Massive MIMO in Mobile Networks: Self-Calibration with Channel Estimation Error

Time-division-duplexing (TDD) massive multiple-input multiple-output (MIMO) systems will play a crucial role in the deployment of emerging mobile networks in 5G and beyond. Such systems heavily rely on the reciprocity-based channel estimation for its scalability. However, the imperfect channel reciprocity, mainly caused by radio-frequency mismatches among the base station antennas, can contaminate the estimate of the effective channel response thus become a performance-limiting factor. In practice, self-calibration schemes are often applied to compensate for this type of imperfections. This work investigates two self-calibration schemes, namely relative calibration and inverse calibration. Considering a TDD massive multi-user MIMO system in the presence of both channel reciprocity error and imperfect channel estimation, we derive closed-form expressions for the receive mean-square error and provide an in-depth comparative analysis of the post-equalisation performance of two calibration schemes. The proposed analytical results are verified via Monte-Carlo simulations