Estimation of Wideband IQ Imbalance in MIMO OFDM Systems With CFO

Sandell, Magnus; Tsimbalo, Evgeny; Jardak, Seifallah; Uchida, Daisuke; Akita, Koji; Yoda, Daiki; Kawaguchi, Takeshi; Sano, Masahiko

doi:10.1109/twc.2021.3070387

Cited by 14 publications

(9 citation statements)

References 16 publications

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“…Input: Setting the initial population while ðT < Maximum number of iterationsÞ calculate the fitness value of each search agent for each search agent update the density and volume of every object utilizing equation (12) update transfer and density reducing factors using equation (13) if ðT < 0:5Þ update acceleration through equation ( 14) and normalize the acceleration through equation (15) update position with the help of equation (11) else update direction flag using D p end if end for estimate every object and select one with best fitness value…”

Section: Optimization Using Hybrid Archimedes Optimization Algorithm ...mentioning

confidence: 99%

“…9,10 Fully connected deep neural network (FCDNN) is developed as DL-based CE and signal identification technique for OFDM systems that directly recovers the broadcast symbols and estimates the CSI indirectly. 11,12 Consider the super-resolution network cascade with de-noising imagery renovation network to evaluate single-input singleoutput (SISO) fast fading channel while treating the pilot data as a low resolution image. 13 The end-to-end DL is employed for signal transmitting and receiving with communication being deemed as a black-box.…”

Section: Introductionmentioning

confidence: 99%

“…In beam space millimeter wave massive MIMO schemes, the receiver is designed with a small number of radio‐frequency (RF) chains using learned denoising‐base approximate message passing network 9,10 . Fully connected deep neural network (FCDNN) is developed as DL‐based CE and signal identification technique for OFDM systems that directly recovers the broadcast symbols and estimates the CSI indirectly 11,12 . Consider the super‐resolution network cascade with de‐noising imagery renovation network to evaluate single‐input single‐output (SISO) fast fading channel while treating the pilot data as a low resolution image 13 .…”

Section: Introductionmentioning

confidence: 99%

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Dual interactive Wasserstein generative adversarial networks optimized with hybrid Archimedes optimization and chimp optimization algorithm‐based channel estimation in OFDM

Mydhili

2024

Int J Communication

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SummaryDual interactive Wasserstein generative adversarial networks optimized with hybrid Archimedes optimization and chimp optimization algorithm‐based channel estimation in OFDM (DiWGAN‐Hyb AOA‐COA‐MIMO‐OFDM) is proposed in this manuscript. In OFDM, there is a non‐stationary channel physical appearance during channel estimation (CE). Therefore in this work, Hyb AOA‐COA is employed to enhance the DiWGAN weight parameters. The proposed DiWGAN‐Hyb AOA‐COA‐MIMO‐OFDM technique is executed in network simulator (NS2) tool. The proposed technique attains lower computational cost 99.67%, 92.34%, and 97.45%; lesser bit error rate 98.33%, 83.12%, and 88.96%; and lesser mean square error 93.15%, 79.90%, and 92.88% compared with existing methods, like MIMO‐OFDM system using deep neural network and MN‐based improved AMO model (DNN‐IAMO‐MIMO‐OFDM), MIMO‐OFDM systems using the deep learning and optimization (RBFNN‐PSO‐MIMO‐OFDM), and MIMO‐OFDM systems using hybrid neural network (HNN‐CSI‐MIMO‐OFDM) respectively.

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Section: Optimization Using Hybrid Archimedes Optimization Algorithm ...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Dual interactive Wasserstein generative adversarial networks optimized with hybrid Archimedes optimization and chimp optimization algorithm‐based channel estimation in OFDM

Mydhili

2024

Int J Communication

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“…Reformulating the preceding equations allows us to arrive at a solution to the issue at hand. Using ( 6), (10), into (12), we describe y…”

Section: Proposed Em Estimation Algorithmmentioning

confidence: 99%

“…OFDM systems are more susceptible to the IQ discrepancy than singlecarrier systems because of the spectral overlap between the subcarriers. As a consequence of the IQ mismatch issue, sub-carrier orthogonality is lost, which in turn causes inter-carrier interference and a significant drop in performance [12], [13]. There is a wealth of literature on the topic of the impact, estimate, and correction of IQ mismatch for non-cooperative OFDM transmissions, see e.g., [14] and references therein.…”

Section: Introductionmentioning

confidence: 99%

Coded Assisted Transmit and Receive IQ Mismatch Compensation With Channel Estimation for AF Cooperative OFDM Systems

Marey

Mostafa

2023

IEEE Access

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Amplify-and-forward (AF) orthogonal frequency division multiplexing (OFDM) transmissions encounter a significant difficulty in the form of in-phase and quadrature phase (IQ) mismatch. Previous reports on this problem have solely been discussed in the context of uncoded transmissions. In addition, in these precedent studies, IQ equalization must be conducted following the estimation stage for accurate detection of data symbols. This research delves into the issue of the IQ mismatch between transmission and reception in AF-OFDM systems in the context of channel coding. We design a magnificent code-aided approach to predict the overall channel impulse responses (CIRs), which encompass the actual CIRs and IQ mismatch originating at the source, relay, and destination. Instead of using a collection of algorithms, the proposed approach can be utilized to estimate nine parameters simultaneously. Due to the impractical nature of the precise maximum-likelihood (ML) strategy to this situation, we instead utilize an expectation-maximization (EM) process as a low complexity strategy to predict the parameters under consideration. The suggested estimation approach uses an iterative process to improve predictions exploiting the a priori knowledge gained from the soft information supplied by the channel decoder. In addition, we demonstrate how to carry out data detection by making use of the estimated parameters. The simulation results verify the effectiveness of the proposed estimator and detector for usage in real-world settings, with superiority over the conventional ones.

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Joint Channel and IQ Imbalance Compensation Method for MIMO-OFDM Using in Coastal Railway

Nishibe,

Shibakura,

Miyamoto

et al. 2024

J. Electr. Eng. Technol.

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Estimation of Wideband IQ Imbalance in MIMO OFDM Systems With CFO

Cited by 14 publications

References 16 publications

Dual interactive Wasserstein generative adversarial networks optimized with hybrid Archimedes optimization and chimp optimization algorithm‐based channel estimation in OFDM

Dual interactive Wasserstein generative adversarial networks optimized with hybrid Archimedes optimization and chimp optimization algorithm‐based channel estimation in OFDM

Coded Assisted Transmit and Receive IQ Mismatch Compensation With Channel Estimation for AF Cooperative OFDM Systems

Joint Channel and IQ Imbalance Compensation Method for MIMO-OFDM Using in Coastal Railway

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