A new PAPR reduction method based on clipping technique using compressive sensing

Masoumian, Seyyed Hadi Seyyed; Shabani, Maryam; Tazehkand, Behzad Mozaffari

doi:10.1109/istel.2012.6482990

Cited by 10 publications

(11 citation statements)

References 24 publications

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“…For instance, the authors in [49] have used CS to reduce the PAPR of the optical OFDM signal. In [50], CS is applied to recover the original signal after the clipping issue by using l 1 -norm optimization which has a high computational complexity. However, the OMP is often used as a CS algorithm to reconstruct the linear signal due to its simplicity and less complexity than Basis Pursuit (BP) algorithms [51][52][53].…”

Section: Related Workmentioning

confidence: 99%

BER Analysis and CS-Based Channel Estimation and HPA Nonlinearities Compensation Technique for Massive MIMO System

et al. 2022

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Massive Multiple Input Multiple Output (MIMO) system has gathered lately a huge interest from researchers and it has been known as a backbone technology for the 5th generation because it can greatly improve the capacity of wireless communication and it can potentially provide energy efficiency and security. Before ensuring the full advantages, massive MIMO system has to overcome many challenges. One of them is to accurate an exact estimation of the Channel Impulse response (CIR) between each transmitreceive antenna pair. The other problem arises when implementing such a system in presence of High Power Amplifiers (HPA) which imposes a nonlinear distortion on the transmitted signals. This paper proposes contributions in three key areas. Firstly, we investigate the nonlinear effects of memoryless HPA, which is modeled using Saleh model, by deriving its Bit Error Rate expression (BER) in massive MIMO Orthogonal Frequency Division Multiplexing (OFDM) system. Secondly, we highlight the necessity of providing the accurate channel characteristics by estimating it using Compressive Sensing (CS) techniques. Moreover, we propose also a CS compensation algorithm based on Orthogonal Matching Pursuit (OMP) to mitigate the nonlinear distortion in the receiver. The proposed CS-based compensation technique has been compared to the Neural Network (NN) pre and post compensation technique and it has shown a good performance not only in terms of BER but also in terms of complexity.

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Section: Related Workmentioning

confidence: 99%

BER Analysis and CS-Based Channel Estimation and HPA Nonlinearities Compensation Technique for Massive MIMO System

et al. 2022

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“…To verify the effectiveness of the proposed algorithm, under different clipping ratios (i.e., the clipping distortion is to be reconstructed).The BER performance of the proposed algorithm is to be analyzed under Rayleigh channel model, and then a suitable clipping threshold is to be selected for the proposed algorithm. Figure 3 shows the BER performance comparison of the proposed algorithm and clipping algorithm in [10] with different clipping ratios, under Rayleigh fading channel. The BER performance of the proposed algorithm is slightly worse than the algorithm in [10], this is because the clipping noise, when the clipping ratio is high is relatively small, the noise impact is relatively large at low SNR, and the corresponding compensation is selected.…”

Section: Ber Performancementioning

confidence: 99%

“…The Compressive Sensing (CS) algorithms proposed in literature [27][28][29] reserve the empty subcarriers, these algorithms need to reserve the empty subcarriers in advance as observation vectors, which reduces the data transmission efficiency. In literature [10] an improved CS algorithm is proposed, which selects the part affected by noise as the observation vector from the data subcarriers and uses the CS algorithm to reconstruct the Website: www.ijeer.forexjournal.co.in Novel Algorithm for Nonlinear Distortion Reduction Based on Clipping and Compressive Sensing in OFDM/OQAM System clipped noise signal. This algorithm needs reserve empty subcarriers, thereby reducing the data transmission efficiency.…”

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confidence: 99%

Novel Algorithm for Nonlinear Distortion Reduction Based on Clipping and Compressive Sensing in OFDM/OQAM System

Vaigandla

Benita

2022

IJEER

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Orthogonal Frequency Division Multiplexing with Offset Quadrature Amplitude Modulation (OFDM/OQAM) signal has high peak-to-average power ratio (PAPR) problem. It not only affects the distortion in High Power Amplifier (HPA) but also results in bit error ratio (BER) degradation. In this paper an improved algorithm based on Clipping and Compressed Sensing (CS) is proposed. The transmitter uses clipping to reduce the PAPR and, the receiver uses an improved inverse model, to reduce the nonlinear distortion introduced by HPA and CS cancels the signal distortion introduced by clipping. Simulation results show that the proposed method not only significantly reduces the PAPR of OFDM/OQAM signals, but also effectively improves the BER performance of the system.

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“…The early proposed clipping distortion recovery methods used the principle of peak regeneration of the clipping signal, and iteratively recovers the clipping distortion in the time domain or the frequency domain [20], [21]. Compressed sensing(CS) was proposed in 2006, and some scholars noticed that the clipping distortion is sparse in the time domain, so they applied the CS technology to the clipping distortion recovery [22], [23]. Early scholars proposed to use a pilot or empty sub-carriers to recover clipping distortion based on compressed sensing, but both methods waste the frequency domain resources [24], [25].…”

Section: Introductionmentioning

confidence: 99%

Signal Assisted Clipping Distortion Recovery for OFDM Systems Based on Compressed Sensing

Deng

2020

IEEE Access

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The clipping distortion, which generated in the orthogonal frequency division multiplexing systems will have a serious impact on the bit error performance, can be mitigated by clipping distortion recovery techniques. In this paper, we propose a compressed sensing (CS) based signal assisted Clipping Distortion Recovery (saCDR). At the transmitter, we use the clipping position to generate an auxiliary signal to transmit sparse information. The proposed method solves the problem that it is difficult to obtain the sparsity K when the receiver uses orthogonal matching pursuit (OMP) for clipping distortion recovery. At the receiver, we propose the location-assisted OMP algorithm (laOMP), which greatly reduces the system complexity and can still ensure good recovery performance under severe clipping scenarios. Simulation results show that the proposed method can obtain good bit error rate performance under different channels.INDEX TERMS clipping distortion, orthogonal frequency division multiplexing systems(OFDM), clipping, compressed sensing(CS)

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A new PAPR reduction method based on clipping technique using compressive sensing

Cited by 10 publications

References 24 publications

BER Analysis and CS-Based Channel Estimation and HPA Nonlinearities Compensation Technique for Massive MIMO System

BER Analysis and CS-Based Channel Estimation and HPA Nonlinearities Compensation Technique for Massive MIMO System

Novel Algorithm for Nonlinear Distortion Reduction Based on Clipping and Compressive Sensing in OFDM/OQAM System

Signal Assisted Clipping Distortion Recovery for OFDM Systems Based on Compressed Sensing

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