Block Equalization Research Articles

A predictive model with time-varying delays employing channel equalization convolutional neural network for NOx emissions in flexible power generation

This study aims to predict NOx (i.e. NO + NO2) emissions at the selective catalytic reduction inlet from coal-fired boilers. It develops a lightweight predictive model that can be adapted to the generation system dominated by renewable energy with fluctuating power. The random forest algorithm was first used to select the input variables from the auxiliary variables. The maximum information coefficient algorithm was then used to estimate the time delay between the input variables and the NOx emissions. Afterwards, to overcome the “channel collapse” issue in convolutional neural networks (CNNs), a Channel Equalization block (CE-Block) was proposed to activate the suppressed channels, and a lightweight network, referred to as CE-CNN, was designed by fusing a CNN with the CE-Block. Finally, a dynamic NOx emissions prediction model was developed employing the CE-CNN, and the model was evaluated using real data from a 600 MW down-fired boiler. The results showed that the dimensionality reduction policy decreased the model training time by 21.74 %, and the analysis of the time delay decreased the RMSE by 7.31 %. Compared to the baseline model 3-layer CNN, the proposed model achieves performance improvements of 20.97 %, 22.11 %, and 3.48 % in terms of RMSE, MAE, and R2, respectively.

PoiseNet: Dealing With Data Imbalance in DensePose

Data imbalance, a foundational problem in machine learning, has received little attention in DensePose and has become one of the main obstacles in front of existing methods. We reveal two imbalances in DensePose: inter-surface imbalance and intra-surface imbalance. First, the human body parts can be of various sizes, making 3D surfaces contain different numbers of annotations. Classifiers trained on such unbalanced data suffer a decline on surfaces with fewer annotations. Second, annotations within each surface are not uniformly distributed. Regressors trained on such uneven data suffer a decline in 3D surface areas with sparse annotations. To solve these imbalances, we propose PoiseNet which integrates adaptive equalization loss (AEQL) and block balanced localization (BBL). Specifically, to address the inter-surface imbalance, AEQL adaptively reweights surfaces based on the number of annotations and the classification scores. BBL alleviates the intra-surface imbalance by unevenly blocking each surface according to annotation distribution. Experimental results on the DensePose-COCO dataset show that our PoiseNet surpasses baselines by up to 1.4 AP.

Low Complexity Block Equalizer for OTFS Based on Expectation Propagation

Orthogonal time-frequency space signaling (OTFS) is a novel delay-Doppler (DD) domain modulation scheme that has the potential to exploit two-dimensional time-frequency (TF) diversity. To realize such diversity while retaining low complexity, this letter develops an efficient block equalizer for OFDM-based OTFS via expectation propagation (EP). In particular, the DD-domain channel matrix is decomposed as a function of symbol interval, which has the form of the superimposed diagonal-times-doubly circulant matrices. We exploit such decomposition to facilitate the computation of the moment-matching step for channel factor update, reducing the overall equalizer complexity order from cubic to log-linear while achieving almost the same bit-error-rate (BER) performance as compared to the exact computing case.

Iterative Equalization of STSK-Aided Single-Carrier Systems: Design and Analysis With Non-Ideal Power Amplifiers

A plethora of new applications will be enabled by next generation wireless networks. These demand sophisticated medium access control and physical layer protocols in order to fulfill the requirements in terms of spectral efficiency, bit error rate (BER), energy efficiency, reliability, and security, among others. This paper develops an advanced space-time multiple-input, multiple-output (MIMO) solution that builds on the concept of space-time shift keying (STSK) for single-carrier frequency domain equalization (SC-FDE). STSK-aided SC-FDE, or SSF, ensures space-time and frequency diversity in dispersive channels, but can only support suboptimal linear receiver schemes. We therefore introduce a turbo equalizer for SSF in frequency-selective multipath channels. It enables inter-symbol-interference cancellation by means of iterative space-time processing. We coin it the iterative space-time block equalizer (SSF-ISTBE). We provide the mathematical formulation for the proposed SSF-ISTBE framework in non-linear channel conditions. We demonstrate that the SSF-ISTBE achieves a substantial 4 dB gain in terms of BER over the linear minimum mean square error equalizer while significantly reducing the computational complexity of the optimal maximum likelihood SSF. When considering practical transceivers, in particular non-linear power amplifiers, the gain of the SSF-ISTBE becomes more prominent over state-of-the-art approaches, demonstrating its robustness against non-linear distortion.

Power-Ordered NOMA with Massive MIMO for 5G Systems

The aim of this article is to study the conventional and cooperative power-order Non-Orthogonal Multiple Access (NOMA) using the Single Carrier with Frequency Domain Equalization (SC-FDE) block transmission technique, associated with massive Multiple-Input Multiple-Output (MIMO), evidencing its added value in terms of spectral efficiency of such combined scheme. The new services provided by Fifth Generation of Cellular Communications (5G) are supported by new techniques, such as millimeter waves (mm-wave), alongside the conventional centimeter waves and by massive MIMO (m-MIMO) technology. NOMA is expected to be incorporated in future releases of 5G, as it tends to achieve a capacity gain, highly required for the massive number of Internet of things (IoT) devices, namely to support an efficient reuse of limited spectrum. This article shows that the combination of conventional and cooperative NOMA with m-MIMO and SC-FDE, tends to achieve capacity gains, while the performance only suffers a moderate degradation, being an acceptable alternative for future evolutions of 5G. Moreover, it is shown that Cooperative NOMA tends to outperform Conventional NOMA. Moreover, this article shows that the Maximum Ratio Combiner (MRC) receiver is very well fitted to be combined with NOMA and m-MIMO, as it achieves a good performance while reducing the receiver complexity.

On the 5G and Beyond

This article provides an overview of the fifth generation of cellular communications (5G) and beyond. It presents the transmission techniques of current 5G communications and those expected of future developments, namely a brief study of non-orthogonal multiple access (NOMA) using the single carrier with frequency domain equalization (SC-FDE) block transmission technique, evidencing its added value in terms of spectral efficiency. An introduction to the sixth generation of cellular communications (6G) is also provided. The insertion of 5G and 6G within the Fourth Industrial Revolution framework (also known as Industry 4.0) is also dealt with. Consisting of a change in paradigm, when compared to previous generations, 5G supports a myriad of new services based on the Internet of things (IoT) and on vehicle-to-vehicle (V2V) communications, supporting technologies such as autonomous driving, smart cities, and remote surgery. The new services provided by 5G are supported by new techniques, such as millimeter waves (mm-wave), in addition to traditional microwave communication, and by massive multiple-input multiple-output (m-MIMO) technology. These techniques were not employed in the fourth generation of cellular communications (4G). While 5G plays an important role in the initial implementation of the Fourth Industrial Revolution, 6G will address a number of new services such as virtual reality (VR), augmented reality (AR), holographic services, the advanced Internet of things (IoT), AI-infused applications, wireless brain–computer interaction (BCI), and mobility at higher speeds. The current research on systems beyond 5G indicates that these applications shall be supported by new MIMO techniques and make use of terahertz (THz) bands.

Low-Complexity Equalization of MIMO-OSDM

Orthogonal signal-division multiplexing (OSDM) is an attractive alternative to conventional orthogonal frequency-division multiplexing (OFDM) due to its enhanced ability in peak-to-average power ratio (PAPR) reduction. Combining OSDM with multiple-input multiple-output (MIMO) signaling has the potential to achieve high spectral and power efficiency. However, a direct channel equalization in this case incurs a cubic complexity, which may be expensive for practical use. To solve the problem, low-complexity per-vector and block equalization algorithms of MIMO-OSDM are proposed in this paper for time-invariant and time-varying channels, respectively. By exploiting the channel matrix structures, these algorithms have only a linear complexity in the transformed domain. Simulation results demonstrate their validity and the related performance comparisons.

Constructive Signal Approximations for Fast Transient Simulation of Coupled Channels

This paper addresses the problem of fast transient simulation of high-speed coupled channels driven by transceivers that include transmitter feed-forward equalization (TX-FFE). Practical circuit hardware implementations of such drivers may not be correctly represented by industry-standard algorithmic modeling interfaces (AMIs), which are usually based on ideal digital finite impulse response filters. In particular, slow transients may arise when aggressive FFE is activated and particular switching sequences significantly stress local voltage regulators integrated in the output buffers. In this paper, we model this effect using a constructive hierarchical approximation of the analog waveforms that form a linearized vector Thevenin or Norton representation of the driver. This representation enables the accurate simulation of coupled channels including both differential- and common-mode signals. Analog waveforms at the receiver input are readily obtained by standard time-frequency transformations while including channel characteristics and any additional linear equalization block, if present. This proposed framework is compatible with industry-standard AMIs, extending their scope to coupled channels with nonideal TX-FFE circuit blocks. Eye diagrams and transient waveforms corresponding to millions of bits are computed in few seconds using a nonoptimized software implementation. Random jitter and crosstalk are seemlessly included as in standard AMI frameworks. The results of various numerical experiments on commercial transceivers are reported in this paper, confirming both the accuracy and the efficiency of the proposed framework.

Vehicle detection and classification using LTE‐CommSense

We demonstrated a vehicle detection and classification method based on Long Term Evolution (LTE) communication infrastructure based environment sensing instrument, termed as LTE-CommSense by the authors. This technology is a novel passive sensing system which focuses on the reference signals embedded in the sub-frames of LTE resource grid. It compares the received signal with the expected reference signal, extracts the evaluated channel state information (CSI) and analyzes it to estimate the change in the environment. For vehicle detection and subsequent classification, our setup is similar to a passive radar in forward scattering radar (FSR) mode. Instead of performing the radio frequency (RF) signals directly, we take advantage of the processing that happens in a LTE receiver user equipment (UE). We tap into the channel estimation and equalization block and extract the CSI value. CSI value reflects the property of the communication channel between communication base station (eNodeB) and UE. We use CSI values for with and vehicle and without vehicle case in outdoor open road environment. Being a receiver only system, there is no need for any transmission and related regulations. Therefore, this system is low cost, power efficient and difficult to detect. Also, most of its processing will be done by the existing LTE communication receiver (UE). In this paper, we establish our claim by analyzing field-collected data. Live LTE downlink (DL) signal is captured using modeled LTE UE using software defined radio (SDR). The detection analysis and classification performance shows promising results and ascertains that, LTE-CommSense is capable of detection and classification of different types of vehicles in outdoor road environment.

GSM-based commsense system to measure and estimate environmental changes

Facilitating the coexistence of radar systems with communication systems has been a major area of research in radar engineering. The current work presents a new way to sense the environment using the channel equalization block of existing communication systems. We have named this system CommSense. In the current paper we demonstrate the feasibility of the system using Global System for Mobile Communications (GSM) signals. The implementation has been done using open-source Software Defined Radio (SDR) environment. In the preliminary results obtained in our work we show that it is possible to distinguish environmental changes using the proposed system. The major advantage of the system is that it is inexpensive as channel estimation is an inherent block in any communication system and hence the added cost to make it work as an environment sensor is minimal. The major challenge, on which we are continuing our work, is how to characterize the features in the environmental changes. This is an acute challenge given the fact that the bandwidth available is narrow and the system is inherently a forward looking radar. However the initial results, as shown in this paper, are encouraging and we intend to use an application specific instrumentation (ASIN) scheme to distinguish the environmental changes.

Pre-Channel Equalization and Distributed Beamforming in Asynchronous Single-Carrier Bi-Directional Relay Networks

We consider a single-carrier asynchronous two-way amplify-and-forward relay network, where two single-antenna transceivers exchange information with the help of several single-antenna relay nodes. We assume that the propagation delay of each relaying path, originating from one transceiver, going through a certain relay, and ending at the other transceiver, can be different from those of the other relaying paths. This assumption turns the end-to-end link into a multi-path channel, which produces inter-symbol-interference at the transceivers. In a block transmission/reception scheme, ISI results in inter-block-interference (IBI) between successive transmitted blocks. To combat IBI, cyclic prefix insertion and deletion as well as pre-channel block equalization are used at the two transceivers. Assuming a limited total transmit power budget, we minimize the total mean squared error between the transmitted and received signals at both transceivers by optimally obtaining the transceivers’ transmit powers and the relay beamforming weight vector as well as the pre-channel block equalizers at the transceivers. We prove that this optimization problem leads to a relay selection scheme, where only the relays contributing to one tap of the end-to-end channel impulse response, are turned on and the remaining relays are switched off. We present an efficient method to obtain the optimal values of the design parameters. Our simulation results show that compared to post-channel equalization, the proposed pre-channel equalization technique has the same performance as the post-channel equalization approach does, when the total available power is relatively low compared to the noise power at the transceivers, while offering receiver simplicity.

Multi-Feedback Interference Cancellation Algorithms for OFDM Systems over Doubly-Selective Channels

Orthogonal frequency-division multiplexing (OFDM) systems over rapidly time varying channels may suffer from significant inter-carrier interference (ICI), which destroys the orthogonality between subcarriers and degrades the detection performance. Without sufficient ICI suppression, OFDM systems usually experience an error floor. According to the approximate matched filter bound (AMFB), the error floor in a coded OFDM system is not irreducible. In this work, we introduce novel multiple feedback matched filter (MBMF)-based ICI cancellation receivers. Based on the output of a novel MBMF scheme, the approach employs a multiple ICI cancellation strategy with or without signal-to-interference-plus-noise-ratio (SINR) ordering. The developed schemes can significantly improve the performance and remove the error floor with a negligible complexity increase. Given the multiple cancellation approach, we compare the SINR performance of the MBMF outputs with that employing single feedback and show that the SINR performance with multiple cancellation candidates is improved over that with a single one at practical SNR values. Additionally, for time-varying channels, we exploit partial fast Fourier transform (PFFT) by splitting one OFDM symbol into multiple segments; the channel state is separately estimated by least-squares (LS) methods without inserting more pilots. Simulation results demonstrate the superiority of the proposed methods over serial and block equalizers and the robustness to the Doppler effects compared to conventional single-segment method.

Improvement in the Performance of WiMAX with Channel Equalizers and Space Time Block Coding Techniques Using Simulink

WiMAX is a coming forth broadband wireless technology that considered as one of the most prominent solution to provide high speed data services. This paper addresses the design of WiMAX end to end physical layer (PHY) in Simulink with channel equalization and space time block coding techniques. The authors analyzed the performance of WiMAX PHY with decision feedback equalizers (DFE), linear equalizers and blind equalizers over AWGN and multipath faded channels. Results include MISO channel power spectral density (PSD), antenna amplitude/PSD/phase difference, multipath faded and AWGN channel's effect on the transmitted signal and the performance of proposed equalizers on the received signals. This paper concluded that the linear equalizers have higher frame error rates (FER) than DFE. However, blind equalizers have higher FERs compared to conventional equalizers with better spectral efficiency as they need no training sequence.

Signal to Interference Ratio Based Antenna Selection for Spatial Multiplexing

To achieve reliable high throughput wireless links spatial multiplexing and diversity modes of multiple-input multiple-output are used in combination. Antenna selection (AS) has minimal complexity among other spatial diversity methods. Bell Labs Layered Space Time (BLAST) is a low complexity spatial multiplexing technique, especially when minimum mean squared error (MMSE) receivers are considered. However, optimal AS is known to be computationally intensive when used along with spatial multiplexing, since an orthogonal subset channel matrix is required to be found. Known suboptimal algorithms are still relatively complex and incur performance penalties. In this paper we propose a low complexity AS algorithm for BLAST. It uses an approximate signal to interference ratio metric as a heuristic measure to select a given number of antennas. It produces the selection choice after a single iteration only. A structure to reduce hardware complexity by reusing the MMSE equalizer block is also proposed. Such reuse can be applied to several AS algorithms. We compare the performance of the proposed algorithm against others using mean spectral efficiency (SE), 10 % outage SE, symbol error rate performance and implementation complexity. The impact of approximate expressions used in the proposed algorithm is also analyzed.

Iterative estimation of doubly selective underwater acoustic channel using basis expansion models

An iterative channel estimation scheme is proposed for orthogonal frequency division multiplexing (OFDM) systems over doubly selective underwater acoustic channels. The channel estimator is developed based on the basis expansion model (BEM) with two different types of basis functions, complex exponential (CE) basis and discrete prolate spheroidal sequences (DPSS). Considering the different Doppler characteristics for each cluster, we use cluster-specific parameters in the BEM for the most significant taps, such that the number of unknowns during channel estimation can be considerably reduced. The frequency domain received samples are expressed in terms of the model coefficients of the most significant taps. The channel estimator operates in an iterative, decision-directed fashion. At the first iteration, it utilizes only pilot symbols. After the first iteration, the estimator also uses the symbol decisions produced by a linear minimum mean squared error (LMMSE) block equalizer, in addition to the pilot symbols. We verify the bit-error-rate (BER) performance of the OFDM system over a simulated underwater acoustic channel based on Monterey-Miami Parabolic Equation modeling. It is shown that the LMMSE equalizer with the BEM-based channel estimators and the one-tap equalizer with perfect channel state information have similar BER performances. Both the proposed BEM-based channel estimation schemes perform much better than the basic matching pursuit method, a classic sparsity-aware channel estimation technique.

Linear Block Equalizers in Rayleigh Fading Channel with Normalized Channel Impulse Response

Linear adaptive equalizers are widely used in wireless communication systems in order to reduce the effects of the channel distortion. Various researchers have used linear block equalizers for different modulations techniques. In this paper the BER performance of different M-PSK and M-QAM modulations with the block based LMS and RLS linear equalizers are compared over the flat and frequency selective Rayleigh fading channel. For achieving better performance the Rayleigh channel is modeled with four multipath channels and normalized channel impulse response under the presence of AWGN noise. The maximum Doppler shifts frequencies are varied for evaluating the performance of the equalizers. Using the normalized channel impulse response improves the BER performance of the communication system for the higher values of M as 512 and 1024. Transmitted and received constellation diagrams are also compared for different equalizers. Performance is also compared for the different equalizer weights and block sizes. General Terms Adaptive Equalizers, Rayleigh fading channel, Wireless communication

A General Framework for Optimum Iterative Blockwise Equalization of Single Carrier MIMO Systems and Asymptotic Performance Analysis

The paper proposes a general framework for both time-domain (TD) and frequency-domain (FD) iterative blockwise equalization in single carrier (SC) wideband multiple-input multiple-output (MIMO) channels. First, a novel turbo blockwise operating equalizer structure is proposed by jointly optimizing the feed-forward and feedback filters at each iteration based on the minimum mean squared error (MMSE) criterion. Optimization of the filter coefficients, utilized for feed-forward equalization and decision feedback, is performed in both time and frequency domains, and the equivalence between them is established by unifying the iterative block equalization with the feed-forward and feedback filters in various domains. The corresponding filters are obtained analytically in a closed form as a solution of the constrained Wiener-Hopf equation with the use of average reliability information. Second, asymptotic performance and diversity analysis of the proposed single carrier frequency domain equalizer (SC-FDE) is carried out that leads to insights on the structures of the filters in the high SNR regime. Furthermore, we elaborate on the rate and diversity tradeoff of the space-time coded SC-FDE based on the proposed equalizer structure and the space-frequency coded OFDM systems. Performance comparison between the proposed SC-FDE scheme and OFDM is made. The proposed SC-FDE scheme performs very close to the genie-aided performance bounds and better than OFDM based transmission.

Linear and Nonlinear Time Domain Block Equalizers on MIMO Frequency Selective Channels

Single-Carrier (SC) transmission with the same bandwidth as Multi-Carrier (MC) transmission (such as OFDM) may have far shorter symbol duration and is considered to be more robust against time selective fading. In this paper, we proposed the novel equalization and signal separation schemes in time domain for short block length transmission, i.e., Block Linear Equalization (BLE) and Block Nonlinear Equalization (BNLE) on MIMO frequency selective fading channels. The proposed BLE uses the MMSE based inverse matrix in time domain and the BNLE utilizes the QRD-M (QR Decomposition with M algorithm) with appropriate receiver complexity. We compared the computational complexity among the conventional SC-FDE (Frequency Domain Equalization) scheme and the proposed equalizers. We also used the Low-Density Parity Check (LDPC) decoder concatenated to the proposed BLE and BNLE.

Frequency-Domain Equalization for Orthogonal and Quasi-Orthogonal STBCs over Frequency-Selective Wireless and Power-Line Channels

In recent years, combination of single-carrier frequency-domain equalization (SC-FDE) and space-time block coding/code (STBC) techniques to exploit the advantages of both, has received a great attention. In this paper we propose new techniques for combining SC-FDE with orthogonal and Quasi-orthogonal STBCs applicable to any number of transmit antennas. For Quasi-orthogonal STBC we first propose a new structure for codes with four transmit antennas and then extend it to higher numbers. We convert Quasi-orthogonal system to two equivalent orthogonal subsystems and equalize and decode these subsystems based on our proposed procedure for orthogonal codes. Finally, we present our simulation results for different frequency-selective wireless and power-line channels and show that a significant SNR gain is achieved when SC-FDE is combined with diversity techniques.

Time-Domain Block and Per-Tone Equalization for MIMO–OFDM in Shallow Underwater Acoustic Communication

Shallow underwater acoustic (UWA) channel exhibits rapid temporal variations, extensive multipath spreads, and severe frequency-dependent attenuations. So, high data rate communication with high spectral efficiency in this challenging medium requires efficient system design. Multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO---OFDM) is a promising solution for reliable transmission over highly dispersive channels. In this paper, we study the equalization of shallow UWA channels when a MIMO---OFDM transmission scheme is used. We address simultaneously the long multipath spread and rapid temporal variations of the channel. These features lead to interblock interference (IBI) along with intercarrier interference (ICI), thereby degrading the system performance. We describe the underwater channel using a general basis expansion model (BEM), and propose time-domain block equalization techniques to jointly eliminate the IBI and ICI. The block equalizers are derived based on minimum mean-square error and zero-forcing criteria. We also develop a novel approach to design two time-domain per-tone equalizers, which minimize bit error rate or mean-square error in each subcarrier. We simulate a typical shallow UWA channel to demonstrate the desirable performance of the proposed equalization techniques in Rayleigh and Rician fading channels.