Unused Beam Reservation for PAPR Reduction in Massive MIMO System

Ivanov, Andrey; Volokhatyi, Artyom; Lakontsev, Dmitry; Yarotsky, Dmitry

doi:10.1109/vtcspring.2018.8417537

Cited by 18 publications

(9 citation statements)

References 8 publications

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“…In a different class of approaches, the PAPR reduction signal is generated using free spatial directions [17]. Extra benefit in the downlink of MU-MIMO applications is provided by the [18] method for unused beam reserve (UBR), which makes use of free spatial beams. By employing non-iterative amplitude modulation of idle beams without users, it is possible to avoid signal deterioration for target users while lowering PAPR for every transmitting antenna.…”

Section: A Papr Reduction Methodsmentioning

confidence: 99%

Selective tone reservation for PAPR reduction in wireless communication systems

Ivanov

Lakontsev

2017

2017 IEEE International Workshop on Signal Processing Systems (SiPS)

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In this paper, we propose a trainable least squares (LS) approach for reducing the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals in a hybrid beamforming (HBF) system.Compared to digital beamforming (DBF), in HBF technology the number of antennas exceeds the number of digital ports. Therefore, PAPR reduction capabilities are restricted by both a limited bandwidth and the reduced size of digital space. The problem is to meet both conditions. Moreover, the major HBF advantage is a reduced system complexity, thus the complexity of the PAPR reduction algorithm is expected to be low.To justify the performance of the proposed trainable LS, we provide a performance bound achieved by convex optimization using the CVX Matlab package. Moreover, the complexity of the proposed algorithm can be comparable to the minimal complexity of the digital "twin" calculation in HBF. The abovementioned features prove the feasibility of the trained LS for PAPR reduction in fully-connected HBF.

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Section: A Papr Reduction Methodsmentioning

confidence: 99%

Selective tone reservation for PAPR reduction in wireless communication systems

Ivanov

Lakontsev

2017

2017 IEEE International Workshop on Signal Processing Systems (SiPS)

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“…A PAPR reduction scheme assisted by DL for a MIMO-OFDM system was suggested in [34]. The authors apply selective tone reservation [35] on each antenna separately and then apply unused beam reservation [36] on all antennas together. An ML-based method for approximating the optimal tabular hyperparameters required for using selective tone reservation and unused beam reservation was suggested.…”

Section: Deep-learning-based Schemes (Data Driven) For Papr Reductionmentioning

confidence: 99%

Low PAPR MIMO-OFDM Design Based on Convolutional Autoencoder

Huleihel¹,

Permuter²

2023

Preprint

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An enhanced framework for peak-to-average power ratio (PAPR) reduction and waveform design for Multiple-Input-Multiple-Output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems, based on a convolutional-autoencoder (CAE) architecture, is presented. The end-to-end learning-based autoencoder (AE) for communication networks represents the network by an encoder and decoder, where in between, the learned latent representation goes through a physical communication channel.We introduce a joint learning scheme based on projected gradient descent iteration to optimize the spectral mask behavior and MIMO detection under the influence of a non-linear high power amplifier (HPA) and a multipath fading channel. The offered efficient implementation novel waveform design technique utilizes only a single PAPR reduction block for all antennas. It is throughput-lossless, as no side information is required at the decoder. Performance is analyzed by examining the bit error rate (BER), the PAPR, and the spectral response and compared with classical PAPR reduction MIMO detector methods on 5G simulated data. The suggested system exhibits competitive performance when considering all optimization criteria simultaneously. We apply gradual loss learning for multi-objective optimization and show empirically that a single trained model covers the tasks of PAPR reduction, spectrum design, and MIMO detection together over a wide range of SNR levels.

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“…In addition, an extension to non-linear precoding is not presented. In [24], a two-dimensional tone reservation method utilizing reserved tones and unused beams are proposed where peak cancellation signals are designed by combining the frequency-domain PAPR reduction (i.e., TR) and space-domain PAPR reduction (i.e., utilizing the unused beam). However, this method requires extra subcarriers, in addition, extra beams (i.e., spatial degree of freedom).…”

Section: Related Workmentioning

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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Unused Beam Reservation for PAPR Reduction in Massive MIMO System

Cited by 18 publications

References 8 publications

Selective tone reservation for PAPR reduction in wireless communication systems

Selective tone reservation for PAPR reduction in wireless communication systems

Low PAPR MIMO-OFDM Design Based on Convolutional Autoencoder

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

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