Alexander Karataev, Christian Forsch & Laura Cottatellucci

We consider a cell-free massive multiple-input multiple-output (CF-MaMIMO) communication system in the uplink, which is particularly prone to the detrimental effects of pilot contamination (PC), a phenomenon that occurs when pilot sequences assigned to user equipments (UEs) are not mutually orthogonal, eventually due to their reuse. To combat PC, the presenters propose a novel algorithm for blind or semi-blind joint channel estimation and data detection (JCD). They formulate the problem in the framework of bilinear inference and develop a solution based on the expectation propagation (EP) method for both channel estimation and data detection. Specifically, they introduce a new approximation of the joint a posteriori distribution of the channel and transmitted data whose representation as a factor graph enables the application of EP through message-passing. This allows for local low-complexity computations at the nodes and effectively capture the interplay between channel and data. The resulting algorithm, called bilinear-EP JCD, supports distributed implementation across access points (APs) and the central processing unit (CPU) and operates with polynomial complexity. Their simulation results show that their approach outperforms existing EP-based, state-of-the-art polynomial-time algorithms and effectively reduce pilot contamination.