern wireless access systems and to study algorithms for increasing network capacity by applying adaptive spatial signal processing methods and finding a balance between increasing the throughput of MIMO technology and reducing the probability of reception errors. Research methods: the study uses methods of information transmission in modern wireless access systems and algorithms for increasing network capacity. The scientific novelty of the study is that the analysis of modern methods of wireless information transmission revealed that space-time coding successfully combines the advantages of spatial diversity methods with the ability to correct errors with a corrective code when using optimal decoding algorithms, while the effectiveness of research and development of new methods of space-time coding largely depends on how well the channel models match real-world conditions. One of the promising methods for improving network quality parameters is the method of synthesizing convolutional-block signal-code structures using internal signals from the class of space-time block coding and external signal structures, which is an effective technique for reducing the effect of fading on signals, improving the quality and throughput of the Wi-Fi communication system. Conclusions. The development of these algorithms and methods opens up broad prospects for the future development of wireless communication systems. One of the key prospects is to further improve the methods of adaptive spatial signal processing and optimize the balance between increasing throughput and reducing the probability of reception errors. Additionally, the capabilities of convolutional-block signal-code designs can be expanded by researching and implementing new technologies, such as using machine learning to optimize signal coding and decoding parameters. There are also opportunities to apply these techniques to high-speed mobile networks, such as fifth generation (5G) and future generations, where high bandwidth and data efficiency are becoming key requirements.