OFDM Research Articles

Integrated Sensing and Communication Target Detection Framework and Waveform Design Method Based on Information Theory.

Target detection is a core function of integrated sensing and communication (ISAC) systems. The traditional likelihood ratio test (LRT) target detection algorithm performs inadequately under low signal-to-noise ratio (SNR) conditions, and the performance of mainstream orthogonal frequency division multiplexing (OFDM) waveforms declines sharply in high-speed scenarios. To address these issues, an information-theory-based orthogonal time frequency space (OTFS)-ISAC target detection processing framework is proposed. This framework adopts the OTFS waveform as its fundamental signal. The target detection is implemented through a relative entropy test (RET) comparing echo signals against target presence/absence hypotheses. Furthermore, to enhance the system's target detection capability, the iterative OTFS-ISAC waveform design (I-OTFS-WD) method which maximizes the relative entropy is proposed. This method utilizes the minorization-maximization (MM) algorithm framework and semidefinite relaxation (SDR) technique to transform the non-convex optimization problem into an iterative convex optimization problem for resolution. The simulation results demonstrate that, under sufficient sample conditions, the RET algorithm achieves a 9.12-fold performance improvement over LRT in low-SNR scenarios; additionally, the optimized waveform reduces the sample requirements of the RET algorithm by 40%, further enhancing the target detection capability of the OTFS-ISAC system.

A Novel Flip-Filtered Orthagonal Frequency Division Multiplexing-Based Visible Light Communication System: Peak-to-Average-Power Ratio Assessment and System Performance Improvement

Filtered orthogonal frequency division multiplexing (F-OFDM), employed in visible light communication (VLC) systems, has been considered a promising technique for overcoming OFDM’s large out-of-band emissions and thus reducing bandwidth efficiency. However, due to Hermitian symmetry (HS) imposition, a challenge in VLC involves increasing power consumption and doubling inverse fast Fourier transform IFFT/FFT length. This paper introduces the non-Hermitian symmetry (NHS) Flip-F-OFDM technique to enhance bandwidth efficiency, reduce the peak–average-power ratio (PAPR), and lower system complexity. Compared to the traditional HS-based Flip-F-OFDM method, the proposed method achieves around 50% reduced system complexity and prevents the PAPR from increasing. Therefore, the proposed method offers more resource-saving and power efficiency than traditional Flip-F-OFDM. Then, the proposed scheme is assessed with HS-free Flip-OFDM, asymmetrically clipped optical (ACO)-OFDM, and direct-current bias optical (DCO)-OFDM. Concerning bandwidth efficiency, the proposed method shows better spectral efficiency than HS-free Flip-OFDM, ACO-OFDM, and DCO-OFDM.

Analysis of PAPR reduction algorithms for optical OFDM 5G radio waveform system for visible light communication

Abstract The integration of Optical Orthogonal Frequency Division Multiplexing (OFDM) with the 5G radio waveforms has lately been attracting special attention toward its possible Visible Light Communication (VLC) systems. On the other hand, however, a key challenge in the Optical OFDM is the presence of very high PAPR, degrading the overall system performance by introducing nonlinear distortions in the optical transmitter. In the present paper, different kinds of PAPR reduction algorithms specifically developed for Optical OFDM in VLC systems are developed and investigated. Analyze techniques like clipping, selective mapping (SLM), partial transmit sequence (PTS), and companding for their PAPR reduction efficiency along with the preservation of spectral efficiency and signal integrity. Based on the above aspects, various performance metrics, such as BER, computational complexity, and SNR, have been considered in order to understand each technique’s trade-off. It can be clearly seen that the hybrid and adaptive approaches achieve greater PAPR reduction without much loss of performance and are thus appropriate for future generation optical communication systems. This analysis underlines the use of optimized PAPR reduction algorithms to achieve robust and efficient systems for 5G VLC applications.

Remote Radio Frequency Sensing Based on 5G New Radio Positioning Reference Signals.

In this paper, the idea of a radar based on orthogonal frequency division multiplexing (OFDM) is applied to 5G NR Positioning Reference Signals (PRS). This study demonstrates how the estimation of the communication channel using the PRS can be applied for the identification of objects moving near the 5G NR receiver. In this context, this refers to a 5G NR base station capable of detecting a high-speed train (HST). The anatomy of a 5G NR frame as a sequence of OFDM symbols is presented, and different PRS configurations are described. It is shown that spectral analysis of time-varying channel impulse response weights, estimated with the help of PRS pilots, can be used for the detection of transmitted signal reflections from moving vehicles and the calculation of their time and frequency/Doppler shifts. Different PRS configurations with varying time and frequency reference signal densities are tested in simulations. The peak-to-noise-floor ratio (PNFR) of the calculated radar range-velocity maps (RVM) is used for quantitative comparison of PRS-based radar scenarios. Additionally, different echo signal strengths are simulated while also checking various observation window lengths (FFT lengths). This study proves the practicality of using PRS pilots in remote sensing; however, it shows that the most dense configurations do not provide notable improvements, while also demanding considerably more resources.

Modeling of Data Transmission in Polymer Optical Fibers Using DMT and Machine Learning Techniques

ABSTRACTIn local networks and other short links, polymeric optical fiber may be used due to its mechanical properties; however, some undesired and strong effects appear in these environments. This work proposes three different models to fine‐tune the electrical parameters of discrete multi‐tone (DMT) modulation to predict the signal‐to‐noise rate (SNR) over each subcarrier used with a 560 nm central wavelength. Considering the present setup, the devised models achieve some bold results, demonstrating the possibility of explaining more than 99% of the experimental data, in the best scenario. Several models are mathematically fit to obtain distinct adjustments for the nonlinearity present in the link considering the electrical parameters.

Characterization of A2G UAV communication channels under rician fading conditions

The variation in the k-factor value significantly influences the performance of unmanned aerial vehicle (UAV) air-to-ground point-to-point line of sight (A2G PTP LOS) communications over a Rician channel at 1,800 MHz using quadrature phase shift keying (QPSK) modulation and orthogonal frequency division multiplexing (OFDM) techniques. The research emphasizes the impact of the k-factor, which quantifies the dominance of the line-of-sight component over multipath scattering. The variation in the k-factor significantly influences UAV A2G PTP LOS communication performance for the empirical model (EM), as it involves precise measurements of the received power level in dBm from UAV to ground control station (GCS) across varying distances and altitudes. We introduce a method to compute the k-factor by assessing the ratio of the line-of-sight signal power to the multipath signal power, thereby enhancing channel modeling accuracy. Empirical analysis shows a strong correlation between bit error rate (BER) and signal-to-noise ratio (SNR) with differing k-factor values; a higher k-factor of 16.3 markedly improves performance, virtually eliminating errors at a 10 dB SNR, while a lower k-factor of 2.39 still shows significant errors at a 30 dB SNR. These results highlight the necessity of optimizing the k-factor in UAV A2G PTP LOS systems to ensure stable and reliable communication under diverse operational conditions.

Agile Detection of DRM Signal via GLRT

AbstractDigital Radio Mondiale (DRM) is a digital Orthogonal Frequency Division Multiplexing (OFDM) broadcasting standard that has been employed all over the world. The operating carrier frequency and time of DRM station change with the scheduling period. The user terminal commonly uses channel decoding and audio decoding to detect the DRM radio. This conventional signal detection method always fail when the station is not working, or the signal‐to‐noise ratio (SNR) is weak, or the designated frequency band is illegally occupied. Besides, the conventional method needs at least one DRM transmission super frame with a duration of 1.2 s, which causes delay and brings additional computations. To solve the challenges faced by conventional method, this paper has proposed an agile and efficient signal detection method based on the Generalized Likelihood Ratio Test. The proposed method coherently integrates the frequency pilots of successive OFDM symbols via discrete Fourier transform, then propose a sufficient statistic to detect the DRM radio. The required number of OFDM symbols, which is much smaller than that of one transmission super frame, is adaptively chosen from the given probabilities of false alarm and correct detection. The computations and SNR requirement of the proposed method are both smaller than the conventional method, which help the user terminal quickly detect the DRM signal over the given frequency band. The proposed method also provides a new perspective for electromagnetic spectrum management.

A few more optimal optical orthogonal codes with non-constant auto-correlation function

A few more optimal optical orthogonal codes with non-constant auto-correlation function

PAPR Reduction Techniques in MIMO-OFDM Systems Using PSO and Advanced Modulation Schemes for Next-Generation Wireless Networks

The increasing need for rapid communication led to the development of two multicarrier regulating systems: Code Division Multiple Access (CDMA) and Orthogonal Frequency Division Multiplexing (OFDM). The OFDM is a type of frequency division multiplexing (FDM) plot used in complex multi carrier regulation. To transport information, many evenly spaced orthogonal sub-carriers are used. The data is split up into several equal bursts of streams for every sub-carrier. At a low image rate, each sub-carrier is adjusted using a traditional tweak plot (like QPSK) to maintain complete information rates that are comparable to traditional single carrier regulation methods at a similar capacity for transmission.

Transmission system with adaptive LDPC-Coded OFDM modulation implemented in GNU Radio

Real-time testing in wireless channel conditions of Forward Error Correction (FEC) coding techniques, Modulation and Coding Scheme (MCS) selection algorithms is a complex and challenging task. GNU Radio and Software Defined Radio (SDR) concept allow a wide range of practical and low-cost solutions to perform the testing operations mentioned above. The paper proposes a duplex transmission system with adaptive LDPC (Low Density Parity Check) coding and OFDM (Orthogonal Frequency Division Multiplexing) modulation implemented in GNU Radio. The frame structure, design principles, system architecture, and mechanisms controlling the transmission process are presented. The system’s modular architecture provides the framework for testing various LDPC coding and MCS selection techniques. The system’s design allows us to maximize the transmission’s efficiency, the encapsulation of various data structures, i.e., frame and transport block, using reduced overheads and the necessity of padding operations is minimized.

Optimized Bayesian Matching Pursuit for Joint Channel Estimation and Impulse Noise Mitigation

Orthogonal frequency division multiplexing (OFDM) is adopted in most wireless communication systems, and the performance of OFDM is affected by impulse noise (IN). Better channel estimation (CE) performance is required to detect the channel information on the receiving side. The OFDM system is considered with the number of subcarriers carrying the data and pilot symbols. In the OFDM modulator, the symbols of the frequency domain are transformed into the signals of the time domain using inverse discrete Fourier transformation (IDFT). Effective impulsive noise mitigation is crucial for improving the effectiveness of OFDM communication systems, and it improves the signal-to-noise ratio (SNR) at the receiver. A cyclic prefix is then appended before transmission through the channel. In the receiver noise, the effect of IN is mitigated jointly with CE using the Bayesian matching pursuit (BMP) and Moth-flame algorithm (MFA). In this approach, the IN and channel information is considered as a sparse vector. Here, the data symbols used are considered an unknown parameter. The approach incorporating all subcarriers has a lower mean square error (MSE) of IN estimate for impulsive noise reduction. The MFA algorithm is used to optimize the sensor matrix in BMP. The sparsity of the channel and the impulse response are observed in the time domain to represent the channel and IN together. It exactly recovers the sparse signal for finding the convex objectives of the sparse minimizer, and the sparse solution is obtained with fixed point updates. The proposed BMP algorithm improves the CE by explicitly considering the existence of IN. The BMP is a greedy algorithm that selects the most correlated residuals at each column. Under mutual incoherence, it recovers the signal with a higher probability. The simulated outcomes proved that the proposed CE and noise mitigation model achieved better performance based on the bit error rate (BER), throughput and MSE.

High dynamic-range dimming control for CFMO-OFDM-based VLC systems utilizing a grouped direct current scheme

Since visible light communication (VLC) uses light-emitting diode (LED) as transmitters, it has dual functions of illumination and communication. To meet flexible lighting and energy-saving needs, we propose a novel, to the best of our knowledge, dimming control scheme for spectrally efficient clipping-free multilayer optical orthogonal frequency division multiplexing (CFMO-OFDM)-based VLC systems. In order to achieve high dynamic-range dimming control for LEDs, the time-domain CFMO-OFDM signals are first grouped based on frequency-domain subcarrier distribution. Then, the periodic grouped direct current (DC) signal can be flexibly chosen and added to the above CFMO-OFDM signals. Simulation results demonstrate that, compared with classical asymmetrical hybrid optical OFDM (AHO-OFDM) and DC bias-based dimming methods, the proposed scheme offers higher dimming range, better flexibility, and lower implementation complexity, as well as superior bit error rate (BER) performance.

Spectral Sampling and Signal Decomposition (SSSD) for Improved Spectral Efficiency

Spectrally Efficient Frequency Division Multiplexing (SEFDM) aims to enhance spectral efficiency by compressing subcarriers in the frequency domain, thereby reducing the required bandwidth. This approach primarily focuses on minimizing Inter-Carrier Interference (ICI), which typically necessitates a complex receiver design. We propose a simpler receiver design based on Spectral Sampling and Signal Decomposition (SSSD) technique. This technique facilitates the receiver to process Orthogonal Frequency Division Multiplexing (OFDM) signals outside the conventional orthogonality points in the frequency domain. Unlike traditional SEFDM approaches, the SSSD receiver utilizes interfering carriers as useful signals. Through simulations, we showcase the SSSD receiver’s performance in extracting SEFDM signals and accommodating various pulse shapes beyond the conventional sinc pulse. However, our results also highlight a significant challenge posed by severely ill-conditioned matrices, which can be mitigated by exploring alternative pulse types.

Deep Reinforcement Learning Based Subcarrier Allocation With End‐To‐End Implicit CSI Acquisition in Multiuser OFDM Systems

ABSTRACTIn multiuser orthogonal frequency division multiplexing (OFDM) systems, subcarrier allocation is a key means for improving the system capacity. During subcarrier allocation process, the channel state information (CSI) plays a key role. Recently, implicit CSI is considered as a possible alternative to replace explicit CSI. But under the condition of implicit CSI, the existing subcarrier allocation algorithms using explicit CSI need to be redesigned. In this article, subcarrier allocation with implicit CSI acquisition in frequency‐division duplex (FDD) OFDM systems is investigated. To adapt to the implicit CSI, a corresponding deep reinforcement learning (DRL) based proportional fairness (PF) subcarrier allocation algorithm is proposed to maximize the long term PF utility. Simulation results show that compared with the subcarrier allocation algorithms with explicit CSI acquisition such as LS/MMSE channel estimation and individual neural network (NN) based channel estimation and feedback, the proposed scheme achieves higher system sum rate and user fairness and gets close to the traditional PF algorithm with perfect CSI, which demonstrates the effectiveness of the proposed subcarrier allocation scheme with implicit CSI acquisition.

Joint Power and Delay Optimization‐Based Resource Allocation in Mu‐MIMO‐OFDM System: Deep Convolutional Red Piranha Pyramid‐Dilated Neural Network

ABSTRACTIn general, Multi‐User Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MU‐MIMO‐OFDM) enables multiple users to simultaneously communicate with a single base station using multiple antennas and OFDM modulation. Nevertheless, resource allocation challenges such as power management and delay optimization arise within MU‐MIMO‐OFDM systems, requiring sophisticated solutions to ensure efficient use of resources and optimal system performance. Thus, joint power and delay optimization‐based resource allocation using a Deep Convolutional Pyramid‐Dilated Neural Network (DCPDNN) with Red piranha optimization and Optimal Delay Scheduling conflict graphs Algorithm (DCPDNN‐RPO‐ODSCGA) in MU‐MIMO‐OFDM system is proposed in this presented research. The proposed mechanism is performed in two stages: power allocation and delay optimization. In the first stage, through a Deep Convolutional Pyramid‐Dilated Neural Network (DCPDNN), which aims to maximize throughput, the network resources are distributed to user equipment (UEs) based on power and transmission rate. To reduce the loss function, Red Piranha Optimization (RPO) is proposed to optimize the layers of DCPDNN. In the second stage, the Optimal Delay Scheduling conflict graphs Algorithm (ODSCGA) is proposed for the optimizing delay in the MU‐MIMO‐OFDM system. The multiracial envelope procedure and service curve for traffic flows in the uplink transmission are used in the ODSCGA approach to estimate the delay‐bound value. Ideas like the maximal weight independent set and optimal conflict graph are also utilized. The simulations of DCPDNN‐RPO‐ODSCGA were conducted using MATLAB software. Thus, the proposed approach has attained higher spectral capacity, higher fairness index, and increased cumulative distribution function (CDF), 29.74%, 32.98%, and 16.46% lower loss rate, 28.05%, 24.09%, and 17.45% improved energy efficiency, 15.09%, 13.78%, and 12.05% lower processing time than other conventional approaches like MPQM‐SCA, Hyb‐BF‐DSA, and SIA‐FDBD methods, respectively.

Analysis of bit error rate and receiver sensitivity of a DC biased optical OFDM transmission link using single mode fiber with distributed Raman amplifier

Abstract In this paper, an analytical method is presented to assess the performance of bit error rate (BER) of a DC biased optical orthogonal frequency division multiplexing (DCO-OFDM) SMF transmission with distributed Raman amplifier (DRA). Formulas are developed to determine the signal-to-noise ratio (SNR) at the output of a DCO-OFDM receiver and the bit error rate (BER) for an OFDM demodulator’s output. By considering the Gaussian probability density function (pdf) for the OFDM demodulator output, the average BER is calculated numerically. The results are presented based on receiver sensitivity, bit error rate and optical SNR at a given BER of 10−9, with variations in system parameters such as input signal power, data rate, fiber distance, modulation index and OFDM sub-channel number. A comparison of BER performance indicates that DC biased optical OFDM with intensity modulation direct detection (DCO-DD-OFDM) offers better receiver sensitivity compared to optical OFDM without DC bias at a BER of 10−9. Our analytical results align with the published findings on optical OFDM.

Communication Channel Influence on Self Interference Cancellation for In-Band Full-Duplex Underwater Acoustic Systems

This paper employs a self-interference cancellation (IBFD-UWA) system for shallow-water acoustic channels by depending on the model of communication channel for SI cancellation, which is based on geometry to accommodate any possible changes in the underwater environment. UWA channels have propagation characteristics based on the configurations of straight and multi-direction mirrors between a transmitter and a receiver. This propagation at the node itself and between the two nodes to transfer information between the nodes operating in the IBFD mode, orthogonal frequency division multiplex (OFDM) modulation with quadrature phase-shift keying (QPSK) mapping. By using numerical simulations, it can be shown that the developed model is able to accurately describe the underwater acoustic environment. The results indicate that local multipath propagation delays can exceed 1.4s with transmission losses of up to 80dB, and the SIC requires about 4 seconds to reduce SI signals to background noise levels successfully.

Multimedia Transmission Technique for Smart Ambulance with multi-carrier OFDM in a V2V and V2I Channel model using Software Defined Radio Technology

This research explores the implementation of a cutting-edge Software Defined Radio (SDR) framework to transmit multimedia files that can be assumed to be medical data in smart ambulances. The system utilizes multi-carrier Orthogonal Frequency-Division Multiplexing (OFDM) across V2V and V2I channels. The research is based on the notion that adaptive real-time communication is essential for the uninterrupted supply of key patient data to medical facilities and vehicles in transit, in order to address the problems posed by high mobility and dynamic environmental conditions. A comprehensive SDR system has been constructed and assessed in comparison to conventional communication mechanisms, demonstrating notable advancements in data accuracy and uninterrupted transmission. Our system successfully established stable connections in V2I channels, even in the presence of environmental obstacles. It maintained average power levels of approximately 32.074 dBm and a Peak-to-Average Power Ratio (PAPR) of 1.037 dB. These results indicate a constant signal envelope that promotes optimal signal transmission with excellent fidelity. In V2V scenarios, we successfully maintained data integrity with a low Peak-to-Average Power Ratio (PAPR) of 3.316 dB, even while vehicles were moving at a speed of 20 km/h. Additionally, we secured a high likelihood (94.5%) that the signal power remained close to the average, showing the robustness of our system against Doppler effects and signal dispersion. Text transmissions experienced errors when subjected to a Doppler shift of 20 km/h, which impacted the decoding of the received text. Similarly, image transmissions revealed limitations in bandwidth, as a transmitted image of 3640 KB was received with a degraded 4 KB. This emphasizes the importance of implementing effective error handling and recovery mechanisms. The results illustrate the efficacy of the suggested system in maintaining a high Quality of Service (QoS), offering proof of the effectiveness of contemporary wireless communication technologies in improving emergency medical services and setting new standards in smart ambulance capabilities.

Nearly collimated 940-nm Buried-Photonic-Crystal Surface-Emitting Laser for Lens-free Discrete Multitone Transmission at 22-Gbit/s over 20 meters

Nearly collimated 940-nm Buried-Photonic-Crystal Surface-Emitting Laser for Lens-free Discrete Multitone Transmission at 22-Gbit/s over 20 meters

Decoding of polar-coded OFDM systems over multipath fading channels with interleaving and channel state information

In this paper, we investigate the decoding performance and corresponding decoding strategies for polar-coded orthogonal frequency division multiplexing (OFDM) system operating under multipath fading channels. Multipath fading channels lead to frequency selective fading of the OFDM signal, resulting in varying levels of noise interference across different subcarriers after equalization. Furthermore, frequency selective fading induces burst errors in the equalized information, thereby significantly degrading the decoding performance. To address these issues, we propose two schemes in this paper to enhance the decoding performance of polar-coded OFDM system. Firstly, we integrate the channel state information of each subcarrier into the generation of soft information for the polar codes decoder, in order to alleviate the degradation of decoding performance caused by variations in signal-to-noise ratio across subcarriers during OFDM demodulation. Secondly, we introduce a packet interleaving design after the polar codes encoder to enhance the robustness of polar codes against burst errors. Simulation results demonstrate that the combined application of these two decoding strategies significantly outperforms the conventional scheme in terms of transmission performance over multipath fading channels. The findings of this study suggest that, within the context of future wireless communication systems utilizing Polar-OFDM, the concurrent implementation of our two proposed decoding strategies is essential for achieving robust error correction performance in the OFDM system.