Cognitive Networks in the Presence of I/Q Imbalance and Imperfect CSI: Receiver Design and Performance Analysis

Alsmadi, Malek; Canbilen, Ayşe Elif; Ali, Najah Abu; Ikki, Salama; Başar, Ertuğrul

doi:10.1109/access.2019.2908787

Cited by 15 publications

(3 citation statements)

References 33 publications

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“…Therefore, [515] investigates the combined effect of transmit and receive frequency-flat IQ imbalances and imperfect CSI in cognitive radio secondary systems. Consequently, the performance degrades, and the noise behavior changes from a proper to improper Gaussian distribution.…”

Section: ) Cognitive Radio Networkmentioning

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: ) Cognitive Radio Networkmentioning

confidence: 99%

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

Mohammadian

Tellambura

2021

IEEE Access

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“…This detector has also been derived in [28] before. It has the same form as the detector in (23), except that the received signal y R and y I in (29) are determined by (6), while those in (23) are determined by (4). The performances of these detectors will be examined and compared later.…”

Section: Ad and Iqimentioning

confidence: 99%

Further Results on Detection and Channel Estimation for Hardware Impaired Signals

Chen

Yang

Zhang

et al. 2021

IEEE Trans. Commun.

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“…Indeed both inphase (I) and quadrature (Q) modulator and demodulator at the Tx and Rx may introduce phase and/or amplitude mismatch [22]. Additional harmful effects could degrade the system performance such as crosstalk and frequency interference [23][24][25]. Hence, taking into account IQI effects is a crucial factor for RIS effective design policies.…”

Section: Introductionmentioning

confidence: 99%

Impact of IQ Imbalance on RIS‐Assisted SISO Communication Systems

Bouhlel

Sakly

2021

Wireless Communications and Mobile Computing

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Reconfigurable intelligent surface (RIS) for wireless networks has emerged as a promising future transmission technique to create smart radio environments that improve the system performance by turning the wireless channel into an adjustable system block. However, transceivers come with various hardware impairments, such as phase noise and in-phase/quadrature-phase imbalance (IQI). Hence, for robust configuration of RIS-based communication under practical conditions, assuming the identical performance analysis when subject to IQI, will lead to inaccurate analysis. In this paper, the implementation of this novel transmission technique is thoroughly investigated under intensive realistic circumstances. For this purpose, based on the maximum likelihood (ML) detector, a novel analytical expression of average pairwise error probability under IQI is proposed and compared to the standard ML detector. Further, the proposed analytical approaches are confirmed by numerical simulations.

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Cognitive Networks in the Presence of I/Q Imbalance and Imperfect CSI: Receiver Design and Performance Analysis

Abstract: The work of E. Basar was supported by the Turkish Academy of Sciences (TUBA) GEBIP Programme.

Cited by 15 publications

References 33 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

Further Results on Detection and Channel Estimation for Hardware Impaired Signals

Impact of IQ Imbalance on RIS‐Assisted SISO Communication Systems

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