Orthogonal Frequency Division Multiplexing Technique Research Articles

System architecture for a compact high range resolution frequency comb OFDM radar

AbstractWith increasing demands on resolution and flexibility in current and future radar applications, the focus is moving to digital radar systems such as orthogonal frequency-division multiplexing (OFDM) radars. To achieve high bandwidths and consequently a high range resolution, high sampling rates are needed. To overcome this constraint, an approach called frequency comb OFDM radar has been developed. This paper presents a novel, hardware efficient implementation of such a frequency comb OFDM radar including a novel way of comb generation. Special attention is put on the suppression of unwanted frequency components. Measurements which demonstrate the functionality of the hardware efficient radar system in combination with the frequency comb OFDM technique are presented.

Multiuser Massive MIMO-OFDM for Visible Light Communication Systems

Visible light communication (VLC) has emerged as a viable supplement to existing radio frequency (RF) communication systems. The limited modulation bandwidth of sources is one of the significant challenges in the multiuser (MU) VLC systems, which prohibits transmission at high data rates for each user. Since an array of LEDs is used to illuminate a room, a MU VLC system utilizing massive multiple-input multiple-output (mMIMO) orthogonal frequency-division multiplexing (OFDM) is proposed for achieving high data rates in this paper. Since the distances of the multiple transmitter-receiver links are different, their temporal delays are also different, resulting in complex channel gain and phase differences when transformed to the frequency domain in the OFDM technique. Complex channel vectors associated with different users are mutually spatially orthogonal as the number of transmitters increases. Therefore, inter-user interference (IUI) can be eliminated with simple linear signal processing, and more users can simultaneously communicate in the same time-frequency resource. In this paper, three linear precoding methods, including the maximum ratio transmission (MRT), the minimum mean square error (MMSE), and the zero-forcing (ZF), are investigated for VLC systems based on proposed MU-mMIMO-OFDM in intensity-modulation and direct-detection link. We evaluate and compare the performance of the aforementioned precoding methods in terms of the achievable spectral efficiency and total downlink optical power for different scenarios. Moreover, we derive a closed-form expression for the lower bound on the average achievable sum-rate, which we confirm the accuracy of the derived expression with the numerical simulation. The results demonstrate that the performance of the proposed method in this paper for all precoder techniques, i.e., ZF, MMSE, and MRT, is better than the previous works since the complex channel in the frequency domain is used in this paper. Furthermore, the ZF and MMSE methods are better than MRT when the ratio of the number of LEDs to the number of users is large. At the same time, when this ratio is relatively small, the MRT precoding technique outperforms the ZF and MMSE techniques.

Evaluation of a high-speed hybrid OAM-OFDM-MDM multiplexed coherent FSO system under desert conditions

To meet the needs of future wireless optical networks, this paper introduces a high-speed, hybrid multiplexed, coherent free-space optical (FSO) communication system that integrates an orbital angular momentum (OAM) multiplexed signal with an orthogonal frequency division multiplexing (OFDM) technique. Two independent QAM polarized beams, each carrying in-phase and quadrature (I/Q) phase 16-QAM-OFDM modulated data, are combined using mode division multiplexing (MDM) to increase the capacity of the proposed system. The reason of choosing OFDM is its capability to support higher data rate, and mitigating intersymbol interference (ISI). The signal is detected using a coherent detection-based digital signal processing (DSP) algorithm at the receiver end. The proposed hybrid FSO system is evaluated in low and heavy dust environments using bit error rate (BER), link distance, optical signal-to-noise ratio (OSNR), and received optical power performance matrices. The simulation results demonstrate the successful transmission of a 120 Gb/s single carrier over the longest link ranges of 1.5 and 0.40 km, respectively, under low and heavy dust weather environments below the signal degradation threshold value (forward error correction (FEC) limit) of BER 2.2 × 10–3 in strong turbulent conditions.

PSO-DBNet for Peak-to-Average Power Ratio Reduction Using Deep Belief Network

Data transmission through a wireless network has faced various signal problems in the past decades. The orthogonal frequency division multiplexing (OFDM) technique is widely accepted in multiple data transfer patterns at various frequency bands. A recent wireless communication network uses OFDM in long-term evolution (LTE) and 5G, among others. The main problem faced by 5G wireless OFDM is distortion of transmission signals in the network. This transmission loss is called peak-to-average power ratio (PAPR). This wireless signal distortion can be reduced using various techniques. This study uses machine learning-based algorithm to solve the problem of PAPR in 5G wireless communication. Partial transmit sequence (PTS) helps in the fast transfer of data in wireless LTE. PTS is merged with deep belief neural network (DBNet) for the efficient processing of signals in wireless 5G networks. Result indicates that the proposed system outperforms other existing techniques. Therefore, PAPR reduction in OFDM by DBNet is optimized with the help of an evolutionary algorithm called particle swarm optimization. Hence, the specified design supports in improving the proposed PAPR reduction architecture.

Hybrid Deep Learning-Based Adaptive Multiple Access Schemes Underwater Wireless Networks

Achieving sound communication systems in Under Water Acoustic (UWA) environment remains challenging for researchers. The communication scheme is complex since these acoustic channels exhibit uneven characteristics such as long propagation delay and irregular Doppler shifts. The development of machine and deep learning algorithms has reduced the burden of achieving reliable and good communication schemes in the underwater acoustic environment. This paper proposes a novel intelligent selection method between the different modulation schemes such as Code Division Multiple Access(CDMA), Time Division Multiple Access(TDMA), and Orthogonal Frequency Division Multiplexing(OFDM) techniques using the hybrid combination of the convolutional neural networks(CNN) and ensemble single feedforward layers(SFL). The convolutional neural networks are used for channel feature extraction, and boosted ensembled feedforward layers are used for modulation selection based on the CNN outputs. The extensive experimentation is carried out and compared with other hybrid learning models and conventional methods. Simulation results demonstrate that the performance of the proposed hybrid learning model has achieved nearly 98% accuracy and a 30% increase in BER performance which outperformed the other learning models in achieving the communication schemes under dynamic underwater environments.

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.

A New Adaptive OMP-MAP Algorithm-based Iterative Sparse Channel Estimation for OFDM Underwater Communication

A sparse channel estimation approach based on doubly spread underwater acoustic (UWA) channels is widely used todetect coherent acoustic orthogonal frequency division multiplexing (OFDM) signals. A new time-domain channelestimation (CE) technique for OFDM based UWA communication with Rician fading is used to exploit the channel sparsity.First, to improve the estimation accuracy in high noise conditions, we have exploited the channel sparsity to generate aclosed-form equation for the termination condition. Then, in low-level noise instances, the additional criterion to balanceestimation accuracy and computing costs has been established. By incorporating these two requirements within theorthogonal-matching-pursuit (OMP) structure, an adaptive-OMP (AOMP) algorithm has been proposed. The AOMP andmaximum a posteriori probability (MAP) techniques are combined to provide a computationally efficient, and a newAOMP-MAP scheme for estimating the sparse complex channel path gain has been proposed. Further, The minimumvariance unbiased estimator is used to improve the proposed CE technique. Exploiting the experimental channel data,computer simulations reveal that the proposed CE technique obtains the outstanding outcomes.

The channel WDM system incorporates of Optical Wireless Communication (OWC) hybrid MDM-PDM for higher capacity (LEO-GEO) inter satellite link

The rising demand for exponential growth in data rate and effectiveness of satellite communication systems has drawn the attention of several researchers recently. The Inter Satellite OWC (Is-OWC) technology, which combines Optical Wireless Communication (OWC) and Inter Satellite Link (ISL), is critical for achieving high data rate transport around the world. The challenge in ISL's transmission range is limited for a variety of reasons, including the appropriate modulation format, pointing error, and space turbulence. As a result, this paper designs and implements a high-capacity 8-channel Wavelength Division Multiplexing (WDM) system that uses the Orthogonal Frequency Division Multiplexing (OFDM) technique to support high data rates by implementing multiple low-data rate subcarriers and achieves high tolerance to dispersion and Inter Symbol Interference (ISI). Additionally, by using a hybrid scheme for Mode Division Multiplexing (MDM) and Polarization Division Multiplexing (PDM) for cost-effectiveness requirements and transmit eight independent channels over a 48,000 km Is-OWC link. Each channel is capable of carrying 320 Gbps of data rate, and by using the novel hybrid MDM-PDM scheme, the data rate for each channel is raised to 640 Gbps. The simulation analysis achieved a maximum data rate of 5.12 Tbps using the 8-channel Is-OWC WDM OFDM. The maximum distance achieved was 48,000 km at a log BER of − 3.1101 and the average received power of − 70.14 dBm. The proposed system shall prop the transfer of high data rates and meet the requirements for reliable satellite connectivity links.

Design and development of coherent-OOFDM techniques in wavelength division multiplexing optical network for long-haul communication

Abstract Today, communication is a crucial factor and requires a high data rate for transmission with in an error-free environment, so optical communication has emerged as a best solution to high-speed transmission systems due to its higher bandwidth and higher data rates. Fiber optic transmission integrating with some modern processing and modulator techniques are applied in various areas that need transfer of data from one point to another through reducing an optical affect. Coherent optical orthogonal frequency division multiplexing is a popular technique in optical communication today because of the excessive spectral efficiency, immune to interference, tolerance of the fiber dispersion and it is long-haul application. It employs the OFDM modulation method, which is a type of multicarrier modulation in which data statistics are distributed over a large number of low-cost subcarriers and is a solution to inter-symbol interference. Inter-symbol interference is generated by chromatic dispersion in high-speed optical transmission systems, and it is a severe issue in long-haul systems in the case of higher data rates transmission. The use of standard dispersion compensating devices, such as dispersion compensating fiber, does not completely compensate for high order dispersion, which includes third-order and high dispersion effects and also increase the loses of the system because it is a fiber in itself. This study proposes introducing the concept of coherent optical orthogonal frequency division multiplexing techniques in to the wave division optical network in the case of multiple users, high data rate transmission and long-haul and ultra-long-haul optical link to reduce the optical transmission on related issues and to improve the performance of optical network. The performance of the proposed network can be evaluated by using different parameters such as signal to noise ratio, bit error rate, optical signal to noise ratio, Quality factor and eye-diagram at different distance transmission up to 8000 km by using Optisystem software.

Multicarrier technique for 5G massive MIMO system based on CDMA and CMFB

Filterbank multicarrier (FBMC) is an effective method for modulation over massive multiple-input multiple-output (MIMO) channels in the future fifth generation wireless networks. This multicarrier technique provides high spectral efficiency, and it is resilient against synchronization errors compared to the well-known orthogonal frequency division multiplexing technique. This paper introduces a new technique, that combines the Code-division multiple-access (CDMA) and cosine modulated filter banks, a specific class of FBMC, to massive MIMO communication systems. In the proposed technique, the data symbols are transmitted on different sub-bands and also, they are spread in each sub-band by CDMA code. The proposed technique reduces the interference between data symbols, which consequently improves bit-error-rate (BER) performance. Simulation results show that the overall BER performance of the proposed multicarrier transmission technique is significantly enhanced. The results obtained show that as the number of base station antennas increases, different channel distortions are averaged out, thus BER decreases (in average by 10–2) for the same signal-to-noise ratio.

Multiuser neural network detectors for large scale MIMO OFDM over Rayleigh Winner‐II channel

Large scale (LS) MIMO orthogonal frequency division multiplexing (OFDM) technique satisfies the demands on performance and the service quality preferred in wireless communication system. Since numerous antenna terminals have been incorporated in the base station, multiuser detection is crucial for retrieving the data appropriately. Thus, the complexities of the detectors increase rapidly in large scale MIMO OFDM schemes. A unique neural network detection approach for multiuser detection in LS MIMO OFDM model is presented. The performance of multilayer perceptron (MLPNN) and radial basis (RBNN) detectors with minimum mean square (MMSE) MUDs are analyzed. The neural network multiuser detecting methodologies are also analyzed by the loss function in LS MIMO OFDM systems. The performance analyses of the detectors are also done by analyzing the radiation patterns of the antennas which is equipped at the both ends of the uplink channels. Radial basis MUDs have 23 dB bit error rate which gains over linear MMSE detector and of 14 dB than multilayer perceptron detectors specifically at 10(−5) bit error rate. According to the bit error rate analysis of estimations at the output of the multiuser detector, the suggested neural network models are more effective in reducing multiuser interference in MU LS MIMO OFDM. Analysis also verifies, radial basis function (RBF) multiuser detector are exhibiting an optimal BER performance than multilayer perceptron detector with sufficient number of hidden neurons. This study thus emphasis a RBF MUD scheme for detecting multiuser signals in LS MIMO OFDM system due to its dynamic performance in low probability of bit error.

Routing, modulation and spectrum allocation of dynamic anycast based on ant colony optimization in elastic optical networks

Elastic optical networks (EONs) using optical orthogonal frequency division multiplexing (O-OFDM) technique are considered to be promising optical networks due to their ability to achieve flexible spectrum management. This paper studies dynamic anycast in EONs. The rapid growth of service demand has brought enormous challenges to the network environment, resulting in the increase of blocking rate. In order to reduce the traffic blocking rate, we propose a spectrum-aware ant colony optimization (SA−ACO) algorithm to optimize the anycast transmission problem in EONs and improve the spectrum utilization in the network. Different from the traditional anycast allocation algorithm, the proposed SA−ACO algorithm can adapt to the real-time changes of the system. We add bandwidth factor into the node pseudo-random selection rule, and add a weight factor to weigh the impact of bandwidth on the system. In the found candidate path set, the link distance and link spectrum availability are processed to find the optimal path suitable for the current service transmission. In terms of pheromone update, we delay the secretion of ant pheromone, and secrete pheromone on the path where the relatively optimal solution is located in the solution space found by the ant colony. Through extensive simulation experiments, we evaluate the performance of the algorithm. By comparing with the reference algorithms in previous literature, our proposed algorithm significantly outperforms other methods in reducing bandwidth blocking probability performance.

PAPR Reduction of OFDM with DFT Spreading Method

Future communication systems will demand the transmission of huge amounts of data, therefore will require a highly linear power amplifier. The Orthogonal Frequency Division Multiplexing (OFDM) technique is widely used in multimedia services for providing high data rates and providing high Quality of Service. The transmitter power amplifier's range of operation in a communication system is linear. Signal distortion happens when the input signal's amplitude exceeds the linear range of the transmitter power amplifier. Therefore, the transmitter's input signal has to have a low peak to average power ratio (PAPR). The OFDM system has been recognized as the high rate wireless radio channel transmission. Therefore, it will also be highly beneficial for the high-speed communication system. However, due to the extremely high PAPR issue, using the OFDM system in a communication system is not simple. It results in extremely low power efficiency. Therefore, it is crucial to lower the PAPR in the OFDM system in order to employ it in the communication system. By using a discrete Fourier matrix, the Discrete Fourier Transform spreading strategy may significantly lower the PAPR of an OFDM signal. This paper describes the PAPR reduction approach in OFDM signals and examines the effectiveness of OFDM.

Integrated Radar and Communications Waveform Design Based on Multi-Symbol OFDM

Integrated radar and communications (IRC) technology has become very important for civil and military applications in recent years, and IRC waveform design is a major challenge for IRC development. In this paper, we focus on the IRC waveform design based on the multi-symbol orthogonal frequency division multiplexing (OFDM) technique. In view of the defects resulting from high peak-to-mean envelope power ratios (PMEPRs) and high range sidelobes in IRC systems, an intelligent and effective IRC waveform design method jointly optimized with the PMEPR and peak-to-sidelobe ratio (PSLR) is proposed. Firstly, a flexible tone reservation (TR)-based IRC waveform structure is applied in both temporal and frequency domains, i.e., multi-symbol OFDM waveform. Secondly, the optimization problem considering PMEPR and PSLR and extending them to the Lp-norm form is reformulated. Then, the conjugate gradient of the objective function is analytically derived and the conjugate gradient algorithm (CGA) is presented to simultaneously improve the PMEPR and PSLR. Finally, the simulation results show that the proposed algorithm can efficiently generate IRC waveforms with an excellent PMEPR, PSLR, radar signal-to-noise ratio (SNR), and bit error rate (BER) performance.

Design of an adaptive CRSN using OFDM

Cognitive Radio (CR) is a novel concept that enables wireless devices to detect and adapt to their surroundings in order to enhance communication quality. The cognitive radio sensor network (CRSN) has proved to be a cost-effective solution for the spectrum constraints in wireless sensor networks (WSN). Optimizing the optimum packet size is regarded to be an essential energy constrained issue to address the practical implementation of CRSN out of all the difficulties. Small packets generate data traffic in device-to-device communication, while big packets may cause data bit corruption, requiring retransmission at a greater frequency. This will not allow access from the secondary network to the main network, since it may cause further disturbance. To maximise the WSN's energy efficiency, the optimum packet size for CRSN should be maintained while keeping the same degree of interference as the primary licenced users. The purpose of this article is to examine formulations for small, medium, and large packet sizes in order to determine the optimum packet size for adaptive CRSN. To do so, CR requires a flexible physical layer capable of carrying out the necessary tasks. This article examines the performance of CR systems that use the Orthogonal Frequency Division Multiplexing technique, which is a possible transmission technology for CR. Interference and delays are minimised and the channels are ultimately utilised effectively through Scheduling MAC protocol. This article gives the design steps to adjust the network design to get the better performance. For achieving the greatest performance on the Cognitive Radio Sensor Network (CRSN). The Jellyfish Search Optimization algorithm and the hybrid Momentum Search Algorithm are hybridized and results are achieved. This makes it possible to calculate precise packet sizes. The suggested approach decision outperforms existing methods like the Group Sparse Optimization algorithm and the Throughput Maximization Algorithm. The MATLAB/SIMULINK Platform were used to get the results.

Robust hybrid beamforming in full-duplex broadband mmWave relay systems

In this paper, the robust hybrid beamforming scheme in full-duplex (FD) millimeter-wave (mmWave) relay systems is designed under imperfect channel estimates. The inherent characteristic of mmWave signals, i.e., the large available bandwidth, is considered in the design, and the orthogonal frequency division multiplexing (OFDM) technique is utilized to overcome the multipath fading. A self-interference cancellation module is inserted at the relay to attenuate the self-interference, which is the main challenge of the FD mode. A decomposition algorithm for mmWave OFDM relay systems is proposed to obtain the hybrid processors with analog-digital-analog structures and closed-form least-squared-based solutions. Numerical results show that the proposed design provides significant improvements by comparing with existing designs.

Fast joint estimation for time delay and angle of arrival based on smooth preprocessing with orthogonal frequency division multiplexing

In order to solve the problems of high complexity and absence of adaptability with the joint estimation for time delay (TD) and angle of arrival (AOA) in coherent multipath environments, a fast estimation algorithm based on orthogonal frequency division multiplexing (OFDM) technique is proposed. First, we combine OFDM signal characteristics with array features to obtain extended arrays. Then, we obtain the channel frequency domain response covariance matrices for TD and AOA estimation separately by smoothing preprocessing in the spatial and frequency domains, respectively. Finally, we estimate the TD values by a one-dimensional (1-D) spectral peak search, as well as determine the closed-form solution for AOA by Unitary-ESPRIT. In comparison with previous work, the proposed algorithm not only improves the adaptability in correlated or mixed multipath environments but also significantly reduces the complexity. The simulation results show the effectiveness and robustness of the proposed joint estimation algorithm.

MIMO-OFDM channel estimation based on minimum error entropy criterion under non-Gaussian environment

ABSTRACT Using the orthogonal frequency division multiplexing (OFDM) technique, a multiple-input multiple-output (MIMO) system can provide high spectral efficiency and high data transmission over a fading channel. To achieve the best performance in a MIMO-OFDM system, high accuracy in channel estimation is a very important factor which leads to appropriate receiver design. Therefore, in the most channel estimation algorithms, the mean square error (MSE) is the main criterion for noise minimisation which is robust in the case of Gaussian noise. However, in telecommunication systems which do not have noise with Gaussian distribution, the MSE criterion is not appropriate. So as to tackle this problem, a robust adaptive filtering algorithm was proposed using minimum error entropy (MEE) criterion and improved least square (ILS) approach which by far is better than MMSE criterion to robust channel estimation. In this work, impulsive noise is used for non-Gaussian environment simulation. Furthermore, MEE is employed to attenuate the impulsive noise, and ILS is adopted to reduce LS estimation variance. Compared to the MSE-based algorithms, simulation results indicate that the proposed method outperforms the channel estimation in a non-Gaussian environment.

Throughput improvement and PAPR reduction for OFDM-based VLC systems using an integrated STC-IMADJS technique

Visible light communication (VLC) is a technology that is currently being employed to achieve high data rates. Orthogonal frequency division multiplexing (OFDM) is a powerful scheme for intensity modulation and direct detection (IM-DD) that is becoming increasingly important. OFDM systems based on VLC are accomplished through the implementation of IM-DD constraints, including direct current biased optical OFDM (DCO-OFDM), asymmetrically clipped optical OFDM (ACO-OFDM), and asymmetrically clipped DC-biased (ADO-OFDM), among others. The OFDM technique based on VLC is inefficient in terms of spectral efficiency and has a high peak to average power ratio (PAPR). In this article, the symbol time compression-image adjust (STC-IMADJS) technique will be proposed for throughput maximization and PAPR reduction in the DCO-OFDM, ACO-OFDM, and ADO-OFDM systems. Furthermore, the STC technique enables the simultaneous transmission of two sub-carriers through Walsh spreading codes without inference between them. As a result, the OFDM symbol has been reduced by 50%. The IMADJS strategy reduces the high PAPR of transmitted signals by compressing large signals and expanding small signals, as long as the average power level remains constant after compression. Therefore, the proposed STC-IMADJS technique doubles the throughput as well as significantly reduces the PAPR for OFDM systems based on VLC. The simulation results are performed using Matlab-2021a for 1024 sub-carriers. As a result, the simulation results show that the proposed technique reduces the PAPR by 3.7 dB (86%), 8.16 dB (93%), and 1.81 dB (20%) for DCO-OFDM, ACO-OFDM, and ADO-OFDM systems respectively. Furthermore, the technique has a significantly lower computational complexity than conventional OFDM systems based on VLC. Finally, the measures of performance through this article are bit error rate and complementary cumulative distribution function.

A novel fault detection technique for PV systems based on the K-means algorithm, coded wireless Orthogonal Frequency Division Multiplexing and thermal image processing techniques

Solar energy is considered one of the most ecological energy systems, which provides clean, reliable, and unlimited power. However, the solar system can be exposed during its operation to numerous failures that can immediately lead to a dangerous incident such as fire ignition. To ensure the productivity and safety of the system, it must be accompanied by fault detection and diagnostic (FDD) techniques. A new wireless communication system and its application in PV systems to detect damaged areas of solar panels are proposed to address these issues. The proposed approach is composed mainly of two parts; the first part aims to check and detect the existence of damaged areas in the thermal images of PV panels, while the second part focuses on the transmission of faulty panels using Orthogonal Frequency Division Multiplexing (OFDM) modulation with three decoding algorithms, namely, Min-sum, Bit-Flipping, and Viterbi, to send and correct errors induced by a wireless transmission channel. The simulation results have shown that employing the K-means algorithm, OFDM modulation, and the Min-sum decoding scheme offers a significant performance improvement giving a rapid degradation with a BER of 10−4 for SNR = 3.7 dB and a null BER from SNR = 4 dB. From a financial point of view, it was proved that the adopted solution is cost-effective compared to literature-based ones. This solution could be very useful since the overall capital cost is about 5.41 USD/m2.