Frequency Division Multiplexing Systems Research Articles

Implementing intelligent‐based sparse channel estimation in Multi User‐Multiple Input Multiple Output‐Orthogonal Frequency Division Multiplexing system with hybridized optimization algorithm

SummaryThe channel plays a significant role as the multipath in Multiple Input Multiple Output‐Orthogonal Frequency Division Multiplexing (MIMO‐OFDM) systems. The precoding‐based channel estimation algorithms estimate the channel capacity at the receiver node and they provide efficient channel estimates under worst case channel scenarios. To estimate the channel capacity in the mobile node, semi‐blind scenario is a crucial task in Multi User (MU) MIMO systems. Therefore, a semi blind sparse channel estimation algorithm is demonstrated in the MU‐MIMO system to provide better performance. In the transmitter side, the signal modulation is performed with the help of Quadrature Phase Shift Keying (QPSK), and the modulated signal is given to Pulse Shaping Algorithm (PSA) to reduce the inter‐carrier interference as well as inter symbol interference. At each transmitter, the Inverse Fast Fourier Transforms (IFFT) technique is used for mapping the symbols and then the mapped signal is send to the receiver. In the receiver side, the FFT, pulse reshaping, and QPSK demodulation blocks are serially connected and perform inverse operations of the transmitter in the receiver. Then, the sparse channel is estimated at the receiver by using the semi blind sparse algorithm, where the parameters are optimized by using the Hybridized Drosophila with Virus Colony Search Optimization (HD‐VCSO). The objective function of the developed sparse channel estimation is the reduction of Minimum Mean Square Error (MMSE) in the channel. The performance of the developed sparse channel estimation algorithm is analyzed through different conventional algorithms to validate the effectiveness of the proposed algorithm.

An Efficient Symbol Timing Scheme for OFDM Systems Using Optimal Correlation-Based Circular-Shifted Preamble

We propose a coarse symbol timing scheme for wireless orthogonal frequency division multiplexing (OFDM) systems using an optimal correlation-based circular-shifted preamble (CSP). Our proposed scheme is implemented by off-line correlation-ranking and on-line processing. The on-line processing derives an optimal CSP for transmission according to the off-line correlation-ranking, and employs a delayed multiplication operation for symbol timing. The conducted simulation results show that our proposed scheme outperforms the other existing representative schemes over typical multi-path fading channels in terms of mean square error (MSE) while keeping the computational complexity low.

Closed‐form expression of long‐range modulated massive multiple‐input multiple‐output fractional Fourier transform‐orthogonal frequency division multiplexing system under two‐wave with diffuse power fading channel

SummaryIn this paper, the massive multiple‐input multiple‐output fractional Fourier transform‐based orthogonal frequency division multiplexing (MIMO FrFT‐OFDM) system is investigated using the Long Range (LoRa) modulation technique. The conventional system relies on quadrature amplitude modulated (QAM) modulation technology; high‐power amplifiers are needed to transmit the QAM signal. The LoRa modulation technique produces long‐range and low power signals. The two‐wave with diffused power (TWDP) fading channel is used to examine the system's performance. The expression of the bit‐error rate (BER) of the proposed system is also represented in a unique closed form. The proposed system is applied to a state‐of‐the art hospital, one of the Internet of Things (IoT) applications. As the problem of heart stroke is common, it needs to be monitored every second. The electrocardiogram (ECG) data are used to evaluate how well the proposed system is working. Using the proposed model, the physicians get the patient's ECG data while moving in the hospital, getting it at a high data rate, at a low cost because of the extended battery life, a long range, and a low BER. The data considered are from the MIT‐BIH Arrhythmia Database. The result displays that the proposed model achieves a BER of at 10 dB of signal‐to‐noise ratio (SNR), and the conventional model achieves the same BER at 15 dB of SNR. The BER performance of the proposed system is improved by nearly 5 dB.

Non‐linear modelling and distortion compensation in optical Fast‐orthogonal frequency division multiplexing systems

AbstractFast‐OFDM‐based intensity‐modulation and direct‐detection (IM/DD) has been proposed for deployment of cost‐efficient optical access networks, due to its implementation simplicity and high spectral efficiency. In this article, the accuracy of the generalised memory polynomial (GMP) for the non‐linear modelling of optical Fast‐OFDM links is studied, including memory effects and considering different model parameters. After model validation using measured data of a 10 km single mode fibre link, the GMP is used for performance investigations of a distortion compensation approach to optical Fast‐OFDM, for up to 16PAM modulation formats and different number of Fast‐OFDM subcarriers. This study firstly reports the performance results of optical 16PAM‐Fast‐OFDM systems using either 2PAM‐ or 4PAM‐based training signals for digital post‐distortion and FFT‐based channel estimation, and firstly investigates the influence of the zero padding (ZP) length on the performance of optical Fast‐OFDM. Excellent performance improvements are achieved using the proposed distortion compensation scheme, relative to conventional system implementation.

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

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

Frequency division multiplexing readout of a transition edge sensor bolometer array with microstrip-type electrical bias lines.

We demonstrate multiplexed readout of 43 transition edge sensor (TES) bolometers operating at 90 mK using a frequency division multiplexing (FDM) readout chain with bias frequencies ranging from 1 to 3.5MHz and a typical frequency spacing of 32kHz. We improve the previously reported performance of our FDM system by two important steps. First, we replace the coplanar wires with microstrip wires, which minimize the cross talk from mutual inductance. From the measured electrical cross talk (ECT) map, the ECT of all pixels is carrier leakage dominated. Only five pixels show an ECT level higher than 1%. Second, we reduce the thermal response speed of the TES detectors by a factor of 20 by increasing the heat capacity of the TES, which allows us to bias all TES detectors below 50% in transition without oscillations. We compare the current-voltage curves and noise spectra of the TESs measured in single-pixel mode and multiplexing mode. We also compare the noise equivalent power (NEP) and the saturation power of the bolometers in both modes, where 38 pixels show less than 10% difference in NEP and 5% difference in saturation power when measured in the two different modes. The measured noise spectrum is in good agreement with the simulated noise based on measured parameters from an impedance measurement, confirming that our TES is dominated by phonon noise.

Performance Analysis of ML-based Low Complex CFO Estimation for MIMO-OFDMA Uplink Systems

Carrier frequency offset (CFO) estimation in multiuser multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) system is investigated in this study. MIMO-OFDM is very sensitive to CFOs due to oscillator frequency mismatch and/or Doppler shift. Inaccurate CFO estimation results in intercarrier interference (ICI) through the loss of orthogonality among subcarriers. In this paper, the performance of the ML and APFE algorithm is analyzed for CFO estimation. ML becomes extremely complex due to the multidimensional exhaustive search issue, which is the basic concern in ML estimation. However, making use of the iterative low complex APFE method, here this multidimensional search is replaced with a sequence of mono-dimensional searches. This results in an estimation algorithm of reasonable complexity which is suitable for practical applications. In addition, ML accuracy is compared with the Cramer-Rao bound (CRB).

Preamble-Based Symbol Timing Algorithms in OFDM Systems

In orthogonal frequency division multiplexing (OFDM) systems, a preamble is added at the start of the OFDM data frame in order to find the correct frame starting point. In the receiver, the symbol starting point is estimated by a correlation-based timing metric that uses the periodic properties of the preamble. In this study, a novel preamble structure using the constant amplitude zero autocorrelation (CAZAC) sequence is proposed. The performance of the timing synchronization algorithms has been compared with the proposed method in terms of mean squared error (MSE). The simulations are performed under additive white Gaussian noise (AWGN) and Rayleigh multipath fading channels. The simulation results indicate that our proposed method provides better timing MSE performance for the low signal-to-noise ratio (SNR) values.

Generalized Receiver Designs for OFDM Systems with Alamouti Decoding in Fast Fading Channels

In the present paper, the generalized receiver designs for orthogonal frequency-division multiplex-ing (OFDM) systems that exploit the Alamouti transmit diversity technique are addressed. In Alamouti space-time coded OFDM systems, the simple Alamouti decoding at the generalized receiver relies on the assumption that the channels do not change over an Alamouti codeword period (two consecutive OFDM symbol periods). Unfortunately, when the channel is fast fading, the assumption is not met, resulting in severe performance deg-radation. In the present paper, a sequential decision feedback sequence estimation (SDFSE) scheme based on the generalized receiver with an adaptive threshold, a traditionally single-carrier equalization technique, is used to mitigate the performance degradation. A new method to set the threshold value is proposed. For small signal constellations like binary phase-shift keying (BPSK) and quadrature phase shift-keying (QPSK), the SDFSE generalized receiver with the adaptive threshold requires much lower complexity than a previous minimum me-an square error (MMSE) approach based on the generalized receiver at the cost of small performance degradati-on. Furthermore, we show that the performance difference becomes smaller when the channel estimation error is included. Adaptive effort sequence estimation (AESE) scheme based on the generalized receiver is also pro-posed to further reduce the average complexity of the SDFSE generalized receiver scheme with the adaptive threshold. The AESE generalized receiver scheme is based on the observation that a high Doppler frequency does not necessarily mean significant instantaneous channel variations. Simulations demonstrate the efficacy of the proposed SDFSE generalized receiver with the adaptive threshold and AESE generalized receiver schemes.

Comparison on BER Performance Using Linear Filtering Least Square Method and Least Square Method for MIMO-OFDM Based Communication Systems

In Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems, the Bit Error Rate is poor by using Linear Filtering Least Square method (LFLS) and Least Square (LS) method for massive MIMO-OFDM systems to extend the strength of the signal and to scale back the noise. Therefore the objective of the project is to maintain better Bit Error Rate performance. Materials and methods: Using Linear Filtering Least Square method, different values are used to enhance the Bit Error Rate (BER). The proposed method is compared with the least square method, the results are obtained by using Matlab simulation software. Results: The performance of Bit Error Rate is calculated by using the Linear Filtering Least Square method and enhanced Least Square method parameters. At 20 dB SNR, the linear filtering least-square provides the BER value is 10-3, whereas the Novel enhanced least-square scheme provides the BER value around 10-5. Conclusion: Based on experimental results and statistical analysis using the independent sample T-test, the Least Square method significantly performs better than the Linear Filtering Least Square method.

Filter Bank Multicarrier Modulation Techniques for 5G and Beyond Wireless Communication Systems

Higher data rates, higher mobility, lower latency, and better quality of service are the prime requirements for future communication systems. It is expected to provide connectivity to the Internet of everything, time-sensitive/time-engineered application, and service to high-fidelity holographic society. Its performance in terms of data rate, latency, synchronization, security, and reliability will be much better compared to 4G and 5G mobile communication systems. This paper investigates the performance of the pulse shaping-based filter bank multicarrier (FBMC) modulation technique used in 5G mobile communication systems. Simulation results show that the FBMC system has a better performance compared to the conventional orthogonal frequency division multiplexing (OFDM) system in terms of many parameters such as achievable channel capacity, signal to noise ratio, time, and frequency response, out of band leakage, etc.

Gyre Precoding and T-Transformation-Based GFDM System for UAV-Aided mMTC Network

In this paper, an unmanned aerial vehicle (UAV)-aided multi-antenna configured downlink mmWave cooperative generalized frequency division multiplexing (GFDM) system is proposed. To provide physical layer security (PLS), a 3D controlled Lorenz mapping system is introduced. Furthermore, the combination of T-transformation spreading codes, walsh Hadamard transform, and discrete Fourier transform (DFT) techniques are integrated with a novel linear multi-user multiple-input multiple-output (MU-MIMO) gyre precoding (GP) for multi-user interference reduction. Furthermore, concatenated channel-coding with multi-user beamforming weighting-aided maximum-likelihood and zero forcing (ZF) signal detection schemes for an improved bit error rate (BER) are also used. The system is then simulated with a single base station (BS), eight massive machine-type communications (mMTC) users, and two UAV relay stations (RSs). Numerical results reveal the robustness of the proposed system in terms of PLS and an achievable ergodic rate with signal-to-interference-plus-noise ratio (SINR) under the implementation of T-transformation scheme. By incorporating the 3D mobility model, brownian perturbations of the UAVs are also analyzed. An out-of-band (OOB) reduction of 320 dB with an improved BER of 1×10−4 in 16-QAM for a signal-to-noise ratio, Eb/N0, of 20 dB is achieved.

Decision Feedback Kurtosis Minimum Crosstalk Mitigation in Super-Nyquist Multiband CAP Systems

In multiuser access visible light communication (VLC) systems, many multiplex techniques can be utilized to fully exploit the limited bandwidth. In frequency-division multiplexing systems, one possible solution is to dynamically allocate limited bandwidth resources for users to support multiple-service access. To enable high-speed transmissions, the super-Nyquist multiband concept has been proposed in recent years. Specifically, the center frequency spacing is narrowed, and the subcarriers are nonorthogonally overlapped to enable more services and users in multiband systems. Studies have shown that this strategy can support higher spectral efficiency (SE) while simultaneously, introducing intersymbol interference (ISI) and intercarrier interference (ICI). Therefore, a well-designed ICI mitigation scheme is required. In multiband carrierless amplitude phase ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</i> -CAP) modulation systems, it is technically challenging to achieve the SE beyond one baud/s/Hz under the pre-forward error correction (pre-FEC) threshold without increasing the modulation order. Inspired by the distinctive pulse shaping filter (PSF) structure in a non-orthogonal <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</i> -CAP scheme, we propose the iterative decision feedback kurtosis minimum (DFKM) scheme and achieve the super-Nyquist SE of approximately 1.06 baud/s/Hz. In contrast to existing ICI mitigation schemes, the theoretical framework reveals that symbol-level crosstalk filters are indispensable to reap the benefit of super-Nyquist transmission, not limited to VLC.

Carrier Diversity Incorporation to Low-Complexity Near-ML Detection for Multicarrier Systems over V2V Radio Channel.

Inter-carrier interference (ICI) in vehicle to vehicle (V2V) orthogonal frequency division multiplexing (OFDM) systems is a common problem that makes the process of detecting data a demanding task. Mitigation of the ICI in V2V systems has been addressed with linear and non-linear iterative receivers in the past; however, the former requires a high number of iterations to achieve good performance, while the latter does not exploit the channel’s frequency diversity. In this paper, a transmission and reception scheme for low complexity data detection in doubly selective highly time varying channels is proposed. The technique couples the discrete Fourier transform spreading with non-linear detection in order to collect the available channel frequency diversity and successfully achieving performance close to the optimal maximum likelihood (ML) detector. When compared with the iterative LMMSE detection, the proposed system achieves a higher performance in terms of bit error rate (BER), reducing the computational cost by a third-part when using 48 subcarriers, while in an OFDM system with 512 subcarriers, the computational cost is reduced by two orders of magnitude.

Optimization of Acoustic Communication Links for a Swarm of AUVs: The COMET and NEMOSENS Examples

Underwater acoustic communication is a key point for performance improvement in an autonomous underwater vehicle (AUV) swarm. The communication process is essential for improving the AUVs localization accuracy for navigation and is a convenient way for sharing information among the AUVs in a network. The objective of this work, which was developed in the COMET and NEMOSENS projects, is to address the communication process required in a mobile underwater wireless network, with a focus on the proposal of an adaptive physical layer methodology. We discuss about the employed channel access method, the frame structure, and we propose the usage of an adaptive guard interval in order to ameliorate the network usage rate. We explain the physical layer aspect of the communication: the data processing at the transmitter and receiver side. In addition to that, we propose the usage of smart communications among AUVs. We design a method for adapting some physical layer parameters. The proposed approach relies only on the knowledge of the transmission geometry, and it optimizes the number of subcarriers and the cyclic-prefix length of the Orthogonal Frequency-Division Multiplexing (OFDM) system. The obtained results show a performance improvement in terms of bit-error rate when compared with the case of random parameters selection. These results corroborate the benefits of our adaptive parameters approach.

Fractional weighted ZF equalizer: A novel approach for channel equalization in MIMO-OFDM system under impulse noise environment

Impulse noise is the major factor degrading the performance of the wireless system, imposing the need for the impulse noise mitigation strategy. Mainly, in the multiple-input multiple-output (MIMO) and orthogonal frequency-division multiplexing (OFDM) system contaminated with the impulse noise creates a major impact in the performance as the conventional zero-forcing (ZF) equalizer as there is no satisfactory results. Thus, the paper concentrates on the impulse noise mitigation strategy based on the fractional weighed zero-forcing (FWZF) equalizer, which is the integration of the fractional concept in the Zero-Forcing equalizer. The noise impacts in the MIMO-OFDM system are minimized and the performance is enhanced due to the usage of the fractional theory in the ZF equalizer as the equalization values of the previous instances are interpreted for the formulation of the effective equalization value in the current instance of the ZF equalizer. The performance of the methods is done based on the valuation metrics, Bit Error Rate (BER), Mean Square Error (MSE), and Symbol Error Rate (SER) with respect to the Signal-to-Noise Ratio (SNR) and dissimilar antenna array size. It is found that the proposed Fractional Weighed Zero-Forcing equalizer outperformed the existing methods with a minimal BER and SER of 0.063, and 0.1038 while analyzing the methods in the Rayleigh environment.

OFDM PAPR Reduction via Time-Domain Scattered Sampling and Hybrid Batch Training of Synchronous Neural Networks

Peak-to-average power ratio (PAPR) reduction in multiplexed signals in orthogonal frequency division multiplexing (OFDM) systems has been a long-standing critical issue. Clipping and filtering (CF) techniques offer good performance in terms of PAPR reduction at the expense of a relatively high computational cost that is inherent in the repeated application of fast Fourier transform (FFT) operations. The ever-increasing demand for low-latency operation calls for the development of low-complexity novel solutions to the PAPR problem. To address this issue while providing an enhanced PAPR reduction performance, we propose a synchronous neural network (NN)-based solution to achieve PAPR reduction performance exceeding the limits of conventional CF schemes with lower computational complexity. The proposed scheme trains a neural network module using hybrid collections of samples from multiple OFDM symbols to arrive at a signal mapping with desirable characteristics. The benchmark NN-based approach provides a comparable performance to conventional CF. However, it can underfit or overfit due to its asynchronous nature which leads to increased out-of-band (OoB) radiations, and deteriorating bit error rate (BER) performance for high-order modulations. Simulations’ results demonstrate the effectiveness of the proposed scheme in terms of the achieved cubic metric (CM), BER, and OoB emissions.

Pilot design for underwater MIMO cosparse channel estimation based on compressed sensing

In multiple-input multiple-output–orthogonal frequency-division multiplexing underwater acoustic communication systems, the correlation of the sampling matrix is the key of the channel estimation algorithm based on compressed sensing. To reduce the cross-correlation of the sampling matrix and improve the channel estimation performance, a pilot design algorithm for co-sparse channel estimation based on compressed sensing is proposed in this article. Based on the time-domain correlation of the channel, the channel estimation is modeled as a common sparse signal reconstruction problem. When replacing each pilot indices position, the algorithm selects multiple pilot indices with the least cross-correlation from the alternative positions to replace the current pilot indices position, and it uses the inner and outer two-layer loops to realize the bit-by-bit optimal replacement of the pilot. The simulation results show that the channel estimation mean squared error of pilot design algorithm for co-sparse channel estimation based on compressed sensing can be reduced by approximately 18 dB compared with the least square algorithm. Compared with the genetic algorithm and search space size methods, the structural sequence search proposed by pilot design algorithm for co-sparse channel estimation based on compressed sensing is used to design the pilot to complete the channel estimation. Thus, the mean squared error of the channel estimation can be reduced by 2 dB. At the same bit error rate of 0.03, the signal-to-noise ratio can be decreased by approximately 7 dB.

Joint Timing and Frequency Synchronization Using Convolutional Neural Network in WLAN Systems

In wireless communication systems, the performance of the receiver is very sensitive to time and frequency offsets. In particular, orthogonal frequency division multiplexing (OFDM) systems are highly vulnerable to those offsets due to inter-carrier interference (ICI) and inter-symbol interference (ISI). To solve this problem, wireless local area network (WLAN) systems transmit a preamble for synchronization. In this paper, we propose a joint time and frequency offsets estimation technique based on convolutional neural network (CNN) for WLAN systems. In the proposed technique, the correlation between the received signal and the transmitted preamble is performed first. Then the frequency offset is coarsely compensated by several hypothesized offsets. The compensated signals are inputted to the proposed CNN and the CNN predicts the time and frequency offsets. The estimation performance is examined through computer simulation. According to the results, the proposed time offset estimator shows 3 dB to 6 dB performance gain, and the frequency offset estimator shows much lower root mean square error (RMSE) performance than the conventional technique at low SNRs

Improved ACE and ICF low complexity joint algorithm to reduce PAPR of CO-OFDM system

Active constellation expansion (ACE) and iterative clipping and filtering (ICF) are simple and effective techniques for reducing the peak-to-average ratio (PAPR) in coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems, but effective PAPR suppression requires a lot of iterations. To overcome this shortcoming, a joint algorithm based on improved active constellation expansion (IACE) and ICF (IACE-ICF) is proposed. The simulation results show that at the complementary cumulative distribution function (CCDF) of 10−4, the PAPR of IACE-ICF (G=4, iter=4) algorithm is optimized by 1.507 dB, 1.13 dB and 0.204 dB compared with that of the IACE, ICF (iter=4) and ICF-IACE (G=4, iter=4) algorithms, respectively. Meanwhile, when the bit error rate (BER) is 10−3, the optical signal to noise ratio (OSNR) of the proposed scheme is optimized by 2.04 dB, 1.75 dB and 1.4 dB compared with that of clipping, ICF (iter=4) and ICF-IACE (G=4, iter=4) algorithms, respectively. On the other hand, the proposed scheme can reduce the number of complex multiplications by 14.29% and complex additions by 28.57% compared with the ICF (iter=14) scheme.