OFDM Signal Research Articles

Retraction Note: Quantum-enhanced OFDM signal processing: advancing 5G mobile network and IoT communication for healthcare application

Retraction Note: Quantum-enhanced OFDM signal processing: advancing 5G mobile network and IoT communication for healthcare application

60-GHz Millimeter-Wave over Visible Light Communications for Downlink Wireless Networks

Background and Objective: In this paper, we address potential solution for downlink wireless communications by integrating visible light communications (VLC) with the broadband radio frequency (RF) networks operating at 60 GHz-millimeter wave (mmWave) band. For this hybrid design, the outdoor 60 GHz-mmWave based RF link is utilized to ensure backhaul connectivity for VLC indoor system, while the VLC exploiting the lighting infrastructure that essentially used LEDs as optical source to provide low-cost and high-speed data access. Methods: The hybrid 60 GHz-mmWave/VLC system is analyzed by using 16-QAM OFDM signal, and its performance is investigated by evaluating the signal to noise ratio (SNR) and the received signal power distributions, for regular placement of LEDs and random location of receivers within the room. The impact of the transmitter-receiver parameters, and their orientations and directivities are also considered. Results: Numerical results show the efficiency of the proposed system, which can retransmit RF signals at 60 GHz-mmWave band using visible optical carriers in the indoor environment. Conclusion: The results suggest that the hybrid 60 GHz-mmWave/VLC system is able to provide reliable wireless data transmission, making it an attractive solution for downlink indoor communications.

Joint range and velocity super-resolution estimation with Doppler effects for innovative OFDM-based RFA RadCom system

Conventional radar and communication signals face challenges when integrating for accurate sensing in dense electromagnetic environments, especially in scenarios involving high-velocity targets estimation. To address this issue, we propose the random frequency agile-orthogonal frequency division multiplexing-based radar and communication (RFA-OFDM-based RadCom) signal, a novel framework that combines RFA hopping radar signal and OFDM signal. This framework effectively handles high-velocity Doppler scenarios, enhancing electronic countermeasure capabilities. In high-velocity scenarios, achieving accurate range and velocity estimation is crucial. We introduce a comprehensive received signal model that considers intrapulse and intersubcarrier Doppler effects, often overlooked in traditional high-velocity contexts. The proposed two-phase hierarchical perceptual methodology enables joint super-resolution estimation using the shared signal. We transform the shared signal echo model into a uniform linear array-like model and employ the matrix decomposition algorithm based on bidirectional weighted frequency smoothing (BWFS-MD) for decoherence processing. Subsequently, the estimation of signal parameters via rotational invariance techniques (ESPRIT)-complementary integrated subspace fitting (E-CISF) algorithm accurately estimates joint range and velocity. Meanwhile, the contrastive analysis of the mutual impacts between radar and communication functions is conducted. Theoretical analysis and simulation results robustly validate the superior performance of the proposed BWFS-MD algorithm. Furthermore, considering the precision of joint range-velocity estimation, real-time constraints, and super-resolution capability (which is emphasized), the E-CSIF algorithm demonstrates the best overall performance from a comprehensive perspective.

OptiFusion steganography method based on masking OFDM signal in Gaussian beam intensity

OptiFusion steganography method based on masking OFDM signal in Gaussian beam intensity

Localization With the Fingerprints of Multipath Angle Delay Spectrum of OFDM Signal

Localization With the Fingerprints of Multipath Angle Delay Spectrum of OFDM Signal

Encrypted-OFDM: A secured wireless waveform

Wireless communication has been a broadcast system since its inception, which violates security and privacy issues at the physical layer between the intended transmit and receive pairs. Consequently, it is essential to secure the wireless signal such that only the intended receiver can realize the signal properties. In this paper, we propose Encrypted-OFDM, a new waveform, where the signal structure is altered to encrypt the waveform with a shared secret key. We achieve the signal level security by modifying the OFDM signal in time-domain, thus erasing the OFDM properties and obfuscating the signal properties to an eavesdropper. We present a two-stage encryption algorithm to increase the robustness of the transmitted waveform and achieve a high level of secrecy, even when low entropy keys are used. We also introduce a novel channel estimation algorithm by removing the pilots, so that only the intended receiver can estimate the channel correctly. Furthermore, we perform both secrecy and error analysis for the transmitted and received Encrypted-OFDM waveform. Extensive simulation and over-the-air experiments show that the performance of Encrypted-OFDM is comparable to legacy OFDM, and the SNR penalty due to the secured waveform varies between ≈ 1–4 dB. In all these scenarios, Encrypted-OFDM remains unrecognized at the eavesdropper.

Quantum-Dash Semiconductor Optical Amplifier for Millimeter-Wave over Fibre Wireless Fronthaul Systems

This paper demonstrates a five-layer InAs/InP quantum-dash semiconductor optical amplifier (QDash-SOA), which will be integrated into microwave-photonic on-chip devices for millimeter-wave (mmWave) over fibre wireless networking systems. A thorough investigation of the QDash-SOA is conducted regarding its communication performance at different temperatures, bias currents, and input powers. The investigation shows a fibre-to-fibre (FtF) small-signal gain of 18.79 dB and a noise figure of 6.3 dB. In a common application with a 300 mA bias current and 25 °C temperature, the peak FtF gain is located at 1507.8 nm, which is 17.68 dB, with 3 dB gain bandwidth of 56.6 nm. Furthermore, the QDash-SOA is verified in a mmWave radio-over-fibre link with QAM (32 Gb/s 64-QAM 4-GBaud) and OFDM (250 MHz 64-QAM) signals. The average error vector magnitude of the QAM and OFDM signals after a 2 m wireless link could be as low as 8.29% and 6.78%, respectively. These findings highlight the QDash-SOA’s potential as a key amplifying component in future integrated microwave-photonic on-chip devices.

Elimination of Phase Offsets for Microwave Ranging Using OFDM Signals

Elimination of Phase Offsets for Microwave Ranging Using OFDM Signals

Noise mitigation method for power line communication based on cross-correlation analysis

Abstract Noise has a significant impact on the transmission rate and reliability of power line communication(PLC), which has become a crucial factor affecting PLC. In order to enhance the noise resistance of PLC, this paper proposes a noise mitigation method for PLC based on cross-correlation analysis. Firstly, the characteristics of OFDM signals based on PSK modulation are analyzed. Subsequently, reference signals are created for the purpose of cross-correlation with the PLC signal. Then, the phase of each subcarrier can be obtained. The PLC signal is reconstructed by utilizing the obtained phase, thereby achieving noise mitigation. Finally, the algorithmic program has been written for the simulation of the method in MATLAB. The simulation results show that the noise mitigation method can successfully remove the noise from PLC signals with signal-to-noise ratios within -20dB.

PRNet with Convolution Layer for PAPR Reduction of OFDM Signals

PRNet with Convolution Layer for PAPR Reduction of OFDM Signals

Reconstruction of OFDM Signals Using a Dual Discriminator CGAN with BiLSTM and Transformer.

Communication signal reconstruction technology represents a critical area of research within communication countermeasures and signal processing. Considering traditional OFDM signal reconstruction methods' intricacy and suboptimal reconstruction performance, a dual discriminator CGAN model incorporating LSTM and Transformer is proposed. When reconstructing OFDM signals using the traditional CNN network, it becomes challenging to extract intricate temporal information. Therefore, the BiLSTM network is incorporated into the first discriminator to capture timing details of the IQ (In-phase and Quadrature-phase) sequence and constellation map information of the AP (Amplitude and Phase) sequence. Subsequently, following the addition of fixed position coding, these data are fed into the core network constructed based on the Transformer Encoder for further learning. Simultaneously, to capture the correlation between the two IQ signals, the VIT (Vision in Transformer) concept is incorporated into the second discriminator. The IQ sequence is treated as a single-channel two-dimensional image and segmented into pixel blocks containing IQ sequence through Conv2d. Fixed position coding is added and sent to the Transformer core network for learning. The generator network transforms input noise data into a dimensional space aligned with the IQ signal and embedding vector dimensions. It appends identical position encoding information to the IQ sequence before sending it to the Transformer network. The experimental results demonstrate that, under commonly utilized OFDM modulation formats such as BPSK, QPSK, and 16QAM, the time series waveform, constellation diagram, and spectral diagram exhibit high-quality reconstruction. Our algorithm achieves improved signal quality while managing complexity compared to other reconstruction methods.

Enhanced 4D-OFDM optical communication systems with color-coded constellations and probability constellation shaping.

The present work introduces a four-dimensional probability constellation mapping OFDM optical transmission system based on a two-dimensional inverse fast Fourier transform (2D-IFFT). A four-dimensional constellation structure employing color coding is designed, amalgamating geometric shaping with probability shaping to enhance the constellation figure of merit (CFM). Successful transmission of OFDM signals at 51.49 Gb/s is achieved over a 2 km seven-core optical fiber, validating the performance of the proposed constellation diagram. Under the conditions of multicore multiplexing and a bit error rate of 3.8 × 10-3, the receiver sensitivity of the OFDM signals mapped with the proposed color-coded four-dimensional constellation exhibits gains of 0.8 dB, 1.33 dB, and 1.83 dB compared to traditional four-dimensional constellations, 3D-OFDM, and 2D-OFDM modulation, respectively. Furthermore, under an entropy value of 4.4 bits/symbol, a receiver sensitivity gain of 1.36 dB is attained compared to a uniform distribution constellation, indicating the favorable error performance of this scheme with promising prospects for short-distance communication in the future.

Implementation of companding scheme for performance enhancement of optical OFDM structure

Abstract Due to its great spectral efficiency and resistance to multi-path fading, OFDM, or orthogonal frequency division multiplexing, is commonly utilized in optical communication systems. However, because of nonlinear distortions in optical components, OFDM signals are prone to a high peak-to-average power ratio (PAPR), which can severely impair bit error rate (BER) performance. This paper introduces a companding scheme to address high PAPR in optical OFDM systems and improve BER performance. The proposed scheme uses a nonlinear transformation to compress signal peaks and expand valleys, effectively reducing PAPR. Specifically, we investigate the µ-law companding technique, known for its simplicity and effectiveness in handling the active range of OFDM signals in optical communication. The companded signals are transmitted through an optical link and demodulated at the receiver. Simulation results show that the µ-law companding technique substantially reduces PAPR, leading to a significant improvement in BER performance. The companding process maintains signal integrity and spectral efficiency with minimal computational complexity and implementation cost. By mitigating nonlinearities introduced by optical components, this companding scheme enhances the overall reliability and efficiency of the optical OFDM system. An SNR gain of 2 dB–3 dB was achieved at a BER of 10−3.

Spectral Analysis of Nonlinear Phase Noise Arising in Coherent Fiber-Optic Transmission Systems of OFDM Signals

Spectral Analysis of Nonlinear Phase Noise Arising in Coherent Fiber-Optic Transmission Systems of OFDM Signals

Secure transmission in a W-band RoF system based on delta-sigma modulation.

In this Letter, a delta-sigma modulation (DSM) encryption technique in a W-band RoF system is proposed. By performing DSM with different over-sample ratios (OSRs) on the OFDM signal based on the controlled keys generated by the chaotic system at the transmitter and performing constellation masking to disturb the transmitting signal for encryption, a high-order QAM-OFDM-DSM encrypted signal is achieved. In order to further improve the security of the system, bit bidirectional diffusion scrambling is used to resist chosen-plaintext attacks. After experimental verification, under the same transmission power, the encrypted DSM signal can achieve better security than single OSR of DSM signals through a 50-km standard single-mode fiber (SSMF) and a 3-m wireless channel, with the gain of sensitivity increased by ∼1 dBm. From the reliability of the system, the encrypted signal of the proposed scheme can be recovered, which meets a hard decision-forward error correction (HD-FEC) threshold of 3.8 × 10-3.

5G Channel Estimation using Deep Learning

The abstract focuses on the integration of 5G channel estimation and the vulnerability of deep learning models, specifically in the context of OFDM signals, while employing a student-teacher model architecture. Channel estimation is a crucial aspect of 5G communication systems, ensuring reliable data transmission in dynamic wireless environments. Simultaneously, the advent of deep learning introduces susceptibility to adversarial attacks, where malicious inputs can deceive the model's predictions. This paper explores the intricate relationship between 5G channel estimation and deep learning vulnerabilities, emphasising the application of a student-teacher model to enhance system robustness. By delving into the nuances of OFDM signals, the study aims to provide a comprehensive understanding of how these elements intertwine, offering insights into potential security enhancements for next-generation wireless communication systems.

Machine Learning Algorithms for Performance Enhancement in DCO-OFDM-Based LiFi Systems

This study describes how machine learning methods can be used to enhance the performance of LiFi (light fidelity) systems that are based on DCO-OFDM (direct current bias optical orthogonal frequency division multiplexing). LiFi, a rapidly developing technology that uses light for wireless communication, has to contend with issues like channel impairments and signal interference. This work investigates several machine learning strategies to address these problems and improve the DCO-OFDM LiFi systems' overall performance. It is determined how well various machine learning techniques perform in terms of improving system parameters, decreasing latency, and raising throughput by analyzing real-world data and simulation studies. Various sorts of symmetrical recurrence division multiplexing (OFDM, for example, DC one-sided optical OFDM (DCO-OFDM), are utilized in light devotion (LiFi). A critical DC predisposition in DCO-OFDM brings about optical power failure, while a minor inclination increment cutting commotion. In this manner, it's essential to decide the appropriate DC predisposition level for DCO-OFDM. This examination finds the ideal DC-predisposition an incentive for DCO-OFDM based LiFi frameworks utilizing machine learning (ML) algorithms. To do this, a MATLAB device is utilized to create a dataset for DCO-OFDM. Thusly, Python writing computer programs is utilized to apply machine learning methods. ML is used to recognize the basic DCO-OFDM qualities that influence the ideal DC predisposition. Here, it is exhibited that the base, greatest, and standard deviation of the bipolar OFDM signal, as well as the size of the heavenly body, decide the ideal DC inclination.

Spatial Selection-Based Intelligent N-OFDM Signal Processing in Wireless Communication Systems

The method of joint processing of pulses and OFDM (N-OFDM) signals is proposed. The corresponding analytical relations for the lower Cramer-Rao boundary on the dispersion of OFDM (N-OFDM) signals amplitude ratings in the presence of sources of pulsed radiation are obtained. Using mathematical modeling properties and limitations of the demodulation method of OFDM (N-OFDM) signals in the background of impulse signals in the integrated radar and telecommunication systems are established. It is determined that the use of the angular distance between the pulsed and OFDM signals sources at a value that is not less than 0.75 widths of the secondary beam of the digital antenna array pattern does not affect the accuracy of the OFDM signal amplitudes. The same applies to the active interferences.

Chaotic discrete Fresnel transform for secure OFDM-PONs

A chaotic discrete Fresnel transform (DFnT) precoding scheme is proposed for physical-layer security enhancement in orthogonal frequency division multiplexing passive optical networks (OFDM-PONs). A multi-fold OFDM data encryption is applied in terms of the chaotic scale factor, and chaotic row/column permutations in the DFnT matrix, and the chaos sensitivity creates a huge key space of 10138. The peak-to-average power ratio (PAPR) performances of OFDM signals associated with a scale factor in DFnT are fully analyzed. A 38.2 Gb/s OFDM signal transmission with chaotic DFnT is successfully demonstrated over a 20 km standard single-mode fiber (SSMF), where the gain of receiver sensitivity is ∼2 dB (BER @10−3), compared with OFDM without precoding.

Modified SiP single-polarization CADD receiver.

In cost-sensitive application scenarios, increasing the data rate per channel under a limited receiver bandwidth is critical, and thus, the transceivers with low costs and high electrical spectral efficiencies (ESEs) are highly desirable. In this Letter, we demonstrate a modified silicon photonic (SiP) carrier-assisted differential detection (CADD) receiver with a record ESE for single polarization. The ESE of the conventional CADD is mainly limited by the transfer function that originated from the optical delay and hybrid. We modify the transfer function of the CADD by placing an additional delay in parallel to the original delay path. Consequently, the modified transfer function exhibits a sharper slope around the zero frequency, leading to a higher ESE. Here we employ complementary metal-oxide-semiconductor-compatible SiP integration to further reduce the cost and footprint of the modified CADD receiver. In the experiment, 280-Gb/s raw rate (net 226-Gb/s) 16-QAM OFDM signal after 80-km SMF transmission was detected using a 36.5-GHz SiP modified CADD receiver, with a bit error ratio below the 24% SD-FEC threshold. To our best knowledge, we achieve a record net 6.2-b/s/Hz ESE for an integrated single-polarization DD receiver with a 16-QAM format.