Doubly-selective Fading Channels Research Articles

Pipelined Neural Network Assisted Mobility Speed Estimation Over Doubly-Selective Fading Channels

The speed estimation has been widely used for tracking mobile device locations, providing essential information in location/mobility-aware communications, enhancing received signal quality/robustness, and reducing energy consumption and latency. Deep learning can be used to improve the performance constrained by signal/system model. This work focuses on the issues on machine learning (ML) based speed estimation using primary synchronous signal (PSS), which is embedded in the 5G standards, over general time-variant multipath channels. Aiming to reduce the complexity involved in the ML algorithms for the speed estimation in mobile networks, we propose a pipelined ML algorithm to decompose the original ML model into several smaller ones. The advantages of the proposed convolutional neural network (CNN) based approach have been verified by simulations.

2D Off-Grid Decomposition and SBL Combination for OTFS Channel Estimation

Orthogonal time-frequency space (OTFS) is a promising technique for high mobility wireless communications, as it approaches a sparse representation of doubly-selective fading channel and can obtain delay-Doppler (DD) diversity gain. However, in practical OTFS systems, fractional channel parameter is a great challenge and will seriously deteriorates the sparsity and the performance of channel estimation. In this paper, we propose a novel channel estimation scheme for doubly selective channel in the presence of both fractional Doppler and fractional delay. First, we analyze the input-output relationship of single-input single-output (SISO) OTFS system based on the integer sampling DD grid, then extend it to the fractional DD grid. Compared with the integer DD domain, the model in the fractional DD domain is sparser and more accurate. Based on our analysis, two kinds of off-grid models, i.e., doubly fractional model and mixed one- and two-dimensional (1&2D) fractional models are proposed and compared. The mixed 1&2D fractional model has an advantage of low complexity, but encounters a tandem off-grid distortion. To tackle this distortion problem, as well as to balance the accuracy and the computational workload, a novel two dimensional off-grid decomposition and combination scheme is proposed based on the doubly and mixed 1&2D fractional model. Simulation results demonstrate the effectiveness and superiority of the proposed channel estimation schemes, compared with the existing work for OTFS systems under doubly selective channels.

Joint Compensation of TX/RX IQ Imbalance and Channel Parameters for OTSM Systems

Orthogonal time sequency multiplexing (OTSM), robust to doubly-selective fading channel, performs similar to orthogonal time frequency space (OTFS) system with less modulation/demodulation complexity. Direct conversion OTSM system suffers from hardware impairments such as in-phase and quadrature phase (IQ) imbalance at the transmitter (TX) and receiver (RX). At high frequencies, hardware imperfections are inevitable and should be compensated for better performance. In this Letter, we propose joint estimation of TX and RX IQ imbalance and estimate channel parameters in the delay time domain using pseudo noise based training sequence approach. The mean square error of the estimated channel parameters reduce with increase in training sequence length and power. With matched filtered Gauss-Seidel iterative method of detection of low complexity, it is shown that the compensated system performs close to ideal system under fractional delay and fractional Doppler.

Learning-Based Channel Estimation and Phase Noise Compensation in Doubly-Selective Channels

In this letter, we propose a learning based channel estimation scheme for orthogonal frequency division multiplexing (OFDM) systems in the presence of phase noise in doubly-selective fading channels. Two-dimensional (2D) convolutional neural networks (CNNs) are employed for effective training and tracking of channel variation in both frequency as well as time domain. The proposed network learns and estimates the channel coefficients in the entire time-frequency (TF) grid based on pilots sparsely populated in the TF grid. In order to make the network robust to phase noise (PN) impairment, a novel training scheme where the training data is rotated by random phases before being fed to the network is employed. Further, using the estimated channel coefficients, a simple and effective PN estimation and compensation scheme is devised. Numerical results demonstrate that the proposed network and PN compensation scheme achieve robust OFDM performance in the presence of phase noise.

Analysis, Estimation and Compensation of Hardware Impairments for CP-OTFS Systems

Orthogonal time frequency space (OTFS) waveform, which is robust to doubly-selective fading channels is a strong contender for the Fifth generation (5G) communications. At high frequencies, hardware imperfections are prominent in practice at the transceivers. In this letter, we consider impairments such as carrier frequency offset (CFO), direct current (DC) offset and in-phase and quadrature (IQ) imbalance at the transmitter (Tx) and receiver (Rx) for cyclic prefix (CP) OTFS system. We derive the input-output (I/O) relation in the delay-Doppler (DD) domain under these impairments and show that due to the DC offset and IQ imbalance, image Doppler interference (IDI) appears along the Doppler domain and the CFO becomes part of the channel parameters. We estimate impairment parameters in the DD domain and compensate these at Tx and Rx in the time domain. The normalized mean square error (NMSE) of the estimated imbalance parameters are evaluated and it is observed that NMSE reduces with increase in, pilot power, number of Doppler bins and with windowing techniques applied in time-frequency (TF) domain.

Joint Activity and Blind Information Detection for UAV-Assisted Massive IoT Access

Grant-free non-coherent index-modulation (NC-IM) has been recently considered as an efficient massive access scheme for enabling cost- and energy-limited Internet-of-Things (IoT) devices that transmit small data packets. This paper investigates the grant-free NC-IM scheme combined with orthogonal frequency division multiplexing for applicant to unmanned aerial vehicle (UAV)-based massive IoT access. Specifically, each device is assigned a unique non-orthogonal signature sequence codebook. Each active device transmits one of its signature sequences in the given time-frequency resources, by modulating the information in the index of the transmitted signature sequence. For small-scale multiple-input multiple-output (MIMO) deployed at the UAV-based aerial base station (BS), by jointly exploiting the space-time-frequency domain device activity, we propose a computationally efficient space-time-frequency joint activity and blind information detection (JABID) algorithm with significantly improved detection performance. Furthermore, for large-scale MIMO deployed at the aerial BS, by leveraging the sparsity of the virtual angular-domain channels, we propose an angular-domain based JABID algorithm for improving the system performance with reduced access latency. In addition, for the case of high mobility IoT devices and/or UAVs, we introduce a time-frequency spread transmission (TFST) strategy for the proposed JABID algorithms to combat doubly-selective fading channels. Finally, extensive simulation results are illustrated to verify the superiority of the proposed algorithms and the TFST strategy over known state-of-the-art algorithms.

Time-domain dual component computation diversity based on generalized hybrid carrier

In this paper, the concept of computation diversity is proposed by employing generalized hybrid carrier (GHC) system. The signal is backed up by transform-domain computation to enhance the anti-fading capability. Theoretical analysis is presented to demonstrate the superiority of the proposed method. Numerical simulations in doubly-selective fading channels are provided to verify the results. The bit error rate (BER) performance is guaranteed with a small computational complexity increment. The proposed method not only extends the new diversity dimension, but also improves the diversity gain of the system without occupying additional wireless resources. Moreover, the proposed method shows good adaptability with single carrier modulation and improves diversity performance. As the simulation results shown, time-domain dual component computation diversity (TDC-CD) has 1dB BER gain and 0.1 diversity gain at high signal-to-noise ratio, and single carrier system with TDC-CD achieves 2dB BER gain at 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−4</sup> .

Maximum Likelihood Time Synchronization for Zero-Padded OFDM

Existing Orthogonal Frequency-Division Multiplexing (OFDM) variants based on cyclic prefix (CP) allow for efficient time synchronization, but suffer from lower power efficiency compared to zero-padded (ZP)-OFDM. Because of its power efficiency, ZP-OFDM is considered as an appealing solution for the emerging low-power wireless systems. However, in the absence of CP, time synchronization in ZP-OFDM is a very challenging task. In this paper, the non-data-aided (NDA) maximum-likelihood (ML) time synchronization for ZP-OFDM is analytically derived. We show that the optimal NDA-ML synchronization algorithm offers a high lock-in probability and can be efficiently implemented using Monte Carlo sampling (MCS) technique in combination with golden-section search. To obtain the optimal NDA-ML time synchronization algorithm, we first derive a closed-form expression for the joint probability density function (PDF) of the received ZP-OFDM samples in frequency-selective fading channels. The derived expression is valid for doubly-selective fading channels with mobile users as well. The performance of the proposed synchronization algorithm is evaluated under various practical settings through simulation experiments. It is shown that the proposed optimal NDA-ML synchronization algorithm and its MCS implementation substantially outperforms existing algorithms in terms of lock-in probability.

HCM Successive Transmission Scheme With Banded MMSE Equalization Based on Fast Convolution Over Doubly-Selective Fading Channels

A novel hybrid carrier modulation (HCM) successive transmission scheme with banded minimum mean square error (MMSE) equalization based on fast convolution (FC) is proposed and analyzed. The proposed scheme not only further suppresses the residual interference of banded MMSE equalization by the overlap-save operation of FC, but improves the spectral efficiency by removing the cyclic prefix. Additionally, the proposed HCM scheme with particular orders outperforms the single carrier modulation and the multicarrier modulation transmission scheme. Theoretical analysis and numerical simulations are presented to demonstrate the superiority of the proposed scheme at a moderate complexity over doubly-selective fading channels.

Novel Adaptive Distributed Compressed Sensing Algorithm for Estimating Channels in Doubly-Selective Fading OFDM Systems

Doubly-selective (DS) fading channel is often occurred in many orthogonal frequency division multiplexing (OFDM) communication systems, such as high-speed rail communication systems and underwater acoustic (UWA) wireless networks. It is challenging to provide an accurate and fast estimation over the doubly-selective channel, due to the strong Doppler shift. This paper addresses the doubly selective channel estimation problem based on complex exponential basis expansion model (CE-BEM) in OFDM systems from the perspective of distributed compressive sensing (DCS). We propose a novel DCS-based improved sparsity adaptive matching pursuit (DCS-IMSAMP) algorithm. The advantage of the proposed algorithm is that it can exploit the joint channel sparsity information using dynamic threshold, variable step size and tailoring mechanism. Simulation results show that the proposed algorithm achieves 5dB performance gain with faster operation speed, in comparison with traditional DCS-based sparsity adaptive matching pursuit (DCS-SAMP) algorithm.

OFDM symbol detection integrated with channel multipath gains estimation for doubly-selective fading channels

Orthogonal Frequency Division Multiplexing (OFDM) is a technique for wideband transmission that is commonly used in modern wireless communication systems because of its good performance over frequency selective channels. However OFDM systems are sensitive to channel time variations resulting in Inter-Carrier Interference (ICI), that without suitable detection methods can degrade performance significantly. Channel State Information (CSI) is essential to various OFDM detection schemes, and its acquisition is a critical factor over time varying channels. This work considers a Kalman filter channel multipath gains estimation technique for time varying environments, integrated with a novel detection scheme for OFDM based on a Sphere Decoding (SD) algorithm derived to exploit the banded structure of the channel matrix. This combined scheme employs decision–feedback from the SD requiring only a low pilot symbol density, and hence improves bandwidth efficiency. Three techniques for integrating the Kalman filter operating in decision–feedback mode, with SD data detection that produces these decisions, are considered in this paper. When compared with other competing schemes, this integrated symbol detection and channel multipath gains estimation approach for OFDM provides performance advantages over time varying channels. Furthermore, it is shown that for moderate Doppler shifts the degradation that carrier phase noise induces in this scheme is small.

Differential Orthogonal Space-Time Block Coding Modulation for Time-Variant Underwater Acoustic Channels

Reliable underwater acoustic (UWA) communications are challenging since the channels are well known to be doubly selective in both time and frequency domains. The doubly-selective fading UWA channels, however, also provide double diversity gains. In addition, multiple transducers and/or hydrophones are often deployed, providing space diversity to combat channel fading. To exploit all these diversities, a differential multiple-input–multiple-output (MIMO) scheme for doubly-selective fading channels is presented in this paper. The proposed differential orthogonal space-time block coding (DOSTBC) approach adopts the basis expansion model (BEM) to capture the channel variation in time domain. Both analytical and simulated results show that the proposed BEM–DOSTBC approach is reliable by collecting 3-D diversity: space, multipath, and Doppler. The proposed approach was tested during the RACE08 sea experiment and its reliability was confirmed by the experiment results.

Joint Channel Estimation and Signal Detection for the OFDM System Without Cyclic Prefix Over Doubly-Selective Channels

In the high-speed railway wireless communication, a joint channel estimation and signal detection algorithm is proposed for the orthogonal frequency division multiplexing (OFDM) system without cyclic prefix in the doubly-selective fading channels. Our proposed method first combines the basis expansion model (BEM) and the inter symbol interference (ISI) cancellation to overcome the situation that exists with the fast time-varying channel and the normalized maximum multipath channel exceeding the length of the cyclic prefix (CP). At first, the channel estimation and signal detection can be approximated without considering the ISI. Then, the channel parameters and signal detection are updated through ISI cancellation and circular convolution reconstruction from the frequency domain. The simulations show the algorithm can improve the performance of channel estimation and signal detection.

Sparsity Enhanced Mismatch Model for Robust Intercell Interference Management in Heterogeneous Networks With Doubly-Selective Fading Channels

Transmission over doubly-selective fading (DSF) interference channel often relies on the use of robust precoder due to a lack of accurate channel state information, with performance often depending on the conservativeness of the mismatch model. Previously proposed mismatch models either have been deemed too conservative (deterministic models) or are prone to error due to inaccuracy in the probability density function (pdf) and corresponding parameters (stochastic models). A deterministic mismatch model called Sparsity Enhanced Mismatch Model - Reverse discrete prolate spheroidal sequence, or SEMMR, is proposed herein in an attempt to alleviate this problem. Different from all previously deterministic models, the proposed model exploits the inherent sparse characteristics of DSF interference channels which lead to a two-stage robust transceiver design that outperforms precoding only strategy incorporating conventional norm ball mismatch model (NBMM). The inherent sparsity in the channel is brought forth by modeling the channel using a basis expansion model (BEM) where discrete prolate spheroidal sequence (DPSS) is used as a basis. Analytical and simulation results are provided to validate the performance gains of the SEMMR transceiver over the NBMM precoder.

Low Complexity Equalization of HCM Systems with DPFFT Demodulation over Doubly-Selective Channels

To mitigate the inter-carrier interference (ICI) of doubly-selective (DS) fading channels, we consider a hybrid carrier modulation (HCM) system employing the discrete partial fast Fourier transform (DPFFT) demodulation and the banded minimum mean square error (MMSE) equalization in this letter. We first provide the discrete form of partial FFT demodulation, then apply the banded MMSE equalization to suppress the residual interference at the receiver. The proposed algorithm has been demonstrated, via numerical simulations, to be its superior over the single carrier modulation (SCM) system and circularly prefixed orthogonal frequency division multiplexing (OFDM) system over a typical DS channel. Moreover, it represents a good trade-off between computational complexity and performance.

A Low-Complexity Robust OFDM Receiver for Fast Fading Channels

Orthogonal frequency division multiplexing (OFDM) receivers suffer significant performance degradation in time-varying fast fading channels because of the inter-carrier interference (ICI) induced by the Doppler effect. We previously proposed a novel iterative decision-directed channel estimation and ICI cancellation technique which can provide robust performance for mobile OFDM receivers moving at fast vehicle speed. The nutshell of the proposed technique is a channel estimator which is capable of estimating the ICI gains on each off-diagonal vector of the channel frequency response matrix of a doubly-selective fading channel, which corresponds to the ICI induced by the neighbor subcarrier symbol to current subcarrier. In this paper, we generalize the channel estimator and provide theoretical analysis on the achievable performance. As an application to digital video broadcasting terrestrial system, we provide intensive simulation results and detailed comparison on implementation complexity and performance with existing techniques to showcase the significance of the proposed technique in practical applications.

Joint Frequency-Domain Multiuser Turbo Equalization with Successive Interference Cancellation for Doubly-Selective Fading Channels

A novel multiuser separation and equalization scheme is proposed for single carrier wireless communication systems integrating frequency-domain (FD) multiuser turbo equalization (MUTE) and successive interference cancellation (SIC). The proposed iterative structure consists of multiple layers of detection, and at each layer the user with strongest power is processed by a frequency-domain multiuser equalizer to yield the soft extrinsic information on the coded bits of that user, which is delivered to a channel decoder after deinterleaving. The extrinsic information gleaned by the decoder is fed back to both the current and previous multiuser equalizers for the next iteration as a-priori information. The soft symbols of the current user are evaluated by the a-posteriori information of coded bits provided by the multiuser equalizer, and the interference reconstructed by the current user’s soft symbols is canceled out from the received signals in frequency domain. The interference-canceled signals are fed forward to subsequent layers for detection of other users. The proposed scheme effectively mitigates multiple access interference and intersymbol interference by an iterative (turbo) detection method. Numerical simulation examples demonstrate that the proposed FD MUTE with SIC outperforms the traditional MMSE multiuser equalizer over the severely doubly-selective channels, and the bit-error-rate performance tends to be better with the increase of iterations.

Efficient Channel Delay Estimation for OFDM Systems over Doubly-Selective Fading Channels

In this paper, we propose an efficient channel delay estimation method for orthogonal frequency-division multiplexing (OFDM) systems, especially over doubly-selective fading channels which are selective in both the symbol time domain and subcarrier frequency domain. For the doubly-selective fading channels in single frequency network (SFN), long and strong echoes exist and thus the conventional discrete Fourier Transform (DFT) based channel delay estimation system often fails to produce the exact channel delay profile. Based on the analysis of the discrete-time frequency response of the channel impulse response (CIR) coefficients in the DFT-based channel delay estimation system, we develop a method to effectively extract the true CIR from the aliased signals by employing a simple narrow-band low-pass filter (NB-LPF). The performance of the proposed system is verified using the COST207 TU6 SFN channel model.

Timing Acquisition for Bandlimited Long-Code DS-CDMA in Doubly-Selective Fading Channels

The code timing acquisition problem of bandlimited long-code based DS-CDMA systems operating in doubly-selective time-varying multipath channels is considered. We extend the unstructured schemes proposed by Buzzi to long-code spreading, which first estimates the Symbol Weighted Composite Channel Impulse Response (SW-CCIR) vectors and then extracts the timing informations. We also propose novel structured acquisition schemes, which directly estimate the multipath propagation delays by exploiting the a priori knowledge of the chip waveform. Both the structured and unstructured schemes are blind, since they require no other a priori information but the aperiodic spreading code of the desired user. Our numerical results demonstrate that the structured acquisition significantly outperforms both its unstructured counterpart and the classic correlator-based acquisition at a reasonable complexity increase.

Cooperative Intelligent Transport Systems: 5.9-GHz Field Trials

The mobile outdoor radio environment is challenging for vehicular communications. Although multipath propagation offers diversity and benefits in non-line-of-sight (NLOS) conditions, simultaneous multipath and mobility results in a doubly-selective fading channel. In practice, this means that the channel parameters vary significantly in both time and frequency within the bandwidth and typical packet durations used in 802.11p/WAVE standards for short-range vehicular communications. This paper presents the results of extensive field trial campaigns conducted in several countries, totaling over 1100 km. These field trials are scenario based, focusing on challenging low-latency, high-reliability vehicle-to-vehicle (V2V) safety applications including intersection collision warning, turn across path, emergency electronic brake light, do not pass warning, and precrash sensing. Vehicle-to-infrastructure (V2I) applications are also considered. The field trials compared the performance of off-the-shelf WiFi-based radio equipment with a more advanced 802.11p compliant radio employing more sophisticated channel estimation and tracking. Field trial results demonstrate significantly improved performance using the advanced radio, translating into greatly increased driver warning times and stopping distances. In fact the results show that off-the-shelf WiFi equipment fails to provide sufficient stopping distance to avert accidents in some cases. During the field trials, channel sounding data were also captured. Analysis of these channel measurements reveals the critical importance of accurate channel estimation, tracking the channel in both time and frequency within each packet. Delay spread and Doppler spread statistics computed from the channel measurements validate previously reported results in the literature. The results in this paper, however, provide the first instance of channel measurements performed simultaneously to application performance evaluation. The objective is to firmly establish the link between radio channel characteristics and the performance of critical V2V safety applications.