Intersymbol Interference Research Articles

Lamb-Waves-Based Sparse Distributed Penetrating Communication via Phase-Position Modulation for Enclosed Metal Structures

Sensor nodes have been widely used for mechanical equipment condition monitoring, especially for enclosed metal structures. In these cases, it is important to achieve communication between the sensor nodes inside the enclosed metal structures and the outside receiver node. Conventional wired communication using cables will affect the structural integrity, and wireless communication using electromagnetic waves will be shielded by metal structures, so neither is desirable. Motivated by these issues, this study proposes a Lamb waves-based sparse distributed penetrating communication (SDPC) system using the propagation characteristics of Lamb waves considered harmful in previous studies to accomplish wireless simultaneous data communication. Combining phase shift keying and pulse position modulation mechanisms, a phase-position modulation (P-PM) technology is proposed to improve the communication rate. To overcome the intersymbol interference (ISI) problem caused by the propagation characteristics of Lamb waves, a phase-position sparse reconstruction (P-PSR) strategy is proposed for demodulation, which is more convenient and accurate compared with the conventional cross-correlation method. It should be noted that the maximum bit rate without bit error reaches 830.48 kbps via P-PM parameter optimization, which is 8.3 times higher than that of on-off keying modulation approach under the same experimental conditions. Finally, distributed communication experiments and simulations further verify the high accuracy, efficiency and strong robustness of the proposed SDPC system, which can meet the communication requirements of enclosed metal structures.

Signal Integrity Analysis of Through-Silicon-Via (TSV) With Passive Equalizer to Separate Return Path and Mitigate the Inter-Symbol Interference (ISI) for Next Generation High Bandwidth Memory

Signal Integrity Analysis of Through-Silicon-Via (TSV) With Passive Equalizer to Separate Return Path and Mitigate the Inter-Symbol Interference (ISI) for Next Generation High Bandwidth Memory

Error Vector Magnitude as a Performance Standard for Antennas in the Millimeter-Wave Era: Part 2: Modeling, simulation, and measurement methods

The error vector magnitude (EVM) is a comprehensive measure of the amplitude and phase distortion of digitally modulated signals and a potential tool for characterizing the performance of active beamforming arrays, especially at millimeter-wave frequencies, because of the high level of integration and limited spacing between the radiating elements. A review of the EVM measurement process and fundamental principles for time-domain demodulation with a vector signal analyzer (VSA) and spectral correlation with a vector network analyzer (VNA) was presented in [1]. This article demonstrates how researchers have modeled and measured impairments from antenna and phased array signal transmission to characterize their influence on the EVM of single and multicarrier digital signals. It presents examples of simulation models and measurements of the distortion from ultrawideband (UWB) passive antenna transmission, power amplifier (PA) nonlinearities, and phased array beam squint and beam scan intersymbol interference (ISI). A brief survey of over-the-air (OTA) test ranges for EVM analysis is also provided. This overview of state-of-the-art EVM simulation and measurement methods is intended to help interested readers understand and enhance the EVM performance analysis methods applied to antennas and phased arrays in this new era of millimeter-wave communications.

Iterative Equalization and Decoding over an Additive White Gaussian Noise Channel with ISI Using Low-Density Parity-Check Codes

In this article we present an iterative system of equalization and decoding to manage the intersymbol interference over an additive white Gaussian noise (AWGN) channel. Following the classic turbo equalization scheme, the proposed system consists of low-density parity-check (LDPC) coding at the transmitter side; we applied a Log maximum a posteriori probability (Log-MAP) equalizer and min-sum LDPC decoding at the receiver side. The equalizer and decoder, linked through interleaving and deinterleaving, iteratively update each other’s information. We performed the performance analysis of the proposed system, bit error rate (BER) vs. signal-to-noise ratio (SNR), considering three different impulse responses of the channel (h). Our experimental results indicated that increasing the number of iterations performed by the LDPC decoder from 10 to 20 during the iterative process of equalization and decoding leads to better outcomes. The proposed system was compared with turbo equalization and separate equalization, performed before the decoding process with minimum mean-square error (MMSE) and LDPC decoding, in terms of BER vs. SNR, considering the three different h. Based on the analyzed results, it can be concluded that the equalization performance depends on both the impulse responses of the channel and the chosen decoding and equalization method; therefore, the equalization method does not always offer good results for any h.

Performance Analysis of Adaptive Equalizers Over Multipath Faded Channels: Error Vector Magnitudes

Due to the increasing popularity of digital transmission systems, the need for channel equalizers has been acknowledged. These techniques are designed to counteract the effects of the inter-symbol interference (ISI) caused by the communication channels. An adaptive equalizer is used to operate on the output of a channel in order to provide an approximation of the transmission medium. An adaptive equalizer usually requires a training period to operate successfully. This method eliminates the effects of the wireless transmission channel and allows the subsequent symbol modulation. The paper presents an overview of the various adaptive equalizers, such as the least mean squares (LMS), decision feedback equalizers (DFE), and the Recursive least squares (RLS). It also explores their performance in terms of error vector magnitudes (EVM) over Rician and Rayleigh channels. The paper looks into the effects of adaptive equalizers on various digital modulation techniques for rectangular quadrature phase shift, amplitude modulation, such as the BPSK, QPSK, 4-QAM, 16-QAM, 64-QAM and 256-QAM. These modulations are analysed and measured in terms of symbol error rates and number of incorrect symbols.

Low-complexity characterized-long-short-term-memory-aided channel modeling for optical fiber communications

In this work, a low-complexity data-driven characterized-long-short-term-memory (C-LSTM)-aided channel modeling technique is proposed for optical single-mode fiber (SMF) communications. To fully utilize the sequence correlation learning ability of traditional long short-term memory (LSTM) networks and solve the gradient explosion problem, the feature information is introduced into the traditional LSTM input layer to better characterize the intersymbol interference caused by dispersion in SMF modeling. The simulation results show that the proposed C-LSTM can effectively alleviate the gradient explosion problem with a stable and ultimately lower mean square error (MSE) than traditional LSTM. Compared with the split-step Fourier method (SSFM) and the conditional generative adversarial network (CGAN), the proposed C-LSTM has superior computational complexity. Moreover, due to the sequence correlation learning ability inherent to C-LSTM, coupled with the flexibility of feature information selection, the proposed C-LSTM-aided modeling technique has a higher modeling accuracy than traditional LSTM. Moreover, the C-LSTM-aided modeling technique can be effectively extended to other channel modeling applications with strong sequence correlations.

Design of Non-Isolated Modulation Code With Minimum Hamming Distance of 3 for Bit-Patterned Media-Recording Systems

In bit-patterned media recording (BPMR), the magnetic islands are adjusted closer together to increase the areal density. This makes the bit-error rate (BER) performance of BPMR worse by inter-symbol interference (ISI) and inter-track interference (ITI) from cross-and down-track directions, respectively. To solve the ISI and ITI issues, the data is modulated into non-isolated patterns before storing on the medium of BPMR systems. Furthermore, for improving the non-isolated patterned modulation code, we introduced a method to create the non-isolated patterned code with a minimum Hamming distance (MHD) of 3 instead of 2 as in the previous studies. In our proposed method, firstly, we considered the generator matrix of the Hamming code to create one-dimensional codewords with an MHD of 3. Further, these codewords were converted into two-dimensional codewords, mitigating the isolated pattern. Finally, to create a fast encoder and decoder, we used the multi-layer perceptron to encode the original data into the non-isolated codewords with an MHD of 3. The results show that our proposed model improved the BER performance of the BPMR system.

Adaptive Cancellation of Inter-Symbol Interference in High-Speed Continuous-Time DACs

Adaptive Cancellation of Inter-Symbol Interference in High-Speed Continuous-Time DACs

XPM estimation and compensation in the WDM system based on a low-complexity inner FEC.

In this work, we focus on compensation of inter-channel nonlinearity in optical wavelength division multiplexed (WDM) systems. We consider pre-coding with a high-rate forward error correction (FEC) code and a low-complexity and low-latency decoding and equalization scheme at the receiver. The 2 × 2 multiple-input multiple-output (MIMO) recursive least square (RLS) equalizer is applied to reduce the inter-symbol interference (ISI) caused by the inter-channel nonlinearity, while the decoder improves the quality of the data feedback. Decisions based on feedback reliability have been implemented to prevent error propagation. We demonstrate that our system can readily utilize the inner FEC part of a mainstream concatenated optical FEC designs such as the 400ZR standard FEC. We evaluate the proposed algorithm for the dual-polarization 16QAM and 256QAM optical links. Based on our simulation results, the Q-factor has been increased by 0.36 and 0.67 dB for the 16QAM and 256QAM, respectively. The optimum launch power has been increased by 0.4 dB for both cases.

Performance enhancement of LACO-OFDM BER and PAPR using a K-means algorithm for a VLC system

Layered asymmetrical clipped optical-orthogonal frequency division multiplexing (LACO-OFDM) enhances spectral efficiency by mandating the use of a K-means algorithm in LACO-OFDM (KLACO-OFDM), which enables efficiency gains to nearly double by modulating odd and even subcarriers. The traditional receiver is not sufficiently sophisticated enough to exploit the full potential of LACO-OFDM, thereby restricting its performance. In this paper, a K-means algorithm was used to increase the spectral efficiency of LACO-OFDM by integrating machine learning to cluster the inward signal such that the original locations of the received constellations can be retrieved. A K-means algorithm is used for assigning the received constellation points into their clusters of the ordinary quadrature amplitude modulator constellation points. The new mathematical framework in the proposed scheme is structured to analyze the PAPR and BER performance of LACO-OFDM systems that have been derived. The K-means algorithm development in LACO-OFDM (KLACO-OFDM) has also reduced the intersymbol interference, hence improving the spectral efficiency of LACO-OFDM compared with the conventional system in visible light communication (VLC) systems. BER gains were about 1.2–1.6 dB at 10−3 BER value, which rises from 1.4 to 2 dB for a 10−4 BER value because a lower BER facilitates precise estimation.

A decision feedforward channel equalization system based pseudo affine projection (DFE-PAP) algorithm

This paper addresses the problem of channel equalization in the context of digital communication systems. The important problem in these systems is the inter-symbol interference (ISI) that distorts the signal quality. In this work, we propose a new adaptive equalizer based on a pseudo affine projection technique to equalize the channel. The proposed equalizer uses multi-pseudo affine projections of the channel output to update the filter equalizer. Our proposed solution uses the Decision Feedforward Equalization (DFE) structure to eliminate the ISI and accelerate the convergence speed by the multi-projection technique. Our proposed equalizer is noted DFE-PAP (Decision Feedforward Equalizer based Pseudo Affine Projection). We have done intensive experiments to evaluate the performance of the proposed DFE-PAP equalizer even in the case of dispersive channels. We have used objective and subjective criteria to compare the proposed DFE-PAP with the classical DFE Normalized Least Mean Square (DFE-NLMS) equalizer. All the obtained results show the good performance of the proposed equalizer.

FrFT equalization for underwater sweep-spread communication system

In underwater acoustic channels, multipath propagation and Doppler frequency can distort the received signal and reduce system reliability. In order to effectively combat multipath interference, the Sweep-Spread Carrier (SSC) system using frequency swept signal is proposed, however, the SSC receiver performs well only when the maximum delay spread of path arrivals and the Doppler spread are moderate. In this paper, fractional Fourier transform (FrFT) is applied to channel equalization of the SSC system, which improves the ability to resist the Doppler effect and intersymbol interference (ISI). FrFT can simplify the channel characteristics by selecting an appropriate transform order. We analyze the FrFT equalizer in the SSC system under the zero forcing (ZF) criterion and minimum mean squared error (MMSE) criterion. Compared with typical nonlinear Turbo equalization, FrFT equalizer only requires lower complexity to achieve good performance. The numerical simulation results in bellhop and ray tracing channels and the results of the Wu-yuan Bay test channel show the high robustness of the proposed method in doubly dispersive channels.

Orthogonal Circulant Multiplexing for Bandwidth- Limited Direct-Detected Optical Communication Systems

We propose and investigate a novel orthogonal circulant multiplexing (OCM) technology for bandwidth-limited direct detection (DD) optical systems. We analytically derive that any OCM, i.e. using any orthogonal circulant matrix for multiplexing, can redistribute the noise uniformly across the subcarriers. However, the distribution of inter-symbol interference (ISI) and inter-carrier interference (ICI) strongly depends on the design of OCM. The previously proposed orthogonal chirp division multiplexing (OCDM), although showing better ISI/ICI tolerance than discrete-Fourier-transform spread (DFT-S) orthogonal frequency division multiplexing (OFDM), is a kind of OCM with poorer performance. We propose and analytically reveal that OCM based on chirp-like polyphase sequence (CLPS), general chirp sequence (GCS), sparse CLPS (SCLPS), and sparse GCS (SGCS) can achieve flatter ISI/ICI distribution across subcarriers and so better performance than OCDM in bandwidth-limited DD systems. The optimal parameter vector of the E-parameter CLPS is a Zadoff-Chu sequence while the parameter α in GCS should be larger. The optimal performance can be achieved by either CLPS (or GCS) using a larger E (or α) or SCLPS (or SGCS) with optimized sparsity. ∼110Gbit/s experiments using Mach-Zehnder modulator or electro-absorption modulator and receiver of 10-GHz photodiode or 8-GHz avalanche photodiode are conducted. The results agree with the theory and show that the proposed OCM outperforms conventional OFDM, DFT-S OFDM, and OCDM.

Interference Estimation Using a Recurrent Neural Network Equalizer for Holographic Data Storage Systems

Holographic data storage (HDS) utilizes the unique properties of light for writing and reading two-dimensional (2D) data from holographic media, providing significantly higher densities and faster data transfer rates than traditional storage media for short-term dependencies. With its ability to store terabytes of data in a single crystal, HDS has garnered attention as a promising candidate for next-generation storage technologies. However, the 2D interference caused by hologram dispersion during the reading process poses a significant obstacle to achieving reliable and efficient HDS systems. This study proposes a method for enhancing the accuracy of estimating the 2D intersymbol interference (ISI) using a recurrent neural network (RNN) equalizer for HDS systems. The proposed method leverages the ability of RNNs to model complex and temporal dependencies in data and more accurately estimate the interference caused by ISI and interchannel interference (ICI) in HDS systems. In addition, to recreate the relationship between the samples in the training process, RNN is applied to fields such as computer vision, natural language process, speech recognition, and so on. We evaluated the performance of our proposed method on a simulation model of HDS system and compared it with the previous studies. In the simulations, the proposed method outperformed the previous schemes in terms of bit error rate, indicating its potential for improving the reliability and efficiency of HDS systems.

Channel State Information Based Equalizer Design for Frequency Selective Channels

Abstract—Equalizer design is an extremely critical aspect for wireless networks. This paper presents an approach combining the decision feedback mechanism and successive signal detection to equalize frequency selective channel effects for signals traversing different run-lengths. In this approach, the errors on comparison between the transmitted signal and received signal are fed to the equalizer to adjust the tap weights. Still the irreversible nature of inter symbol interference is a huge challenge due to multi path propagation mechanisms in wireless channels. It is a common observation that signals traversing a smaller path reach the receiver earlier compared to the multi-path component traversing a longer path. Assuming similar shadowing effects, it is seen that fading effects make it difficult to accurately receive long distance MPCs, thereby degrading the BER performance. It has been shown that the proposed system attains almost similar BER performance irrespective of the shadowing effect or run length of the MPCs. Keywords— Multi Path Component (MPC), Inter Symbol Interference (ISI), Adaptive Equalizer, Channel State Information (CSI), , Bit Error Rate (BER), Probability of Error

Temporal Convolutional Network-Based Signal Detection for Magnetotactic Bacteria Communication System.

Molecular communication (MC) aims to use signaling molecules as information carriers to achieve communication between biological entities. However, MC systems severely suffer from inter symbol interference (ISI) and external noise, making it virtually difficult to obtain accurate mathematical models. Specifically, the mathematically intractable channel state information (CSI) of MC motivates the deep learning (DL) based signal detection methods. In this paper, a modified temporal convolutional network (TCN) is proposed for signal detection for a special MC communication system which uses magnetotactic bacteria (MTB) as information carriers. Results show that the TCN-based detector demonstrates the best overall performance. In particular, it achieves better bit error rate (BER) performance than sub-optimal maximum a posteriori (MAP) and deep neural network (DNN) based detectors. However, it behaves similarly to the bidirectional long short term memory (BiLSTM) based detector that has been previously proposed and performs worse than the optimal MAP detector. When both BER performance and computational complexity are taken into account, the proposed TCN-based detector outperforms BiLSTM-based detectors. Furthermore, in terms of robustness evaluation, the proposed TCN-based detector outperforms all other DL-based detectors.

Simplified THP and M-Log-MAP Decoder Based Faster Than Nyquist Signaling for Intra-Datacenter Interconnect

In this paper, a joint application of simplified Tomlinson-Harashima precoding (THP) and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</i> -log-maximum a posteriori probability ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</i> -log-MAP) decoder at transceivers is proposed for low complexity faster than Nyquist (FTN) 4-ary pulse amplitude modulation (PAM4) signaling. A THP with only two taps is applied at the transmitter for FTN-induced inter-symbol interference elimination and equalization-induced noise amplification issue mitigation, which effectively relieves the burden of the receiver. At the receiver, a low complexity M-log-MAP decoder is equipped for residual impairments cancellation, thus a feedback channel is not required to accurately obtain the channel state information for the transmitter. Taking advantage of this collaborative approach, the proposed scheme performs much better than applying the two schemes separately. We experimentally demonstrate the proposed scheme in 70, 75, and 80GBaud PAM4 systems with a 32-GHz brick-wall filter, corresponding to 0.914, 0.853, and 0.8 FTN compression factor, respectively. The results show that the 80GBaud PAM4 signal is successfully transmitted over 2-km single mode fiber with the bit-error-rate (BER) under the 7% hard-decision forward error correction (HD-FEC) threshold of 3.8×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−3</sup> . It is also observed that the proposed scheme shows about 0.7dB receiver sensitivity improvement compared to the error propagation-free decision feedback equalizer, namely the performance upper bound of the THP, at BER of 7% HD-FEC threshold in a 75GBaud FTN PAM4 system. According to the experimental results, the proposed scheme is a promising solution for bandwidth-starved low-cost intra-datacenter interconnect.

Study and Analysis of OFDM under Rayleigh fading Channel using Various Modulation Methods

Orthogonal Frequency Division Multiplexing (OFDM) is well recognized as a very efficient multicarrier technology. OFDM has witnessed a significant increase in its utilization within contemporary wideband digital communication systems. The technology possesses several notable benefits, including its capacity to effectively manage challenging channel circumstances, optimize spectrum utilization, mitigate inter symbol interference (ISI), and support high data transmission rates. Hence, it has been employed in several forthcoming wired and wireless communication systems, such as 4G LTE mobile communications. This work primarily concentrates on the performance assessment and investigation of the OFDM system in the presence of Rayleigh fading channels. By analyzing the outcomes of simulations, we may gain insights into various impacts and signal-to-noise ratios (SNRs). In order to determine their respective signal delivery capabilities, channels are compared and ranked. The evaluation of system performance involves assessing the quality of received signals, including factors like as signal quality, bit-error rates (BERs), and peak signal-to-noise ratios (PSNRs).

8.8 Gbps PAM-4 visible light communication link using an external modulator and a neural network equalizer.

This Letter presents an experimental demonstration of a visible light communication system utilizing a LiNbO3 external modulator to support the transmission of pulse amplitude modulation (PAM)-4 signals. To solve the problem of the low-frequency fluctuations and inter-symbol interference (ISI) introduced by the external modulator-based system, a neural network with a low-frequency signal as the second label (LFNN) is proposed. A data rate of 8.8 Gbps using PAM-4 is experimentally achieved under the 7% hard-decision forward error correction (HD-FEC) bit-error-ratio (BER) limit of 3.8 × 10-3. To the best of our knowledge, this work represents the highest transmission data rate achieved thus far using external modulation in visible light communication systems.

Non-line-of-sight optical camera communications based on CPWM and a convolutional neural network.

Non-line-of-sight (NLOS) optical camera communications (OCC) exhibit greater link availability and mobility than line-of-sight links, which are more susceptible to blocking and shadowing. In this work, we propose an NLOS OCC system, where the data signal is mapped into color pulse width modulation (CPWM) symbols prior to transmission using a red-, green-, and blue light-emitting diode. A convolutional-neural-network-based receiver is used to demodulate the CPWM signal. Based on experimental results, the proposed scheme effectively mitigates the effects of diffuse reflection induced intersymbol interference, resulting in an increased data transmission rate to 7.2kbps over a link span of more than 2m, which is typical for indoor applications.