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Cloud radio access network (C-RAN) is a promising technology forfifth-generation (5G) cellular systems. However the burden imposed by the hugeamount of data to be collected (in the uplink) from the radio remote heads(RRHs) and processed at the base band unit (BBU) poses serious challenges. Inorder to reduce the computation effort of minimum mean square error (MMSE)receiver at the BBU the Gaussian message passing (MP) together with a suitablesparsification of the channel matrix can be used. In this paper we propose twosets of solutions, either centralized or distributed ones. In the centralizedsolutions, we propose different approaches to sparsify the channel matrix, inorder to reduce the complexity of MP. However these approaches still requirethat all signals reaching the RRH are conveyed to the BBU, therefore thecommunication requirements among the backbone network devices are unaltered. Inthe decentralized solutions instead we aim at reducing both the complexity ofMP at the BBU and the requirements on the RRHs-BBU communication links bypre-processing the signals at the RRH and convey a reduced set of signals tothe BBU.

Centralized and Distributed Sparsification for Low-Complexity Message Passing Algorithm in C-RAN Architectures