Eliminate Intersymbol Interference Research Articles

Low-complexity adaptive multipath interference and channel noise mitigation scheme based on optimized detection for bandwidth-limited IM/DD systems.

In this Letter, we propose a low-complexity adaptive multipath interference (MPI) and channel noise mitigation (AMCM) scheme in the receiver digital signal processing (DSP) for bandwidth-limited intensity modulation and direct detection (IM/DD) transmission systems. Following channel equalization, MPI and channel noise are distributed in the low- and high-frequency parts, respectively, and exhibit the characteristics of bandstop filtering. The proposed AMCM is designed based on optimized detection, which incorporates an adaptive bandpass filter (BPF) and a log-maximum a posteriori estimation with a lookup table-based fixed number of surviving states (LUT-based FS-MAP) decoder. The adaptive BPF is capable of mitigating the MPI and channel noise based on spectral distribution. Moreover, the LUT-based FS-MAP decoder can eliminate intersymbol interference (ISI) introduced by the BPF. The proposed AMCM is implemented in an O-band 56-Gbaud IM/DD optical 4-level pulse amplitude modulation (PAM-4) system with a 10.7-GHz bandwidth over a 10-km standard single-mode fiber with different linewidths. The results demonstrate that the proposed AMCM scheme can enhance signal-to-interference ratio (SIR) tolerance to 11 dB with only three real-valued multiplications per symbol, achieving a 7% hard-decision forward error correction threshold. To the best of our knowledge, for the first time, this represents the inaugural instance of optimized detection being employed for MPI mitigation.

Design and analysis of CP-free OFDM PDMA transmission system

The paragraph introduces a proposed CP-free OFDM PDMA downlink transmission system. The main focus of the system is to address the capacity limitations caused by the overhead of cyclic prefix in traditional PDMA systems. The transmitter utilizes a pattern mapping unit before CP-free OFDM modulation to enhance system capacity and frequency efficiency. Decision feedback equalization (DFE) is employed in the receiver to eliminate intersymbol interference. The output signals from the DFE are then passed through a CP restoration unit to convert a linear-shifted signal into a cyclic-shifted signals. To assess the system's performance, simulations are conducted, investigating different key parameters such as overload rate, channel condition, and signal-to-noise ratio. The results indicate that, compared to CP OFDM PDMA systems, the proposed CP-free PDMA system significantly enhances system capacity under the same overload rate. Additionally, bit error rate is also evaluated during the simulations. Overall, the paragraph provides an overview of the proposed CP-free OFDM PDMA system, its components, and the simulation-based evaluation of its performance compared to traditional PDMA systems.

Two-Stage LMMSE/DNN Receiver for High-Order Modulation

High-order modulation has been seen as a promising technology to increase the spectral efficiency of wireless communications. Unfortunately, higher-order signals are susceptible to power amplifier (PA) nonlinearities and multi-path effects of the channel, leading to nonlinear distortion and severe inter-symbol interference. To guarantee the reliable detection of high-order signals, a two-stage receiver consisting of linear minimize mean squared error (LMMSE) equalizer and deep neural network (DNN) demodulator, namely TSLD receiver, is proposed, where LMMSE equalizer and DNN are deployed to eliminate inter-symbol interference and handle the amplifier nonlinearity, respectively. To facilitate the implementation of our proposed receiver, the specific pilot structure is designed, where low-order modulations are used for LMMSE equalizer and high-order modulations are used for DNN training. Simulation results show that our proposed TSLD receiver for high-order demodulation could recover the transmitted symbols effectively, even under serious multi-path and nonlinerity scenarios.

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).

A 15-Gb/s Single-Ended NRZ Receiver Using Self-Referenced Technique With 1-Tap Latched DFE for DRAM Interfaces

This brief presents a single-ended (SE) receiver (RX) with a self-referenced (SR) technique using sample and hold (S&H) circuits. The proposed RX does not require a reference voltage (VREF) for data recovery by comparing the present data with previous data. The RX was implemented as half-rate architecture to halve the clock frequency and facilitate the S&H operation. Moreover, the proposed decision feedback equalizer (DFE) is suitable for SR RX and improves the reliability of RX by eliminating inter-symbol interference (ISI). The prototype RX, fabricated using 28-nm CMOS technology, occupies a 0.0016 mm2 active area. The measurement result of the proposed RX achieves a bit-error-rate (BER) under 10−12 with a 15-Gb/s data rate in a 17-inch PCB FR4 channel. The RX consumes 13.56 mW of power and has a power efficiency of 0.90 pJ/bit.

Research on Equalization Technology of Broadband Satellite Communication Channel

Satellite channel is the representative non-linear channel with limited frequency band. The random change of the channel causes the communication stability to be affected. With the development of satellite communication technology, the bandwidth of satellite communication has increased and the data rate has also increased significantly, resulting in more serious code interference, which has become a key factor affecting communication quality. Finding an efficient equalization technology to eliminate channel inter-code interference is the key to ensuring satellite broadband communications. This article first briefly discusses the principle of eliminating inter-symbol interference and common equalizer algorithms, and summarizes the main factors that affect the performance of channel equalization algorithms. On this basis, an improved LSTM blind equalization algorithm is proposed.

Matched Filtering for MIMO Coherent Optical Communications with Mode-Dependent Loss Channels.

The use of digital signal processors (DSP) to equalize coherent optical communication systems based on spatial division multiplexing (SDM) techniques is widespread in current optical receivers. However, most of DSP implementation approaches found in the literature assume a negligible mode-dependent loss (MDL). This paper is focused on the linear multiple-input multiple-output (MIMO) receiver designed to optimize the minimum mean square error (MMSE) for a coherent SDM optical communication system, without previous assumptions on receiver oversampling or analog front-end realizations. The influence of the roll-off factor of a generic pulse-amplitude modulation (PAM) transmitter on system performance is studied as well. As a main result of the proposed approach, the ability of a simple match filter (MF) based MIMO receiver to completely eliminate inter-symbol interference (ISI) and crosstalk for SDM systems under the assumption of negligible MDL is demonstrated. The performance of the linear MIMO fractionally-spaced equalizer (FSE) receiver for an SDM system with a MDL-impaired channel is then evaluated by numerical simulations using novel system performance indicators, in the form of signal to noise and distortion ratio (SNDR) loss, with respect to the case without MDL. System performance improvements by increasing the transmitter roll-off factor are also quantified.

LSTM-Autoencoder Deep Learning Technique for PAPR Reduction in Visible Light Communication

Visible light communication (VLC) is a relatively new wireless communication technology that allows for high data rate transfer. Because of its capability to enable high-speed transmission and eliminate inter-symbol interference, orthogonal frequency division multiplexing (OFDM) is widely employed in VLC. Peak to average power ratio (PAPR) is an issue that impacts the effectiveness of OFDM systems, particularly in VLC systems, because the signal is distorted by the nonlinearity of light-emitting diodes (LEDs). The proposed method Long Short Term Memory-Autoencoder (LSTM-AE) uses an autoencoder as well as an LSTM to learn a compact representation of an input, allowing the model to handle variable length input sequences as well as predict or produce variable length output sequences. This study compares the suggested model with various PAPR reduction strategies to demonstrate that it offers a superior improvement in PAPR reduction of the transmitted signal while maintaining BER. Also, this model provides a flexible compromisation between PAPR and BER.

Frame Boundary Detection and Deep Learning-Based Doppler Shift Estimation for FBMC/OQAM Communication System in Underwater Acoustic Channels

Underwater acoustic (UWA) communication is the only option for underwater long-distance wireless communication. However, its data rate is very low, in tens of kbps, and the time-varying nature of the UWA channel exhibits a Doppler effect. The data rate can be increased using a multicarrier technique, such as Filter Bank Multicarrier (FBMC). The FBMC-OQAM system does not require a cyclic prefix (CP) to eliminate intersymbol interference (ISI). Therefore, compared to other multicarrier techniques, the FBMC-OQAM system achieves the maximum spectral efficiency. Despite the well-designed filter, synchronisation errors cause performance degradation in the FBMC-OQAM system. In this paper, we propose frame boundary and Doppler frequency estimation methods for the FBMC-OQAM system under UWA channels. In this study, we propose a preamble-based frame boundary. The conjugate symmetry property is used in the frame boundary estimation. The performance of the proposed technique was studied under different UWA channels with different Doppler scale. The proposed time synchronisation technique yielded multiple peaks under UWA channels. A method for identifying the peak that represents the frame boundary is proposed. We compared the performance of proposed timing metric with existing three reference timing metrics. The proposed timing metric exhibited superior over two metrics and almost identical performance with the Liming’s metric with less computational complexity. In addition, we propose a convolutional neural network (CNN)-based Doppler scale estimation method. The proposed technique was shown to estimate a wide range of Doppler scale factors. The performance of the proposed technique was studied by considering different UWA channels at different SNRs. The proposed CNN architecture is analysed by changing the CNN parameters. Stacked autoencoders were adopted for Doppler scale estimation and the performance of the proposed CNN-based Doppler scale estimation method was compared with the stacked autoencoders based Doppler scale estimation method. Simulation results show that the proposed CNN-based Doppler Scale estimator exhibits good performance in UWA channels at different SNRs and Doppler scale factors.

Efficient Machine Learning-Enhanced Channel Estimation for OFDM Systems

Recently much research work has focused on employing deep learning (DL) algorithms to perform channel estimation in the upcoming 6G communication systems. However, these DL algorithms are usually computationally demanding and require a large number of training samples. Hence, this work investigates the feasibility of designing efficient machine learning (ML) algorithms that can effectively estimate and track time-varying, frequency-selective channels. The proposed algorithm is integrated with orthogonal frequency-division multiplexing (OFDM) to eliminate intersymbol interference (ISI) induced by the frequency-selective multipath channel and compared with the well-known least square (LS) and linear minimum mean square error (LMMSE) channel estimation algorithms. The obtained results have demonstrated that even when a small number of pilot samples, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N_{P}$ </tex-math></inline-formula> , is inserted before the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> subcarriers OFDM symbol, the introduced ML-based channel estimation is superior to the LS and LMMSE algorithms. This dominance is reflected in the bit-error-rate (BER) performance of the proposed algorithm, which attains a gain of 2.5 dB and 5.5 dB over the LMMSE and LS algorithms, respectively, when <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N_{P}=\frac {N}{8}$ </tex-math></inline-formula> . Furthermore, the BER performance of the proposed algorithm is shown to degrade by only 0.2 dB when the maximum Doppler frequency is randomly varied. Finally, the number of iterations required by the proposed algorithm to converge to the smallest achievable mean-squared error (MSE) are thoroughly examined for various signal-to-noise ratio (SNR) levels.

Fast Blind Equalization Using Bounded Non-Linear Function With Non-Gaussian Noise

Blind equalization is widely utilized to eliminate inter-symbol interference in communication system. It is still a challenge to support blind equalization method within non-Gaussian noise environments. Aiming at improving its convergence speed and robustness performance, in this letter, a novel fast blind equalization method is proposed by using bounded nonlinear function (BNF) and quasi-Newton method. Firstly, BNF-based cost function is proposed to effectively eliminate non-Gaussian noise and realize equalization. Next, quasi-Newton method is developed as the iteration method, which can accelerate the convergence speed. Moreover, theoretical analysis is provided to illustrate that the proposed algorithm has a robust convergence performance. Simulation results show that the proposed method enables evident performance improvement in terms of convergence speed and robustness with non-Gaussian noise.

Beyond DVB-S2X: Faster-Than-Nyquist Signaling With Linear Precoding

Faster-than-Nyquist (FTN) signaling with linear precoding is investigated as a potential technique to transcend digital video broadcasting-satellite-second generation extension (DVB-S2X). Combining cyclic prefix (CP), cyclic suffix (CS) and discrete Fourier transform (DFT) with existing linear precoding algorithms, such as G-to-minus-half (GTMH) precoding (GTMHP), the CPS-GTMH-DFTP algorithm is proposed to eliminate inter-symbol interference (ISI) for FTN signaling. By comparison with most existing algorithms, our proposed CPS-GTMH-DFTP algorithm requires much lower implementation complexity. Specifically, only two multipliers and the corresponding fast Fourier transform (FFT)/inverse fast Fourier transform (IFFT) operations are required with the proposed CPS-GTMH-DFTP algorithm, which makes our proposed algorithm more suitable for practical implementation. Furthermore, the CPS-GTMH-DFTP algorithm has better bit error rate (BER) performance than most existing precoding algorithms. Simulation results show that even when the time acceleration parameter and roll-off factor equal to 0.75 and 0.35 respectively, our proposed CPS-GTMH-DFTP algorithm can still approach the BER performance of the ISI-free Nyquist signaling for all the modulation types adopted in DVB-S2X. More precisely, with 256-amplitude phase shift keying (APSK), the BER performance degradation is almost 0.03 and 0.01 dB in uncoded and coded FTN systems respectively. As far as we know, with regard to low complexity ISI elimination algorithms for FTN signaling, this is the first time to achieve such excellent performance with a time acceleration parameter 0.75 and a practical roll-off factor 0.35.

Optimal Deployment of Vector Sensor Nodes in Underwater Acoustic Sensor Networks.

Underwater acoustic sensor networks have recently attracted considerable attention as demands on the Internet of Underwater Things (IoUT) increase. In terms of efficiency, it is important to achieve the maximum communication coverage using a limited number of sensor nodes while maintaining communication connectivity. In 2017, Kim and Choi proposed a new deployment algorithm using the communication performance surface, which is a geospatial information map representing the underwater acoustic communication performance of a targeted underwater area. In that work, each sensor node was a vertically separated hydrophone array, which measures acoustic pressure (a scalar quantity). Although an array receiver is an effective system to eliminate inter-symbol interference caused by multipath channel impulse responses in underwater communication environments, a large-scale receiver system degrades the spatial efficiency. In this paper, single-vector sensors measuring the particle velocity are used as underwater sensor nodes. A single-vector sensor can be considered to be a single-input multiple-output communication system because it measures the three directional components of particle velocity. Our simulation results show that the optimal deployment obtained using single-vector sensor nodes is more effective than that obtained using a hydrophone (three-channel vertical-pressure sensor) array.

On the Possibility of using Vertical Receiving Arrays for Underwater Acoustic Communication on the Arctic Shelf

Numerical simulation is applied to analyze the possibilities of using vertical receiving arrays covering the entire waveguide for underwater acoustic communication on the shallow Arctic shelf. Binary phase shift keying with a carrier frequency of 750 Hz is selected for data transfer. It is shown that an algorithm for selecting acoustic signals corresponding to the first waveguide mode or an algorithm based on using passive-phase conjugation eliminates intersymbol interference. In case of spatial signal processing and waveguide depth of 30 m the error-free information transmission is possible when the signal-to-noise ratio is ≈15 dB less than that for a single receiver. It has been demonstrated these advantages to be present in different conditions on the Arctic shelf: with an acoustically soft or acoustically hard bottom, with surface waves, or with ice cover.

Channel Estimation Scheme in Oversampled Frequency Domain for FBMC-QAM Systems Based on Prototype Filter Set

This paper proposes a channel estimation scheme for the filter-bank multicarrier systems with quadrature amplitude modulation (FBMC-QAM). Under frequency selective channels, the adjacent data symbols cause interference to the pilot symbols in FBMC-QAM systems and degrade the performance of the channel estimation. To handle this problem, we analyze the interference of the pilot symbols in an oversampled frequency domain before the receiver filtering process. Exploiting the interference analysis, we propose a pilot symbol configuration and condition of filter coefficients to cancel the inter-carrier interference. Moreover, we apply a time domain data symbol precoding to eliminate inter-symbol interference. The simulation results show that the proposed scheme outperforms conventional channel estimation schemes.

Enhanced channel estimation in OFDM systems with neural network technologies

Orthogonal frequency division multiplexing (OFDM) provides an effective and low complexity means of eliminating inter-symbol interference for transmission over frequency selective fading channels. In OFDM systems, channel state information (CSI) is required for the OFDM receiver to perform coherent detection or diversity combining, if multiple transmit and receive antennas are deployed. In practice, CSI can be reliably estimated at the receiver by transmitting pilots along with data symbols. In this paper, we investigate and compare various efficient pilot-based channel estimation schemes by neural network technologies for OFDM systems. We present further the application of functional link neural fuzzy network (FLNFN) for channel estimation in the investigated OFDM systems. We compared bit error rates of the proposed neural network with that of the other neural network technologies, the least square (LS) algorithm, and the minimum mean square error (MMSE) algorithm. Our results demonstrate that the proposed FLNFN algorithm can enhance the performance of channel estimation in existing OFDM channel environments.

An interleave division multiple access receiver for multi-user underwater acoustic communication

A downlink interleave division multiple access (IDMA) receiver, employing sparse channel estimation and interference canceller (IC), is proposed for multi-user underwater communications. To eliminate inter-symbol interference (ISI) and multiple access interference (MAI), an equalizer, a decoder, and an interference canceller are implemented in the receiver. The equalizer is used to eliminate ISI. The channel parameters used in the equalizer are estimated by a modified OMP sparse channel estimation algorithm. The performance of channel estimation is further improve ed using the decoder soft output information during the receiver iteration. MAI, reconstructed by the decoder output and channel parameters, can be eliminated in IC section of other users. The receiver’s performance is verified in shallow water acoustic channels during a sea-trail in the South China Sea. Three different ranges between the transmitter and the receiver, i.e., 4.5 km,6 km, and 7 km, were investigated with a maximum of four users at the data rate of 500 bps per user. The results demonstrated that the proposed IDMA receiver provides good performance with low bit error rate (BER). Furthermore, the receiver has been applied in a real-time underwater communication network.

A Kalman Filter-Based Blind Adaptive Multi-User Detection Algorithm for Underwater Acoustic Networks

An underwater acoustic Kalman filter-based blind adaptive multi-user detection algorithm, suitable for underwater acoustic communication networks, is proposed in this paper. The algorithm can be employed to effectively improve the system capacity of multi-user communication in underwater acoustic sensor networks, reduce transmitting power and costs on power control, extend the multi-user communication distance, weaken or eliminate intersymbol interference, multiple access interference and near-far effect, thus effectively utilizing limited underwater frequency band resource. First, the dynamic model of underwater acoustic multi-user communication system and the optimal filter equation of the proposed algorithm are found. Second, computation complexity is analyzed, and convergence analysis is carried out in terms of excess mean output energy. Finally, pool, river, sea, and under-ice asynchronous communication experiments have been carried out for both the scalar and the vector hydrophones. Good experimental results verify the effectiveness of the proposed algorithm.

Reconfigurable OFDM based transceiver for Wireless Communication

Orthogonal Frequency Division Multiplexing (OFDM) is a multi-carrier modulation technique which is very much popular in new wireless networks of IEEE standard. It has improved the quality of long- distance communication by eliminating Inter Symbol Interference (ISI) and improving Signal-to-Noise Ratio (SNR) And Multipath Fading. Reconfigurable OFDM based transceiver in information security gives high benefits to the wireless communication and used for multipurpose requirements. Reconfigurable transmitters with all the digital modulation techniques are flexible to all the end users without reconfigurable receiver with single modulation technique. Digital 8 bit data which is input to the system that is converted to the high digital signals at the end of receiver side. Receiver output is given to the microcontroller and examining the input data in connected mobile, hence communications between two end users are fully secured.

Security of OFDM through Steganography

Communication through wireless medium is widely used in today’s world. Orthogonal frequency-division multiplexing (OFDM) is a multiplexing method in which data transmission is done over the equally spaced, overlapped carrier frequencies. Transmission of data through OFDM has the advantage that it can achieve high data rate with greater bandwidth and flexible underlying modulations. It can easily eliminate intersymbol interference (ISI). Therefore OFDM has become a leading choice for data transmission. .So it becomes important to secure data that is transferred through wireless OFDM communication systems. Different techniques have been used for secure data transmission like cryptography, watermarking etc. In this paper, literature studies of various techniques are discussed. Enhanced security using steganography is proposed.