Partial Transmit Sequence Research Articles

ENHANCING OTFS MODULATION FOR 6G THROUGH HYBRID PAPR REDUCTION TECHNIQUE FOR DIFFERENT SUB-CARRIERS

Peak-to-average power ratio (PAPR) in orthogonal time frequency space (OTFS) is vital for optimizing signal efficiency, minimizing distortion, and enhancing the performance of a beyond fifth-generation (B5G) system. The paper focuses on lowering the PAPR while retaining the bit error rate (BER) and power spectral density (PSD) for 64 and 256 sub-carriers. The PAPR is minimized by using a fractal optimization process known as selective mapping (SLM) and partial transmission sequence (PTS) at the transmitting block of the OTFS framework. The combination of SLM and PTS reduces peak power by selectively modifying the phase of transmitted symbols. SLM generates multiple versions of the signal, while PTS allocates power to these versions optimally, collectively mitigating amplitude peaks and minimizing PAPR. According to the simulation results, the suggested SLM+PTS works better than the traditional SLM and PTS, achieving low spectrum leakage and PAPR improvements of 5.5 dB and 4.9[Formula: see text]dB as well as SNR gains of 2.4[Formula: see text]dB and 2.1[Formula: see text]dB. In the future, SLM+PTS may work on lowering PAPR by making computers faster, researching adaptive algorithms, and combining machine learning methods for real-time optimization in various communication settings. Complex modeling, including fractal-based SLM and PTS approaches, provides a detailed understanding of waveform behavior and interference patterns, enabling more accurate and effective hybrid PAPR reduction techniques. This combination enhances the ability to manage to mitigate non-linear distortion across various sub-carriers, crucial for the performance and efficiency of 6G OTFS modulation.

A BACTERIA FORAGING ALGORITHM-BASED HYBRID A-LAW AND PTS PAPR REDUCTION METHOD FOR BEYOND 5G WAVEFORM

One of the most advanced waveforms available in the beyond-fifth-generation radio (B5GR) framework is nonorthogonal multiple access (NOMA). The power amplifier (PA) of the NOMA structure performs less efficiently when the signal is strong and the peak-to-average power ratio (PAPR) is high. This study applies a hybrid algorithm to the NOMA structure, combining fractal partial transmit sequence (PTS), A-law companding, and the bacterial foraging algorithm (BFA). Fractals are known for their self-repeating structures at different scales, allowing for efficient coverage and exploration of space. Fractals enhance the bacteria foraging algorithm (BFA) by improving search efficiency, enabling better exploration of complex, multi-dimensional optimization landscapes. Similarly, BFA balances exploring the search in promising areas. We utilized BFA to achieve optimal phase factors for the PTS algorithm and applied A-Law companding to the NOMA symbols to further enhance the structure’s performance. The intermediate computational complexity in the Rician and Rayleigh channels improves PAPR, bit error rate (BER), and power spectral density performance. Simulation results reveal that the performance of the proposed hybrid method is superior to that of existing PAPR reduction algorithms and substantially enhances the efficiency of NOMA.

PEAK TO AVERAGE POWER COMPUTING AND OPTIMIZATION OF OPTICAL OTFS 5G WAVEFORM USING HYBRID FRACTAL-BASED SIGNAL PROCESSING ALGORITHM

Optical orthogonal time frequency space (OTFS) is better at handling Doppler shifts and multipath fading, making signals more reliable and valuable in places with much movement beyond the fifth generation (B5G). Using practical power amplifiers at the transmitter causes power inefficiency and signal distortion because of the OTFS system’s high peak-to-average power ratio (PAPR), severely reducing system efficiency. Combining partial transmit sequence (PTS) and selective mapping (SLM), a technique known as PTS+SLM, reduces peak power. While SLM generates numerous phase-modulated signal candidates and chooses the one with the lowest PAPR, PTS separates the signal into sub-blocks and optimizes their phases to decrease peak power. With few changes to the signal structure, this dual strategy effectively reduces PAPR while improving power spectral density (PSD) efficiency. As a result, we ensure the accuracy and dependability of the transferred data by maintaining the bit error rate (BER). Fractal optimization methods could be applied to these algorithms. For example, fractal-inspired optimization techniques might be used to explore the phase space more effectively or to discover new phase sequences that result in lower PAPR. According to the simulation findings, the suggested PTS+SLM method works better than the traditional PTS and SLM methods.

PAPR reduction of OTFS using an automatic amplitude reduction neural network with vendermonde matrix-based PTS and SLM algorithms

Orthogonal time frequency selectivity is considered one of the most promising advanced waveforms for high-mobility conditions in beyond-fifth-generation networks. A high peak-to-average power ratio in orthogonal time frequency introduces nonlinearity and degrades the power amplifier performance. In this work, we propose a novel automatic amplitude reduction neural network algorithm combined with partial transmission sequence and selective mapping methods using the Vendermonde matrix for generating phase sequences. In a conventional selective mapping methods or partial transmission sequence, selecting an optimal phase increases the complexity, which is overcome via Vendermonde matrix in a proposed framework. The minimization of the peak-to-average power ratio is obtained at the double-stage process: in the first stage, the threshold amplitude is set, and the amplitude exceeding the threshold is reduced by using an automatic amplitude reduction neural network and then the partial transmission scheme or selective mapping methods. The simulation results reveal that, compared with the conventional algorithms, the proposed algorithms yield a significant peak average-to-power ratio, bit error rate, and power spectrum density performance.

Visible light communication optical FBMC-OQAM PAPR reduction using FHT-PTR algorithm for beyond 5G system

Abstract This paper addresses the reduction of peak-to-average power ratio (PAPR) in optical filter bank multicarrier (FBMC) with offset quadrature amplitude modulation (OQAM) using a fast Hadamard transform (FHT) centered partial transmit sequence (PTS) algorithm. High PAPR in FBMC-OQAM systems can cause non-linear distortions in optical transmitters, such as LEDs, leading to signal degradation. The proposed FHT-PTS algorithm effectively mitigates this issue by dividing the data symbols into disjoint subsets, applying phase rotations, and performing inverse FHT to generate multiple candidate sequences. The sequence with the lowest PAPR is selected for transmission. This technique ensures significant PAPR reduction while maintaining acceptable bit error rate (BER) performance. Simulation results demonstrate that the FHT-PTS algorithm achieves substantial PAPR reduction gain of 3 dB–6 dB compared to conventional PTS and other existing methods. The power spectrum density (PSD) analysis shows that the spectral efficiency of the FBMC-OQAM system is preserved, with minimal out-of-band emissions. The FHT operations significantly reduce the complexity compared to traditional Fourier transform-based methods, making the algorithm more feasible for real-time applications.

Partial Transmit Sequence Chaotic Sand Cat Swarm Optimization Based Phase Optimizer for Peak-to-Average Power Ratio Reduction

Partial Transmit Sequence Chaotic Sand Cat Swarm Optimization Based Phase Optimizer for Peak-to-Average Power Ratio Reduction

Exploring and Analyzing a Hybrid PAPR Reduction Method for OFDM Optimization

Orthogonal Frequency Division Multiplexing (OFDM) is a effective modulation technique widely used in modern communication systems, including 5G and wireless networks because of its high spectral efficiency and robustness towards multipath fading. However, OFDM signals are characterized by a high Peak-to-Average Power Ratio (PAPR), which can severely impact the power efficiency and operational cost of these systems. This research investigates and analyse effectiveness of two conventional PAPR reduction methods that is Selective Mapping (SLM), and Partial Transmit Sequence (PTS) with incorporating their approach of PAPR reduction to develop a hybrid variant: SLM-PTS. This study utilized MATLAB simulations to implement and test each PAPR reduction technique on a standard OFDM system model. Parameters such as the number of subcarriers, oversampling factor, and modulation types were systematically varied to analyze the impact on PAPR, BER, and computational complexity. The effectiveness of each technique was measured using the Complementary Cumulative Distribution Function (CCDF) of PAPR values and BER performance under different channel conditions. Key findings reveal that hybrid techniques, particularly SLM & PTS, offer significant improvements in PAPR reduction compared to traditional methods alone, without a corresponding increase in BER or computational overhead. The research underscores the potential of hybrid PAPR reduction techniques to significantly enhance the efficiency and reliability of OFDM systems. These findings have important implications for the design and optimization of next-generation wireless communication systems, suggesting that hybrid approaches can provide a balanced solution to the longstanding issue of PAPR in OFDM transmissions. This study contributes valuable insights into the practical application of combined PAPR reduction strategies, offering a pathway toward more power-efficient and robust OFDM technologies. Keywords : OFDM, PAPR, CCDF, SLM and PTS

Reducing peak‐to‐average power ratio of filtered non‐orthogonal multiple access and new radio 5g waveforms using hybrid partial transmit sequence‐companding technique

AbstractFor fifth‐generation (5G) and beyond 5G communications, filtered nonorthogonal multiple access (F‐NOMA) can be used as a waveform contender. Filtering‐based waveform frameworks provide suppression of out‐of‐band emission (OOBE) and asynchronous transmission. For new types of waveforms, a high peak‐to‐average power ratio (PAPR) remains a challenge. A high PAPR in multicarrier systems can be efficiently mitigated by applying partial transmit sequence (PTS). Combining PAPR reduction techniques can improve the transmission efficiency by nonlinearly scaling the signal amplitudes before transmission and inversely scaling them at the receiver. We propose a hybrid technique that combines PTS and companding to reduce the PAPR in an F‐NOMA system. Conventional nonorthogonal multiple access (NOMA) is compared with F‐NOMA, and systems with and without the hybrid technique are examined regarding metrics including the power spectral density, bit error rate (BER), and computational complexity. Compared with NOMA, simulation results show that F‐NOMA using the proposed technique improves the PAPR and OOBE while preserving the BER performance of F‐NOMA.

PAPR reduction techniques optimization-based OFDM signal for wireless communication systems

OFDM (Orthogonal Frequency Division Multiplexing) is a widely used modulation technique in many standards such as Wi-Fi (Wireless Fidelity), LTE (Long Term Evolution), and 4 G. It allows for high transmission data rates and excellent spectral efficiency. However, one of the main limitations of OFDM is its high PAPR (Peak-to-Average Power Ratio). In this paper, we will first describe some methods to reduce the PAPR associated with OFDM signal. We will discuss some methods such as the clipping, the Selective mapping SLM, the Partial Transmit Sequence (PTS), and the Tone Reservation (TR). Let's list their advantages and disadvantages before focusing on the TR method which we will detail. This work aims to improve the performance of the TR method in terms of speed of convergence and reduction of the PAPR, using the conjugate different algorithms while respecting the frequency specifications of the IEEE 802.11a standard. The proposed algorithm which is based on the gradient method, Conjugate gradient methods, and Quasi-Newton method shows good performance regarding PAPR reduction and speed of convergence. The choice of an appropriate technique depends on several factors: required PAPR reduction, acceptable complexity, and performances (spectral efficiency, latency, etc.). A trade-off must be found in practice between these different criteria. It has been shown that the Quasi-Newton method algorithm with its two variants converges more quickly.

Two-stage collaborative information interaction reliability improvement for the distribution grid

The impulse noise generated by a large volume of power electronics devices imposes a hazardous impact on information interaction reliability in low-voltage distribution grids. In this paper, we propose a two-stage collaborative information interaction reliability improvement algorithm to minimize the bit error rate (BER) of the information interaction under impulse noise. In the first stage, the transmission-side peak-to-average power ratio (PAPR) is reduced based on the adaptive particle swarm optimization (PSO)-enabled partial transmit sequence (PTS). In the second stage, the reception-side dual-signal blanking is proposed based on the transmission-side PAPR and reception-side useful signal power estimation and peak median ratio. The transmission–reception collaborative information interaction reliability improvement is realized through two aspects. First, transmission-side PAPR reduction improves the performance of reception-side signal blanking by making it easier to distinguish useful signals from impulse noise. Second, the transmission-side PAPR is utilized to improve the estimation accuracy of both coarse and precise thresholds in dual-signal blanking. Simulation results show that the proposed algorithm outperforms existing algorithms in both PAPR reduction and BER performances to achieve information interaction reliability improvement effectively.

PAPR analysis in OTFS using the centre phase sequence matrix based PTS method

Orthogonal time–frequency space (OTFS) is a multicarrier modulation technique for high-speed data transfer in wireless communications. In an OTFS system, many subcarriers are used to send the modulated symbols. This makes OTFS signals have a high peak-to-average power ratio (PAPR). We suggest a partial transmit sequence (PTS) approach based on the Centre Phase Sequence Matrix (CPSM) to lower the high PAPR. Furthermore, the suggested method effectively searches for the best possible combination of phase rotation factors to reduce computing complexity. We examine the outcomes regarding bit error rate (BER), power spectral density (PSD), and PAPR to validate the competing transforms in the OTFS system. Along with non-orthogonal multiple access (NOMA), filter bank multi-carrier (FBMC), universal filter multi-carrier (UFMC), and orthogonal frequency division multiplexing (OFDM), the PAPR, BER, and PSD performance of OTFS were also compared. According to the data, the suggested PTS + CPSM reduces PAPR more effectively than the current PTS. It is also mentioned that by increasing the number of sub-blocks (s = 2 and 4), the suggested PTS + CPSM can achieve an even better PAPR rate. According to the experimental results, the suggested approach has dramatically decreased the PAPR while maintaining the BER and PSD performance with the least amount of computational complexity.

A hybrid approach based on companding and PTS methods for PAPR reduction of 5G waveforms

ABSTRACT As a crucial enabler for the fifth-generation air interface, the filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) is being investigated by several researchers. This article suggests using partial transmit sequence (PTS) and companding to create a hybrid peak-to-average power ratio (PAPR) reduction strategy for FBMC/OQAM signals. In the novel PTS Companding scheme, there are several segments to the data block signal, and the overlapping factor determines the number of data blocks in each segment. To obtain the lowest signal power in each segment, we choose the best data block to broadcast and examine the next overlapping data block concurrently. After that, the segment FBMC/OQAM signal peaks are compressed using companding. Based on simulation results and analysis, the proposed hybrid PTS Companding method in FBMC/OQAM systems may reduce PAPR more effectively than conventional PTS and Companding schemes. According to simulation results, the hybrid process can achieve around 5 dB greater PAPR performance than the conventional PTS and companding schemes.

Exploring PTS method in MIMO advanced waveforms signal for 5G network security analysis

Peak-to-average power ratio (PAPR) issues lead to a reduction in the scheme’s throughput. In this research, we propose a beneficial method for lowering the high PAPR of an orthogonal frequency division multiplexing (OFDM) system, called partial transmission sequence (PTS). The PTS method of PAPR reduction in advanced waveforms will depend on the usage of PAPR reduction technologies in 5G waveforms. This paper presents the simulation of an OFDM PTS reduction technique. The simulation results demonstrate that the proposed approach performs better than the conventional PAPR reduction approach. Further. it is also seen that enhances network security by increasing data diversity, reducing interference, and improving resilience against eavesdropping and jamming attacks.

High Spectral Efficient Free-Space Optical Communication using Multi-Stage Noise Shaping Delta-Sigma Modulation with Partial Transmit Sequence Algorithm and Arithmetic Coding

High Spectral Efficient Free-Space Optical Communication using Multi-Stage Noise Shaping Delta-Sigma Modulation with Partial Transmit Sequence Algorithm and Arithmetic Coding

Improved Algorithm of Partial Transmit Sequence Based on Discrete Particle Swarm Optimization

Orthogonal frequency division multiplexing (OFDM) in 5G has many advantages; however, one of the disadvantages is that the superposition of a large number of subcarriers leads to a high peak-to-average power ratio (PAPR) of the transmit signal. A high PAPR results in high-power amplifier distortion and performance degradation. The partial transmit sequence (PTS) algorithm is commonly used for PAPR reduction. It enumerates all combinations of phase factors, weighs the signal using each phase factor combination, and finds the set of phase factors that minimizes the PAPR value of the OFDM signal. The advantage of the PTS is that it determines the optimal solution through enumeration; however, its major drawback is the higher complexity caused by the use of enumeration. Some studies have introduced the discrete particle swarm optimization (DPSO) algorithm instead of enumeration to determine the optimal solution of the PTS algorithm. As an excellent optimization method, the DPSO algorithm represents each individual as a solution during the optimization. Through iterative updates of the initial population, individuals in the population continuously move closer to the optimal solution. This approach significantly reduces complexity compared with the exhaustive enumeration used in the traditional PTS algorithm. However, the disadvantage of the general DPSO algorithm is that it can result in premature and early convergence, which leads to degradation of the PAPR reduction performance. In this study, we propose an improved method based on the general DPSO-based PTS algorithm, and the improved algorithm MDPSO-PTS adopts dynamic time-varying learning factors, which can find the optimal combination of phase factors more efficiently. The MDPSO-PTS algorithm expands the search space when seeking the optimal combination of phase factors. This avoids the drawback of premature convergence commonly observed in general DPSO-PTS algorithms, preventing early consideration of local optima as global optima. A comparative simulation of the improved MDPSO-PTS algorithm with the general DPSO-PTS algorithm shows that the improved algorithm has stronger PAPR reduction, whereas the complexity remains basically unchanged. A comparative simulation with the traditional PTS algorithm shows a significant reduction in complexity, with only a slight, acceptable loss of reduction performance.

A Permutated Partial Transmit Sequence Scheme for PAPR Reduction in Polar-Coded OFDM-IM Systems

A Permutated Partial Transmit Sequence Scheme for PAPR Reduction in Polar-Coded OFDM-IM Systems

A novel PAPR reduction scheme based on time-delay neural network for CO-OFDM systems

In this paper, we propose a low-complexity peak-to-average power ratio (PAPR) reduction scheme based on time-delay neural network (TDNN) for coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems to reduce the limitation of PAPR on the total power of laser diodes and the impact of fiber nonlinear effects. The proposed scheme is jointly trained on traditional iterative clipping and filtering (ICF) scheme and simplified clipping and filtering (SCF) scheme, and changes the objective function by adjusting the given training weight α. Compared to the original orthogonal frequency division multiplexing (OFDM) signal of existing system, our method achieves an adjustable PAPR reduction of 5.31 dB to 6.12 dB for 10−4 complementary cumulative distribution function (CCDF). When bit error rate (BER) Pe=10−3, the proposed scheme (α=0.5) achieves additional transmission distances of 220 km, 55 km, 105 km, and 100 km, compared to the original OFDM signal, partial transmission sequence (PTS) scheme, ICF scheme, and feedforward neural network (FNN)-based ICF scheme, respectively. Besides, our method achieves 86.3% and 80.0% floating-point operations (FLOPs) reductions, compared with PTS scheme and ICF scheme, respectively, which effectively reduces the complexity of PAPR reduction module, saving the system computational time.

Improved PAPR Reduction Technique in 5G Systems: Addressing Limitations and Challenges with Computational Techniques

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.

PAPR, Spectral Efficiency, BER and SNR Analysis of OFDM: A Novel Partial Transmit Sequence-Particle Swarm Optimization Technique

Orthogonal frequency division multiplexing (OFDM) is a widely used multicarrier modulation (MCM) technique in the field of wireless communications, specifically designed to facilitate high-speed data transmission. The use of several subcarriers inside an OFDM system for the transmission of modulated symbols results in the generation of OFDM signals with a significant peak-to-average power ratio (PAPR). In this study, we propose a novel approach for mitigating the high PAPR in wireless communication systems (WCS). Our method utilizes a partial transmit sequence (PTS) strategy, which is enhanced by using an adaptive particle swarm optimization (PSO) algorithm. In this study, we present a description of an OFDM system employing the standard PTS technique in conjunction with PSO. To mitigate computational complexity, the suggested methodology efficiently explores the optimal amalgamation of phase rotation components. Experimental findings demonstrate that the computational complexity and PAPR have been greatly minimized by the suggested method.

PAPR reduction using SLM-PTS-CT hybrid PAPR method for optical NOMA waveform

In this article, we focus on optimising the SLM-PTS-CT (selective mapping, partial transmission sequence, circular transformation) hybrid method for optical non-orthogonal multiple access (O-NOMA) waveforms. The goal is to enhance the spectrum performance and practicality of O-NOMA systems while mitigating the PAPR issue through a hybrid approach. The SLM-PTS-CT hybrid method is applicable to O-NOMA waveforms, providing effective PAPR reduction. By dividing the data sequence into sub-blocks, applying phase factors, and rotating the phase of the subcarriers in such a way that the peaks of the signal are distributed more uniformly, the proposed SLM-PTS-CT achieves an optimal PAPR reduction while maintaining the benefits of O-NOMA. The efficiency of the proposed method is analysed by estimating the performance of several parameters, such as bit error rate (BER), PAPR, and power spectral density (PSD), by increasing the number of sub-blocks (S) and phase factor (P). Further, the proposed SLM-PTS-CT is compared with the conventional SLM-PTS, SLM, and PTS. The simulation results demonstrate that the proposed approach efficiently improves spectral efficiency, preserves BER performance, and reduces PAPR as compared with conventional methods.