Filter Bank Multicarrier With Offset Quadrature Amplitude Modulation Signals Research Articles

Papr reduction of FBMC-OQAM signals using Phase Search-PTS and modified discrete fourier transform spreading

In this research, a novel peak-to-average power ratio (PAPR) reduction technique for filter bank multicarrier (FBMC) modulation systems is presented. With multicarrier systems like FBMC, the strategy focuses on the survival of the fittest principle to suit the value of PAPR. The Filter Bank Multicarrier with Offset Quadrature Amplitude Modulation (FBMC-OQAM) has recently captured the attention of numerous academics due to its minimal adjacent channel leakage ratio (CLR). Unfortunately, the issue of increased PAPR measurement has a negative impact on the effectiveness of the FBMC system's energy measurement. In this study, the Phase search-based Partial Transmit Sequence (PS-PTS) approach and Modified Discrete Fourier Transform Spreading (MDFT) are developed for the PAPR reduction of the FBMC-OQAM signals. The increased PAPR measurement is reduced using the PTS and MDFT with osprey optimization method, which may result in a PAPR reduction of roughly 5.1 dB as comparable to the conventional approach.

Analysis of peak-to-average power ratio in filter bank multicarrier with offset quadrature amplitude modulation systems using partial transmit sequence with shuffled frog leap optimization technique

<p class="Abstract">Because of its low adjacent channel leakage ratio, the Filter Bank Multicarrier with Offset Quadrature Amplitude Modulation (FBMC-OQAM) has sparked the attention of many researchers in recent times. However, the problem of high Peak-to-Average Power Ratio (PAPR) measurement has a detrimental influence upon the FBMC system's energy measurement efficiency. We study PAPR reduction of FBMC-OQAM signals using the Partial Transmit Sequence (PTS) methods in this work. The PTS with shuffled frog leap phase optimization method is proposed in this paper to reduce the larger PAPR measurement, which is the major disadvantage of the filter bank multicarrier with offset quadrature amplitude modulation system. According to the simulation software findings, the suggested approach has a considerably superior PAPR, which may reduce the PAPR by about 2 dB at complementary cumulative distribution function 10<sup>-3</sup> when compared to the traditional PTS method, and it has a much lower computational complexity than the previous ways. The experimental parameters are measured, and results are evaluated using MATLAB tool.</p>

Supervised learning and frequency domain averaging‐based adaptive channel estimation scheme for filterbank multicarrier with offset quadrature amplitude modulation

Filterbank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) is an attractive alternative to the orthogonal frequency division multiplexing (OFDM) modulation technique. In comparison with OFDM, the FBMC-OQAM signal has better spectral confinement and higher spectral efficiency and tolerance to synchronization errors, primarily due to per-subcarrier filtering using a frequency-time localized prototype filter. However, the filtering process introduces intrinsic interference among the symbols and complicates channel estimation (CE). An efficient way to improve the CE in FBMC-OQAM is using a technique known as windowed frequency domain averaging (FDA); however, it requires a priori knowledge of the window length parameter which is set based on the channel's frequency selectivity (FS). As the channel's FS is not fixed and not a priori known, we propose a k-nearest neighbor-based machine learning algorithm to classify the FS and decide on the FDA's window length. A comparative theoretical analysis of the mean-squared error (MSE) is performed to prove the proposed CE scheme's effectiveness, validated through extensive simulations. The adaptive CE scheme is shown to yield a reduction in CE-MSE and improved bit error rates compared with the popular preamble-based CE schemes for FBMC-OQAM, without a priori knowledge of channel's frequency selectivity.

New scheme for PAPR reduction in FBMC-OQAM systems based on combining TR and deep clipping techniques

Filter bank multi-carrier with offset quadrature amplitude modulation (FBMC-OQAM) system is a very efficient multicarrier modulation technique for 5G, but it suffers as all multicarriers designs from large peak-to-average power ratio (PAPR). Tone reservation (TR) is a method designed to solve this problem by reserving several subcarriers called tones in the frequency domain to generate a cancellation signal in the time domain to eliminate high peaks. In this paper, we suggest a serial combination of tone reservation (TR) method with an enhanced version of clipping called deep clipping (DC) method (TR&DC) to enhance the peaks (PAPR) mitigation in FBMC-OQAM signal model without significantly impacting the quality of transmission. Numerical results and analysis show that the new TR&DC approach allows better overall performance and offers remarkable gain in term of PAPR mitigation than the TR method, with similar BER performance to TR over additive white gaussian noise channel and Rapp HPA model.

Spectral Re-Growth Suppression in the FBMC-OQAM Signal Under the Non-linear Behavior of a Power Amplifier

Typically, the filter bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) bears some impressive properties that make it popular as one of the substitutes to orthogonal frequency division multiplexing (OFDM) for the upcoming technology of broadband wireless communication systems. Although FBMC-OQAM preserves the multicarrier modulation (MCM) features, its spectrum usually suffers from impairments when subjected to the nonlinear behavior of a power amplifier (PA) which results in spectral re-growth. Due to the spectrum limitation and low energy efficiency foreseen in the forthcoming 5G networks, it is vital to confine the spectrum of the FBMC-OQAM signal within the allocated band of interest. In this paper, the suppression of the spectral re-growth experienced on the FBMC-OQAM signal due to the nonlinear distortion effects introduced by the PA is investigated. The crest factor reduction (CFR) method in combination with an adaptive digital pre-distortion (DPD) are used. The peak windowing technique based on sequential asymmetric superposition windowing (SASW) algorithm is used in the CFR part while the least square estimation with QR-decomposition (LSE/QR) has been used as the coefficient’s estimator and adaptation algorithm in the DPD part. The performance of the two combined techniques has been evaluated on SystemVue2018 simulation platform. The adjacent channel leakage ratio (ACLR) and the error vector magnitude (EVM) have been considered as the performance merits. The simulation results show that the proposed techniques significantly improve the spectrum, first by reducing the PAPR of the FBMC-OQAM signal by about 1.5dB. Secondly, the spectral re-growth has been reduced by about -45.74dB adjacent channel leakage suppression and the error vector magnitude measure has been obtained to be about 7.12%. (-22.95dB). These values lead to better average input power of the FBMC-OQAM signal and improvement in the spectral efficiency and they are in accordance with the 3GPP standard for wideband signals in nonlinear systems.

Nonlinear Complex Support Vector Regression for Fading Channel Estimation in FBMC-OQAM System

Most channel estimation techniques for orthogonal frequency division multiplexing system are not directly applicable to filter bank multi-carrier with offset quadrature amplitude modulation (FBMC-OQAM) system because of the imaginary interference of FBMC-OQAM system. Thus, a novel support vector regression (SVR) algorithm for fading channel estimation in FBMC-OQAM system is proposed. We propose a nonlinear complex SVR algorithm (NCSVR) adapted to two auxiliary pilots (AP)-based FBMC-OQAM signal, namely as AP-NCSVR. The practicality of our method is proved by simulation results obtained for Jakes fading model and vehicular A model. Simulation results reveal the accuracy of the proposed AP-NCSVR algorithm to estimate channel frequency response coefficients and show that the bit error rate performance of the proposed AP-NCSVR algorithm is better than the conventional interpolation method for Jakes fading model and vehicular A model.

Compressive Sensing-Based Channel Estimation for FBMC-OQAM System Under Doubly Selective Channels

Filter-bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) has been considered as an alternative scheme to orthogonal frequency division multiplexing (OFDM). However, the traditional channel estimation techniques of the OFDM cannot be directly applied to the FBMC-OQAM system because of the real-field orthogonality of the FBMC-OQAM signals. Although traditional channel estimation techniques, such as least square (LS) and minimum mean square error (MMSE), are widely applied to the FBMC-OQAM system via canceling the intrinsic imaginary interference from adjacent data symbols, the LS algorithm is subject to noise enhancement and it results in large mean square error (MSE), while the mmse algorithm needs to know the statistical information of channel in advance. Due to sparsity of the wireless channel, channel estimation is investigated as a compressive sensing (CS) problem. In this paper, we first introduce the coding method to cancel intrinsic imaginary interference for the FBMC-OQAM system. Then, a novel sparse adaptive subspace pursuit (SASP) method is proposed to improve the accuracy of LS channel estimation. Finally, we develop two distinctive algorithms, namely, auxiliary pilot (AP) SASP and coding-SASP, to estimate channel frequency respond (CFR) in the FBMC-OQAM system. The simulation results show that the AP-SASP and coding-SASP algorithms can offer a low complexity and fewer measurements compared with conventional orthogonal matching pursuit (OMP) and regularized OMP (ROMP) methods. Moreover, the proposed AP-SASP and coding-SASP algorithms have a better bit error ratio (BER) performance than the conventional OMP and ROMP methods for FBMC system in the doubly selective channels.

Low-Complexity PTS Scheme for PAPR Reduction in FBMC-OQAM Systems

Most of the peak-to-average power ration (PAPR) reduction techniques, such as partial transmit sequence (PTS) algorithm and selective mapping algorithm, for conventional OFDM systems are not directly applied to filter bank multi-carrier with offset quadrature amplitude modulation (FBMC-OQAM) systems because of the overlapping structure of FBMC-OQAM signals. Furthermore, the complexity of the existing algorithms based on PTS is very high for the FBMC-OQAM systems. In this letter, we propose a low-complexity PTS based on hybrid processing algorithm (H-PTS) to reduce the PAPR values of FBMC-OQAM systems. Firstly, the proposed algorithm processes phase factors of the PTS by double-layer search. As a result, the complexity of searching the optimal phase factors is simplified. Moreover, an efficient algorithm of estimating the PAPR values of the FBMC-OQAM signals is employed to further reduce computational complexity. Simulation results show that, compared with the conventional PTS algorithm and segmental PTS algorithm, the proposed H-PTS algorithm could achieve a better PAPR reduction as well as lower computational complexity.

Sparse PTS scheme based on TR schemes for PAPR reduction in FBMC‐OQAM systems

The filter bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) has aroused widespread concern in the 5G communication. However, FBMC-OQAM has an inherent drawback of high peak-to-average power ratio (PAPR) that should be mitigated. Here, the authors propose an efficient hybrid scheme based on sparse partial transmit sequence (sparse PTS) scheme and tone reservation (TR) scheme to reduce the PAPR in FBMC-OQAM systems. The first step is to detect and record the location of peak of FBMC-OQAM signals and adopt phase rotation factors (based on PTS) to directly optimise the phase of recorded peak signals, which is called sparse PTS. Then the result is further processed by TR scheme for PAPR reduction. Simulation results show that the proposed hybrid scheme provides better PAPR reduction performance than the two schemes, and can achieve less side information transmitted than the sparse PTS scheme.

Modified PTS-based PAPR Reduction for FBMC-OQAM Systems

The filter bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) has been raised great concern in the 5G communication research. However FBMC-OQAM has also the inherent drawback of high peak-to-average power ratio (PAPR) that should be addressed. Due to the overlapping structure of FBMC-OQAM signals, it is proven that directly employing conventional partial transmit sequence (PTS) scheme proposed for OFDM to FBMC-OQAM is ineffective. In this paper, we propose a modified PTS-based scheme by employing phase rotation factors to optimize only the phase of the sparse peak signals, called as sparse PTS (S-PTS) scheme. Theoretical analysis and simulation results show that the proposed S-PTS scheme provides a significant PAPR reduction performance with lower computational complexity.

Multi-Block Joint Optimization for the Peak-to-Average Power Ratio Reduction of FBMC-OQAM Signals

Recently, the filter bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) has attracted increasing attention. However, most peak-to-average power ratio (PAPR) reduction schemes developed for orthogonal frequency division multiplexing (OFDM) signals are not effective for FBMC-OQAM signals, due to the overlapping structure of FBMC-OQAM signals. In this paper, we propose an improved partial transmit sequence (PTS) scheme by employing multi-block joint optimization (MBJO) for the PAPR reduction of FBMC-OQAM signals, called as MBJO-PTS scheme. In PTS scheme, one data block is divided into several subblocks and each subblock is multiplied by a phase rotation factor for the subblock. The PTS scheme searches over all combinations of allowed phase factors to lower the PAPR. Unlike existing PAPR reduction schemes of independently optimizing the data blocks, the MBJO-based scheme exploits the overlapping structure of the FBMC-OQAM signal and jointly optimizes multiple data blocks. Moreover, we develop two algorithms for the optimization problem in the MBJO-PTS scheme, including a dynamic programming (DP) algorithm to guarantee the optimal solution and avoid exhaustive search. Theoretical analysis and simulations show that the proposed MBJO-PTS scheme could provide a significant PAPR reduction in the FBMC-OQAM system, by exploiting the overlapping structure of the FBMC-OQAM signal. Employing the proposed DP algorithm, the FBMC-OQAM system with the proposed MBJO-PTS scheme even outperforms the OFDM system with the conventional PTS scheme by 0.9 dB at CCDF of 10-3 in PAPR reduction, under the same number of subcarriers, modulation type and PTS parameters given in Section V.

Sliding Window Tone Reservation Technique for the Peak-to-Average Power Ratio Reduction of FBMC-OQAM Signals

The filter bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) has attracted increasing attention recently. In this paper, we address the problem of PAPR reduction for FBMC-OQAM systems using Tone Reservation (TR) technique. Due to the overlapping structure of FBMC-OQAM signals, directly applying TR schemes of OFDM systems to FBMC-OQAM systems is not effective. We improve the tone reservation (TR) technique by employing sliding window for the PAPR reduction of FBMC-OQAM signals, called sliding window tone reservation (SW-TR) technique. The proposed SWTR technique uses the peak reduction tones (PRTs) of several consecutive data blocks to cancel the peaks of the FBMC-OQAM signal inside a window. Furthermore, we propose a method to overlap the sliding windows to control the out-of-window peak regrowth caused by the peak-canceling signal.