Asynchronous Channel Training in Massive MIMO Systems

Pilot contamination has been regarded as the bottleneck in time division duplexing (TDD) multi-cell massive multiple-input multiple-output (MIMO) systems. The pilot contamination problem cannot be addressed with large-scale antenna arrays. We provide a novel asynchronous channel training scheme to reduce the impact of pilot contamination without the cooperation of base stations. The scheme takes advantage of sampling diversity by inducing intentional timing mismatch. Then, the optimal linear minimum mean square error (LMMSE) estimator is designed to minimize the channel matrix estimation error. Finally, simulation results demonstrate that our scheme can provide significant performance improvement compared with the conventional synchronous systems that suffer from pilot contamination.