Intelligent Omni Surface-Assisted Cell-Free Massive MIMO System for 6G Wireless Network

The coming 6G wireless communication system requires an intelligent networking system with higher network capacity. Therefore, we consider an intelligent omni surface (IOS)-assisted cell-free massive MIMO (ICFMM) system that extends the network coverage by providing services on both sides of the IOS with minimized power. The base stations and IOSs cooperatively serve the users in the ICFMM system and require a smaller number of IOS compared to the intelligent reflecting surfaces. An optimization problem is formulated that maximizes the channel capacity of the users, which in turn maximizes the signal-to-interference-noise ratio and achievable rate of the users. A gated recurrent unit (GRU)-based artificial intelligence (AI) framework is proposed to solve the formulated NP-hard problem, which allocates the required power for the users on both sides of the IOS based on user requirements. Finally, simulation results show that our proposed GRU-based AI framework ensures a cumulative SINR improvement of 1.58 dB and a cumulative achievable rate improvement of 8.61 bps/Hz compared to the long short-term memory method. Therefore, simulation results evaluate the performance of the proposed framework and demonstrate efficient power allocation for the intended users.