Multiple Orthogonal Frequency Division Multiplexing Symbols Research Articles

Time-Varying Channel Estimation Based on Distributed Compressed Sensing for OFDM Systems.

For orthogonal frequency division multiplexing (OFDM) systems in high-mobility scenarios, the estimation of time-varying multipath channels not only has a large error, which affects system performance, but also requires plenty of pilots, resulting in low spectral efficiency. To address these issues, we propose a time-varying multipath channel estimation method based on distributed compressed sensing and a multi-symbol complex exponential basis expansion model (MS-CE-BEM) by exploiting the temporal correlation and the joint delay sparsity of wideband wireless channels within the duration of multiple OFDM symbols. Furthermore, in the proposed method, a sparse pilot pattern with the self-cancellation of pilot intercarrier interference (ICI) is adopted to reduce the input parameter error of the MS-CE-BEM, and a symmetrical extension technique is introduced to reduce the modeling error. Simulation results show that, compared with existing methods, this proposed method has superior performances in channel estimation and spectrum utilization for sparse time-varying channels.

Monostatic Sensing With OFDM Under Phase Noise: From Mitigation to Exploitation

We consider the problem of monostatic radar sensing with orthogonal frequency-division multiplexing (OFDM) joint radar-communications (JRC) systems in the presence of phase noise (PN) caused by oscillator imperfections. We begin by providing a rigorous statistical characterization of PN in the radar receiver over multiple OFDM symbols for free-running oscillators (FROs) and phase-locked loops (PLLs). Based on the delay-dependent PN covariance matrix, we derive the hybrid maximum-likelihood (ML)/maximum a-posteriori (MAP) estimator of the deterministic delay-Doppler parameters and the random PN, resulting in a challenging high-dimensional nonlinear optimization problem. To circumvent the nonlinearity of PN, we then develop an iterated small angle approximation (ISAA) algorithm that progressively refines delay-Doppler-PN estimates via closed-form updates of PN as a function of delay-Doppler at each iteration. Moreover, unlike existing approaches where PN is considered to be purely an impairment that has to be mitigated, we propose to exploit PN for resolving range ambiguity by capitalizing on its delay-dependent statistics (i.e., the range correlation effect), through the formulation of a parametric Toeplitz-block Toeplitz covariance matrix reconstruction problem. Simulation results indicate quick convergence of ISAA to the hybrid Cramér-Rao bound (CRB), as well as its remarkable performance gains over state-of-the-art benchmarks, for both FROs and PLLs under various operating conditions, while showing that the detrimental effect of PN can be turned into an advantage for sensing.

A CP Reduction Scheme Based on Symbol Repetition for Narrow-Band IoT Systems

In this article, we propose a novel waveform with low cyclic prefix (CP) overhead for narrow-band Internet-of-things (NB-IoT) systems. Compared with the classical orthogonal frequency-division multiplexing (OFDM), the proposed waveform employs the concept of symbol repetition on multiple successive OFDM symbols (SR-OFDMs) and only one CP is occupied by multiple SR-OFDM symbols; hence, the CP overhead is reduced significantly, improving the spectral and energy efficiencies in NB-IoT systems. It is proved that the proposed SR-OFDM can effectively fight against the multipath fading channels by a simple single-tap equalization, avoiding the mutual interference among symbols. In addition, it is shown that the proposed SR-OFDM and classical OFDM have the same size of the inverse discrete Fourier transform (IDFT) at the transmitter, which indicates the same subcarrier spacing. Especially, it is demonstrated that the signals of multiple symbols are separated at the receiver, and the demodulation of each symbol can be performed independently, which is helpful to reduce the complexity of symbol demodulation. To evaluate the proposed SR-OFDM, simulations have been done by considering the Stanford university interim (SUI) channels, which have large channel delay spread and exhibit high frequency selectivity.

OFDM PAPR Reduction via Time-Domain Scattered Sampling and Hybrid Batch Training of Synchronous Neural Networks

Peak-to-average power ratio (PAPR) reduction in multiplexed signals in orthogonal frequency division multiplexing (OFDM) systems has been a long-standing critical issue. Clipping and filtering (CF) techniques offer good performance in terms of PAPR reduction at the expense of a relatively high computational cost that is inherent in the repeated application of fast Fourier transform (FFT) operations. The ever-increasing demand for low-latency operation calls for the development of low-complexity novel solutions to the PAPR problem. To address this issue while providing an enhanced PAPR reduction performance, we propose a synchronous neural network (NN)-based solution to achieve PAPR reduction performance exceeding the limits of conventional CF schemes with lower computational complexity. The proposed scheme trains a neural network module using hybrid collections of samples from multiple OFDM symbols to arrive at a signal mapping with desirable characteristics. The benchmark NN-based approach provides a comparable performance to conventional CF. However, it can underfit or overfit due to its asynchronous nature which leads to increased out-of-band (OoB) radiations, and deteriorating bit error rate (BER) performance for high-order modulations. Simulations’ results demonstrate the effectiveness of the proposed scheme in terms of the achieved cubic metric (CM), BER, and OoB emissions.

Efficient pilot design scheme for OFDM‐based full‐duplex systems

In orthogonal frequency-division multiplexing (OFDM)-based full-duplex (FD) systems, the terminal is allowed to transmit and receive signals simultaneously in the same frequency band. This leads to new challenges to pilot for channel estimation. The conventional pilot design methods are no longer effective for such systems. In this study, the authors propose a new practical pilot design method for OFDM-based FD systems and its performance is analysed in terms of the self-interference cancellation capability. Unlike the existing OFDM-based FD pilot design schemes, which require the channel to be constant during multiple continuous OFDM symbols, the authors' proposed scheme can be implemented in the block fading channel (i.e. channels that vary from one OFDM symbol to another). Besides, the optimal pilot pattern of the proposed scheme is studied. Their simulation results demonstrate the efficiency of the proposed pilot design.

ECCM Schemes against Deception Jamming Using OFDM Radar with Low Global PAPR.

In this paper, a type of effective electronic counter-countermeasures (ECCM) technique for suppressing the high-power deception jamming using an orthogonal frequency division multiplexing (OFDM) radar is proposed. Concerning the velocity deception jamming, the initial phases of the pulses transmitted in a coherent processing interval (CPI) are designed to minimize the jamming power within a specific range, forming a notch around the jamming in the Doppler spectrum. For the purpose of suppressing the range deception jamming and the joint range-velocity deception jamming, the phase codes of the subcarriers belonging to the OFDM pulses are optimized to minimize the jamming power, distributing some specific bands in the range and the range-velocity domain, respectively. According to Parseval’s theorem, the phase encoding, acting as the coding manner of the OFDM subcarriers can ensure that the energy of each OFDM symbol stays the same. It is worth noticing that the phase codes of the OFDM subcarriers can influence the peak-to-average power ratio (PAPR). Thus, an optimization problem is formulated to optimize the phase codes of the subcarriers under the constraint of global PAPR, which can regulate the PAPRs of multiple OFDM symbols at the same time. The proposed problem is non-convex; therefore, it is a huge challenge to tackle. Then we present a method named by the phase-only alternating direction method multipliers (POADMM) to solve the aforementioned optimization problem. Some necessary simulation results are provided to demonstrate the effectiveness of the proposed radar signaling strategy

一种带有ICI自消除的多OFDM符号时变信道估计方法

高速移动环境下，由于多普勒频移增大，信道的时变性破坏了正交频分复用(Orthogonal Frequency Division Multiplexing, OFDM)系统子载波之间的正交性，从而产生子载波间干扰(Inter Carrier Interference, ICI)，导致系统性能严重下降。为了减少待估计量，通常采用基扩展模型(BEM)来近似模拟时变信道。为了提升性能，当信道的相干时间与发送码元的周期可相比拟的时候，本文采用多块(多个OFDM符号)。同时在使用导频符号对参数估计时，忽略了相邻非导频符号的ICI干扰，降低了整个时变信道下的估计准确性。因此我们通过分析子载波所产生的ICI系数变化特点，提出了一种带有ICI自消除的多OFDM符号时变信道估计方法，提高估计的准确性。但是由于基于多OFDM符号的信道估计性能在归一化多普勒频移较大时该方法成立条件不再满足，因此性能呈现明显的衰减，为了解决此问题，我们提出一种带有ICI自消除的自适应OFDM符号个数时变信道估计方法。仿真实验从误码率，归一化均方误差两方面分别验证了该方法的有效性。 In high-speed mobile environment, time-varying channel destroys the orthogonality between subcarriers of orthogonal frequency-division multiplexing (OFDM) systems, giving rise to in-ter-carrier interference (ICI), and degrading the performance of the systems. Basis expansion model (BEM) is usually used to approximate the time-varying channels to reduce the estimators. In order to improve performance, this paper adopts multi block (multiple OFDM symbols) when the coherent time of the channel variations and the symbols can be compared. However, when using pilot-symbol to parameter estimation, the ICI interference from near non-pilot-symbol is ignored, reducing its estimated accuracy of time-varying channel. And in this work the paper proposes a multiple OFDM symbols time-varying channel estimation method with ICI self-cancellation after analyzing the high correlation between subcarriers, improving the accuracy of estimation. But due to the condition of utilizing the multiple OFDM symbols channel estimation method is no longer met in large Doppler frequency shift, the performance of resulting channel estimation attenuates obviously. In order to solve this problem, we put forward a kind of adaptive OFDM symbol time-varying channel estimation method with the ICI self-cancellation. The simulation results show that the proposed method is effective from two aspects of error rate and normalized mean square error.

Structured Distributed Compressive Channel Estimation Over Doubly Selective Channels

For an orthogonal frequency-division multiplexing (OFDM) system over a doubly selective (DS) channel, a large number of pilot subcarriers are needed to estimate the numerous channel parameters, resulting in low spectral efficiency. In this paper, by exploiting temporal correlation of practical wireless channels, we propose a highly efficient structured distributed compressive sensing (SDCS) based joint multi-symbol channel estimation scheme. Specifically, by using the complex exponential basis expansion model (CE-BEM) and exploiting the sparsity in the delay domain within multiple OFDM symbols, we turn to estimate jointly sparse CE-BEM coefficient vectors rather than numerous channel taps. Then a sparse pilot pattern within multiple OFDM symbols is designed to obtain an ICI-free structure and transform the channel estimation problem into a joint-block-sparse model. Next, a novel block-based simultaneous orthogonal matching pursuit (BSOMP) algorithm is proposed to jointly recover coefficient vectors accurately. Finally, to reduce the CE-BEM modeling error, we carry out smoothing treatments of already estimated channel taps via piecewise linear approximation.Simulation results demonstrate that the proposed channel estimation scheme can achieve higher estimation accuracy than conventional schemes, although with a smaller number of pilot subcarriers.

An OFDM‐based physical‐layer feedback mechanism for relay selection in virtual MIMO systems

PurposeThe purpose of this paper is to introduce an orthogonal frequency‐division multiplexing (OFDM)‐based 2‐phase physical‐layer feedback space (PFS) for distributed relay selection (RS) in virtual multiple‐input multiple‐output (VMIMO) systems. The proposed method is evaluated with numeric and simulation results.Design/methodology/approachUnlike minislots used in current MAC layer feedback, the authors introduce physical‐layer feedback space (PFS) which hosts one‐bit for each candidate relay (CR), for instance, a 48‐subcarrier OFDM symbol hosts 48 bits. In the two‐phase feedback procedure, each CR firstly hears the invitation and respond between cluster heads (CH) of upper‐/down‐stream cluster and decides whether to be a qualified relay or not. Then if it is qualified, it randomly selects one subcarrier and sends a pre‐equalized one‐bit feedback. The upper‐stream CH evaluate all feedbacks in PFS, then selects all or a subset of relays with successful feedback and broadcasts its decision to all nodes. Although the number of successful feedbacks (NSF) drops as number of CR increases (NCR), 7∼8 CR can be selected with high probability when NCR is triple that of total subcarriers (48).FindingsIn current literature, several traditional MAC layer feedback mechanisms are designed for relay selection in virtual MIMO (VMIMO) system most of which are based upon feedback minislots. For such methods, the number of active nodes should be estimated first and known to all participating nodes to choose optimal feedback possibility to obtain best successful feedback possibility. Furthermore, each minislot should include unique identification of candidate relay thus such methods can NOT be referred as one‐bit feedback. In the new method, though OFDM subcarriers play the same role as minislots, they are exactly one‐bit fashioned and occupies only multiple OFDM symbols which is much shorter than that in current methods.Originality/valueBy using physical‐layer feedback space, exactly only one‐bit is required for each candidate relay to send its feedback, and the overall overhead introduced for all of them is K‐bit provided by the required PFS, which spans only fixed duration of the PFS, which is one or more OFDM symbols. Therefore, the proposed scheme can greatly reduce overhead and feedback delay during relay selection.

Identifying time-varying channels with aid of pilots for MIMO-OFDM

In this paper, we consider pilot-aided channel estimation for orthogonal frequency division multiplexing (OFDM) systems with a multiple-input multiple-output setup. The channel is time varying due to Doppler effects and can be approximated by an oversampled complex exponential basis expansion model. We use a best linear unbiased estimator (BLUE) to estimate the channel with the aid of frequency-multiplexed pilots. The applicability of the BLUE, which is referred to as the channel identifiability in this paper, relies upon a proper pilot structure. Depending on whether the channel is estimated within a single OFDM symbol or multiple OFDM symbols, we propose simple pilot structures that guarantee channel identifiability. Further, it is shown that by employing more receive antennas, the BLUE can combat more effectively the Doppler-induced interference and therefore improve the channel estimation performance.

Recursive maximum likelihood estimation of time‐varying carrier frequency offset for orthogonal frequency‐division multiplexing systems

ABSTRACTA recursive maximum likelihood carrier frequency offset (CFO) estimator is proposed in this work, where redundancy information contained in the cyclic prefix of multiple consecutive orthogonal frequency‐division multiplexing (OFDM) symbols is exploited in an efficient recursive fashion. Because the estimator is based on multiple OFDM symbols, the time‐varying CFO must be considered. We investigate the effect of time‐varying CFO on the performance of the estimator and the trade‐off between fast tracking ability and low estimation variance. We show that, without channel noise, the mean squared error (MSE) of estimation due to CFO estimation variation increases approximately quadratically with n, where n is the number of OFDM symbols used for CFO estimation (estimation window size), whereas the MSE due to channel noise decreases proportionally to 1/n (approximately) if the CFO is constant. A closed‐form expression of the optimal estimation window size (approximately) is derived by minimizing the MSE caused by both time‐varying CFO and channel noise. For wireless systems with time‐varying rate of change for CFO, the proposed estimator can be implemented adaptively. In addition, typical optimal estimation window sizes for WiMAX, DVB‐SH and MediaFLO systems are evaluated as an example. Copyright © 2011 John Wiley & Sons, Ltd.

Linearly time-varying channel estimation and training power allocation for OFDM/MIMO systems using superimposed training

We address the problem of estimating the linearly time-varying (LTV) channel of orthogonal frequency division multiplexing (OFDM)/multiple-input multiple-output (MIMO) systems using superimposed training (ST). The LTV channel is modeled by truncated discrete Fourier bases. Based on this model, a two-step approach is adopted to estimate the LTV channel over multiple OFDM symbols. We also present performance analysis of the channel estimation and derive a closed-form expression for the channel estimation variances. It is shown that the estimation variances, unlike that of the conventional ST-based schemes, approach to a fixed lower-bound as the training length increases, which is directly proportional to information-pilot power ratios. For wireless communication systems with a limited transmission power, we optimize the ST power allocation by maximizing the lower bound of the average channel capacity. Simulation results show that the proposed approach outperforms the frequency-division multiplexed training schemes.

Optimal training design and placement for MIMO orthogonal frequency division multiplexing channel estimation

This paper deals with optimal training design and placement over multiple orthogonal frequency division multiplexing (OFDM) symbols for the least squares (LS) channel estimation in multiple-input multipleoutput (MIMO) OFDM systems. First, the optimal pilot sequences over multiple OFDM symbols are derived by co-cyclic Jacket matrices based on the minimum mean square error (MSE) of the LS channel estimation. Then, an enhanced channel estimation method using sliding window is proposed to improve further the performance for the optimal pilot sequences in fast-varying channels. Simulation results show that the enhanced method can efficiently improve the performances for the optimal pilot sequences over two and four OFDM symbols, especially in fast-varying channels.

A Sidelobe Suppression Technique by Regenerating Null Signals in OFDM-Based Cognitive Radios

In this paper, a sidelobe suppression technique for orthogonal frequency division multiplexing (OFDM)-based cognitive radios (CR) is proposed. In the OFDM-based CR systems, after the CR terminal executes spectrum sensing, it transmits a CR packet by activating the subcarriers in the frequency bands where no signals are detected (hereinafter, these subcarriers are called “active subcarrier”) and by disabling (nulling) the subcarriers in the frequency bands where the signals are detected. In this situation, a problem arises in that the signals that leak from the active subcarriers to the null subcarriers may interfere with the primary systems. Therefore, this signal leakage has to be minimized. In many OFDM-based wireless communication systems, one packet or frame consists of multiple OFDM symbols and the discontinuity between the consecutive OFDM symbols causes the signal leakage to the null subcarriers. In the proposed method, signal leakage to the null subcarriers is suppressed by regenerating null subcarriers in the frequency-domain signal of the whole packet as follows. One CR packet consisting of multiple OFDM symbols having null subcarriers and guard interval (GI) is buffered and oversampled, and then the oversampled signal is Fourier transformed at once and consequently the frequency-domain signal of the packet is obtained. The null subcarriers in the frequency-domain signal are zeroed again, and then the signal is inverse Fourier transformed and transmitted. The proposed method significantly suppresses the signal leakage. The spectral power density, the peak-to-average power ratio (PAPR) and the packet error rate (PER) performances of the proposed method are evaluated by computer simulations and the effectiveness of the proposed method is shown.

A Novel Channel Estimation Method Using Virtual Pilots in MIMO OFDM Systems

To improve the performance of the optimal pilot sequences over multiple OFDM symbols in fast time-varying channels, this letter proposes a novel channel estimation method using virtual pilot tones in multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. Assuming that the superimposed virtual pilot tones at the data locations over the specific sub-carriers are transmitted from all transmit antennas, the corresponding virtual received pilot signals at the same locations are obtained from the neighboring real received pilot signals over the same sub-carriers by Wiener filter. Based on the least squares (LS) channel estimation, the channel parameters can be obtained from the combination of the virtual and real received pilot signals over one OFDM symbol. Simulation results show that the proposed channel estimation method greatly outperforms the previous method for the optimal pilot sequences over multiple OFDM symbols in fast time-varying channels, as well as approaches the method for the comb-type optimal pilot sequences in performance.

Peak power reduction scheme base on transform kernel scrambling for OFDM systems

This work presents a novel transform kernel scrambling (TKS) scheme for reducing the peak-to-average transmitter power ratio (PAPR) for Orthogonal Frequency Division Multiplexing (OFDM) symbols. This scrambling scheme suppresses the peak envelope power of OFDM signals due to de-correlation among the original QAM constellation in multiple OFDM symbols via transformation. The performance of the reduction of PAPR for OFDM signals with various unitary transform kernels is also evaluated. Since specific unitary transform kernels in TKS processing block is only used for scrambling, no side information is required. For the ease of presentation, the system performance has been demonstrated by a computer simulation. Simulation results confirm the superiority of the proposed scheme in the PAPR reduction.

Optimal training design for MIMO OFDM systems in mobile wireless channels

This paper describes a least squares (LS) channel estimation scheme for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems based on pilot tones. We first compute the mean square error (MSE) of the LS channel estimate. We then derive optimal pilot sequences and optimal placement of the pilot tones with respect to this MSE. It is shown that the optimal pilot sequences are equipowered, equispaced, and phase shift orthogonal. To reduce the training overhead, an LS channel estimation scheme over multiple OFDM symbols is also discussed. Moreover, to enhance channel estimation, a recursive LS (RLS) algorithm is proposed, for which we derive the optimal forgetting or tracking factor. This factor is found to be a function of both the noise variance and the channel Doppler spread. Through simulations, it is shown that the optimal pilot sequences derived in this paper outperform both the orthogonal and random pilot sequences. It is also shown that a considerable gain in signal-to-noise ratio (SNR) can be obtained by using the RLS algorithm, especially in slowly time-varying channels.