Training sequence design for joint channel and I/Q imbalance parameter estimation in mobile SC-FDE transceivers

Narayanan, Sudharsan; Narasimhan, Balachander; Al-Dhahir, Naofal

doi:10.1109/icassp.2010.5496056

Cited by 10 publications

(6 citation statements)

References 4 publications

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“…However, the reported design procedure does not guarantee sequences possessing constant magnitude in time and frequency domains. In [9] even though the conditions to perform unbiased joint estimation of channel and I/Q imbalance are identified, the sequences there proposed do not accomplish the stated objectives.…”

Section: Introductionmentioning

confidence: 78%

Widely Linear System Estimation Using Superimposed Training

Arriaga-Trejo

Orozco-Lugo

Veloz-Guerrero

et al. 2011

IEEE Trans. Signal Process.

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In this correspondence, the use of superimposed training (ST) as a mean to estimate the finite impulse response (FIR) components of a widely linear (WL) system is proposed. The estimator here presented is based on the first-order statistics of the signal observed at the output of the system and its variance is independent of the channel components if suitable designed training sequences are employed. The construction of such sequences having constant magnitude both in time and frequency domains is also addressed.Index Terms-Joint channel I/Q imbalance estimation, optimum channel independent sequences, superimposed training, widely linear system estimation.

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Section: Introductionmentioning

confidence: 78%

Widely Linear System Estimation Using Superimposed Training

Arriaga-Trejo

Orozco-Lugo

Veloz-Guerrero

et al. 2011

IEEE Trans. Signal Process.

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“…However, these works [9]- [13] only presented linear-minimum-mean-squareerror (LMMSE) [14] based CE, that requires strong prior CSI. On another front, there are also some works on least-squares (LS) based CE under IQI [15]- [17]. A special structured pilot was used in [15] to obtain LS estimator (LSE) for both actual and IQI-based virtual signal terms.…”

Section: A State-of-the-artmentioning

confidence: 99%

Optimal Least Squares Estimator and Precoder for Energy Beamforming Over IQ-Impaired Channels

Mishra

Johansson

2019

IEEE Signal Process. Lett.

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Usage of low-cost hardware in large antenna arrays and low-power wireless devices in Internet-of-Things (IoT) has led to the degradation of practical beamforming gains due to the underlying hardware impairments like in-phase-and-quadraturephase imbalance (IQI). To address this timely concern, we present a new nontrivial closed-form expression for the globally-optimal least-squares estimator (LSE) for the IQI-influenced channel between a multiantenna transmitter and single-antenna IoT device. Thereafter, to maximize the realistic transmit beamforming gains, a novel precoder design is derived that accounts for the underlying IQI for maximizing received power in both single and multiuser settings. Lastly, the simulation results, demonstrating a significant −8dB improvement in the mean-squared error of the proposed LSE over existing benchmarks, show that the optimal precoder designing is more critical than accurately estimating IQI-impaired channels. Also, the proposed jointly-optimal LSE and beamformer outperforms the existing designs by providing 24% enhancement in the mean signal power received under IQI.

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“…The estimates of c 1 and c 2 can be obtained using the least squares (LS) criterion as in [14] and described bŷ…”

Section: Joint Tx and Rx Iqi Parameter Estimationmentioning

confidence: 99%

Joint TX/RX IQ imbalance parameter estimation using a generalized system model

Zhang

Lamare

Pan

et al. 2015

2015 IEEE International Conference on Communications (ICC)

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The joint estimation and compensation of IQ imbalance (IQI) parameters at both transmitter (TX) and receiver (RX) is studied in this paper. We develop a generalized system model with a reduced number of parameters (RNP) that covers a wide range of mobile communications scenarios. We devise efficient direct least-squares (DLS) and alternating least-squares (ALS) techniques for IQI parameter estimation based on the generalized system model. For the ALS based method, we prove that the algorithm will converge to a local optimal solution of the optimization problem. Numerical results show that compared with a previously reported method, the proposed DLS-RNP achieves similar performance with a reduced computational complexity, and the proposed ALS-RNP algorithm has significantly better performance with comparable complexity, with a gain over 5 dB for QPSK and 10 dB for 64QAM in the high signal-to-noise-ratio (SNR) region.

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Training sequence design for joint channel and I/Q imbalance parameter estimation in mobile SC-FDE transceivers

Cited by 10 publications

References 4 publications

Widely Linear System Estimation Using Superimposed Training

Widely Linear System Estimation Using Superimposed Training

Optimal Least Squares Estimator and Precoder for Energy Beamforming Over IQ-Impaired Channels

Joint TX/RX IQ imbalance parameter estimation using a generalized system model

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