Doubly-selective Channels Research Articles

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.

Joint ML Estimation of CFO and Channel, and a Low Complexity Turbo Equalization Technique for High Mobility OFDMA Uplinks

In this paper, we propose a pilot aided joint estimation technique for carrier frequency offsets (CFOs) and doubly selective channels (DSCs), and a low complexity turbo equalization (TE) scheme for orthogonal frequency division multiple access (OFDMA) uplink systems with high mobility users. We propose the use of Chebyshev polynomials of the first kind (CPF) for accurately representing the DSCs. As the exact solution to the estimation problem is computationally intensive, we make use of space alternating generalized expectation maximization (SAGE) algorithm, that replaces the complex multidimensional search with many one dimensional searches. We derive the exact Cramer-Rao bound (CRB) of the joint estimation problem and the mean squared error of the proposed estimation technique is shown to be closely comparable to it. The convergence characteristics are also studied and it is proved analytically that the proposed method converges. Additionally, we propose a low complexity turbo equalization method with iterative multiple access interference (MAI) cancellation, which uses the soft feedback symbol estimate for removing the MAI and self inter-carrier interference (ICI) in each iteration. Our proposed estimation and equalization technique can be applied to any type of carrier assignment scheme (CAS) in OFDMA and offers very good performance even at high mobile speeds.

A New Equalizer in Doubly-Selective Channels for TDS-OFDM

Various factors contribute to the intercarrier interference (ICI) in orthogonal frequency-division multiplexing (OFDM), which violates the orthogonality among subcarriers and greatly degrades the performance. Traditional ICI compensation methods incorporate iterative estimation and cancelation for pilot subcarriers, bearing too much complexity and reducing the spectral efficiency. In this paper, a novel channel equalization method is proposed for time domain synchronous-orthogonal frequency-division multiplexing (TDS-OFDM), where fast and accurate channel estimation is achieved by utilizing the padded pseudo-noise sequence in consecutive blocks. The new equalizer refers to fast suboptimal-minimum mean square error structure, other than traditional overlap-add structure, inspired by the fact that linear convolution structure is better preserved than circular convolution structure in TDS-OFDM under time-varying channels. With the approximation of linear time-varying channel, the proposed equalizer achieves considerable performance with low complexity (linear) and no additional spectral overhead.

Energy Detection Based Spectrum Sensing for Cognitive Radios Over Time-Frequency Doubly Selective Fading Channels

Cognitive radios may operate in practice under various adverse environments. For typical mobile and short-range scenarios, wireless links may tend to be time and frequency selective, i.e., the multipath propagations with time-varying fading coefficients will be inevitable. To cope with the encountered doubly-selective channels, in this paper we present a new spectrum sensing algorithm for distributed applications. First, a dynamic discrete state-space model is established to characterize sensing process, where the occupancy state of primary band and the time-varying multipath channel are treated as two hidden states, while the summed energy is adopted as the observed output. With this new paradigm, spectrum sensing is realized by acquiring primary states and time-dependent multipath channel jointly. For the formulated problem, unfortunately, Bayesian statistical inference may be impractical due to the absence of likelihoods and involved non-stationary distributions. To remedy this problem, an iterative algorithm is further designed by resorting to sequential importance sampling techniques; thus, the dynamic non-Gaussian multipath channel and primary states are estimated recursively. Another critical challenge, e.g., the noise uncertainty, is also considered, which may be incorporated conveniently into this sensing diagram and, furthermore, addressed effectively by the designed algorithm. Simulations validate the proposed algorithm. While classical schemes fail to deal with doubly selective channels, the new sensing scheme can exploit the underlying channel memory and operate well, which provides a great promise to realistic applications.

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.

Hybrid Carrier Modulation System with Partial FFT Demodulation Over Doubly Selective Channels in Presence of Carrier Frequency Offset

The effectiveness of communication system is impaired by the carrier frequency offset (CFO) and inter-carrier interference (ICI) due to the significant time variation under doubly selective (DS) channels. In this paper, we consider the weighted-type fractional Fourier transform (WFRFT)-based hybrid carrier modulation (HCM) system with partial fast Fourier transform (PFFT) demodulation for DS channels in presence of CFO. The influence of CFO and ICI, after PFFT demodulation and optimal channel compensation, can be further suppressed under certain WFRFT domain. Numerical results are presented to demonstrate the superiority of HCM with PFFT demodulation over the single carrier modulation and orthogonal frequency division multiplexing systems with PFFT demodulation at a very moderate complexity.

Low-complexity MMSE-SD Algorithm for OFDM Systems over Doubly-selective Channels

在时频双选信道OFDM系统中，针对最小均方误差连续检测(MMSE-SD)算法求逆运算导致计算复杂度过高的问题，该文提出一种改进的低复杂度MMSE-SD算法。该算法首先对信道矩阵和检测矩阵进行扩展处理，然后建立扩展矩阵和原矩阵之间的关系，每次检测用扩展矩阵的迭代求逆代替原矩阵的直接求逆。理论分析和仿真结果表明：和原MMSE-SD算法相比，该改进算法在保持原算法性能的基础上，大幅度降低其计算复杂度；与其它算法相比，该改进算法兼顾了系统性能与计算复杂度，当归一化多普勒频移增大时，其计算复杂度保持不变而性能更优。

Time-Varying Channel Multi-Carrier Modulation Technology Research

With frequency selective fading from multi-path characteristic and time selective fading from high speed mobility, double selective channel has become the typical context for the current wireless communication system. To realize high performance transmission in time-varying channel, this paper presents DAFT-OFDM multicarrier modulation scheme. The simulation results show that the scheme is applicable to time-varying fading channel, in which each path experiences independent Doppler spread. The scheme can also reduce ICI effectively.

Unified Analysis of ICI-Cancelled OFDM Systems in Doubly-Selective Channels

Unified Analysis of ICI-Cancelled OFDM Systems in Doubly-Selective Channels

Channel Estimation for OFDM Systems over Doubly Selective Channels: A Distributed Compressive Sensing Based Approach

Channel estimation for an orthogonal frequency-division multiplexing (OFDM) broadband system over a doubly selective channel is very challenging. This is mainly due to the significant Doppler shift, which results in a time-frequency doubly-selective (DS) channel. The DS channel features a large number of channel coefficients, which introduces inter-carrier interference (ICI) and forces the need for allocating a large number of pilot subcarriers. To tackle this problem, in this paper we propose a novel channel estimation scheme based on distributed compressive sensing (DCS) theory. Taking advantage of the basis expansion model (BEM) and the channel sparsity in the delay domain, we transform the original DS channel into a novel two-dimensional channel model, where several jointly sparse BEM coefficient vectors become the estimation goal. Then a special decoupling form originating from a novel sparse pilot pattern is designed for such estimation, which results in an ICI-free structure and enables the DCS application to make joint estimation of these vectors accurately. Combined with a smoothing treatment process, the proposed scheme can achieve significantly higher estimation accuracy than the existing ones, although with a much smaller number of pilot subcarriers. Theoretical analysis and simulation results both confirm its performance merits.

Signal Detection for OFDM-Based Virtual MIMO Systems under Unknown Doubly Selective Channels, Multiple Interferences and Phase Noises

In this paper, the challenging problem of signal detection under severe communication environment that plagued by unknown doubly selective channels (DSCs), multiple narrowband interferences (NBIs) and phase noises (PNs) is investigated for orthogonal frequency division multiplexing based virtual multiple-input multiple-output (OFDM-V-MIMO) systems. Based on the Variational Bayesian Inference framework, a novel iterative algorithm for joint signal detection, DSC, NBI and PN estimations is proposed. Simulation results demonstrate quick convergence of the proposed algorithm, and after convergence, the bit-error-rate performance of the proposed signal detection algorithm is very close to that of the ideal case which assumes perfect channel state information, no PN, and known positions and powers of NBIs plus additive white Gaussian noise. Furthermore, simulation results show that the proposed signal detection algorithm outperforms other state-of-the-art methods.

A Novel Subblock-Based Frequency-Domain Equalizer over Doubly-Selective Channels

A novel frequency-domain equalizer (FDE) is proposed for single-carrier block transmission over a doubly-selective channel. The proposed FDE partitions a received block into multiple subblocks in order to reduce the effect of the time variation of the channel. The nonuniformity in the error statistics of a subblock-based FDE is analyzed, when a one-tap minimum mean-squared error (MMSE) equalizer is employed. The nonuniformity is exploited to remove the drawback of subblock processing so that the performance of a subblock-based FDE is significantly improved. Numerical results show that the proposed FDE has much better performance than other known subblock-based FDEs. Furthermore, it has robust performance over high Doppler environments.

Enhanced Mobile Multiple-Input Multiple-Output Underwater Acoustic Communications

This paper focuses on mobile multiple-input multiple-output (MIMO) underwater acoustic communications (UAC) over double-selective channels subject to both intersymbol interference and Doppler scaling effects. Temporal resampling is implemented to effectively convert the Doppler scaling effects to Doppler frequency shifts. Under the assumption that the channels between all the transmitter and receiver pairs experience the same Doppler frequency, a variation of the recently proposed generalization of the sparse learning via iterative minimization (GoSLIM) algorithm, referred to as GoSLIM-V, is employed to estimate the frequency modulated acoustic channels. GoSLIM-V is user parameter free and is easy to use in practical applications. This paper also considers turbo equalization for retrieving the transmitted signal. In particular, this paper reviews the linear minimum mean-squared error (LMMSE) based soft-input soft-output equalizer involved in the turbo equalization scheme and adopts a fast implementation of the equalizer that achieves negligible detection performance degradation compared to its direct implementation counterpart. The effectiveness of the considered MIMO UAC scheme is demonstrated using both simulated data and measurements recently acquired during the MACE10 in-water experiment.

Doubly-Selective Channel Estimation Using Superimposed Training and Weighted First-Order Statistics

Doubly-selective channel estimation using superimposed training and complex exponential basis expansion model is considered. By taking a weighted averaging operation of the received data, a weighted first-order statistical estimator is proposed, where the time-varying channel estimation is reduced to the simple average-based solution of time-invariant coefficients and the dominant effect of information-induced interference on channel estimation can be suppressed. To further improve the estimation performance with a limited training power, a joint iterative channel estimation and symbol detection scheme is developed where the detected symbol is exploited to enhance estimation performance instead of being viewed as interference. Theoretical analysis and simulation results show that the proposed scheme is superior to data-dependent superimposed training scheme and competitive with the conventional time-multiplexed training in terms of symbol error rate over doubly-selective channels.

Time-Varying Channel Estimation Using Two-Dimensional Channel Orthogonalization and Superimposed Training

In this correspondence, a method is presented for estimating double-selective channels using superimposed training (ST). The estimator is based on a subspace projection of the time-varying channel onto a set of two dimensional orthogonal functions. These functions are formed via the outer product of the discrete prolate spheroidal basis vectors and the universal basis vectors. This approach allows the channel to be expanded in both the time-delay and time dimensions with the fewest parameters when incomplete channel statistics are given. This correspondence also provides a theoretical performance analysis of the estimation algorithm and its corroboration via simulations. It is shown that this new method provides an enhancement in channel estimation when compared with state-of-the-art approaches.

On turbo equalization for mobile multi-input multi-output underwater acoustic communications

This paper focuses on mobile multi-input multi-output (MIMO) underwater acoustic communications (UAC) over double-selective channels subject to both inter-symbol interference and Doppler scaling effects. Temporal resampling is implemented to effectively convert the Doppler scaling effects to Doppler frequency shifts. A variation of the recently proposed generalization of the sparse learning via iterative minimization (GoSLIM) algorithm, referred to as GoSLIM-V, is employed to estimate the frequency modulated acoustic channels. GoSLIM-V is user parameter free and is easy to use in practical applications. This paper also considers Turbo equalization for retrieving the transmitted signal. In particular, this paper reviews the linear minimum mean-squared error (LMMSE) based soft-input soft-output equalizer involved in the Turbo equalization scheme, and adopts a fast implementation of the equalizer that achieves negligible detection performance degradation compared to its direct implementation counterpart. The effectiveness of the considered MIMO UAC scheme is demonstrated using both simulated data and measurements recently acquired during the MACE10 in-water experiment. Acknowledgments: This work was supported in part by the Office of Naval Research (ONR) under Grant No. N00014-10-1-0054. We gratefully acknowledge WHOI for the fruitful collaborations with us to conduct the in-water experimentations and for sharing data with us.

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.

Conjugate-Gradient Based Doubly Selective Channel Estimation and Equalization for OFDM Systems

This paper addresses conjugate-gradient (CG) based pilot-assisted channel estimation and equalization in doubly selective channels for orthogonal frequency division multiplexing (OFDM) block transmissions. With the help of the discrete prolate spheroidal sequence, which shows flat mean-square error (MSE) curves for the reconstructed channels in the presence of Doppler frequency mismatch, a basis expansion model for a parsimonious channel representation over multiple OFDM blocks is developed, a system equation for the least square channel estimation under widely used pilot lattices, where the pilot symbols are irregularly placed in the subcarrier domain, is formulated by introducing carving matrices, and the standard CG method is applied to the system. Relying on the CG method again, the linear minimum mean-square error channel equalization is pursued without performing any matrix inversion, while elevating the convergence speed of the iterative algorithm with a simple preconditioner. Finally, we validate our schemes with numerical experiments on the integrated services digital broadcasting-terrestrial system in doubly-selective channels and determine the normalized MSE and uncoded bit error rate.

On the Design of Pilot Symbols for OFDM Systems over Doubly-Selective Channels

We consider the pilot symbols for orthogonal frequency-division multiplexing (OFDM) over doubly selective channels. Locations, powers, and phases of pilot symbols play important roles in the channel estimation. We attempt to minimize the mean-square error (MSE) by selecting powers and phases of pilot symbols. In this paper, based on the MSE-optimal pilot symbols for time-selective and frequency-flat channels, we obtain the pilot symbols for doubly-selective channels. Through simulations, we show the channel estimation performance with the proposed pilot symbols compared to those with the equi-powered pilot symbols and the optimal pilot symbols.