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A new Approach to Iterative Clipping and Filtering PAPR Reduction Scheme for OFDM Systems
Abstract and Figures
While achieving reduced/good peak-to-average power (PAPR) in orthogonal frequency division multiplexing (OFDM) systems is attractive, this must not be performed at the expense of the transmitted signal with over-reduced signal power as it leads to degraded bit error ratio (BER). We introduce a uniform distribution approach to solving the PAPR reduction problem of OFDM signals and then use Lagrange multiplier (LM) optimization to minimize the number of iterations involved in an adaptive fashion. Due to the nonlinear attenuation of the PAPR reduction scheme, we compensate the output signal using a correlation factor that minimizes the error floor in the in-band distortion of the clipped signal using minimum mean square error (MMSE) method so as to improve the BER performance. Three different methods are introduced each enabling PAPR reduction by clipping followed by filtering with no direct dependency on a clipping ratio parameter. We find that our approach significantly reduces the PAPR of the OFDM signals (especially with LM optimization) better than the conventional adaptive iterative clipping and filtering operating without LM optimization. Based on our proposed methods, we additionally outline two simple steps for achieving perfect PAPR reduction (i.e. 0dB). We also evaluate the performance of the three new models over high power amplifier (HPA) for completeness; the HPA is found to induce negligible BER degradation effects on the processed signal compared to the unprocessed signal.
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... Therefore, the reduction in PAPR comes at the cost of increased complexity and reduced data rates due to the transmission of side information. Clipping [57] offers a simple approach to reducing the PAPR by hardlimiting the peaks to a pre-defined threshold. Despite its simplicity, clipping introduces amplitude distortion and spectral spreading. ...
... However, the peaks of the filtered-clipped signal could exceed the clipping threshold due to peak power regrowth after filtering. Alternative solutions that help to reduce the clipping distortion involve repeated or iterative clipping [57] and peak windowing [58]. In contrast to clipping, peak windowing applies soft-limiting to the peaks by multiplying the signal with a window-weighting function. ...
p>Vibration-based condition monitoring (VBCM) is widely utilized in various applications due to its non-destructive nature. Recent advancements in sensor technology, the Internet of Things (IoT), and computing have enabled the facilitation of reliable distributed VBCM where sensor nodes are deployed at multiple locations and connected wirelessly to monitoring centers. However, sensor nodes are typically constrained by limited power resources, necessitating control over the peak-to-average power ratio (PAPR) of the generated vibration signals. Effective control of PAPR is crucial to prevent nonlinear distortion and reduce power consumption within the node. Additionally, avoiding nonlinear distortion in the vibration signal and preserving its waveform is essential to ensure the reliability of condition monitoring. This paper conducts an in-depth analysis of the PAPR of vibration signals in VBCM systems, evaluates the impact of nonlinear power amplification on the system performance, and proposes a lightweight autoencoder-based signal companding scheme to control the PAPR to improve power efficiency and mitigate the impact of nonlinear distortion. The proposed scheme employs a lightweight reconstruction autoencoder with a compression-based activation function in the source to compress the vibration signals and avoid increasing the average power of the compressed signal. In the destination, the proposed scheme uses a denoising-expansion autoencoder to expand the compressed signals while minimizing noise enhancement during the expansion process. The experimental results demonstrate the effectiveness of the proposed companding scheme in preventing nonlinear distortion, improving the efficiency of power amplification in the source, and restoring the PAPR characteristics in the destination while avoiding the undesired effect of noise expansion.</p
... Therefore, the reduction in PAPR comes at the cost of increased complexity and reduced data rates due to the transmission of side information. Clipping [57] offers a simple approach to reducing the PAPR by hardlimiting the peaks to a pre-defined threshold. Despite its simplicity, clipping introduces amplitude distortion and spectral spreading. ...
... However, the peaks of the filtered-clipped signal could exceed the clipping threshold due to peak power regrowth after filtering. Alternative solutions that help to reduce the clipping distortion involve repeated or iterative clipping [57] and peak windowing [58]. In contrast to clipping, peak windowing applies soft-limiting to the peaks by multiplying the signal with a window-weighting function. ...
p>Vibration-based condition monitoring (VBCM) is widely utilized in various applications due to its non-destructive nature. Recent advancements in sensor technology, the Internet of Things (IoT), and computing have enabled the facilitation of reliable distributed VBCM where sensor nodes are deployed at multiple locations and connected wirelessly to monitoring centers. However, sensor nodes are typically constrained by limited power resources, necessitating control over the peak-to-average power ratio (PAPR) of the generated vibration signals. Effective control of PAPR is crucial to prevent nonlinear distortion and reduce power consumption within the node. Additionally, avoiding nonlinear distortion in the vibration signal and preserving its waveform is essential to ensure the reliability of condition monitoring. This paper conducts an in-depth analysis of the PAPR of vibration signals in VBCM systems, evaluates the impact of nonlinear power amplification on the system performance, and proposes a lightweight autoencoder-based signal companding scheme to control the PAPR to improve power efficiency and mitigate the impact of nonlinear distortion. The proposed scheme employs a lightweight reconstruction autoencoder with a compression-based activation function in the source to compress the vibration signals and avoid increasing the average power of the compressed signal. In the destination, the proposed scheme uses a denoising-expansion autoencoder to expand the compressed signals while minimizing noise enhancement during the expansion process. The experimental results demonstrate the effectiveness of the proposed companding scheme in preventing nonlinear distortion, improving the efficiency of power amplification in the source, and restoring the PAPR characteristics in the destination while avoiding the undesired effect of noise expansion.</p
... Furthermore, filtering effects can cause secondary peaks that exceed the clipping level at some points. To solve this problem, the repeated CAF scheme (ICAF) [6] and its improved methods have been proposed [7]- [9] to maintain the desired amplitude level while increasing the IB distortion. In other words, the IB distortion cannot be completely eliminated with the ICAF method. ...
The paper proposes an active constellation modification technique to lower peak-to-average power ratio (PAPR) for orthogonal frequency division multiplexing (OFDM) signals. First, the authors introduce some algorithms to reduce computational complexity while ensuring reduced PAPR performance, including the optimal non-iterative ACE algorithm, the suboptimal non-iterative active constellation extension (ACE) algorithm, and the constrained clipping noise filtering (CCNF) algorithm. Next, a hybrid technique and its hardware architecture are introduced that combines the proposed constrained clipping noise filtering algorithm with the proposed suboptimal non-iterative ACE algorithm. This technique aims to improve peak reduction performance while ensuring the overall criteria of the OFDM system. The proposed hybrid technique is then tested through Matlab simulation and FPGA implementation. The MATLAB simulation results allow the evaluation of the effectiveness of lowering PAPR as well as the bit error rate (BER) performance, comparing it with various other methods. Meanwhile, the FPGA’s experimental results evaluate its hardware resource utilization. Specifically, the proposed technique can obtain a reduction of 6.61 dB compared to the original OFDM signal at a CCDF probability level of 10
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, while resulting in an insignificant rise in the signal’s average power of about 0.09 dB. The experimental results also demonstrate the effectiveness of the proposed technique compared to existing ACE and CAF (clipping and filtering) methods in terms of BER efficiency and hardware resource consumption.
... These techniques inject unavoidable distortion noises into the broadcast stream. NCT is a popular and very effective approach [20][21][22]. The initial O-OFDM signal in NCT is given the companding function to boost low signal amplitudes and compress high signal amplitudes. ...
Optical-orthogonal frequency division multiplexing (O-OFDM) systems, including the direct current biased optical OFDM (DCO-OFDM) and the asymmetrically clipped optical OFDM (ACO-OFDM), are very important to achieve high data rate transmission in visible light communication (VLC). However, the DCO-OFDM and ACO-OFDM systems suffer from adjacent channel interference (ACI) caused by out of band (OOB) and a high peak to average power ratio (PAPR). In this work, a pulse-shaping signal based on a symbol-time compression (STC) scheme is presented. The proposed shaped STC-DCOOFDM and shaped STC-ACOOFDM systems are capable of reducing both the ACI and the PAPR as well. Further, the OOB, PAPR, and computing complexity are analytically investigated. The simulation results verify the analytical study of the proposed methods for OOB reduction and power savings resulting in PAPR reduction. The proposed systems are evaluated for different modulation schemes, including BPSK, QPSK and 8QAM.
... The amount of change in amplitude is based on the value of R, as it is noted that PAPR reduces by decreasing R-value. Rooting de-companding operation is also presented in (30). ...
Orthogonal frequency division multiplexing (OFDM) is a compelling contender for next‐generation fixed and wireless standards to realize high data transmission rates in underwater acoustic (UWA) systems. A specific challenge before transmission over the transducers of the UWA system within an OFDM signal is the high peak to average power ratio (PAPR), which severely affects the energy efficiency of the UWA system. This work aims to enhance the energy efficiency of the UWA system by alleviating the stumbling block mentioned earlier within the OFDM. Moreover, we recommend and design a methodology that incorporates modified repeated frequency‐domain filtering and clipping (RFC) and companding techniques to restrain the PAPR obstacle. Additionally, the modified RFC utilizes various companding techniques (including linear and nonlinear techniques) to achieve the desired objectives without complexity augmentation of the system. We simulate and test our proposed approach against four major parameters: PAPR, bit error rate, energy efficiency, and system performance gain. Statistical results show that our technique offers .36 high‐power amplifier power efficiency (η$$ \eta $$), which is comparatively better than OFDM with selective mapping, OFDM with partial transmit sequences, and OFDM with other hybrid approaches.
Signal clipping is a well-established method employed in orthogonal frequency division multiplexing (OFDM) systems to mitigate peak-to-average power ratio. The utilization of this technique is widespread in electronic devices with limited power or resource capabilities due to its high efficiency and low complexity. While clipping effectively diminishes nonlinear distortion stemming from power amplifiers (PAs), it introduces additional distortion known as clipping distortion. The optimization of system performance, considering both clipping distortions and the nonlinearity of PAs, remains an unresolved challenge due to the intricate modeling of PAs. In this article, we undertake an analysis of PA nonlinearity utilizing the Bessel–Fourier PA model and simplify its power expression through intermodulation product analysis. We mathematically derive expressions for the receiver signal-to-noise ratio and system symbol error rate (SER) for nonlinear clipped OFDM systems. Using these derivations, we explore the optimal system configuration required to achieve the lower bound of SER in practical OFDM systems, taking into account both PA nonlinearity and clipping distortion. The results and methodologies presented in this article contribute to an improved comprehension of system-level optimization in nonlinear OFDM systems employing clipping technology.
The relentless evolution of communication systems, driven by the demands of 5G and the impending 6G networks, necessitates heightened data rates and spectral efficiency. orthogonal frequency division multiplexing (OFDM), a form of multicarrier modulation employed in multi-input multi-output (MIMO) systems, stands as a pivotal technology. Yet, OFDM grapples with challenges, notably the peak-to-average power ratio (PAPR) issue. Selective mapping (SLM) has been a favored technique for mitigating PAPR in OFDM, albeit challenged by computational complexities in its pursuit of discovering optimal phase factors. This paper pioneers a transformative approach by integrating metaheuristic algorithms genetic algorithm (GA), particle swarm optimization (PSO), and the innovative fireworks algorithm (FWA) into SLM for PAPR reduction while minimizing computational complexity. Simulation results not only affirm the efficacy of SLM-based techniques but also spotlight the potential of metaheuristic algorithms in addressing PAPR challenges in modern communication systems. The study transcends single-antenna systems, extending to MIMO-OFDM systems based on WiMAX standards, validating the efficacy of these techniques in multi-antenna configurations. Crucially, the FWA, proposed for the first time in this paper, emerges as a robust candidate, striking an enviable balance between computational efficiency and performance, achieving a notable PAPR reduction with a favorable search number.
Orthogonal Frequency Division Multiplexing (OFDM) is the modulation technology used in Fourth Generation (4G) and Fifth Generation (5G) wireless communication systems, and it will likely be essential to Sixth Generation (6G) wireless communication systems. However, OFDM introduces a high Peak to Average Power Ratio (PAPR) in the time domain due to constructive interference among multiple subcarriers, increasing the complexity and cost of the amplifiers and, consequently, the cost and complexity of 6G networks. Therefore, the development of new solutions to reduce the PAPR in OFDM systems is crucial to 6G networks. The application of Machine Learning (ML) has emerged as a promising avenue for tackling PAPR issues. Along this line, this paper presents a comprehensive review of PAPR optimization techniques with a focus on ML approaches. From this survey, it becomes clear that ML solutions offer customized optimization, effective search space navigation, and real-time adaptability. In light of the demands of evolving 6G networks, integration of ML is a necessity to propel advancements and meet increasing prerequisites. This integration not only presents possibilities for PAPR reduction but also calls for continued exploration to harness its potential and ensure efficient and reliable communication within 6G networks.
A high peak-to-average power ratio (PAPR) in the Orthogonal Frequency Division Multiplexing (OFDM) system reduces the efficiency of the power amplifier (PA) at the transmitter. This flaw lowers the efficiency of the OFDM system overall and results in excessive energy usage. The OFDM signal is preprocessed to lower its peak power before transmission in order to address this problem. For 4G and 5G waveforms, we investigate several crest-factor reduction (CFR) approaches in this work. We emphasize the importance of processing OFDM signals before transmission in order to address the significant PAPR issue. In-depth analysis of the CFR technique known as "clipping," which is frequently utilized in real-time applications, is conducted. We go over the difficulties brought on by the high PAPR of OFDM signals and how they affect power amplifier effectiveness. We evaluate the suggested PAPR reduction technique's performance in terms of PAPR reduction capability, signal distortion, computational overhead, and bit error rate (BER) using simulation models and MATLAB-based evaluations. We contrast the efficiency of our suggested method with the PAPR reduction strategies currently in use, such as the partial transmit sequence (PTS), selected mapping (SLM), and crest factor reduction (CFR) methods. Additionally, we confirm the suggested method using a hardware testbed, highlighting its usefulness in actual 5G systems. Additionally, we assess the suggested method's ability to lower the cost and complexity of hardware design for 5G systems in order to assess the economic benefits.
In future smart cities, smart grid technologies which are usually enabled by Powerline Communication (PLC) techniques are required. However, data transmission over powerline channel traverses a non-Gaussian media due to the presence of Impulsive Noise (IN) operating at the frequencies of PLC system which can be deployed using the IEEE 1901, that uses Orthogonal Frequency Division Multiplexing (OFDM). These OFDM signals have asymmetric amplitude distribution, which makes it difficult to identify and mitigate the IN presence. Converting the amplitude distribution to a uniform distribution can enhance the ability to mitigate IN when nonlinear IN mitigation techniques such as blanking is applied. In this study, we apply Iterative Clipping and Filtering (ICF) and companding schemes which are Peak-to-Average Power Ratio (PAPR) reduction techniques to enable symmetric amplitude distribution of the OFDM signals. With an optimization search for the optimal blanking amplitude for the two PAPR reduction schemes. Results show that companding scheme achieves 4dB gain in terms of received signal-to-noise ratio better than ICF after the blanking was used to remove the IN.
Orthogonal frequency division multiplexing (OFDM) offers spectral efficiency advantage, however, it is limited by peak-to-average power (PAPR) problem. The PAPR can be reduced using iterative clipping and filtering (ICF) scheme but requires that the same signals are iteratively clipped with a fixed clipping threshold at different clipping iterations. This method warrants that fast-Fourier transform (FFT)/inverse IFFT (IFFT) blocks must be driven in the order of iterations many times to attain a desired PAPR threshold which expends the system power and expands processing time. Using a second-order cone program, the number of iterations required to attain the desired PAPR threshold was reduced. This optimized ICF (OICF) was later simplified using Lagrange Multiplier Optimization (LMO). In this study, we apply an adaptive clipping threshold to the LMO scheme to improve the performance of the simplified OICF (SOICF). Our results show significant reduction of the PAPR problem compared to the earlier SOICF schenme albeit with some degradation in the BER performance that can be under 1.0 dB depending on the chosen clipping threshold. In addition, we also illustrated the results of the theoretical relationships and performances between the error vector magnitude (EVM) and PAPR, between clipping ratio (CR) and EVM, and lastly the inter-dependencies of EVM, PAPR, the number of OFDM subcarriers and the CR.
The objective of this survey is to provide the readers and practitioners in the industry with a broader understanding of the high peak-to-average power ratio (PAPR) problem in orthogonal frequency division multiplexing (OFDM) systems and generate a taxonomy of the available solutions to mitigate the problem. Beginning with a description of OFDM systems, the survey describes the most commonly encountered impediment of OFDM systems, the PAPR problem and consequent impact on power amplifiers leading to nonlinear distortion. The survey clearly defines the metrics based on which the performance of PAPR reduction schemes can be evaluated. A taxonomy of PAPR reduction schemes classifies them into signal distortion, multiple signaling and probabilistic, and coding techniques with further classification within each category. We also provide complexity analyses for a few PAPR reduction methods to demonstrate the differences in complexity requirements between different methods. Moreover, the paper provides insights into the transmitted power constraint by showing the possibility of satisfying the constraint without added complexity by the use of companding transforms with suitably chosen companding parameters. The rapid growth in multimedia-based applications has triggered an insatiable thirst for high data rates and hence increased demand on OFDM-based wireless systems that can support high data rates and high mobility. As the data rates and mobility supported by the OFDM system increase, the number of subcarriers also increases, which in turn leads to high PAPR. As future OFDM-based systems may push the number of subcarriers up to meet the higher data rates and mobility demands, there will be also a need to mitigate the high PAPR that arises, which will likely spur new research activities. The authors believe that this survey will serve as a valuable pedagogical resource for understanding the current research contributions in the area of PAPR reduction in OFDM systems, the - ifferent techniques that are available for designers and their trade-offs towards developing more efficient and practical solutions, especially for future research in PAPR reduction schemes for high data rate OFDM systems.
Companding is a well-known technique for the peak-to-average power ratio (PAPR) reduction of orthogonal frequency division multiplexing (OFDM) signals. However, as companding transform is an extra operation after the modulation of OFDM signals, companding schemes reduce PAPR at the expense of increasing the bit error rate (BER). In this paper, a new piecewise linear companding scheme is proposed aiming at mitigating companding distortion. In the design of the companding transform, we study the theoretical characterization of companding distortion. It demonstrates that companding larger signals with smaller amplitude increments are more favorable in reducing companding distortion. Based on the analysis results, a new piecewise linear companding transform is proposed by clipping the signals with amplitudes over a given companded peak amplitude for peak power reduction, and linearly transforming the signals with amplitudes close to the given companded peak amplitude for power compensation. With the careful design of the companded peak amplitude and the linear transform scale, the proposed transform can achieve enhanced BER and power spectral density performance, while reducing PAPR effectively.
A number of basic properties about circularly-symmetric Gaussian random vectors are stated and proved here. These properties are each probably well known to most researchers who work with Gaussian noise, but I have not found them stated together with simple proofs in the literature. They are usually viewed as too advanced or too detailed for elementary texts but are used (correctly or incorrectly) without discussion in more advanced work. These results should have appeared in Section 7.8.
Orthogonal frequency multiplexing (OFDM) is a promising technique for high data-bit-rate in wireless communication systems. However, one of the major drawback of OFDM is high peak-to-average power ratio (PAPR). In this paper, we propose modified Iterative Amplitude clipping and filtering (IACF) technique to reduce the PAPR in OFDM signal. This paper evaluates PAPR reduction effect with a graded band-limiting filter in the iterative clipping and filtering method. The computer simulation result shows that the proposed method achieves target PAPR using fewer iteration numbers as in conventional method and improves the PAPR and BER performance as compared to conventional Amplitude clipping and filtering (AFC) method.
A communication system with non-linear power amplifier (PA) is considered. We introduce three major performance criteria of the system: (i) power efficiency of the PA, (ii) spectral purity of the transmitted signal expressed by adjacent channel interference, and (iii) transmission performance expressed by mutual information or symbol error rate. In order to fulfill the first two criteria it is proposed to use iterative clipping and filtering (ICF) at the transmitter together with low input back-off, while the third criterion is obtained by modified iterative receiver (MIR). The proposed MIR is based on the well-known iterative receiver, but with ICF in the feedback path. The obtained results show that the proposed system is better than its competitors when considering the three performance criteria together. The analysis and results are focused on OFDM; however, the proposed approach may be applied to single carrier.
High peak-to-average power ratio (PAPR) of the transmitted signal is one of the limitations to employing orthogonal frequency division multiplexing (OFDM) system. In this paper, we propose a new nonlinear companding algorithm that transforms the OFDM signals into the desirable statistics form defined by a linear piecewise function. By introducing the variable slopes and an inflexion point in the target probability density function, more flexibility in the companding form and an effective trade-off between the PAPR and bit error rate performances can be achieved. A theoretical performance study for this algorithm is presented and closed-form expressions regarding the achievable transform gain and signal attenuation factor are provided. We also investigate the selection criteria of transform parameters focusing on its robustness and overall performance aspects. The presented theoretical analyses are well verified via computer simulations.
Iterative clipping and filtering (ICF) is a well-known technique to reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals. Recently, Wang and Luo investigated the clipped signal and proposed a modified algorithm called optimized ICF (OICF). This is an optimal algorithm since it can achieve the required PAPR reduction with minimum in-band distortion and far fewer iterations. However, OICF needs to solve a convex optimization problem with {O}(N^3) complexity, where N represents the number of subcarriers. In this paper, instead of analyzing the clipped signal, we study the clipping noise and propose a simplified OICF algorithm. In the new algorithm, solving the convex optimization problem is approximated by some simple algebraic operations and the computational complexity reduces to {O}(N). Simulation results show that after three iterations, the original OICF algorithm can achieve the desired PAPR while the simplified one exhibits almost the same performance: for a 128-subcarrier and quadrature phase shift keying (QPSK) modulated OFDM system, the PAPR-reduction performance difference between the two algorithms are 5x10^{-3}dB at a 10^{-4} clipping probability and the bit-error-rate performance difference is 6x10^{-3}dB at a 10^{-7} error probability.