A Blind Likelihood-Based Approach for OFDM Spectrum Sensing in the Presence of I/Q Imbalance

ElSamadouny, Ahmed; Gomaa, Ahmad; Al-Dhahir, Naofal

doi:10.1109/tcomm.2014.030814.130536

Cited by 13 publications

(4 citation statements)

References 26 publications

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“…Simultaneously, CFO and PN ruin the gains obtained via cyclostationary feature, and sampling clock frequency offset can strongly degrade the performance when long sensing periods are required. Additionally, the study in [517] presents an optimal blind Neyman-Pearson detector for OFDM signals when there is both transmitter and receiver frequency-flat IQ imbalance. The proposed detector is derived by utilizing the correlation between each subcarrier and its image by assuming known received signal covariance at the subcarrier level.…”

Section: ) Cognitive Radio Networkmentioning

confidence: 99%

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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%

“…It is shown that transmit a secondary user can blindly deploy IQ imbalance to enhance the detection probability. Although the works in [516] and [517] illustrate that the receive IQ imbalance does not affect spectrum sensing performance, they only consider narrowband single-channel sensing.…”

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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“…We first define n = n + n RD , where the k-th element of n is n k = g 1 h RD n SRk + g 2 h RD n * SRk . Generally, n is an improper complex Gaussian vector as it depends on both of n SR and n * SR , and the PDF of n is [44,45]…”

Section: Appendix 1: Proof For the Range Of γ In Eq (12)mentioning

confidence: 99%

Amplify-and-forward relay identification using joint Tx/Rx I/Q imbalance-based device fingerprinting

Peng

Wang

Behnad

2019

J Wireless Com Network

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Relay identification is necessary in many cooperative communication applications such as detecting the presence of malicious relays for communication security, selecting the intended relays for signal forwarding, and tracing a specific relay. However, this identification task becomes extremely challenging for amplify-and-forward (AF) relaying systems since AF relays usually have no capability of adopting traditional identification methods implemented above the physical layer. This paper proposes a physical-layer AF relay identification scheme based on the exploitation of the device-specific in-phase and quadrature-phase imbalance (IQI) feature. Given that IQI estimation is mandatory in most present receivers for compensation, it is cost-effective to make use of these estimation results for fingerprinting AF relays. A generalized likelihood ratio test-based fingerprint differentiation technique is adopted to detect the minor difference between two range-limited IQI fingerprints. Using this differentiation technique, a whitelist-based identification algorithm consisting of fingerprint registration, update, and identification is proposed. Furthermore, the optimal training signals that lead to the maximal detection probability are derived for the typical quadrature amplitude modulation and phase-shift keying modulation schemes. The simulation results validate our derivations and confirm that the proposed method can accurately identify AF relays.

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“…More precisely, the authors in [12] proposed a sample-based multichannel energy detector using an energy correction method to compensate the performance degradation caused by IQI. In [13], optimal spectrum sensing has been proposed from the likelihood criterion viewpoint assuming IQI exists at the receiver and at the transmitter sides, whereas in [14], the exact average signal to noise plus interference (SINR) has been obtained in an OFDM system assuming that IQI exists at both the receiver and the transmitter.…”

Section: Introductionmentioning

confidence: 99%

Achieved throughput of OFDM‐based cognitive radio systems in the presence of inphase quadrature imbalance

Mohajeran

Sadough

2016

Trans. Emerging Tel. Tech.

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Cognitive radio (CR) systems based on orthogonal frequency‐division multiplexing have so far obtained a great deal of attention in wireless communications requiring higher data rates. It is well known that the highest achievable data rate in a wireless communication system is restricted by some factors including the wireless communication channel and the hardware imperfection, which are unavoidable in practice. One of the most important implementation issues that significantly affects the performance of the receiver and the transmitter is the amplitude and phase imbalance in the inphase and quadrature branches, or for brevity inphase and quadrature imbalance (IQI). This imbalance is due to non‐ideal local oscillators at the transmitter or at the receiver of direct conversion systems. In this paper, the ergodic capacity is investigated in a CR system based on orthogonal frequency‐division multiplexing. We also inspect the outage probability, which is restricted by the common IQI challenge in the transmitter of the secondary user (SU) and in the receiver of the SU in a Rayleigh fading channel. First, we obtain an approximate closed‐form expression for the ergodic capacity and the outage probability in a multi‐carrier system. Then we investigate the special cases in which IQI only exists at the receiver or at the transmitter. We show that when IQI only exists at the transmitter of the SU, the approximate closed‐form outage probability of the SU approaches its exact value. Also, when IQI only exists at the receiver or at the transmitter of the SU, the approximate closed form of the ergodic capacity of the secondary link approaches its exact value. Numerical results validate the obtained analytical expression in the CR system. Our results may serve in the evaluation of the trade‐off between the required quality of service (in terms of secondary achieved throughput and the outage probability) and CR system parameters in the presence of IQI. Copyright © 2016 John Wiley & Sons, Ltd.

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A Blind Likelihood-Based Approach for OFDM Spectrum Sensing in the Presence of I/Q Imbalance

Cited by 13 publications

References 26 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

Amplify-and-forward relay identification using joint Tx/Rx I/Q imbalance-based device fingerprinting

Achieved throughput of OFDM‐based cognitive radio systems in the presence of inphase quadrature imbalance

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