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This paper proposes an efficient estimation and pilot-free online re-calibration scheme for frequency-selective $I/Q$ imbalance in broadband direct-conversion transmitters (Txs) with multi-band multi-standard capability. For such Txs, the main challenge lies in the online re-calibration during normal operation, where an ordinary Tx signal, instead of dedicated pilot signals, is used for estimation. In particular, it can happen that the Tx signal consists of noncontiguous subbands and has large spectral gaps, which will cause a severe ill-conditioned matrix problem in existing state-of-the-art (SoA) schemes deploying least squares (LS) estimation. In the proposed scheme, this problem is avoided by exploiting the fact that the frequency-selective part of $I/Q$ imbalance is approximately time invariant. Therefore, before normal operation, pilot-based initial estimation is carried out to achieve high-precision estimation of the frequency-selective part. Afterward, pilot-free online re-calibration is applied to cope with the time-varying frequency-independent part. Both theoretical analysis and numerical simulations show that the proposed re-calibration scheme is well conditioned and clearly outperforms the existing SoA schemes deploying LSE. To emphasize practical deployments, we also conduct performance analysis considering time synchronization error (TSE) and provide a Toeplitz-extension-based solution to make the scheme robust against TSE. We further provide complexity analysis and show that the proposed scheme has much lower complexity than the SoA schemes. Finally, the performance of the proposed scheme and the fundamental working assumptions are verified by both numerical simulations and hardware-in-the-loop (HIL) experiments with real radio-frequency signal measurements, including real-time field-programmable gate-array (FPGA) implementation of the developed digital calibration circuits. [ABSTRACT FROM PUBLISHER]

This brief proposes a novel adaptive calibration scheme for frequency-selective I/Q imbalance in broadband direct-conversion transmitters (T\!x) with multiband multistandard capability. The calibration consists of pilot-based initial calibration, followed by pilot-free parameter tracking against time-variant characteristics. Compared to the state-of-the-art (SoA) schemes, the proposed scheme has much lower complexity. Furthermore, the pilot-free tracking can provide good performance independently from the communication signal characteristic and avoids the ill-conditioned matrix problem in the SoA schemes. Its performance is verified by both computer simulations and hardware-in-the-loop experiments. [ABSTRACT FROM AUTHOR]

Received signal strength (RSS) changes of static wireless nodes can be used for device-free localization and tracking (DFLT). Most RSS-based DFLT systems require access to calibration data, either RSS measurements from a time period when the area was not occupied by people, or measurements while a person stands in known locations. Such calibration periods can be very expensive in terms of time and effort, making system deployment and maintenance challenging. This paper develops an Expectation-Maximization (EM) algorithm based on Gaussian smoothing for estimating the unknown RSS model parameters, liberating the system from supervised training and calibration periods. To fully use the EM algorithm's potential, a novel localization-and-tracking system is presented to estimate a target's arbitrary trajectory. To demonstrate the effectiveness of the proposed approach, it is shown that: (i) the system requires no calibration period; (ii) the EM algorithm improves the accuracy of existing DFLT methods; (iii) it is computationally very efficient; and (iv) the system outperforms a state-of-the-art adaptive DFLT system in terms of tracking accuracy. [ABSTRACT FROM AUTHOR]