Orthogonal Frequency Division Multiplexing Symbol Research Articles

Zadoff–Chu Sequence Pilot for Time and Frequency Synchronization in UWA OFDM System

In underwater communications for 6G, Doppler effects cause the coherent time to become similar to or shorter than the orthogonal frequency division multiplexing (OFDM) symbol length. Conventional time and frequency synchronization methods require additional training symbols for synchronization, which reduces the traffic data rate. This paper proposes the Zadoff–Chu sequence (ZCS) pilot-based OFDM for time and frequency synchronization. The proposed method transmits ZCS as a pilot for OFDM symbols and simultaneously transmits traffic data to increase the traffic data rate while estimating the CFO at each coherence time. For time–frequency synchronization, the correlation of the ZCS pilot is used to perform coarse and fine time and frequency synchronization in two stages. Since the traffic data cause interference with the correlation of ZCS pilots, we theoretically analyzed the relationship between the amount of traffic data and interference and verified it through computer simulations. The synchronization and BER performance of the proposed ZCS pilot-based OFDM were evaluated by conduction computer simulations and a practical ocean experiment. Compared to the methods of Ren, Yang, and Avrashi, the proposed method demonstrated a 6.3% to 14.3% increase in traffic data rate with similar BER performance and a 2 dB to 3.8 dB SNR gain for a 14.3% to 23.8% decrease in traffic data rate.

Non-pilot based carrier frequency offset estimation and reflection coefficient optimization for RIS-assisted OFDM systems

Carrier frequency synchronization between the transmitter and receiver is challenging due to oscillator inaccuracies and Doppler shifts, which lead to inter-carrier interference. To address this synchronization error, i.e., carrier frequency offset (CFO), we introduce a novel method for estimating the CFO in reconfigurable intelligent surfaces (RIS)-assisted orthogonal frequency division multiplexing (OFDM) systems. Additionally, we present a method to optimize reflection coefficients, as adjusting the reflection coefficient of RIS can effectively manipulate signal propagation and amplitude, thereby enhancing system performance. In the proposed method, a randomized set of reflection coefficients is applied for the first OFDM symbol, and CFO is estimated using the oversampling method within that symbol over the Rayleigh fading environment. A deterministic approach is adopted to reduce grid search complexity. Simulation results demonstrate the superior performance of the proposed CFO estimation method, particularly in high signal-to-noise ratio scenarios, compared to the existing Zadoff Chu sequence-based estimator in terms of mean square error (MSE). Subsequently, the CFO is compensated in the second OFDM symbol using the estimated CFO, and the reflection coefficient is optimized by identifying the channel tap associated with the maximum channel impulse gain technique. The optimized reflection coefficient enhances system performance in terms of bit error rate (BER) for RIS-assisted OFDM systems.

Time-Varying Channel Estimation Based on Distributed Compressed Sensing for OFDM Systems.

For orthogonal frequency division multiplexing (OFDM) systems in high-mobility scenarios, the estimation of time-varying multipath channels not only has a large error, which affects system performance, but also requires plenty of pilots, resulting in low spectral efficiency. To address these issues, we propose a time-varying multipath channel estimation method based on distributed compressed sensing and a multi-symbol complex exponential basis expansion model (MS-CE-BEM) by exploiting the temporal correlation and the joint delay sparsity of wideband wireless channels within the duration of multiple OFDM symbols. Furthermore, in the proposed method, a sparse pilot pattern with the self-cancellation of pilot intercarrier interference (ICI) is adopted to reduce the input parameter error of the MS-CE-BEM, and a symmetrical extension technique is introduced to reduce the modeling error. Simulation results show that, compared with existing methods, this proposed method has superior performances in channel estimation and spectrum utilization for sparse time-varying channels.

Non pilot data-aided carrier and sampling frequency offsets estimation in fast time-varying channel

This paper considers the non pilot data-aided estimation of the carrier frequency offset (CFO) and sample frequency offset (SFO) of orthogonal frequency division multiplexing (OFDM) signals in fast time-varying channel. The main obstacle is the time-variant channel response, which deteriorates the estimation validity. A practical approach to mitigate this impact is to reduce the time consumption of one-shot estimation. In this way, we propose a method to reduce the time consumption to within one OFDM symbol duration. The maximum likelihood (ML) estimator is derived based on the observations of frequency domain constellations output of two FFTs on one symbol; its closed-form approximation is then derived to reduce the calculation burden. Remarkably, our method does not require any training symbol or pilot tone embedded in the signal spectrum, therefore achieves the highest spectral efficiency. Theoretical analysis and simulation results are employed to assess the performance of proposed method in comparison with existing alternatives.

Full‐duplex capable multifunction joint radar–communication–security transceiver with pseudonoise–orthogonal frequency‐division multiplexing mixture waveform

AbstractThe authors investigate the performance of an original multifunction system with two in‐band full‐duplex capable joint radar, communications and security (JRCS) transceivers in the presence of an eavesdropper. The system concept can be generalised to a network of more than two JRCS transceivers and multiple eavesdroppers, despite the present study focusing on the three‐node scenario. By combining a bandlimited pseudonoise waveform with a data‐containing orthogonal frequency‐division multiplexing (OFDM) waveform, the authors are able to ensure a certain jamming‐to‐signal power ratio (JSR) at the eavesdropper, whilst ideal synchronisation ensures that jamming causes no deterioration to their own data transfer or radar sensing performance as it is possible to remove just the known pseudonoise waveform. To validate the system, the authors investigate through simulations the OFDM symbol error rates of all the receivers, radar target signal‐to‐interference‐plus‐noise power ratios as well as receiver operating characteristic curves, and eavesdropper's detection signal‐to‐noise power ratios through two‐branch receiver cross‐correlation. The results show that already a very low JSR of −20 dB can improve physical‐layer security without a significant increase in friendly symbol error rate or deterioration in radar performance. Additionally, other full‐duplex transceivers potentially occupying the same radio resources improve the secrecy even further.

An Integrated Orthogonal Frequency-Division Multiplexing Chirp Waveform Processing Method for Joint Radar and Communication Based on Low-Density Parity-Check Coding and Channel Estimation

With the advancement of information technology construction, the integration of radar and communication represents a crucial technological evolution. Driven by the research boom of integrated sensing and communications (ISACs), some scholars have proposed utilizing orthogonal frequency-division multiplexing (OFDM) to separately modulate radar and communication signals. However, the OFDM symbols in this paper incorporate a cyclic prefix (CP) and a virtual carrier (VC) instead of zero padding (ZP). This approach mitigates out-of-band power caused by ZP, in addition to reducing adjacent channel interference (ACI). In addition, we introduce low-density parity-check (LDPC) and use an improved normalized min-sum algorithm (NMSA) in decoding. The enhanced decoding efficiency and minimized system errors render the proposed waveform more suitable for complex environments. In terms of signal processing methods, this paper continues to use radar signals as a priori information to participate in channel estimation. Further, we consider the symbol timing offset (STO) and carrier frequency offset (CFO) issues. In order to obtain more reliable data, we use the minimum mean-square error (MMSE) estimation based on the discrete Fourier transform (DFT) to evaluate the channel. Simulation experiments verify that the system we propose not only realizes the transmission and detection functions but also improves the performance index of the integrated signal, such as the bit error rate (BER) of 7 × 10−5, the peak side lobe ratio (PSLR) of −13.81 dB, and the integrated side lobe ratio (ISLR) of −8.98 dB at a signal-to-noise ratio (SNR) of 10 dB.

Design of Intelligent City Communication Network Based on Internet of Things

Abstract In response to the advancements in Internet of Things (IoT) technology and the growing demands for data transmission, there is a crucial need for further integration of communication network technology with IoT to enhance efficiency. This paper presents the design of a multi-node communication network model utilizing the Orthogonal Frequency-Division Multiplexing (OFDM) algorithm. In the realm of physical layer parameter design, uplink, and downlink carriers are allocated based on OFDM symbols, employing the Zadoff-Chu (ZC) sequence as the pilot frequency sequence. Additionally, the Cyclic Redundancy Check (CRC) error-checking code is implemented to ensure the accuracy of network transmissions. The model proposed in this study is applied to the operational dynamics of traffic systems within a smart city, focusing on the security and operational efficiency of the traffic communication network. Empirical testing and analysis demonstrate that the communication network, as designed, is susceptible to malware attacks by 25.68%, representing the least vulnerability among the three algorithms assessed. Moreover, in examining the bus trip time distribution with the implementation of this model, the average running time is predominantly around 11.76 minutes, which is a reduction of 0.74 minutes compared to previous configurations, thereby indicating an improvement in operational efficiency.

Cluster-aware channel estimation with deep learning method in deep-water acoustic communications.

In underwater acoustic (UWA) communications, channels often exhibit a clustered-sparse structure, wherein most of the channel impulse responses are near zero, and only a small number of nonzero taps assemble to form clusters. Several algorithms have used the time-domain sparse characteristic of UWA channels to reduce the complexity of channel estimation and improve the accuracy. Employing the clustered structure to enhance channel estimation performance provides another promising research direction. In this work, a deep learning-based channel estimation method for UWA orthogonal frequency division multiplexing (OFDM) systems is proposed that leverages the clustered structure information. First, a cluster detection model based on convolutional neural networks is introduced to detect the cluster of UWA channels. This method outperforms the traditional Page test algorithm with better accuracy and robustness, particularly in low signal-to-noise ratio conditions. Based on the cluster detection model, a cluster-aware distributed compressed sensing channel estimation method is proposed, which reduces the noise-induced errors by exploiting the joint sparsity between adjacent OFDM symbols and limiting the search space of channel delay spread. Numerical simulation and sea trial results are provided to illustrate the superior performance of the proposed approach in comparison with existing sparse UWA channel estimation methods.

Orthogonal frequency division multiplexing technology based on MATLAB

The subcarriers of an orthogonal frequency division multiplexing (OFDM) system are not identical in the time domain, and their spectra also overlap. As a result, the spectrum is being used effectively. Its effective use of frequency resources and capacity to combat channel fading have made it the de facto technical standard. In wireless communication, numerous pathways in the channel can lead to interference between symbols, known as inter-symbol interference (ISI). This research supplements OFDM systems with some safeguards to eliminate inter-symbol interference. Most traditionally, OFDM symbols have had their post-event sample points duplicated to their beginnings, a process known as Cyclic prefix (CP) padding in the protection interval. In order to further counteract ISI, a protection interval might be added to the beginning of each symbol. An OFDM system's bit error rate (BER) can be decreased by using cyclic prefixes to attenuate inter-code interference. This study explains how OFDM and CP-OFDM work and compares their performance. The primary topic of this study is a contrast between OFDM and CP-OFDM concerning the performance metrics of average symbol error rate (BER) and signal spectrum diagram (PSD).

Multi-band chaotic non-orthogonal matrix-based encryption for physical-layer security enhancement in OFDM-PONs

In this paper, we propose and experimentally demonstrate a novel multi-band chaotic non-orthogonal matrix (CNOM)-based encryption scheme for secure orthogonal frequency division multiplexing (OFDM) passive optical networks. The dimension of non-orthogonality is exploited in the encryption with the CNOM, where both faster-than-Nyquist signaling and redundant precoding were employed to dynamically scramble the original number of subcarriers of each sub-band and fix the overall data rate. Both simulation and experimental results of a 10.6 Gb/s 4-QAM transmission over a 20-km standard single-mode fiber showed that the total key space significantly increases by 1.4×10482 and 1.72×10653 times, as the number of sub-bands increases from 1 to 10 and 15, with a considerable reduction in computational complexity of 90% and 93.33% in complex-valued multiplication, and 90.76% and 94.12% in complex-valued addition, when encrypting one OFDM symbol, respectively. Moreover, the improved resilience to the frequency roll-off has also been verified by using additional permutation matrices in the proposed encryption algorithm.

Digital self-interference cancellation for full-duplex systems based on deep learning

Full-duplex (FD) systems can double the spectrum efficiency by allowing users to transmit and receive signals at the same time and in the same frequency band. However, in FD systems the receiver suffers severe self-interference (SI) caused by the transmitter and eliminating the SI is challenging. In this paper, we propose a novel digital self-interference cancellation (SIC) scheme based on deep learning, which combines the power of sliding window, gated recurrent unit (GRU) network and attention mechanism (AM). The proposed scheme can accurately reconstruct the SI through two steps. It first processes the sample signals utilizing the sliding window and then extracts the dependence in preprocessed signals by applying the GRU with AM. We adopt the orthogonal frequency division multiplexing (OFDM) signal as the baseband transmitted signal to verify the proposed scheme. Extensive experiments demonstrate that the SIC capability of the developed scheme is at least 14.46 dB higher than the existing polynomial and neural network (NN) schemes. Furtherly, the effectiveness of the scheme is verified in different interference-to-noise ratio (INR), multipath channel, training sample and OFDM symbol situations.

A New OFDM System for IIR Channels

In this paper, we propose a new orthogonal frequency division multiplexing (OFDM) system for an infinite impulse response (IIR) channel with the form of B(z)/A(z) for two polynomials A(z) and B(z). Different from the conventional OFDM transmission over a finite impulse response (FIR) channel, a guard interval of an OFDM symbol is added such that the corresponding part at receiver is the cyclic prefix (CP) of the received OFDM symbol. The guard interval and CP lengths are the same and not smaller than the orders of polynomials A(z) and B(z). The OFDM symbol without the guard interval is the same as the conventional OFDM symbol without the CP. At the receiver, the IIR channel is then converted to N intersymbol interference (ISI) free subchannels, where N is the number of subcarriers of an OFDM symbol.

Single-RF MIMO-OFDM Using ESPAR

A novel beamspace multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) transmission system using a single-radio-frequency (RF) electronically steerable parasitic array radiator (ESPAR) is described. It makes use of recent results for decomposing the patterns of any arbitrary ESPAR onto an orthogonal basis set using the Theory of Characteristic Modes (TCM). Leveraging this decomposition, OFDM symbols can be mapped into the beamspace domain so that the ESPAR can be used to transmit multiple streams of OFDM symbols using a single RF chain. In the proposed approach, we use the Linde-Buzo-Gray (LBG) algorithm to quantize the OFDM symbol vectors and form a codebook. A binary search tree is then utilized to efficiently find the reactive loads of ESPAR to excite the radiation patterns corresponding to the quantized symbols. It is shown by simulation that quantized codewords and the corresponding radiation patterns can be excited using ESPAR. In addition, the simulated bit error rate (BER) results of the proposed approach are shown to be close to that of conventional MIMO-OFDM systems, demonstrating the effectiveness of implementing a single-RF MIMO-OFDM transmitter.

Radar Sensor and Data Communication System Based on OFDM Without Cyclic Prefix

The high data rate and large bandwidth of orthogonal frequency division multiplexing(OFDM) modulations have made the integrated waveform design using OFDM-based signals a popular research topic in recent years. However, OFDM signals are sensitive to the Doppler frequency bias and multipath effects, which are traditionally accommodated by cyclic prefixes (CP) inserted before each OFDM symbol. Since the CP is the partial copy of the OFDM symbol, it not only loses energy in communication systems but also forms false targets after radar signal processing. To address the shortcomings of conventional OFDM, this paper proposes a modified CP-free OFDM joint radar communication system(JRCS). It transmits the OFDM pulse signal to certain targets and/or communication systems and receives echoes in the pulse repetition interval. By removing CP, the radar system can compress the echoes without ghost targets. Through reasonable sampling which should be designed significantly, the communication systems demodulate the OFDM pulse to extract information without intersymbol interference in multipath channels. Furthermore, the constraints of the time, frequency, and sampling on the system are analyzed in detail and an illustrating system under an air-to-ground scenario is constructed. Simulation results show that the proposed signal design and processing method has a better performance compared to conventional OFDM signals.

Highly Accurate Technique for CO-OFDM Channel Estimation Technique Using Extreme Learning Machine (ELM)

In wireless systems, channel estimation is considered a problematic technology, due to the fact of the difference in time between wireless channels and the noise effect. Orthogonal frequency-division multiplexing (OFDM) is a promising candidate for future optical communications and has received wide concern. The article proposed a Coherent Optical (CO) orthogonal frequency division multiplexing (OFDM) scheme, which gives a scalable and flexible solution for increasing the transmission rate, being extremely robust to chromatic dispersion as well as polarization mode dispersion. Nevertheless, both coherent detection and OFDM are prone to phase noise due to the phase mismatch between the laser oscillators at the transmitter and receiver sides and the relatively long OFDM symbol duration compared to that of single carrier communications. An Extreme Learning Machine (ELM) with Pilot Assisted Equalization (PEM) is proposed for compensation of impairments caused by fibre nonlinearity in coherent optical communication systems. Channel estimation using ELM and the value of distortion is sent to the OSTBC receiving end based on the distortion information the data is decoded and pilot data is removed. FFT is applied to the data and QPSK demodulation is done in the data to get its original form. In addition, the article utilized a free-space optical communication system of multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) with a modified receiver structure. Simulation reveals that the proposed model exhibits significant BER (0.0112) performance and provides better spectral efficiency as compared with conventional systems and less computational complexity. This suggested that the proposed method shows better performance by using the CO-OFDM-FSO-MIMO-ELM-based channel estimation technique for high-speed data communication networks in real-time scenarios respectively.

Bayesian Joint Channel-and-Data Estimation for Quantized OFDM Over Doubly Selective Channels

This paper investigates the design of orthogonal frequency division multiplexing (OFDM) receiver, which operates over time-frequency doubly selective (DS) channels and uses a low-resolution analog-to-digital converter (ADC) to quantize the received signal. The time-varying multipaths in DS channel and the nonlinear quantization distortion caused by low-resolution ADC, destroy the orthogonality among OFDM subcarriers, incurring severe inter-carrier interference (ICI). Therefore, joint channel-and-data estimation is preferred, since in this way one can effectively tackle the ICI and make the best of the quantized signal in each OFDM symbol. In this paper, we elaborately develop the joint estimation scheme by casting the problem into the Bayesian inference framework. The proposed scheme not only takes into account of the nonlinear quantization in a probabilistic manner, but also exploits the channel sparsity enabled by the basis expansion model (BEM) approximation to DS channels. Furthermore, to benchmark the proposed scheme, we derive the asymptotic theoretical bounds in the large-system regime. Simulation results demonstrate that the proposed scheme can achieve the performance close to the theoretical bounds, thereby verifying the effectiveness of the proposed scheme.

Efficient Convolutional Networks for Robust Automatic Modulation Classification in OFDM-Based Wireless Systems

Orthogonal frequency-division multiplexing (OFDM) is commonly deployed in Internet of Things (IoT) systems to achieve high data rates with reasonable complexity, where noncooperative protocols encode signals with different modulations for multiple users. However, conventional modulation recognition is limited to single-carrier communication systems, and there is an urgent need to design an effective method to blindly identify the unknown modulation format of received signals. In this article, we propose an automatic modulation classification method for the OFDM systems with the presence of channel deterioration. Our method first leverages a data reconstruction mechanism to arrange signals into high-dimensional data arrays and then exploits an efficient convolutional network, namely OFDMsym-Net, to learn underlying radio characteristics. OFDMsym-Net is designed by two kinds of processing modules, which manipulate one-dimensional asymmetric convolution filters to extract the intracorrelation within an OFDM symbol and the intercorrelation between different symbols. Moreover, a sophisticated structure with addition and concatenation layers is developed inside every module to improve learning efficiency. Based on simulation results achieved on a synthetic dataset of OFDM signals, our proposed method shows the classification robustness under various channel impairments. It reveals to have an overall accuracy of 95.41% at 10-dB signal-to-noise ratio, being superior to several state-of-the-art approaches.

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.

Retracted] Research on Localization Parameter Estimation and Algorithm in the Digital Television Terrestrial Broadcasting

This paper mainly studies the positioning based on time of arrival and time difference of arrival. The quantity to be obtained is mainly time. Time of arrival measurement value can be obtained directly through symbolic timing synchronization, and its effective information can be obtained at the same time. Symbolic timing synchronization in digital video broadcast‐terrestrial system can be divided into two stages: rough estimation and fine estimation. Rough estimation is based on the maximum likelihood estimation algorithm. The main purpose of rough estimation is to estimate the starting position of orthogonal frequency division multiplexing symbols, so that the starting position falls within the cyclic prefix of orthogonal frequency division multiplexing symbols. The purpose of fine estimation is to determine exactly the starting position of the orthogonal frequency division multiplexing symbol. In this paper, the symbolic timing synchronization algorithm of digital video broadcast‐terrestrial system is studied and analyzed, and simulation is carried out for different channel models. Simulation results show that the synchronization algorithm achieves the best performance in additive white Gaussian noise channel and has good estimation performance in slow fading Rayleigh channel.

Estimation of Time-Varying Channels in Virtual Angular Domain for Massive MIMO Systems

This paper is concerned with the problem of channel estimation in virtual angular domain in massive MIMO orthogonal frequency division multiplexing (OFDM) systems, in the presence of time varying channels. The proposed channel estimator is based on dichotomous coordinate decent joint sparse recovery (DCD-JSR) algorithm, which was well suited for massive MIMO systems with channels static over several OFDM symbols, but it is not accurate for time-varying channels. The estimator proposed in this paper exploits the basis expansion model (BEM) for approximation of the time-variation of the channel and the sparsity of the channel in the virtual angular domain with a common support over OFDM subcarriers and OFDM symbols for joint estimation of the BEM expansion coefficients. It is shown that, when using the Legendre polynomials as the BEM and depending on the normalized Doppler frequency, only a small number of expansion coefficients is required to provide accurate channel estimation.