Optimum and Adaptive Complex-Valued Bilinear Filters

The identification of nonlinear systems is a frequent task in digital signal processing. Such nonlinear systems may be grouped into many sub-classes, whereby numerous nonlinear real-world systems can be approximated as bilinear (BL) models. Therefore, various optimum and adaptive BL filters have been introduced in recent years. Further, in many applications such as communications and radar, complex-valued (CV) BL systems in combination with CV signals may occur. Hence, in this work, we investigate the extension of real-valued (RV) BL filters to CV BL filters. First, we derive CV BL filters by applying two or four RV BL filters, and compare them with respect to their computational complexity and performance. Second, we introduce novel fully CV BL filters, such as the CV BL Wiener filter (WF), the CV BL least squares (LS) filter, the CV BL least mean squares (LMS) filter, the CV BL normalized LMS (NLMS) filter, and the CV BL recursive least squares (RLS) filter. Finally, these filters are applied to identify multiple-input-single-output (MISO) systems and Hammerstein models.

Tx and Rx IQ Imbalance Compensation for JCAS in 5G NR

Beside traditional communications, joint communications and sensing (JCAS) is gaining increasing relevance as a key enabler for next-generation wireless systems. The ability to accurately transmit and receive data is the basis for high-speed communications and precise sensing, where a fundamental requirement is an accurate in-phase (I) and quadrature-phase (Q) modulation. For sensing, imperfections in IQ modulation lead to two critical issues in the range-Doppler-map (RDM) in form of an increased noise floor and the presence of ghost objects, degrading the accuracy and reliability of the information in the RDM. This paper presents a low-complex estimation and compensation method to mitigate the IQ imbalance effects. This is achieved by utilizing, amongst others, the leakage signal, which is the direct signal from the transmitter to the receiver path, and is typically the strongest signal component in the RDM. The parameters of the IQ imbalance suppression structure are estimated based on a mixed complex-/real-valued bilinear filter approach, that considers IQ imbalance in the transmitter and the receiver of the JCAS-capable user equipment (UE). The UE uses a 5G New Radio (NR)-compliant orthogonal frequency-division multiplexing (OFDM) waveform with the system configuration assumed to be predefined from the communication side. To assess the effectiveness of the proposed approach, simulations are conducted, illustrating the performance in the suppression of IQ imbalance introduced distortions in the RDM.