Hopping pilots for estimation of frequency-offset and multiantenna channels in MIMO-OFDM

We design pilot-symbol-assisted modulation for carrier frequency offset (CFO) and channel estimation in orthogonal frequency-division multiplexing transmissions over multi-input multi-output frequency-selective fading channels. The CFO and channel-estimation tasks rely on -subcarrier and nonzero pilot symbols that we insert and hop from block to block. Because we separate CFO and channel estimation from symbol detection, the novel training patterns lead to further decoupled CFO and channel estimators. The performance of our algorithms is investigated analytically, and then compared with an existing approach by simulations.     

A performance review of PSP for joint phase/frequency and dataestimation in future broadband satellite networks

In unknown channels, nonadaptive maximum likelihood sequence detection (NA-MLSD) is far from optimum in the presence of channel-induced uncertainty. To counteract this uncertainty, conventional solutions augment MLSD with external channel estimators. However, for very low SNR values this estimation procedure becomes marginal and the conventional adaptive MLSD (CA-MLSD) approaches perform poorly. We consider joint data decoding and parameter estimation techniques, and in particular per survivor processing (PSP) techniques, as a potentially effective solutions to this problem, at the expense of increased complexity. The performance/complexity tradeoff is addressed for a convolutionally encoded Q-PSK return link of an SHF/EHF satellite system for multimedia services impaired by phase noise and frequency offsets. By contrasting NA-MLSD, CA-MLSD, and PSP, ranges are provided for channel conditions where the tradeoff favors a particular technique. Further, CA-MLSD and PSP are also contrasted in terms of scalar/ vector estimation performance     

Signal space detection for recording channels with jitter noise

A delay-constrained sequence detector is considered for recording channels whose major impediments include intersymbol interference (ISI) and magnetic transition jitter noise. The jitter noise is data-dependent, and a given noise sample is correlated with neighboring noise samples. A sequence detector with a finite decision delay can be formulated in a finite dimensional vector space. For a correlated noise channel, the decision boundary is generally quadratic. We present a technique for obtaining a minimal set of hyperplanes approximating a quadratic decision boundary with a negligible performance loss. In this process, a distance measure, which is consistent with the notion of the effective SNR, is defined and used as a design parameter to trade the complexity and performance. As an achievable performance bound, we derive the effective SNR for the maximum-likelihood sequence detector (MLSD) for these channels. The performance of the partial response maximum likelihood (PRML) detector commonly adopted for current data storage channels as well as the Viterbi algorithm (VA) based on the traditional Euclidean metric, which serves as the MLSD for additive white Gaussian noise, are also analyzed and compared with that of the proposed signal space detector     

频率选择性慢衰落信道下的快速频率估计

给出了在频率选择性慢衰落信道下适用于突发传输的两种快速频偏估计算法。针对慢衰落选择性信道下的频率估计问题,两种算法均给出了一个简单的闭式解,且算法实现无需任何信道幅度信息。第一种算法要求用于频率估计的训练序列的自相关矩阵具有对角特性,第二种算法使用周期的训练序列,两种算法所需的运算量大大低于最大似然估计算法。仿真结果显示,在较高信噪比下两种算法均具有较好的估计性能。     

Pseudo-maximum-likelihood data estimation algorithm and itsapplication over band-limited channels

A pseudo-maximum-likelihood data estimation (PML) algorithm for discrete channels with finite memory in additive white Gaussian noise environment is developed. Unlike the traditional methods that utilize the Viterbi algorithm (VA) for data sequence estimation, the PML algorithm offers an alternative solution to the problem. The simplified PML algorithm is introduced to reduce the computational complexity of the PML algorithm for channels with long impulse response. The adaptive version of the PML algorithm suitable for time-varying channels such as frequency-selective Rayleigh fading channels is also introduced. Computer simulation results demonstrate the performance of these algorithms and compare them to the VA-based techniques for different types of channels. The performance design criterion for the PML algorithm is derived in the Appendix     

Adaptive signal detection over fast frequency-selective fading channels under class-A impulsive noise

The problem of adaptive detection of signals contaminated with Middleton's class-A impulsive noise and transmitted over a fast time-varying frequency-selective fading channel is addressed. Adaptive algorithms are derived to update the estimate of the channel parameters to the detector. A theoretical performance evaluation of the detector is provided. Computer simulations are performed to validate the theoretical developments.     

Noncoherent adaptive channel identification algorithms fornoncoherent sequence estimation

In this letter, two novel noncoherent adaptive algorithms for channel identification are introduced. The proposed noncoherent least-mean-square (LMS) and noncoherent recursive least squares (RLS) algorithms can be combined easily with noncoherent sequence estimation (NSE) for M-ary differential phase-shift keying signals transmitted over intersymbol interference (ISI) channels. It is shown that the resulting adaptive noncoherent receivers are very robust against carrier phase variations. For zero frequency offset, the convergence speed and the steady-state error of the noncoherent adaptive algorithms are similar to those of conventional LMS and RLS algorithms. However, the conventional algorithms diverge even for relatively small frequency offsets, whereas the proposed noncoherent algorithms converge for relatively large frequency offsets. Simulations confirm the good performance of NSE combined with noncoherent adaptive channel estimation in time-variant (fading) ISI channels     

Space-time turbo equalization in frequency-selective MIMO channels

A computationally efficient space-time turbo equalization algorithm is derived for frequency-selective multiple-input-multiple-output (MIMO) channels. The algorithm is an extension of the iterative equalization algorithm by Reynolds and Wang (see Signal Processing, vol.81, no.5, p.989-995, 2001) for frequency-selective fading channels and of iterative multiuser detection for code-division multiple-access (CDMA) systems by Wang and Poor (see IEEE Trans. Commun., vol.47, p.1046-1061, 1999). The proposed algorithm is implemented as a MIMO detector consisting of a soft-input-soft-output (SISO) linear MMSE detector followed by SISO channel decoders for the multiple users. The detector first forms a soft replica of each composite interfering signal using the log likelihood ratio (LLR), fed back from the SISO channel decoders, of the transmitted coded symbols and subtracts it from the received signal vector. Linear adaptive filtering then takes place to suppress the interference residuals: filter taps are adjusted based on the minimum mean square error (MMSE) criterion. The LLR is then calculated for adaptive filter output. This process is repeated in an iterative fashion to enhance signal-detection performance. This paper also discusses the performance sensitivity of the proposed algorithm to channel-estimation error. A channel-estimation scheme is introduced that works with the iterative MIMO equalization process to reduce estimation errors.     

Receiver structures for time-varying frequency-selective fadingchannels

Several receiver structures for linearly modulated signals are proposed for time-varying frequency-selective channels. Their channel estimators explicitly model the time variation of the channel taps via polynomials. These structures are constructed from the following building blocks: (i) sliding or fixed block channel estimators; (ii) maximum likelihood sequence detectors (MLSDs) or decision feedback equalizers (DFEs); and (iii) single or multiple passes. A sliding window channel estimator uses a window of received samples to estimate the channel taps within or at the end of the window. Every symbol period, the window of samples is slid along another symbol period, and a new estimate is calculated. A fixed block channel estimator uses all received samples to estimate the channel taps throughout the packet, all at once. A single pass receiver estimates the channel and detects data once only. A multipass receiver performs channel estimation and data detection repetitively. The effect of the training symbol positions on the performance of the block multipass approach is studied. The bit error rate (BER) performance of the MLSD structures is characterized through simulation and analysis. The proposed receivers offer a range of performance/complexity tradeoffs, but all are well suited to time-varying channels. In fast fading channels, as the signal-to-noise ratio (SNR) increases, they begin to significantly outperform the per-survivor processing-based MLSD receivers which employ the least mean-squares (LMS) algorithm for channel estimation     

Diversity combining for coherent and differential M-PSK in fading and class-A impulsive noise

In this paper, optimum and suboptimum diversity combining schemes for coherent and differential M-ary phase-shift keying (M-PSK) transmission impaired by general Ricean fading and impulsive Class-A noise are derived and analyzed. The proposed suboptimum coherent combining (SCC) and suboptimum noncoherent combining (SNC) schemes yield similar performance as the corresponding optimum combining schemes but require a lower computational complexity. In addition, the novel SCC and SNC strategies achieve large performance gains over conventional maximum ratio combining (MRC) and equal gain combining (EGC), respectively. For MRC and EGC, respectively, we also provide a performance analysis for coherent and differential M-PSK transmissions over general Ricean fading channels with Class-A noise. Furthermore, tight performance upper bounds for the proposed optimum and suboptimum combining schemes are derived.     

Intercarrier Interference Suppression for OFDMA Uplink in Time- and Frequency-Selective Fading Channels

This paper investigates intercarrier interference (ICI) suppression and channel estimation for the uplink of an orthogonal frequency-division multiple-access (OFDMA) system in a time- and frequency-selective fading channel. In such a doubly selective channel, channel variations within each OFDMA block disrupt the orthogonality among subcarriers and leads to ICI. We develop an appropriate signal model for the OFDMA uplink in a doubly selective fading channel and propose a minimum mean square error (MMSE) scheme and an MMSE successive detection (MMSE-SD) scheme to suppress ICI. It is shown that the MMSE scheme is the optimal linear scheme in terms of maximizing achievable data rate and that the MMSE-SD scheme is able to further remove ICI and exploit the Doppler diversity embedded in time-varying channels. As an essential component in ICI suppression, channel estimation is also considered. A basis expansion model (BEM) is formulated for the OFDMA uplink channel, and a pilot-aided channel-estimation algorithm is developed to track users' channels in the time domain. Simulation results are presented to illustrate the overall performance improvements that can be obtained from using the proposed ICI suppression and channel-estimation schemes.      

Extended MLSE receiver for the frequency-flat, fast-fading channel

This paper develops a maximum likelihood sequence estimation (MLSE) receiver for the frequency-flat, fast-fading channel corrupted by additive Gaussian noise when linear modulations (M-ASK, M-PSK, and M-QAM) are employed. This paper extends Ungerboeck's derivation of the extended MLSE receiver for the purely frequency-selective channel to the time-selective channel. Although the new receiver's structure and metric assume ideal channel state information (CSI) at the receiver, the receiver structure can be used wherever high-quality CSI is available. The receiver is maximum likelihood for a variety of channels, including Ricean, Rayleigh, lognormal, and additive white Gaussian noise (AWGN) channels. Bounds on the receiver's bit error rate (BER) are deduced for ideal and pilot tone CSI for fast Rayleigh fading. A crude lower bound is developed on the BER of predictor-based receivers for the same channel. This paper offers insight into matched filtering and receiver processing for the fast-fading channel and shows how pilot symbols and tones should be exploited     

脉冲噪声环境下改进的顽健循环时延估计算法

研究了脉冲噪声环境下循环平稳信号的时延估计问题,针对脉冲噪声环境中基于传统二阶谱相关函数的时延估计方法性能退化问题,提出了基于分数低阶循环谱的改进顽健算法。相对于传统算法,新算法对脉冲噪声、高斯噪声、干扰信号都具有较好的抑制作用。仿真结果证明了算法的有效性和顽健性。     

An adaptive correlator receiver for direct-sequence spread-spectrumcommunication

This paper presents a novel receiver for direct sequence spread-spectrum signals over channels containing interference and multipath. The receiver employs an adaptive correlator that jointly detects the transmitted data, removes interference, and compensates for multipath. The optimum correlation vector is derived by determining the Wiener vector that minimizes the mean squared error (MSE) between the transmitted data bit and the correlator output. For an additive white Gaussian noise (AWGN) channel, the optimal correlation vector is the spreading sequence used by the transmitter. For interference and multipath channels, the optimal correlation vector will suppress the interference and combine the multipath while optimizing the detection of the transmitted data bit. The paper presents analytical and simulation results which illustrate the bit-error rate (BER) performance of the receiver in multipath and narrowband interference. Additionally, simulation results are presented illustrating the convergence performance of the receiver when the tap weights are adjusted using either the least mean square (LMS) or recursive least squares (RLS) adaptive algorithms     

Fast Time-Varying Dispersive Channel Estimation and Equalization for an 8-PSK Cellular System

In this paper, a novel channel-estimation scheme for an 8-PSK enhanced data rates for GSM evolution (EDGE) system with fast time-varying and frequency-selective fading channels is presented. Via a mathematical derivation and simulation results, the channel impulse response (CIR) of the fast fading channel is modeled as a linear function of time during a radio burst in the EDGE system. Therefore, a least-squares-based method is proposed along with the modified burst structure for time-varying channel estimation. Given that the pilot-symbol blocks are located at the front and the end of the data block, the LS-based method is able to estimate the parameters of the time-varying CIR accurately using a linear interpolation. The proposed time-varying estimation algorithm does not cause an error floor that existed in the adaptive algorithms due to a nonideal channel tracking. Besides, the time-varying CIR in the EDGE system is not in its minimum-phase form, as is required for low-complexity reduced-state equalization methods. In order to maintain a good system performance, a Cholesky-decomposition method is introduced in front of the reduced-state equalizer to transform the time-varying CIR into its minimum-phase equivalent form. Via simulation results, it is shown that the proposed algorithm is very well suited for the time-varying channel estimation and equalization, and a good bit-error-rate performance is achieved even at high Doppler frequencies up to 300 Hz with a low complexity.     

Pilot Contamination Suppression Based Coordination in Multi-cell Massive MIMO Systems

The conventional millimeter wave systems are mostly designed to operate only for the Gaussian noise model. In many physical channels, such as urban and indoor radio channels, the ambient noise is known through experimental measurements to be non-Gaussian. Hence, recent research findings state that a mixture noise model with additive impulsive noise is a more realistic approximation for millimeter wave channels. In this paper, we propose a novel approach to suppress the impulsive noise effects on single-user millimeter wave massive multiple-input-multiple-output system using an adaptive fuzzy logic filter. Hence, a fuzzy median filter is applied to the system and it is aimed to minimize the effects of the impulsive noise by ordering samples based on fuzzy rank. Simulation results show that the proposed filter successfully suppresses the impulsive noise effects and achieves a better bit error rate and spectral efficiency performance than the competing methods in the literature while also working efficiently in Gaussian noise.

     

Performance of pulse-position modulation on measured non-directedindoor infrared channels

We examine the performance of pulse-position modulation (PPM) on measured channels with intersymbol interference (ISI). We summarize the bit-error-rate performance of unequalized systems and review the performance of maximum-likelihood sequence detection (MLSD) for PPM over ISI channels with additive white Gaussian noise. We evaluate the performance of PPM links over 46 experimentally measured indoor infrared channels. Detailed results are presented for 2, 4, 8, and 16-PPM at bit rates of 10 Mb/s and 30 Mb/s, and these techniques are compared to on-off keying. Our results show that when MLSD is employed, 16-PPM provides the best average-power efficiency among the modulation techniques considered in this study     

Block adaptive techniques for channel identification and datademodulation over band-limited channels

A new approach to the problem of data detection for communications over band-limited channels with unknown parameters is introduced. We propose a new way to implement the Viterbi algorithm (VA) for maximum-likelihood data sequence estimation (MLSE) in a known channel environment and utilize it to derive block adaptive techniques for joint channel and data estimation, when the channel-impulse response (CIR) is unknown. We show, via simulations, that we can achieve a probability of error very close to that of the known channel environment and nearly reach a mean-square error in the channel estimate as predicted by analytical bounds, operating on static channels, which exhibit deep nulls in their magnitude response and nonlinear phase. The proposed schemes accomplish channel acquisition after processing a few hundred symbols while operating without a training sequence, whereas linear blind equalizers, such as Sato's (1975) algorithm, fail to converge at all. The application of block processing to adaptive MLSE is also investigated for time-varying frequency-selective Rayleigh-fading channels, which are used for modeling mobile communication systems. In such environments it is shown that the proposed scheme exhibits improved performance compared to the conventional adaptive MLSE receiver using tentative delayed decisions     

莱斯信道的MLSD技术研究

主要研究在时变多径衰落信道下,基于Viterbi算法的最大似然序列检测技术（MLSD）.为了解决MLSD信道估计问题,使均衡器能够及时跟踪信道的变化,提出了基于逐幸存处理（PSP）和最小存活路径（MSP）的MLSD算法.在莱斯信道环境下,对上述算法进行了仿真.仿真结果表明,将RLS-MSP算法与减状态MLSD算法相结合的信道均衡技术具有对复杂信道的强跟踪能力,同时保证了较高的均衡性能和合理的复杂度.     

Multiuser receivers for CDMA systems in Rayleigh fading channels

Multiuser demodulation in relatively fast fading channels is analyzed. The optimal maximum likelihood sequence detection (MLSD) receiver is derived and a general suboptimal receiver to approximate the MLSD is proposed. The performance of the parallel interference cancellation (PIC) and decorrelating receivers is compared. The PIC receiver is demonstrated to achieve better performance in known channels than the decorrelating receiver, but it is observed to be more sensitive to the channel coefficient estimation errors than the decorrelator. At high channel loads the PIC receiver suffers from bit error rate (BER) saturation, whereas the decorrelating receiver does not. The performance of data-aided (DA) and decision-directed (DD) multiuser channel estimation is also compared. DA channel estimation is shown to be more robust than DD channel estimation, which may suffer from BER saturation caused by hangups at high signal-to-noise ratios (SNRs). The impact of channel estimation filter impulse response on the BER is studied by comparing optimal and suboptimal channel estimation filters. The implementation complexity of the decorrelating and PIC receivers is compared in terms of required floating point operations and clock cycles in a practical communication scenario. It is observed that the PIC receiver is only moderately more complex to implement than the conventional matched filter bank receiver, whereas the decorrelating receiver is significantly more complex