MDPSK多符号差分检测

针对MDPSK用于跳频通信只能采用差分解调,而现行差分解调方式与相干解调方式存在一定能量损失这一问题,提出了一种用于MDPSK的多符号差分检测方法,该方法每次比较N(N>2)个符号之间的相位,同时对N-1个符号作出判决。采用N=3,对跳频中常用的QDPSK方式进行了仿真,误比特率曲线表明:与传统的逐一符号差分检测相比,该方法有1dB能量增益。     

Reduced state Viterbi differential phase detection of MDPSK signals

An improved differential phase detection scheme that uses a reduced state Viterbi algorithm (RSVDPD) is proposed for the reception of M-ary differential phase shift keying (MDPSK) signals. The transmitted sequence is estimated from the received signal phases only. The number of trellis states equals that of the signal constellation points M. The branch metric is computed by tracing back the surviving path connected to each state. The bit error rate (BER) performance with RSVDPD is evaluated using computer simulation for 4DPSK transmission in additive white Gaussian noise (AWGN) channels     

Decision-feedback differential detection of MDPSK for flat Rayleighfading channels

In this paper, decision-feedback differential detection (DF-DD) of M-ary differential phase-shift keying (MDPSK) signals, which has been introduced previously for the additive white Gaussian noise (AWGN) channel by Leib et al. (1988) and Edbauer (1992), is extended to flat Rayleigh fading channels. The corresponding DF-DD metric is derived from the multiple-symbol detection (MSD) metric and for genie-aided DF-DD, an exact expression for the bit-error rate (BER) of QDPSK (M=4) is calculated. Furthermore, the dependence of BER on the power spectrum of the fading process is investigated for feedback filters of infinite order. It is shown that in this case, for ideally bandlimited fading processes, the error floor of conventional differential detection (DD) can be removed entirely. Simulation results confirm that both MSD and DF-DD with feedback filters of finite order can reduce the error floor of conventional DD significantly. DF-DD thereby causes considerably less computational load     

Low complexity multisymbol differential detection of MDPSK overflat correlated Rayleigh fading channels

Low complexity algorithms for implementing multisymbol differential detection (MSDD) over flat correlated Rayleigh fading channels are proposed, which are extensions of the low complexity MSDD over additive white Gaussian noise channels also proposed by the authors. The complexities of the proposed algorithms increase roughly linearly with block length N while optimum MSDD increases exponentially with N. Simulation results show almost the same performances for practical N     

Decision-feedback differential demodulation of bit-interleavedcoded MDPSK

A novel simple receiver structure for M-ary differential phase shift keying (MDPSK) transmission over flat Rayleigh fading channels without channel state information is proposed. Convolutional codes are used for error correction and bit-interleaving as an appropriate means to combat the effects of fading, and the hard decisions of the Viterbi algorithm are fed back during the decoding process in order to improve the calculated bit metric. Iterative decoding with this decision-feedback differential demodulation, (DF-DM) results in significant power efficiency gains compared to those achieved using conventional differential demodulation, while the computational complexity remains low     

Decision-feedback differential detection based on linear predictionfor MDPSK signals transmitted over Ricean fading channels

In this paper, linear prediction-based decision-feedback differential detection (DF-DD) for M-ary differential phase-shift keying (MDPSK) signals transmitted over Ricean fading channels is proposed. This scheme can improve conventional DD significantly for a multitude of frequency-nonselective channels, as shown analytically and by computer simulations. Prediction-based DF-DD is particularly well suited for application in mobile communications since the predictor coefficients may be updated regularly using the recursive least squares (RLS) algorithm. Here, adaptation can start blind, i.e., no training sequence and no a prior knowledge about the channel statistics are required. A further important characteristic of the proposed detection scheme is that no degradation occurs under frequency offset. The bit error rate (BER) performance of QDPSK with genie-aided prediction-based DF-DD is analyzed, and it is shown under which conditions the irreducible error floor of conventional DD can be removed entirely. In addition, the influence of Doppler shift is discussed. Last, the proposed scheme is compared with a second DF-DD scheme, which is based on multiple-symbol detection     

Blind sequence detection without channel estimation

This paper proposes a new blind sequence estimation method for single-input single-output (SISO) systems utilizing an optimal trellis search, which is performed by a channel-independent Viterbi algorithm (CIVA). In contrast to the traditional Viterbi algorithm that requires accurate channel estimation, CIVA does not require channel coefficients. Instead, the metrics are calculated from a bank of test vectors designed off-line. The proposed algorithm has outstanding performance under most of the channel conditions. Specifically, it does not suffer from ill-conditioned channels. In addition, it does not depend on channel correlation estimation and, therefore, has fast convergence. Simulations demonstrate its superior performance over even most training-based equalization algorithms     

Maximum likelihood sequence detection in nonlinear satellite channels

A technical study by computer simulation has been performed to assess the potential of maximum likelihood sequence detection (MLSD) in a band-limited nonlinear satellite channel with two nonlinear elements [a high-power amplifier (HPA) and a transponder traveling wave tube amplifier (TWTA)] operating in tandem. Starting with a brief background on digital modem development, this paper outlines the basic principle of MLSD and a conceptual structure suitable for satellite channel applications. The bit-error rate has been computed for a realistic nonlinear satellite channel using Forney's approach with the Viterbi algorithm. The upper bound of channel performance improvement in a typical satellite link has been identified.     

A nonlinear filtering approach to estimation and detection inmobile communications

The paper develops an open-loop digital receiver suitable for operation with frequency flat-fading channels disturbed by fast-fading conditions and large carrier phase variations. The receiver consists of a bank of “matched” stochastic nonlinear filters (NLFs) and a maximum a posteriori probability (MAP) decision processor driven by the filters' innovations processes. This structure is able to perform symbol-by-symbol detection while keeping track of multiplicative distortion (carrier amplitude and phase) within the symbol interval. The NLF propagates probability densities represented as products of Tikhonov and Gaussian functions, whose parameters are computed according to a minimum Kullback (1959) distance criterion, i,e,. we adopt an information preserving strategy. This filter is hangup free and outperforms the extended Kalman-Bucy (1972, 1973) filter (EKBF), especially in terms of phase acquisition. These characteristics explain why the NLF-based receiver may exhibit much lower error probabilities than those obtained with an equivalent EKBF-based receiver. Simulations show that the proposed detection/estimation scheme is robust against mistuning of the receiver parameters, being appropriate for all-digital modems in mobile radio communications     

Channel estimation for nonlinear MIMO receiver with square envelope detection

Two practical channel estimation schemes, the moment‐based first‐and‐second moments and the simplified maximum likelihood estimators, are proposed for the MIMO/on–off keying system with square envelope detection applied for wireless sensor networks. Here, both the channel response and noise power are estimated simultaneously in comparison with other approaches in which the noise quantity is assumed to be known at the receiver. Hence, the developed estimators are more practical than those estimators without noise power estimation. Simulation results reveal that the system with both proposed schemes can achieve an excellent BER performance in a wide signal‐to‐noise ratio (SNR) range. More specifically, we observed that the simplified maximum likelihood estimator performed as well as the moment‐based first‐and‐second moments estimator for SNR greater than 7.5 dB, yet had much more decline at low SNRs. This study also investigated the effects of the numbers of receive antennas and transmit antennas on the system performance. Simulation results demonstrated that, at the BER of 10^?3, the 5 × 5 system had an improvement of 7 dB in SNR compared with the 3 × 3 system. Copyright © 2011 John Wiley & Sons, Ltd.     

Performance of sequence estimation scheme of narrowband digital FMsignals with limiter-discriminator detection

A communication scheme using binary FM with noncoherent limiter-discriminator detection has been well known. Up to now, the improvement of bit error rate at the receiver side has been carried out through the bandwidth optimization of the IF filter, the decision feedback equalization (DFE), or simple two-state maximum likelihood sequence estimator (MLSE). This channel is inherently the intersymbol interference (ISI) channel due to the premodulation baseband filtering as well as the narrowband IF filtering. So the sequence estimation scheme using the Viterbi algorithm can be applied successfully, although the channel is not additive white Gaussian and maximum likelihood in the strict sense. In this paper, through computer simulations, we examine the actual BER improvement of the sequence estimation scheme with multiple-state trellis especially for MSK and GMSK signals. We mainly consider static AWGN and frequency nonselective Rician fading channels. Consequently, by adjusting the IF filter bandwidth, very large estimation gains are obtained compared to the conventional DFE or MLSE detector for AWGN and Rician fading channels. This scheme does not produce large demodulation delay and is implemented only by adding the signal processing part to the final stage of the receiver. This scheme seems to be very useful for any applications including satellite mobile channels     

基于非线性抗噪声估计的视觉显著性弱小目标检测

针对红外图像处理技术中弱小目标检测的重要性及关键性,提出一种基于非线性抗噪声估计的检测算法来解决高可靠性、高鲁棒性的弱小目标检测问题。提出的方法基于传统视觉显著度算法及空间距离处理方法,对目标及背景区域采用非线性加权方法进行估计,在不显著降低目标信号信噪比的基础上,削弱孤立微小噪声点对检测算法性能的影响,可提高抗噪性能。首先,采用模块化及非线性映射方式预测背景;然后,融入距离相关因子滤除噪声干扰;最后,在处理结束的图像上进行二值化阈值分割,自动检测并向下一级处理软件输出目标位置信息。实验结果表明:提出的算法与近年来先进的弱小目标检测算法相比,在受试者测试曲线上,在相同的虚警率下,可获得更高的检测率,对背景噪声的抑制很明显;在局部信噪比及背景抑制因子的测试比对数据上,提出的算法可获得更高的检测指标。缺点是算法采用了非线性处理技术,运算效率较低,需进一步优化算法以提高计算速度,实现算法的实时目标检测。     

Unscented filtering and nonlinear estimation

The extended Kalman filter (EKF) is probably the most widely used estimation algorithm for nonlinear systems. However, more than 35 years of experience in the estimation community has shown that is difficult to implement, difficult to tune, and only reliable for systems that are almost linear on the time scale of the updates. Many of these difficulties arise from its use of linearization. To overcome this limitation, the unscented transformation (UT) was developed as a method to propagate mean and covariance information through nonlinear transformations. It is more accurate, easier to implement, and uses the same order of calculations as linearization. This paper reviews the motivation, development, use, and implications of the UT.     

Decision feedback sequence estimation for unwhitened ISI channelswith applications to multiuser detection

Decision feedback sequence estimation (DFSE), which is a reduced-complexity alternative to maximum likelihood sequence estimation (MLSE), can be used effectively for equalization of intersymbol interference (ISI) as well as for multiuser detection. The algorithm performs very well for whitened (minimum-phase) channels. For nonminimum-phase channels, however, the algorithm is not very effective. Moreover, DFSE requires a noise-whitening filter, which may not be feasible to compute for time-varying channels such as a multiuser direct-sequence code division multiple access (DS-CDMA) channel. Noise-whitening is also cumbersome for applications that involve bidirectional equalization such as the global system for mobile communication (GSM) system. In such conditions, it is desirable to use the Ungerboeck (1974) formulation for sequence estimation, which operates directly on the discrete-time unwhitened statistic obtained from conventional matched filtering. Unfortunately, DFSE based on matched filter statistics is severely limited by untreated interference components. We identify the anticausal interference components, using an error probability analysis. This leads us to a modified unwhitened decision feedback sequence estimator (MUDFSE) in which the components are canceled, using tentative decisions. We obtain approximate error probability bounds for the proposed algorithm. Performance results indicate that the modified algorithm, used on unwhitened channels with relatively small channel correlations, provides similar performance/complexity tradeoffs as the DFSE used on the corresponding whitened minimum-phase channels. The algorithm is especially attractive for multiuser detection for asynchronous DS-CDMA channels with long spreading codes, where it can achieve near-MLSE performance with exponentially lower complexity     

Performance of noncoherent maximum-likelihood sequence detection for differential OFDM systems with diversity reception

For the single-carrier M-ary differential phase-shift keying (MDPSK), the multiple-symbol differential detector, or the noncoherent maximum-likelihood sequence detector (NSD), and its three special cases, namely, the noncoherent one-shot detector, the linearly predictive decision-feedback (DF) detector, and the linearly predictive Viterbi receiver are reviewed based on a hierarchical interpretation. For the multicarrier transmission, the differential orthogonal frequency division multiplexing (OFDM) systems with diversity reception are discussed. It is well known that there are two types of differential OFDM systems, namely, the time domain differential OFDM (TD-OFDM) and the frequency domain differential OFDM (FD-OFDM). In this paper, the NSD and its special cases are incorporated to the differential OFDM systems. Furthermore, we provide a simple closed-form bit-error-rate (BER) expression for the differential OFDM systems utilizing the noncoherent one-shot detector with diversity reception in the time-varying multipath Rayleigh fading channels. Numerical results have revealed that, with multi-antenna diversity reception, the performance of the noncoherent one-shot detector is improved significantly. However, when only one or two receive antennas are available, the implementation of the linearly predictive DF detector or the linearly predictive Viterbi receiver is necessary for achieving better and satisfactory performance.     

On channel estimation and sequence detection of interleaved codedsignals over frequency nonselective Rayleigh fading channels

Due to the receiver complexity introduced by interleaving, the implementation of maximum likelihood (IML) decoding of interleaved coded signals transmitted over frequency nonselective Rayleigh fading channels has been shown to be practically impossible. As an alternative, a two-stage receiver structure has been proposed, where the channel estimation and sequence decoding are done separately. The channel estimation issue in a two-stage receiver is examined in detail in this paper. It is shown that although an optimum (maximum a posteriori (MAP)) channel estimation is not possible in practice, it can be approached asymptotically by joint MAP estimation of the channel and the coded data sequence. The implementation of the joint MAP estimation is shown to be an ML sequence estimator followed by an minimum mean-square error (MMSE) channel estimator. Approximate fill sequence estimation using pilot symbol interpolation is also studied, and through computer simulations, its performance is compared to receivers using hit sequence estimation. The effect of decision delay (DD), prediction order, and pilot insertion rate (PIR) on the reduced complexity ML sequence estimation is investigated as well. Finally, a practical receiver is proposed that makes the best compromise among the error performance, receiver complexity, DD, and power (or bandwidth) expansion due to pilot insertion     

Low-complexity joint channel estimation and decoding for pilotsymbol-assisted modulation and multiple differential detection systemswith correlated Rayleigh fading

Joint channel estimation and decoding in a time-varying Rayleigh fading channel is considered. Knowing that the optimal solution or even the truncated near-optimal solution using iterative processing has an exponential complexity which hinders the practicability, a reduced complexity approach is proposed. This approach keeps the existing channel estimation and decoding schemes almost intact, while applying iterative processing to effectively exchange information between them. Thus, the complexity is rendered linear, and estimator adaptability can be easily established. We apply this approach to pilot symbol-assisted modulation (PSAM) and differentially modulated systems. It turns out that the performance is improved and the robustness to fading parameters is enhanced. Through simulations, we also show that the proposed method performs almost as well as the near-optimal design     

Observability of nonlinear differential algebraic systems

We define the smooth observability of nonlinear DAE systems and give sufficient conditions for this property to hold locally in a neighborhood of a solution. The matrix rank conditions for observability are verifiable by a combination of symbolic and numerical linear algebra computations. These conditions generalize conditions that have appeared in the literature for observability of linear time-varying DAE systems. We indicate how the main result is potentially useful in studying a system's zero dynamics. Some relevant rank properties of Hessenberg DAE systems are established.This work was supported in part by the Grant-In-Aid Program for Faculty of Virginia Commonwealth University.     

Improving the efficiency of Sammon's nonlinear mapping by using clustering archetypes

Sammon's nonlinear mapping technique is discussed and certain inefficiencies are highlighted. It is shown how the algorithm can be streamlined by using appropriately chosen cluster archetypes. This results in reductions in storage requirements and in execution time, the latter by at least an order of magnitude.     

Joint order detection and blind channel estimation by least squaressmoothing

A joint order detection and blind estimation algorithm for single input multiple output channels is proposed. By exploiting the isomorphic relation between the channel input and output subspaces, it is shown that the channel order and channel impulse response are uniquely determined by finite least squares smoothing error sequences in the absence of noise. The proposed subspace algorithm is shown to have marked improvement over existing algorithms in performance and robustness in simulations