We present a framework for joint estimation and compensation of three major oscillator impairments, namely sampling time error (STE), carrier frequency offset (CFO) and phase noise (PN). In particular, we model these impairments as Wiener processes and introduce a pilot-aided approach which facilitates their joint estimation. The proposed solution is carried out in two steps: first, an initial estimation of the transmitted symbols is acquired by applying an extended Kalman filter (EKF) on the pilot symbols and then, a second EKF is applied on the estimated symbols which yields an accurate tracking of STE, PN and CFO over an additive white Gaussian noise channel. Our numerical results demonstrate the efficacy of the proposed solution.

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In this paper, we propose a real-valued multi-input memory polynomial (MP) for behavioral modeling of a mixer, which considers nonlinearity introduced by in-phase , quadrature and the local oscillator (LO) inputs. By splitting the I and Q data of the stimulus and LO signal, we use a 4-input 2-output structure of the real-valued MP model. The experimental validation based on data measured from a real mixer confirms the effectiveness of our proposed model. Compared with the Volterra series in the literature, the real-valued MP has similar modeling accuracy with much lower complexity.