Orthogonal Frequency Division Multiplexing Systems Research Articles

A novel PAPR reduction method for hybrid beamforming transmitter

In orthogonal frequency division multiplexing (OFDM) systems, peak-to-average power ratio (PAPR) is one of the major factors that affect the power efficiency of transmitter. There exist many PAPR reduction methods for the conventional fully digital multiple-input multiple-output (MIMO) systems but there is little discussion on the PAPR reduction for the hybrid beamforming systems. When some output signals of the digital to analogue converter (DAC) are combined by the analogue beamforming network before power amplifier (PA), the one to one mapping between the digital signal and the signal passing through PAs is destroyed. In such hybrid beamforming architectures, the existing methods can only reduce the PAPR of DAC input signal but not PAPR of PA input signal. In this paper, we investigate whether and how we can extend existing PAPR reduction methods to the hybrid beamforming systems. We propose a novel PAPR reduction method, which extends the iteratively clipping and filtering (ICF) to the hybrid beamforming systems. To the best of our knowledge, our proposed algorithm is the first PAPR reduction algorithm dedicated for the hybrid beamforming systems. From the simulation, our proposed algorithm can achieve a smaller PAPR than the improved selective mapping (SLM) algorithm at the cost of minor signal distortion.

Performance Analysis of PAPR minimization in OFDM System Using Clipping, SLM and PTS Techniques

In wireless communications, Orthogonal Frequency Division Multiplexing (OFDM) is a method of modulating multicarrier signals to transmit high speed data. OFDM systems use multiple subcarriers to transmit the modulated symbols. There is a high peak to average power ratio (PAPR) in OFDM. PAPR can be reduced by using various methods. Different PAPR minimization techniques, like clipping, selective mapping (SLM) and partial transmit sequence (PTS) are presented in this project. This paper also focuses on Bit Error Rate (BER) and Signal to Noise Ratio (SNR) relative performance. A significant reduction in the PAPR and computational complexity can be seen from the results. The purpose of this study is to compare the results of an analysis recommended for PAPR reduction methods.

A Joint Channel Estimation and Compression Method Based on GAN in 6G Communication Systems

Due to the increasing popularity of communication devices and vehicles, the channel environment becomes more and more complex, which makes conventional channel estimation methods further increase the pilot overhead to maintain estimation performance. However, it declines the throughput of communication networks. In this paper, we provide a novel two-stage based channel estimation method by using generative adversarial networks (GANs) to handle this problem in orthogonal frequency division multiplexing (OFDM) systems. Specifically, the first stage aims to learn the mapping from a low-dimensional latent variable to the real channel sample. During the second stage, an iterative algorithm method is designed to find the optimal latent variable by matching the pilot channels of a real channel and generated channel. Then, the data channels are recovered based on the learned mapping relationship between the latent variable and the real channel sample. The simulation results show that our proposed method can achieve a performance gain of more than 2 dB with a pilot reduction by 75% when SNR is 10 dB, by comparing with the widely used Wiener filter interpolation method. In addition, as the low-dimensional latent variable can be obtained simultaneously, it can also be used for reducing the feedback overhead.

Curve Fitting Based Piecewise Nonlinear Companding Scheme for PAPR Reduction in OFDM Systems

Peak-to-average power ratio (PAPR) is an important issue for orthogonal frequency division multiplexing (OFDM) systems. In this letter, we derive a new piecewise nonlinear companding scheme for reducing PAPR in OFDM systems. Compared with current state-of-art companding scheme, the new companding scheme improves the power spectral density (PSD) performance. The companding function is derived according to the cumulative distribution function (CDF) of companded OFDM signals’ amplitudes, which is fitted by using several piecewise linear functions to approximate the original Rayleigh distribution CDF. The constraint optimization problem is formulated, and parameter selection method is provided. Simulation results verify that under precondition of similar PAPR reduction levels, the proposed companding scheme could achieve better bit error rate (BER) and PSD performance compared with other typical companding schemes.

Compressive Beam and Channel Tracking With Reconfigurable Hybrid Beamforming in mmWave MIMO OFDM Systems

An efficient beam and channel acquisition and tracking scheme is developed under a reconfigurable hybrid beamforming (R-HBF) architecture for wideband millimeter wave (mmWave) multiple input multiple output (MIMO) systems. Under such an R-HBF, a hierarchical multi-resolution beam scanning and space-frequency compressive sensing method is proposed to achieve fast beam and channel acquisitions in mmWave MIMO orthogonal frequency division multiplexing (OFDM) systems. With the initial frequency-domain beam space channel estimates, Kalman-based algorithms are further developed to track the transmit and receive beamforming directions and the channel coefficients of the sparse propagation paths in mmWave mobile channels. Simulations show that the proposed method can greatly reduce the beam training time, and that the channel capacity evaluated with the estimated channels is only 2 dB inferior to the one with ideal channels. Moreover, the beam selection error rates are less than 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−3</sup> in typical urban mmWave mobile channels and traveling speeds even if the transmit power is only 10 dBm.

Iterative phase noise suppression for full-duplex communication systems

Oscillator phase noise is one of the bottlenecks that limits the self-interference (SI) cancellation capability of full-duplex systems. In this paper, we propose a method for the suppression of common phase error (CPE) and intercarrier interference (ICI) induced by the phase noise in full-duplex orthogonal frequency division multiplexing (OFDM) systems. First, we regard the effect of CPE as a portion of the SI channel and perform estimation, reconstruction and elimination in the time domain. Then, the ICI signal is estimated and suppressed in the frequency domain. Additionally, by analysing the performance of proposed algorithm, we further develop an iterative mechanism to reduce the parameter estimation error and improve SI cancellation capability. Simulation results show that the proposed method has a significant SI cancellation capability improvement over the traditional SI cancellation schemes.

Sparse Channel Estimation With Surface Clustering for IRS-Assisted OFDM Systems

Intelligent reflecting surface (IRS) is deemed as a potential technology for future communications due to its adaptive enhancement for the propagation environment. To achieve the passive beamforming gain of IRS, accurate channel state information (CSI) is essential but practically challenging since its massive passive reflecting elements have no transmitting/receiving capability. This paper presents a new channel estimation problem formulation for IRS-assisted orthogonal frequency division multiplexing (OFDM) systems, where the channel sparsity is exploited in the time-domain. Considering the surfaces are physically close to each other, we further utilize the common sparsity among the different sub-surfaces and automatically cluster them into several groups by introducing a Dirichlet process (DP)-based clustering model. Then, a DP-based variational Bayesian inference (VBI) framework is proposed to jointly estimate the channel and cluster the sub-surfaces, which is expected to significantly improve the channel estimation performance. Moreover, a novel decoupling trick is combined into the VBI framework to efficiently handle the coupling effect brought by the reflection coefficients, as well as facilitate the Bayesian inference. Simulation results verify the effectiveness of the proposed channel estimation scheme and show its significant performance improvement over various benchmark schemes.

CNN-Attention-DNN Design for CFO Estimation of Non-Pilot-Assisted OFDM System

In this letter, we propose a novel attention mechanism inspired convolutional neural network (CNN)-deep neural network (DNN) called CAD model architecture for carrier frequency offset (CFO) estimation in orthogonal frequency division multiplexing (OFDM) systems. The hyperparameters used in the proposed CAD model are optimized using the Bayesian approach. The proposed CFO estimation scheme is robust to small symbol timing offset errors and does not require apriori knowledge of modulation format, channel, and transmitted OFDM signal parameters. Simulations performed over the realistic frequency-selective channel models with and without power amplifier non-linearity indicate that the proposed CAD architecture outperforms the conventional statistical-based and recurrent neural network (RNN)-based models. Lastly, the proposed CAD model is validated on the radio frequency testbed.

A 500 km Long Transmission with Coherent Optical OFDM Using Dual Polarization Quadrature Phase Shift Keying (QPSK) and Double Sideband Suppressed‐Enhanced Carrier (DSS‐EC)

AbstractCoherent optical orthogonal frequency division multiplexing (CO‐OFDM) systems are chosen for this task because of their high spectral efficiency, low inter‐symbol interference (ISI), low intercarrier interference (ICI), robustness against chromatic dispersion (CD), and high nonlinearity interference tolerance (HNIT). The DSS‐EC technique is utilized in this study to investigate a high‐speed 100 Gbps CO‐OFDM with a QPSK encoder over a 500 km uncompensated connection distance. The proposed system is compared to CO‐OFDM‐QPSK and CO‐OFDM‐16QAM systems in terms of log BER at various input optical signal to noise ratios (OSNRs). Results reveal that due to enhanced available bandwidth use of communication channels, the proposed CO‐OFDM‐DSS‐EC‐QPSK system provides minimum log BER at lower input OSNRs while the rest two systems show identical log BER performance at high input OSNRs. Therefore, proposed technique is a prominent solution for future generations high data demands and for a cost‐effective solution due to an uncompensated transmission channel.

Estimation of bit error rate in 2×2 and 4×4 multi-input multi-output-orthogonal frequency division multiplexing systems

&lt;span lang="EN-US"&gt;Multiple-input, multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems with multiple input antennas and multiple output antennas in dynamic environments face the challenge of channel estimation. To overcome this challenge and to improve the performance and signal-to-noise ratio, in this paper we used the Kalman filter for the correct estimation of the signal in dynamic environments. To obtain the original signal at the receiver end bit error rate factor plays a major role. If the signal to noise ratio is high and the bit error rate is low then signal strength is high, the signal received at the receiver end is almost similar to the &lt;/span&gt;&lt;em&gt;&lt;span lang="EN-US"&gt;i&lt;sup&gt;th&lt;/sup&gt;&lt;/span&gt;&lt;/em&gt;&lt;span lang="EN-US"&gt; transmitted signal. The dynamic tracking characteristic of Kalman filter is used to establish a dynamic space-time codeword and a collection of orthogonal pilot sequences to prevent interference among transmissions in this paper. Using the simulation, the Kalman filter method can be compared to the other channel estimation method presented in this paper that can track time-varying channels rapidly.&lt;/span&gt;

Reconfigurable intelligent surface enhanced MISO‐OFDM anti‐jamming communications: Joint active and passive precoding design

AbstractThe reconfigurable intelligent surface (RIS) fundamentally changes the existing anti‐jamming paradigm by reconstructing the wireless propagation environment. However, the existing RIS‐based anti‐jamming work mainly considers narrow‐band frequency‐flat fading channels. As an extension of existing work, the use of RIS to enhance the anti‐jamming capability of broadband orthogonal frequency division multiplexing (OFDM) system in frequency‐selective fading channels is first studied. In the multipath frequency‐selective fading channels, the anti‐jamming design needs to satisfy the channel gains of all signal paths with different delays. To this end, the authors propose a joint design scheme of active precoding at the transmitter and passive precoding at the RIS to attenuate the jamming signal and enhance the legitimate signal, and formulate the joint design objective to maximize the average rate of all subcarriers. An alternating optimization algorithm is developed to address this non‐convex problem due to the complex coupling of active and passive precoding. In detail, the active and passive precoding are solved by the Cauchy–Schwarz inequality and power water‐filling method and the alternating direction method of multipliers method assisted by multidimensional complex quadratic transform, respectively. Simulation results demonstrate that the proposed method can significantly improve the anti‐jamming communication performance of the OFDM system compared with the scheme without RIS. In addition, the impact of the number of RIS elements and deployment location on system performance is revealed.

Power-Delay-Profile-Based MMSE Channel Estimations for OFDM Systems

This paper deals with the problem of the channel estimation of orthogonal frequency division multiplexing (OFDM) signals transmitted through a time-varying fading channel. We show that an accurate power delay profile (PDP) estimator can be obtained by utilizing the cyclic redundancy induced by a cyclic prefix (CP), which can be applicable to OFDM systems with insufficient pilot or training symbols (IEEE 802.11p/WAVE system), and then a least mean square error (MMSE) channel estimation scheme can be obtained in a manner based on the estimated PDP. The simulation results highlight the benefit of the proposed methods compared with the state-of-the-art standard and three achievable performance bounds.

Enhanced diversity scheme for orthogonal frequency division multiplexing systems over doubly selective fading channels

AbstractFrequency‐time selective fading degrades the performance of communication systems, but it also provides an opportunity to collect multipath diversity and Doppler diversity. In this paper, an oversampled grouped‐linear‐constellation‐precoding (GLCP) scheme is proposed for orthogonal frequency division multiplexing (OFDM) systems to extract the diversity inherent in doubly selective fading channels. In the proposed scheme, GLCP is employed to precode the information symbols of OFDM at the transmitter, and the precoded OFDM symbols are oversampled in the time domain at the receiver. A full‐groups maximum likelihood (ML) decoder and a successive group decoder to decode the oversampled OFDM symbols with diversity gains are developed. The successive group decoder combines the group ML decoding algorithm with a block‐decision‐feedback‐equalization (BDFE) algorithm. The proposed scheme can take advantage of both the GLCP scheme and the oversampling scheme to achieve multipath diversity gains and Doppler diversity gains in doubly selective fading channels. Simulation results show that the proposed scheme can significantly improve the performance of OFDM systems in the frequency selective fading channel and the doubly selective fading channel in terms of bit error ratio, indicating that the diversity gains can be greatly enhanced by the proposed scheme in doubly selective fading channels.

A turbo‐based encryption and coding scheme for multiple‐input multiple‐output orthogonal frequency division multiplexing wireless communication systems affected by Doppler frequency offset

AbstractMultiple‐Input Multiple‐Output Orthogonal Frequency Division Multiplexing (MIMO‐OFDM) is an essential technology in the wireless communication system. However, its performance is significantly affected by Carrier Frequency Offset (CFO), which leads to inter‐carrier interference (ICI). The CFO estimation and compensation techniques are used to mitigate the Doppler effect. In addition, the confidentiality of data is a key factor of the system. This paper proposes a Turbo‐based encryption and coding scheme to improve reliability and security for the MIMO‐OFDM wireless communication systems affected by the Doppler frequency offset. In our proposed scheme, the secret key is produced from channel parameters between legitimate users and it is used as a seed for generating a pseudo‐random bit sequence using an Advanced Encryption Standard (AES) generator with variable key lengths. The Turbo code's puncturing mechanism is controlled by this pseudo‐random bit sequence. The proposed method is applied to the system with different modulation schemes through the Rayleigh channel. The simulation results show that the system affected by the Doppler effect would obtain the best performance when using the highest key length of the AES generator, the BPSK, and a great number of receive antennas. Furthermore, the proposed solution outperforms several previous approaches for the MIMO‐OFDM systems.

A Novel Low Complexity Two-Stage Tone Reservation Scheme for PAPR Reduction in OFDM Systems.

Orthogonal frequency division multiplexing (OFDM) has the characteristics of high spectrum efficiency and excellent anti-multipath interference ability. It is the most popular and mature technology currently in wireless communication. However, OFDM is a multi-carrier system, which inevitably has the problem of a high peak-to-average power ratio (PAPR), and s signal with too high PAPR is prone to distortion when passing through an amplifier due to nonlinearity. To address the troubles caused by high PAPR, we proposed an improved tone reservation (I-TR) algorithm to alleviate the above native phenomenon, which will pay some modest pre-calculations to estimate the rough proportion of peak reduction tone (PRT) to determine the appropriate output power allocation threshold then utilize a few iterations to converge to the near-optimal PAPR. Furthermore, our proposed scheme significantly outperforms previous works in terms of PAPR performance and computational complexity, such as selective mapping (SLM), partial transmission sequence (PTS), TR, tone injection (TI), etc. The simulation results show that in our proposed scheme, the PAPR is appreciably reduced by about 6.44 dB compared with the original OFDM technique at complementary cumulative distribution function (CCDF) equal to 10-3, and the complexity of I-TR has reduced by approximately 96% compared to TR. Besides, as for bit error rate (BER), our proposed method always outperforms the original OFDM without any sacrifice.

Deep reinforcement learning-based adaptive modulation for OFDM underwater acoustic communication system

Due to the time-varying and space-varying characteristics of the underwater acoustic channel, the communication process may be seriously disturbed. Thus, the underwater acoustic communication system is facing the challenges of alleviating interference and improving communication quality and communication efficiency through adaptive modulation. In order to select the optimal modulation mode adaptively and maximize the system throughput ensuring that the bit error rate (BER) meets the transmission requirements, this paper introduces deep reinforcement learning (DRL) into orthogonal frequency division multiplexing acoustic communication system. The adaptive modulation is mapped into a Markov decision process with unknown state transition probability. Thereby, the underwater communication channel environment is regarded as the state of DRL, and the modulation mode is regarded as action. The system returns channel state information (CSI) and signal–noise ratio in every time slot through the feedback link. Because the Deep Q-Network optimizes in the changing state space of each time slot, it is suitable for a variety of different CSI. Finally, simulations in different underwater environments (SWellEx-96) show that the proposed adaptive modulation scheme can obtain lower BER and improve the system throughput effectively.

Impulsive Noise Cancellation in OFDM System Using Low Density Parity Check

An effective communication application necessitates the cancellation of Impulsive Noise (IN) from Orthogonal Frequency Division Multiplexing (OFDM), which is widely used for wireless applications due to its higher data rate and greater spectral efficiency. The OFDM system is typically corrupted by Impulsive Noise, which is an unwanted short-duration pulse with random amplitude and duration. Impulsive noise is created by humans and has non-Gaussian characteristics, causing problems in communication systems such as high capacity loss and poor error rate performance. Several techniques have been introduced in the literature to solve this type of problem, but they still have many issues that affect the performance of the presented methods. As a result, developing a new hybridization-based method is critical for accurate method performance. In this paper, we present a hybrid of a state space adaptive filter and an information coding technique for cancelling impulsive noise from OFDM. The proposed method is also compared to Least Mean Square (LMS), Normalized Least Mean Square (NLMS), and Recursive Least Square (RLS) adaptive filters. It has also been tested using the binary phase-shift keyed (BPSK), four quadrature amplitude modulation (QAM), sixteen QAM, and thirty-two QAM modulation techniques. Bit error Rate (BER) simulations are used to evaluate system performance, and improved performance is obtained. Furthermore, the proposed method is more effective than recent methods.

Filtered OFDM System Improvement Using Hamming Code

Orthogonal Frequency Division Multiplexing (OFDM) technique is widely adopted for broadband Forth Generation (4G) wireless communication systems at present, owing to its ability to combat multi-path interference. Nevertheless, it suffers from a large Peak to Average Power Ratio (PAPR) and Out Of Band Emission (OOBE), making it unsuitable for a high-speed transmission system. On the other hand, the Filtered-OFDM (f-OFDM) system is suggested to overcome the traditional OFDM system's disadvantages and maintain its advantages. Nowadays, the developments and growing communications systems are rapid, especially on their applications such as wireless networks, internet, satellite communications, mobile telephony, etc. This increases the demand for raising the bit rates with decreasing power consumption and the bit error rates (BER). In this paper, Hamming codes are proposed to improve the f-OFDM system performance, while the presence of the subband filter in system architecture could decrease the values of OOBE than the familiar OFDM system. The outcomes showed that utilizing interleaver with Hamming code considerably improves the proposed system performance, while the OOBE values were lower than the conventional OFDM system.

An improved least squares (LS) channel estimation method based on CNN for OFDM systems

&lt;abstract&gt;&lt;p&gt;Least squares (LS) is a commonly used pilot-based channel estimation algorithm in orthogonal frequency division multiplexing (OFDM) systems. This algorithm is simple and easy to implement because of its low computation complexity. However, it has poor performance, especially at low signal-to-noise ratio (SNR). To solve this problem, an improved LS channel estimation method based on convolutional neural network (CNN) is proposed on the basis of analyzing the traditional LS channel estimation methods. A channel estimation compensated network is designed based on CNN, which can solve the problem of performance degradation of the mean square error (MSE) through the online and offline modules. By designing the input-output relations, training data set, and testing data set, a CNN network is iteratively trained to learn the relevant features of the channels, so that the traditional LS estimation value can be corrected to improve the accuracy. Simulation results show that the proposed method can achieve better performance in bit error rate (BER) and MSE, compared with the traditional channel estimation methods.&lt;/p&gt;&lt;/abstract&gt;

Obfuscation of Human Micro-Doppler Signatures in Passive Wireless RADAR

When wireless communication signals impinge on a moving human they are affected by micro-Doppler. A passive receiver of the resulting signals can calculate the spectrogram that produces different signatures depending on the human activity. This constitutes a significant privacy breach when the human is unaware of it. This paper presents a methodology for preventing this when we want to do so by injecting into the transmitted signal frequency variations that obfuscate the micro-Doppler signature. We assume a system that uses orthogonal frequency division multiplexing (OFDM) and a passive receiver that estimates the spectrogram based on the instantaneous channel state information (CSI). We analyze the impact of our approach on the received signal and we propose two strategies that do not affect the demodulation of the digital communication signal at the intended receiver. To evaluate the performance of our approach we use an IEEE 802.11-based OFDM system and realistic human signal reflection models.