On the performance of calibration techniques for cognitive radio systems

In Cognitive Radio (CR) systems, primary licensed and secondary unlicensed users share the same spectrum. To minimize the interference caused by secondary users to primary users, we use Beamforming (BF). To perform BF in time division duplex (TDD), we acquire Channel State Information (CSI) with the help of channel reciprocity. This reciprocity is in practice not perfect due to non reciprocal Radio Frequency (RF) front-ends, this non reciprocity can be compensated by calibration algorithms, using only CSI, pilots and signaling. This paper
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compares the performance of three calibration algorithms in OFDM-MIMO (Orthogonal Frequency Division Multiplexing Multiple-Input Multiple-Output) context, namely a M × N SISO and two full MIMO techniques (Alternating Total Least-Squares MIMO: Alt TLS MIMO and TLS MIMO). Simulations performed on synthetic and measured channels show that the TLS MIMO successfully performs full calibration, whereas the less complex SISO method fails to compensate antenna mutual coupling. They also give an approximation of the required CSI to achieve calibration. The final objective is to implement a proper calibration scheme in an existing CR scenario on the EURECOM OpenAirInterface platform.