Regularized Zero-Forcing Precoder for Massive MIMO System With Transceiver I/Q Imbalances

Jee, Jeongju; Kwon, Girim; Park, Hyuncheol

doi:10.1109/lwc.2019.2904496

Cited by 10 publications

(4 citation statements)

References 10 publications

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“…Furthermore, an optimal augmented linear receiver is derived in terms of minimizing the mean-squared error. [496] consider both transmit and receive frequency-flat IQ imbalances and present a regularized ZF precoder scheme in SC massive MIMO downlink systems. In contrast with [495], users are equipped with a single antenna.…”

Section: Iq Imbalance In Emerging/future Technologies 1) Mimo Systemsmentioning

confidence: 99%

RF Impairments in Wireless Transceivers: Phase Noise, CFO, and IQ Imbalance – A Survey

Mohammadian

Tellambura

2021

IEEE Access

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Wireless transceivers for mass-market applications must be cost effective. We may achieve this goal by deploying non-ideal low-cost radio frequency (RF) analog components. However, their imperfections may result in RF impairments, including phase noise (PN), carrier frequency offset (CFO), and in-phase (I) and quadrature-phase (Q) imbalance. These impairments introduce in-band and out-of-band interference terms and degrade the performance of wireless systems. In this survey, we present RF-impairment signal models and discuss their impacts. Moreover, we review RF-impairment estimation and compensation in singlecarrier (SC) and multicarrier systems, especially orthogonal frequency division multiplexing (OFDM). Furthermore, we discuss the effects of the RF impairments in already-established wireless technologies, e.g., multiple-input multiple-output (MIMO), massive MIMO, full-duplex, and millimeter-wave communications and review existing estimation and compensation algorithms. Finally, future research directions investigate the RF impairments in emerging technologies, including cell-free massive MIMO communications, nonorthogonal multicarrier systems, non-orthogonal multiple access (NOMA), ambient backscatter communications, and intelligent reflecting surface (IRS)-assisted communications. Furthermore, we discuss artificial intelligence (AI) approaches for developing estimation and compensation algorithms for RF impairments.

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Section: Iq Imbalance In Emerging/future Technologies 1) Mimo Systemsmentioning

confidence: 99%

RF Impairments in Wireless Transceivers: Phase Noise, CFO, and IQ Imbalance – A Survey

Mohammadian

Tellambura

2021

IEEE Access

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“…In massive MIMO, the base station is generally equipped with a large number of antennas to serve one or multiple users where each user equipped at least with one antenna [3], [4]. Using massive MIMO can provide many benefits for 5G wireless systems by increasing the spatial multiplexing gain and diversity gain which lead to increase system capacity and link reliability, also enhance the spectral efficiency and energy efficiency [5], [6]. By increasing antennas number of massive MIMO system, the physical size of massive MIMO array will be large and practically unfeasible.…”

Section: Introductionmentioning

confidence: 99%

Wideband hybrid precoder for mmWave multiuser MIMO OFDM communications

Shareef

Al-Kindi

2022

Bulletin EEI

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Using millimeter wave (mmWave) transmission for massive multiple input multiple output (MIMO) system can improve system performance and effectively reduce the size of the massive antennas array. However, A wideband beamformer design is needed to take advantage of this wideband channel. In this paper, a downlink multi-user massive MIMO orthogonal frequency division multiplexing (MIMO OFDM) system for mmWave communications is proposed. Each subcarrier channel can be approximated as a narrowband clustered channel, so a narrowband precoder can be applied for each subchannel. The hybrid precoder is implemented in a manner so the digital precoder is obtained for each subcarrier, whilst the analog precoder is common for all subcarriers. A modified “joint spatial division/multiplexing” (JSDM) scheme is used to design the precoder, where each user equipped with more than one antenna. The design of the analog precoder is based on the second order channel statistics to reduce the overhead information need to process and fed back and the subcarrier baseband precoder based on the instantaneous channel state information (CSI). Following the approach of Kronecker channel model, the iteration between the analog beamformers design at both end of link can be avoided. Finally testing the system using various numbers of antennas at base station.

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“…The performance of MIMO and massive MIMO systems in the presence of hardware impairments (specially IQI) has been widely studied and a rich body of literature is available (please see [31]- [39] and references there-in). In contrast, the performance of HBFSs with hardware impairments is not well explored.…”

Section: Introductionmentioning

confidence: 99%

“…The performance of the maximal ratio combining and ZF receivers in uplink (UL) massive MIMO systems with receiver IQI was studied in [36], while the performance limits of massive MIMO systems in the presence of both transmitter and receiver IQI were studied in [37]. The authors of [38] proposed a linear MMSE receiver for UL massive MIMO systems with random IQI, whereas [39] proposed a regularized ZF precoder for DL massive MIMO systems with IQI. However, none of the above works are directly applicable to HBFSs.…”

Section: Introductionmentioning

confidence: 99%

Compensation of Transmitter IQ Imbalance in Multi-User Hybrid Beamforming Systems

2021

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In this paper, we consider the uplink (UL) communication of a massive multi-user (MU) multiple-input multiple-output (MIMO) hybrid beamforming system (HBFS) in which the transmitting userequipments are affected by IQ imbalance (IQI). We first show that if the transmitter IQI is not compensated, it will result in a finite ceiling of the UL achievable sum-rate at high signal-to-noise ratio, which only depends on the transmitter IQI matrices and is independent of the propagation channel and the choice of the hybrid combining matrices. This justifies the need for transmitter IQI compensation in massive MU-MIMO HBFS. Therefore, we propose a novel zero-forcing based transmitter IQI compensation algorithm to be implemented at the base station which effectively mitigates the undesired effects of transmitter IQI and is applicable for any channel model and any choice of the number of RF chains. For uncorrelated Rayleigh fading channel, we derive an approximate closed-form expression of the UL sum-rate achieved by the massive MU-MIMO HBFS with the proposed transmitter IQI compensation. Finally, numerical results are presented which confirm the effectiveness of the proposed transmitter IQI compensation algorithm in mitigating the undesired effects of transmitter IQI in different channel environments.INDEX TERMS Amplitude and phase mismatch, hybrid beamforming systems, IQ imbalance compensation, massive MIMO, multi-user communication, transmitter IQ imbalance.

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Regularized Zero-Forcing Precoder for Massive MIMO System With Transceiver I/Q Imbalances

Cited by 10 publications

References 10 publications

RF Impairments in Wireless Transceivers: Phase Noise, CFO, and IQ Imbalance – A Survey

RF Impairments in Wireless Transceivers: Phase Noise, CFO, and IQ Imbalance – A Survey

Wideband hybrid precoder for mmWave multiuser MIMO OFDM communications

Compensation of Transmitter IQ Imbalance in Multi-User Hybrid Beamforming Systems

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