Precoded massive MU-MIMO uplink transmission under transceiver I/Q imbalance

Hakkarainen, Aki; Werner, Janis; Dandekar, Kapil R.; Valkama, Mikko

doi:10.1109/glocomw.2014.7063451

Cited by 11 publications

(9 citation statements)

References 18 publications

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“…IQI has also been studied in half-duplex and full duplex amplify-and-forward and decode-and-forward cooperative systems [24][25][26][27][28], two-way relay systems and multiantenna systems [29][30][31][32][33][34][35][36][37], as well as cognitive radio systems [38]. Finally, the effects of IQI on uplink transmission have been analyzed in the context of massive multi-user MIMO in [39].…”

Section: A Related Workmentioning

confidence: 99%

Performance Analysis of Coherent and Noncoherent Modulation Under I/Q Imbalance Effects

et al. 2021

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In this paper, we investigate the effects of in-phase/quadrature-phase imbalance (IQI) on the performance of different modulation schemes under multipath fading channels. In particular, a comprehensive framework for the analysis of coherent and noncoherent modulation with IQI is proposed. Specifically, new moment generating function (MGF) expressions for both point-to-point and multiple antenna systems are derived for the cases of transmitter IQI, receiver IQI, and joint transmitter/receiver IQI. Based on the derived MGFs, new analytical expressions for the corresponding symbol error rate (SER) are derived and are subsequently used to provide deep insights into the effects of IQI on the system performance. It is shown that, while in some cases the SER performance degradation due to IQI is marginal, in other cases, this impairment is more pronounced. Accordingly, IQI compensation is of paramount importance as it can guarantee a reliable communication link. This is particularly important in demanding communication technologies where reduction of latency and complexity are essential. INDEX TERMS I/Q imbalance, coherent detection, noncoherent detection, RF impairments, symbol error rate.

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Section: A Related Workmentioning

confidence: 99%

Performance Analysis of Coherent and Noncoherent Modulation Under I/Q Imbalance Effects

et al. 2021

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“…In contrast to [5], [15], [16], [20]- [23], in this work we study the design and performance analysis for downlink precoding in large-scale MIMO systems with transmitter IQI, for both single-and multiple-antenna users. We first adopt a useful mapping function reported in [36], [37], which transforms complex-valued vectors and matrices into real-valued expressions and helps to set up an equivalent real-valued signal model with consideration of IQI.…”

Section: Introductionmentioning

confidence: 99%

Widely Linear Precoding for Large-Scale MIMO with IQI: Algorithms and Performance Analysis

Zhang

Lamare

Pan

et al. 2017

IEEE Trans. Wireless Commun.

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In this paper we study widely-linear precoding techniques to mitigate in-phase/quadrature-phase (IQ) imbalance (IQI) in the downlink of large-scale multiple-input multiple-output (MIMO) systems. We adopt a real-valued signal model which takes into account the IQI at the transmitter and then develop widely-linear zero-forcing (WL-ZF), widely-linear matched filter (WL-MF), widely-linear minimum mean-squared error (WL-MMSE) and widely-linear block-diagonalization (WL-BD) type precoding algorithms for both single-and multiple-antenna users. We also present a performance analysis of WL-ZF and WL-BD. It is proved that without IQI, WL-ZF has exactly the same multiplexing gain and power offset as ZF, while when IQI exists, WL-ZF achieves the same multiplexing gain as ZF with ideal IQ branches, but with a minor power loss which is related to the system scale and the IQ parameters. We also compare the performance of WL-BD with BD. The analysis shows that with ideal IQ branches, WL-BD has the same data rate as BD, while when IQI exists, WL-BD achieves the same multiplexing gain as BD without IQ imbalance. Numerical results verify the analysis and show that the proposed widely-linear type precoding methods significantly outperform their conventional counterparts with IQI and approach those with ideal IQ branches. Index TermsIQ imbalance, large-scale MIMO, widely-linear signal processing, downlink precoding W. Zhang is with Jiangsu University, China. He was with CETUC, PUC-Rio, Brazil.

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“…Note that this model has been extensively used in the majority of relevant works (see e.g. [8], [14], [20], [21]). The RX IQI can be modeled for the n-th (n = 1, ..., N ) individual antenna element on the baseband equivalent level as [20] r imb,n = K 1,n r n + K 2,n r * n…”

Section: A Rf Iq Imbalancementioning

confidence: 99%

“…Although several IQI compensation algorithms have been proposed, especially for the case of single-input single-output (SISO) systems [11]- [13], little is still known for the case of massive MIMO systems. To the best of our knowledge the only relevant works are [8], [14]- [18]. Specifically, [8] studied the sensitivity of massive antenna arrays to RF IQI by elaborating on the design of singleuser beamforming schemes; moreover, [14] proposed augmented spatial post-processing linear minimum-mean-squareerror (LMMSE) filters for mitigating the effect of IQI in the uplink receiver.…”

Section: Introductionmentioning

confidence: 99%

“…To the best of our knowledge the only relevant works are [8], [14]- [18]. Specifically, [8] studied the sensitivity of massive antenna arrays to RF IQI by elaborating on the design of singleuser beamforming schemes; moreover, [14] proposed augmented spatial post-processing linear minimum-mean-squareerror (LMMSE) filters for mitigating the effect of IQI in the uplink receiver. Finally, [16]- [18] proposed widely linear precoding algorithms for massive MIMO systems with IQI.…”

Section: Introductionmentioning

confidence: 99%

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IQ Imbalance in Multiuser Systems: Channel Estimation and Compensation

Kolomvakis

Matthaiou

Coldrey

2016

IEEE Trans. Commun.

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Abstract-In this paper, we consider the uplink of a single-cell multi-user single-input multiple-output (MU-SIMO) system with in-phase and quadrature-phase imbalance (IQI). Particularly, we investigate the effect of receive (RX) IQI on the performance of MU-SIMO systems with large antenna arrays employing maximum-ratio combining (MRC) receivers. In order to study how IQI affects channel estimation, we derive a new channel estimator for the IQI-impaired model and show that the higher the value of signal-to-noise ratio (SNR) the higher the impact of IQI on the spectral efficiency (SE). Moreover, a novel pilotbased joint estimator of the augmented MIMO channel matrix and IQI coefficients is described and then, a low-complexity IQI compensation scheme is proposed which is based on the IQI coefficients' estimation and it is independent of the channel gain. The performance of the proposed compensation scheme is analytically evaluated by deriving a tractable approximation of the ergodic SE assuming transmission over Rayleigh fading channels with large-scale fading. Furthermore, we investigate how many MSs should be scheduled in massive multiple-input multiple-output (MIMO) systems with IQI and show that the highest SE loss occurs at the optimal operating point. Finally, by deriving asymptotic power scaling laws, and proving that the SE loss due to IQI is asymptotically independent of the number of BS antennas, we show that massive MIMO is resilient to the effect of RX IQI.

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Precoded massive MU-MIMO uplink transmission under transceiver I/Q imbalance

Cited by 11 publications

References 18 publications

Performance Analysis of Coherent and Noncoherent Modulation Under I/Q Imbalance Effects

Performance Analysis of Coherent and Noncoherent Modulation Under I/Q Imbalance Effects

Widely Linear Precoding for Large-Scale MIMO with IQI: Algorithms and Performance Analysis

IQ Imbalance in Multiuser Systems: Channel Estimation and Compensation

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