Design and Implementation of AI-Based Signal Processing for 6G Wireless Systems

As sixth-generation (6G) wireless networks are introduced, global data transfer rates will hugely improve, latency will be extremely low, more devices can be connected and networks will become more intelligent. Still, the large scale, changing settings and good performance needs of 6G make it hard for old signal processing methods to work well. To address these issues, this paper introduces a new artificial intelligence (AI) signal processing approach developed for 6G systems. With this framework, deep learning (DL) and reinforcement learning (RL) methods are combined with traditional signal processing to make operations on both physical and higher levels of the network more intelligent and flexible. Modern deep learning techniques are used for channel measurement, figure out the modulation and identify signals which results in more reliable detection of features and patterns in different channel situations. Similarly, reinforcement learning models help in managing how resources are shared, how power is set and how interference can be managed in real time which results in improved use of the wireless spectrum and durability of the system. Using both computer algorithms and known techniques, the integration in AI allows the system to adapt to changes in the environment and resist any uncertainties that may affect signals. Diverse tests are performed on the model to predict how it might adapt in dense 6G systems, highly mobile conditions and a wide range of usage requirements. It is clear that spectral efficiency has increased, there are fewer bit errors, energy efficiency has improved and the system is more flexible compared to other techniques. Also, the framework can grow in limited parts and matches new 6G technologies such as terahertz communications, intelligent reflecting surfaces and massive MIMO. With AI integrated into signal processing in the next-generation networks, researchers lay the foundation for 6G systems to respond well to the strict conditions and requirements coming in the future wireless world.