Performance Analysis of OFDM With Peak Cancellation Under EVM and ACLR Restrictions

Kageyama, Tomoya; Muta, Osamu; Gacanin, Haris

doi:10.1109/tvt.2020.2982587

Cited by 14 publications

(20 citation statements)

References 32 publications

(41 reference statements)

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“…After that,Ŵ r is updated to minimize square error of the error signal in Eq. (12). Similar to the above, W t andŴ r are updated alternatively until number of alternative iterations come to a given number N r .…”

Section: Weight Optimization Methodsmentioning

confidence: 99%

“…Adaptive peak cancellation was proposed for reducing PAPR of OFDM signals 12) . This technique is used to reduce PAPR of OFDM signal while keeping EVM and ACLR below their permissible levels.…”

Section: Ber Analysis Of Mrc-precoded Massive Mimo Ofdm Systems With mentioning

confidence: 99%

“…0 denotes time instance when the i-th maximum peak amplitude is detected. Then, we can estimate distortion power added on the transmit signal by calculating the increased ACLR and EVM due to peak cancellation 12) . Figure 7 illustrates the effect of in-band distortion and out of band (OoB) radiation due to adding the PC signal to cancel the peak amplitude.…”

Section: Adaptive Peak Cancellationmentioning

confidence: 99%

“…When N = 1, only in-band distortion due to PC occurs because there is no IUI. σ P C depends on the required in-band distortion power and it can be theoretically derived 12) .…”

Section: Ber Analysismentioning

confidence: 99%

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[Invited Paper] Performance Analysis of Precoded MIMO Systems with Adaptive Peak Power Suppression

Muta

Kageyama²

2020

MTA

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This paper presents two approaches for reducing the peak power in precoded multi-input multi-output (MIMO) systems with space division multiplexing (SDM). First, we present a peak power aware linear precoding scheme for MIMO-SDM single carrier systems, where the precoder is designed to restrict per-antenna transmit power below a permissible level while mitigating the performance degradation caused by per-antenna power restriction. Second, we present an analytical method to represent bit error rate (BER) performance of maximum ratio combining (MRC) precoded massive MIMO OFDM systems with adaptive peak cancellation, where peak amplitude is canceled below a given threshold to reduce peak-to-average power ratio (PAPR). With this method, we clarify the impact of adaptive peak cancellation on approximated BER of MRCprecoded massive MIMO OFDM with an arbitrary number of the transmit antennas and users. Numerical results prove that our proposed approaches are effective in restricting the peak power at each antenna while mitigating performance degradation in BER performance of the precoded MIMO-SDM systems.

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Section: Weight Optimization Methodsmentioning

confidence: 99%

Section: Ber Analysis Of Mrc-precoded Massive Mimo Ofdm Systems With mentioning

confidence: 99%

Section: Adaptive Peak Cancellationmentioning

confidence: 99%

“…When N = 1, only in-band distortion due to PC occurs because there is no IUI. σ P C depends on the required in-band distortion power and it can be theoretically derived 12) .…”

Section: Ber Analysismentioning

confidence: 99%

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[Invited Paper] Performance Analysis of Precoded MIMO Systems with Adaptive Peak Power Suppression

Muta

Kageyama²

2020

MTA

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“…However, one of the drawbacks in OFDM is high peak-to-average power ratio (PAPR) which may cause non-linear distortion and out-ofband (OoB) radiation at the output of power amplifier. Thus, PAPR reduction for OFDM signal is a challenging issue, and various PAPR reduction methods are investigated [3]- [13].…”

Section: Introductionmentioning

confidence: 99%

Enhanced Peak Cancellation With Simplified In-Band Distortion Compensation for Massive MIMO-OFDM

2020

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This paper presents an enhanced peak cancellation method with simplified in-band distortion compensation for massive multi-input multi-output (mMIMO) orthogonal frequency division multiplexing (OFDM). The method compensates an in-band distortion due to peak cancellation by utilizing extra transmit antennas, where a compensation signal is designed and transmitted using extra antenna elements so that inband distortion is canceled at the receiver end. Consequently, deep peak cancellation is possible without degrading bit error rate performance. The proposed method is further extended to non-linear precoded mMIMO-OFDM systems, where the perturbation vector cancellation signal is superimposed on the compensation signal so that the received signal is demodulated without non-linear processing to remove the perturbation vector. Thus, the proposed method does not require the iterative calculation to compensate for an in-band distortion. Our results show the effectiveness of the proposed method in terms of peak-to-average power ratio (PAPR) characteristics, signal to noise and distortion power ratio (SDNR), bit error rate (BER), and throughput in comparison with the state-of-the-art.INDEX TERMS Massive multiple-input multiple-output (MIMO), orthogonal frequency-division multiplexing (OFDM), peak-to-average power ratio (PAPR).

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Enhanced channel prediction in large‐scale5G MIMO‐OFDMsystems using pyramidal dilation attention convolutional neural network

Rathish,

Manojkumar,

Thanga Mariappan

et al. 2024

Internet Technology Letters

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In order to enhance communication while minimizing complexity in 5G and beyond, MIMO‐OFDM systems need accurate channel prediction. In order to enhance channel prediction, decrease Error Vector Magnitude, Peak Power, and Adjacent Channel Leakage Ratio, this study employs the Pyramidal Dilation Attention Convolutional Neural Network (PDACNN). Simplified clipping with filtering (SCF) reduces PAPR data, and this technique employs a PDACNN trained with the reduced data. By combining attention techniques with pyramidal dilated convolutions, the suggested PDACNN architecture is able to extract OFDM channel parameters across several scales. Attention approaches enhance channel prediction by allowing the model to dynamically concentrate on essential information. The primary objective is to make use of the network's ability to comprehend intricate spatial–temporal connections in OFDM channel data. The goal of these techniques is to make channel forecasts more accurate and resilient while decreasing concerns about EVM, Peak Power, and ACLR. To confirm the effectiveness of the suggested CP‐LSMIMO‐OFDM‐PDACNN, we measure its spectral efficiency, peak‐to‐average power ratio, bit error rate (BER), signal‐to‐noise ratio (SNR), and throughput. Throughput gains of 23.76%, 30.45%, and 18.97% are achieved via CP‐LSMIMO‐OFDM‐PDACNN, while bit error rates of 20.67%, 12.78%, and 19.56% are reduced. PAPRs of 21.66%, 23.09%, and 25.11% are also decreased.

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Performance Analysis of OFDM With Peak Cancellation Under EVM and ACLR Restrictions

Cited by 14 publications

References 32 publications

[Invited Paper] Performance Analysis of Precoded MIMO Systems with Adaptive Peak Power Suppression

[Invited Paper] Performance Analysis of Precoded MIMO Systems with Adaptive Peak Power Suppression

Enhanced Peak Cancellation With Simplified In-Band Distortion Compensation for Massive MIMO-OFDM

Enhanced channel prediction in large‐scale5G MIMO‐OFDMsystems using pyramidal dilation attention convolutional neural network

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