Distributed Channel Estimation and Pilot Contamination in Large scale MIMO

Over the past few years, there has been an exponential growth in the number of mobile users complemented with the availability of new services, applications and wirelessly accessible cloud platforms. Several new types of wireless devices such as smart phones, laptops, tablets, smart watches, digital assistants etc., have also been introduced. This has resulted in the cellular network traffic to explode with an unprecedented rate necessitating some radical improvements in the current design of cellular networks. The introduction of massive MIMO (multiple-input multiple-output) technology holds the promise of resolving these problems efficiently for the sustainable growth of the wireless industry. However, the technology is not yet ready to be deployed as there are two big challenges of efficient channel estimation and pilot contamination that arise with its use. In this research proposal, we propose to tackle these challenges with the aim of advancing the technology to make it practically feasible and deployable. Efficient distributed Bayesian channel estimation strategies will be developed unifying the solution of efficient channel estimation and pilot decontamination. It is expected that the devised strategies will eliminate the bottleneck of pilot contamination and will be able to perform in real time due to their distributed nature. A direct consequence of this research would be to enable the real deployment and commercialization of this technology.