Average Power Ratio Research Articles

Dynamical Embedding of Single-Channel Electroencephalogram for Artifact Subspace Reconstruction.

This study introduces a novel framework to apply the artifact subspace reconstruction (ASR) algorithm on single-channel electroencephalogram (EEG) data. ASR is known for its ability to remove artifacts like eye-blinks and movement but traditionally relies on multiple channels. Embedded ASR (E-ASR) addresses this by incorporating a dynamical embedding approach. In this method, an embedded matrix is created from single-channel EEG data using delay vectors, followed by ASR application and reconstruction of the cleaned signal. Data from four subjects with eyes open were collected using Fp1 and Fp2 electrodes via the CameraEEG android app. The E-ASR algorithm was evaluated using metrics like relative root mean square error (RRMSE), correlation coefficient (CC), and average power ratio. The number of eye-blinks with and without the E-ASR approach was also estimated. E-ASR achieved an RRMSE of 43.87% and had a CC of 0.91 on semi-simulated data and effectively reduced artifacts in real EEG data, with eye-blink counts validated against ground truth video data. This framework shows potential for smartphone-based EEG applications in natural environments with minimal electrodes.

Class iCGF–1 Mode Power Amplifier for Enhancing the Linearity of the Traditional Continuous Class F–1 Mode

ABSTRACTIn this paper, the iCGF−1 mode is proposed to compensate the amplitude‐to‐amplitude modulation (AM/AM) distortion of the traditional continuous class F−1 mode while maintaining the high efficiency. The AM/AM profile of the iCGF−1 mode is mathematically expressed simultaneously as a function of the input nonlinearity parameter and conduction angle , which makes the iCGF−1 mode more flexible in controlling the AM/AM profile. The first inflection point of the AM/AM profile can be moved to a higher output power level through theoretical deduction by adjusting the second harmonic source impedance and gate bias voltage to increase the values of and . This flattens the AM/AM profile while the efficiency profile remains almost the same as that of the traditional continuous class F−1 mode. The performance of the iCGF−1 mode is verified through simulation and experimental measurements. The iCGF−1 PA is fabricated with CGH40010F and has a frequency range of 2–2.6 GHz. The drain efficiency is 70.1%–77.9%, and the output power is 41.1–41.7 dBm. The linearity is tested with a 100 MHz 5G NR signal (the peak average power ratio (PAPR) is 8.5 dB) at 2.3 GHz. The worst adjacent channel power ratio (ACPR) is −32.3 dBc without digital predistortion (DPD) and −52.1 dBc with DPD. The results show that the iCGF−1 mode has successfully compensated the AM/AM distortion of the traditional continuous class F mode and maintaining high efficiency.

Reducing peak to average power ratio in optical NOMA based 5G system using advanced SLM method

Reducing peak to average power ratio in optical NOMA based 5G system using advanced SLM method

Polar coded SCMA-OCDM based on chaotic scrambled SLM

In this work, the polar coded sparse code multiple access (SCMA) scheme based on chaotic scrambled selective mapping (CS_SLM) is proposed for future passive optical networks (PONs). The original bits are coded by polar and mapped into constellation symbols by sparse code. Then orthogonal chirp division multiplexing (OCDM) modulation is adopted which has better anti-interference ability than orthogonal frequency division multiplexing (OFDM). At the receiver, the joint iterative detection and decoding for polar and SCMA is used to further improve the BER performance. The CS_SLM is helpful to improve the reliability and security, while keeping high spectral efficiency of SCMA-OCDM modulation. A 49.42 Gb/s coded SCMA-OCDM PON over 2 km seven-core fiber is demonstrated in the experiment. The results show that the SCMA-OCDM scheme gets a receiver sensitivity of 0.8 dB at a bit error rate (BER) of 3.8 × 10−3, compared with SCMA-OFDM. Because of peak to average power ratio (PAPR), the polar coded SCMA-OCDM based on CS_SLM is compared with clipping and filtering (CAF) method, about 2.08 dB receiver sensitivity gain is obtained when BER is lower than 10−5. The polar coded SCMA-OCDM based on CS_SLM also takes security into the consideration, due to the downlink broadcasting of PON. It can be a promising candidate for the next generation PONs.

Reduce PAPR in Filtered-CPOFDM using Hybrid Method System

5G multicarrier waveform Filtered Cyclic Prefix Orthogonal Frequency Division Multiplexing (F-CPOFDM) allows for high data speeds and increases in spectrum efficiency. The main drawback of F-CPOFDM is its high peak-to-average power ratio (PAPR), a common element of all multicarrier modulation schemes. In this research is investigate the implementation of a Hybrid strategy to reduce the peak to average power ratio (PAPR) in a F-CPOFDM system and evaluated the impact of employing a Hybrid Technique with Group Codeword Shift (GCS), Median Codeword Shift, Selective Codeword Shift (SCS), and Conventional F-CPOFDM on the reduction of peak to average power ratio (PAPR) in CP-OFDM. The novelty of this research is GCS method integration with WHT Precoding technique for reduce PAPR. Simulation results show that compared to traditional Filtered-CPOFDM, the GCS-WHT method reduces peak PAPR by 59.46 %, while the SCS- method reduces it by 32.43 % and the MCS-WHT method reduces it by 31.53%. Compare to the non-hybrid technique, the GCS only reduce 45.95%, while for SCS and MCS reduce 19.82% and 23.42% respectively. From the results, shows that Hybrid method is better performance compare with non-hybrid method.

A Developed Polar Coded Generalized Frequency Division Multiplexing Based on Bit-Interleaved Coded Modulation

Due to the tremendous development in the wireless communication field and the wide requirements of current generations, such as high data rates, extremely low power consumption, and high performance, it is necessary to think about techniques and methods that present improvement to meet the growing requirements. The introduction of the Generalized Frequency Division Multiplexing (GFDM) technique was one of the proposed methods; it is one of the candidate schemes for the current generations and beyond. GFDM was presented as an improved method over other multiplexing techniques, as it provided an improvement in the field of Out Of Band (OOB) and Peak Average Power Ratio (PAPR). At the same time, it provided a lower performance in BER with respect to SNR. In this paper, methods of enhancement were presented based on Matlab to improve the performance of the GFDM system, which was improved by adding a coding system based on Polar Coding (PC). The proposed method is presented to improve the performance of GFDM by using the Genetic Algorithm (GA) to improve the performance of the Pulse shaping Filter (PSF) in GFDM. The channel estimation is accomplished by means of the LS method, and the Artificial Neural Network (ANN) based on feed-forward backpropagation is used to enhance the estimation process. The proposed Genetic Algorithm Artificial Neural Network Polar Code Interleaver GFDM (GNPI-GFDM) presents an enhancement over the traditional GFDM of more than 3.5dB at BER=10-4over the Rayleigh fading channel

Fast Generation of Low PAPR and Low Sidelobe Noise Waveform

Noise radar waveform, as an important waveform in the field of low-probability-of-intercept radars, has been widely studied. However, the general noise waveform has a high peak average power ratio (PAPR), which leads to a reduction of signal-to-noise ratio. Thus, it is necessary to control the noise waveform PAPR to a suitable range. In this paper, the PAPR value reduction problem of low sidelobe noise waveform is studied. First, the proposed new algorithm is given a general overview. Then, the Combined Spectral Shaping and Peak-to-Average Power Ratio Reduction (COSPAR) algorithm is adjusted according to the alternate projection method and phase retrieval algorithm, and an improved COSPAR (ICOSPAR) algorithm with a faster execution speed and higher waveform generation efficiency is derived. The specific method performs waveform projection between the spectral constraint domain and the PAPR constraint domain and then evaluates the computational load of the ICOSPAR algorithm. Simulation results show that the ICOSPAR algorithm is reliable and efficient in generating low PAPRs and low sidelobe noise waveforms.

Peak To Average Power Ratio (PAPR) Reduction Technique Using Selective Mapping in OFDM System

Peak To Average Power Ratio (PAPR) Reduction Technique Using Selective Mapping in OFDM System

Spectral efficiency analysis on massive MIMO filter bank

ABSTRACT This article covers the potential of Filter Bank Multicarrier (FBMC) modulation as an alternative to be used in the future 5 G wireless networks in which Massive Multiple-Input Multiple-Output (MIMO) is implemented. The ‘energy efficient Massive Multiple Input Multiple Output (M-MIMO) Filter bank Multi-carrier Modulation (FBMC)’ is necessary and beneficial for the upcoming wireless communiqué system. This is because there is an ever-increasing demand for higher data rates with higher Spectral Efficiency (SE). This paper compares orthogonal frequency division multiplexing (OFDM) with FBMC. This helps to evaluate the Spectral Efficiency (SE) of a Massive MIMO system that performs transmission under a unicellular environment. The variation in Massive MIMO allows equilibrium of the channel because FBMC has extra benefits due to the confinement of the subcarrier in an assigned range. However, the high Peak to Average Power Ratio (PAPR) in an M-MIMO-FBMC system is recognised as a serious problem that causes nonlinear signal deformation and restricts the effectiveness of the Power Amplifier (PA). In this work, to increase the SE in the system, the antenna count is optimised, such that the SNR or SNDR is maximum. For this, the antenna counts are optimised via Self Improved SSO with a Chaotic Map (SISSO-CM).

Sparse Ramanujan Sequences Transform based OFDM for PAPR reduction

Sparse Ramanujan Sequences (SRS) are periodic series derived from Ramanujan Sums (RS). RS is an exponential summation used to derive infinite series expansions for arithmetic functions, whose application pervades different fields of study from classical mathematics to digital signal processing. SRS has properties similar to RS such as periodicity and orthogonality. SRS transforms allow the sparse representation of signals, hence they have many potential applications, such as denoising and compression. The application of SRS transform to reduce the Peak to Average Power Ratio (PAPR) in Orthogonal Frequency Division Multiplexing (OFDM) is proposed in this paper. The Complementary Cumulative Distribution Function (CCDF) and Bit Error Rate (BER) are used to assess the PAPR reduction performance of the proposed system. The results show that the proposed SRS transform-based OFDM system significantly reduces PAPR and BER with reduced computational complexity in comparison with the existing systems.

Secure high-density constellation mapping OTFS modulation scheme with low PAPR

In this paper, a secure orthogonal time-frequency space (OTFS) modulation transmission system based on 3D dense constellation mapping (DCM) geometric shaping is proposed, and a selective reduction amplitude algorithm (SRA) for DCM to reduce peak average power ratio (PAPR) is presented. The DCM is based on regular tetrahedron construction to improve its space utilization efficiency. The proposed SRA involves reducing high PAPRs transmitter and restoring them at the receiving end, which only requires an additional 0.57% of the total transmission capacity. The algorithm reduces PAPR while ensuring the bit error rate performance of the system, so it is suitable for systems that need to process large amounts of transmitted data quickly. By verifying the actual transmission performance on a 2 km of 7-core optical fiber transmission system, the optical transmission with a bit rate of 33.93Gb/s is achieved. The experimental results show that when the bit error rate (BER) reaches the 3.8×10−3 threshold, the OTFS system using DCM and SRA could improve the receiver sensitivity by 3.7 dB compared with the OTFS system using concentric cube mapping and SRA, and 2.7 dB compared with the OFDM system using DCM. After adding the SRA, the PAPR of the OTFS system is reduced by more than 2.2 dB. When the received optical power reaches near the bit error rate threshold, the SRA valid data can be fully recovered by optimizing the SRA.

DLLBVS: Design of a High-Efficiency Deep Learning based Low-BER Video Streaming Model for High-Noise Wireless Networks

Design of video streaming models for high-noise networks is a multimodal process that requires efficient channel modelling, noise analysis, error-specific stream control, intelligent data augmentation, etc. This article proposes design of a high-efficiency deep learning based low-BER (Bit Error Rate) Video streaming model for high-noise wireless networks. The proposed model initially uses a Long-Short-Term Memory (LSTM) block for estimation of frame level features, and then uses Orthogonal Frequency Division Multiple Access (OFDMA) based modulation platform for transmission and reception of processed video frames. The OFDMA model is cascaded with a chaotic communication module, which assists in improving data fidelity under different noise conditions. The chaotic communication module is optimized using Grey Wolf Optimizer (GWO), which assists in setting up its hyperparameters for better efficiency under real-time communication scenarios. Video frames were pre-processed using Dual Neural Networks that assisted in estimation of differential frame information sets. Due to estimation of this differential frame information, streaming speed is improved, which assists in increasing number of frames transmitted per second, thereby improving streaming performance for different video types. This frame information is further processed by an iterative Gated Recurrent Unit (GRU) based VARMAx Model, which assists in predicting frame removal instances, thus assisting in faster & low error communications. The GRU VARMAx Model optimizes data flow, thus reducing congestion and improving throughput. The model was tested under AWGN (Additive While Gaussian Noise), Rayleigh, & Rician channel types, and its efficiency was compared with standard streaming techniques in terms of communication delay, Bit Error Rate, Peak to Average Power Ratio (PAPR), throughput, communication jitter and computational complexity levels. Based on this comparison it was observed that the proposed model showcased 3.5% lower communication delay, 8.3% lower BER, 5.9% lower PAPR, 10.5% higher throughput, 3.9% lower jitter and 6.4% lower computational complexity, which makes it highly useful for a wide variety of real-time streaming scenarios.

A Survey of PAPR Techniques Based on Machine Learning.

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 New Approximate Sum of Absolute Differences Unit for Bioimages Processing

An inexact 6-transistor full adder (FA) cell is presented. It is low-power and gives full-swing outputs because of the applied gate diffusion input (GDI) along with the dynamic threshold (DT) techniques. The FA which has three errors is used in a 10-transistor inexact 4:2 compressor based on the stacking circuit idea. The implementation by a 16 nm carbon nanotube field-effect transistor (CNTFET) technology shows a small area of 0.027 lm2 and 0.045 lm2 for the FA and compressor, respectively. A new approximate sum of absolute differences (SAD) block is presented by the FA and compressor. The average power, power-delay-product (PDP), and peak signalto-noise ratio (PSNR) of the SAD are 6.80 mW, 33.86 nJ, and 42.98 dB, respectively, which confirm its efficiency for bioimages difference detection.

Modified Error Function Companding for reduction of PAPR in GFDM signals

Generalized Frequency Division Multiplexing (GFDM) is a multicarrier modulation technique, nevertheless, it provides high peak to average power ratio (PAPR) which affects the power amplifier (PA) efficiency. In this work, the modified error function companding is proposed for reducing PAPR in GFDM signals. The power scaling parameter (η) and companding parameter (a) are used to reduce the peak power. The average power is not altered in the proposed method, so there is no need to adjust the dynamic gain of PA. The theoretical expressions for the transform gain, achievable PAPR reduction and closed form expression of attenuation factor are derived. Moreover, the transform gain, attenuation factor, power spectral density, PAPR and bit error rate (BER) performance of the proposed method is analysed for different values of companding parameter. The results ensure that the proposed mEFC method at a=1 provides significant PAPR reduction than existing companding methods.

Deep learning based asymmetrical autoencoder for PAPR reduction of CP-OFDM systems

Adoption of Orthogonal Frequency Division Multiplexing (OFDM) in 5th Generation New Radio (5G NR) as a multicarrier modulation technique allows high data rate transmission with lower complexity. However, problem such as peak to average power ratio (PAPR) has decreased the transmitter efficiency. Recently, several attempts have been made to reduce the high PAPR in OFDM utilizing deep learning (DL) based on autoencoder architecture. However, the proposed autoencoder using symmetrical autoencoder (SAE) is followed by high computational complexity at both transmitter and receiver as well as BER performance degradation. Since 5G NR focuses on massive 5G internet of things eco-system, a flexible carrier spacing is used to support diverse spectrum bands which is afterward named as Cyclic Prefix OFDM (CP-OFDM). In this study, we aimed to contribute to this growing area of research by exploring the potential of our proposed asymmetrical autoencoder (AAE) to reduce high PAPR in the CP-OFDM system. Four AAE models have been developed in this study and the performance of the models were evaluated based on comprehensive conditions such as data training at different corruption levels, cyclic prefix length, upsampling factors and loss function levels. The investigation of AAE in 5G CP-OFDM system has shown superior performance using a 5×1 AAE model that can reduce a substantial amount of PAPR, BER degradation and computational complexity compared to conventional SAE. This study lays the groundwork for future research into the asymmetrical approach of autoencoder especially in 5G and beyond networks.

Interleaving based SCMA Codebook Design Using Arnold’s Cat Chaotic Map

Non-orthogonal multiple access (NOMA) technology is a significant topic of the present 5G investigation. A possible NOMA approach is Sparse Code Multiple Access (SCMA), increasing next-generation communication's ability to handle multiple users. In SCMA, codebook designing and optimization are crucial components that define the performance of multiple access systems. In this work, the complete design procedure of the SCMA codebook based on interleaving is explained and simulated. Furthermore, a chaotic interleaving based onArnold’sCat map is proposed to reduce the computational complexity. The performance of the SCMA codebook based on interleaving is evaluated through comparison with selected codebooks for SCMA multiplexing. The measures used for performance evaluation include Bit Error rate (BER), Peak to Average Power Ratio(PAPR), and minimum EuclidianDistance(MED). The results show that the proposed codebook with chaotic interleaving achieves comparable performance to the traditional codebook based on interleaving and less MED and higher BER compared to computer-generated and 16-star QAM codebook design methods but with reduced complexity.

A low complexity enhanced squirrel search algorithm for reduction of peak to average power ratio in OFDM systems

A low complexity enhanced squirrel search algorithm for reduction of peak to average power ratio in OFDM systems

A Low Complexity Enhanced Squirrel Search Algorithm for Reduction of Peak to Average Power Ratio in OFDM systems

A Low Complexity Enhanced Squirrel Search Algorithm for Reduction of Peak to Average Power Ratio in OFDM systems

Modified Method of PAPR Reduction Using Clipping and Filtering for Image Transmission with OFDM

Due to the capability of OFDM (Orthogonal Frequency Division Multiplexing) to handle difficult channels, the most agreeable modulation for the multi-carrier scheme in present wireless communications is to improve an all-purpose modulation scheme, especially with high data rates. The image in this research article was transmitted and received on a noisy channel using an OFDM simulation technique. Since the average peak power ratio (PAPR) is one of the main disadvantages of OFDM, a new method has been proposed to reduce the PAPR using the clipping and filtering (CF) method. When the OFDM signal has a high PAPR, it means that many subcarrier components will be added through the operation of IFFT. Also, choosing the type of modulation to examine and getting a perfect type of OFDM system that is used for transmitting the image. Furthermore, signal-to-noise ratio (SNR) was considered to find the PAPR effect on the OFDM signal. The new method was tested to get a reduction of PAPR concerning CF and without CF. This method depends on clipping the signal before transmitting it, by using a method to overcome a nonlinear distortion, and therefore, decrease the bit error rate (BER). Then a filter with multi-stages was used to minimize the noise. This whole process was repeated several times to overcome the difficulties of transmitting/receiving the signal including PAPR. BER and SNR show wonderful outcomes when BPSK is chosen. Control over transmission and reception is also considered to be the type of modulation. All simulation results were defined using an Additive White Gaussian Noise (AWGN) channel.