Massive MIMO with IQ Imbalance: Performance analysis and compensation

Kolomvakis, Nikolaos; Matthaiou, Michail; Li, Jingya; Coldrey, Mikael; Svensson, Tommy

doi:10.1109/icc.2015.7248570

Cited by 14 publications

(9 citation statements)

References 14 publications

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“…3 shows the power offset loss of WL-ZF compared with ZF with ideal IQ branches when N = 100. The analysis results are obtained using (20) and the approximation is made according to (21). The simulation results show that the analysis is very accurate for most cases.…”

Section: Numerical Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…In [20], the authors investigated the impact of IQI on the performance of uplink Massive MIMO systems with maximum-ratio combining (MRC) receivers, and showed that IQI can substantially degrade the performance of MRC receivers. The study in [20] also proposed a low-complexity IQI compensation scheme. In order to suppress the impact of IQI, a data-aided widely-linear minimum mean square error (MMSE) receiver is proposed in [23], and an IQI aware receiver was designed in [5] for the large-scale MIMO uplink based on the minimum variance distortionless response (MVDR) criterion.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Numerical Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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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“…3. The effects and compensation of IQ imbalance is well studied [9], [10]. In-line with these works, we define two variables, a and b, which are calculated from the physical parameters as a = cos(δφ) + jǫ sin(δφ) b = ǫ cos(δφ) + j sin(δφ),…”

Section: Iq Imbalance Pre-compensationmentioning

confidence: 99%

“…There is both an attenuation of the correct signal and interference from a frequency mirrored copy of the signal. Various studies on the effects of hardware impairments for massive MIMO systems were performed [3], [10], however, these do not consider any hardware cost. In the following section an analysis of IQ imbalance in the downlink is performed, which show that there is a need for pre-compensation.…”

Section: Iq Imbalance Pre-compensationmentioning

confidence: 99%

Algorithm and hardware aspects of pre-coding in massive MIMO systems

Prabhu

Rodrigues

Liu

et al. 2015

2015 49th Asilomar Conference on Signals, Systems and Computers

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Massive Multiple-Input Multiple-Output (MIMO) systems have been shown to improve both spectral and energy efficiency one or more orders of magnitude by efficiently exploiting the spatial domain. Low-cost RF chains can be employed to reduce the Base Station (BS) cost, however this may require additional baseband processing to handle induced distortions due to the hardware impairments. In this article the reduction of Peak-to-Average power Ratio (PAR) of the transmitted signals and IQ imbalance in the mixer are analyzed for the down-link. We analyze various pre-coding schemes and estimate the required processing energy per transmitted information bit. Simulation on gate-level show that the energy cost of performing pre-coding and tackling of hardware impairments range from very low to reasonable, compared to the processing necessary in a system without impairments.

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A low complexity iterative equalization technique for OFDMA and SC-FDMA uplink systems with Tx-Rx IQ imbalance and CFO under doubly selective channels

Muneer

Sameer

2020

Physical Communication

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Massive MIMO with IQ Imbalance: Performance analysis and compensation

Cited by 14 publications

References 14 publications

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

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

Algorithm and hardware aspects of pre-coding in massive MIMO systems

A low complexity iterative equalization technique for OFDMA and SC-FDMA uplink systems with Tx-Rx IQ imbalance and CFO under doubly selective channels

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