Internal Reciprocity Calibration for TDD Massive MIMO: An Algorithm and Experimental Results

Uplink-downlink channel reciprocity is crucial to realizing the full potentials of time division duplexing (TDD) massive multiple-input multiple-output (MIMO) systems. The hardware ununiformity of the radio frequency (RF) chains, however, may destroy this recicprocity. Thus, such RF mismatches need to be carefully calibrated via the process of internal calibration where the base station is required to estimate the relative effects of its RF chains accurately to the uncertainty level of a complex-valued scalar. The existing internal calibration algorithms, however, often require high computational complexity, large processing delays and perfect time alignment. Also, much prior work relies on simulation results to evaluate its proposed internal calibration algorithms. In this paper, we propose a method to transform the complicated internal calibration problem into a number of much simpler least squares (LS) problems. We then propose a novel internal calibration algorithm to address the above issues of existing algorithms. Measurement results obtained based on our TDD massive MIMO testbed show that the proposed algorithm with over-the-air configuration is a viable solution to this testbed.