A Pragmatic Investigation of Artificial Intelligence Algorithms Implementation to Signal Processing for Cellular Networks

  • S. Orike
  • S. M. Ekolama
  • J. C. Adinnu
Keywords: Mobile, Cellular Network, Algorithms, Artificial Intelligence, Communication, Signal Processing, Artificial Neural Network, Network boosting


The paper review investigates the revolutionary capacity of artificial intelligence (AI) algorithms within the domain of signal processing for cellular networks. AI has become an indispensable instrument in the digital age for augmenting the intelligence and adaptability of networks. This research examines the use of AI-powered methods, such as neural networks and reinforcement learning, to optimise the distribution of resources in accordance with user demand and network capacity. The use of artificial intelligence (AI) in signal processing has the potential to decrease interference, improve signal quality, and proactively resolve prospective problems by employing predictive maintenance that leverages historical data. The notion of self-healing networks is presented, placing emphasis on customised services, latency, and data rates, with the aim of automating the process of ensuring network resilience. The use of artificial intelligence is considered essential for optimising energy consumption and ensuring the security of cellular communication systems. Particularly as cellular networks transit to 6G, sophisticated techniques such as beamforming and MIMO (multiple input, multiple output) are recognised as indispensable for attaining increased data rates and spectral efficiency. By incorporating artificial intelligence (AI) into the optimisation of these processes, the complete potential of next-generation cellular networks could be unlocked, leading to enhancements in both data speed and communication reliability.


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How to Cite
Orike, S., Ekolama, S. M., & Adinnu, J. C. (2024). A Pragmatic Investigation of Artificial Intelligence Algorithms Implementation to Signal Processing for Cellular Networks. European Journal of Science, Innovation and Technology, 3(6), 470-481. Retrieved from https://ejsit-journal.com/index.php/ejsit/article/view/353