A new dynamic cooperation cluster empowered cell-free massive MIMO architecture network for future networks

Cell free Massive Multi-input Multi-output (m-MIMO) is considered as a promising technology towards the development of 5G and beyond 5G networks. This network has the capability of deploying a large number of access points over the vast geographical area to provide service to small number of users exploting same frequency and other resources. However, the deployment and practical implementation of Massive MIMO cell free communications have been the major research gap between the existing and the m-MIMO cell free communications. This paper investigates cell free massive Multiple Input Multiple Output (MIMO) where in access points are aided by the optimized multiple antenna system. The cell free networks have been created by connecting large number of distributed access points (AP’s) to the central processing unit (CPU) through fronthaul connections with the user equiments. Additionally achieving desired computing efficiency, fronthaul needs and scalability for larger networks are other challenges which needs due consideration. To address such challenging issues, we incorporate the concept of dynamic cooperation cluster to develop a new framework for scalable CF-Massive-MIMO system. The scabilibity issues in the Massive MIMO cell free communications have also been addressed by exploiting much sophisticated search algorithm such as A*. The objective of the work was also to solve the scalable and other architectural issues in massive MIMO cell free communications using soft signal processing techniques. The A* Algorithm has been exploited to enhance the signal-to-noise-plus-interference ratio (SNIR), capacity and throughput. Tackling the complexity issues are another feature of A* algorithms in high degree of freedom system such as Massive MIMO cell free communications. The traditional channel estimation, pre-coding, and combining techniques have also been scaled in the proposed technique. A new uplink and downlink duality based on vector combining is demonstrated for the heuristic creation of precoding vectors. The performance of the proposed schme is presented in terms of parameters such as commulative distribution function, specrral effieciency and sum rate.