双向中继信道中物理层网络编码的检测

对双向中继信道中物理层网络编码的检测进行了研究,最大似然检测性能好但是实现复杂度高。因此,在信源节点未知信道状态信息情况下,提出了2种检测方案:基于似然比函数的似然比检测和基于最大后验概率准则的最大后验概率检测。同时,针对信源节点已知信道状态信息的特殊情形,进行了同样的推导。分析和仿真结果表明,相比于分别检测出2个信源信息的最大似然检测,似然比检测的BER性能更优,但似然比检测需要知道额外的噪声方差信息,最大后验概率检测与最大似然检测等价,而且最大后验概率检测在实现复杂度上相对较低。     

New Soft Output Viterbi Algorithm for Mobile Communication System

Soft output Viterbi algorithm(SOVA) is a turbo decoding algorithm that is suitable for hardware implementation. But its performance is not so good as maximum a posterior probability(MAP) algorithm. So it is very important to improve its performance. The non-correlation between minimum and maximum likelihood paths in SOVA is analyzed. The metric difference of both likelihood paths is used as iterative soft information, which is not the same as the traditional SOVA. The performance of the proposed SOVA is demonstrated by the simulations. For 1024-bit frame size and 9 iterations with signal to noise ratio from 1dB to 4dB, the experimental results show that the new SOVA algorithm obtains about more 0.4dB and 0.2dB coding gains more than the traditional SOVA and Bi-SOVA algorithms at bit error rate(BER) of 1×10~ -4 , while the latency is only half of the Bi-direction SOVA decoding.     

Coherent MAP detection of DQPSK bits

Both IS-136 and PDC digital cellular systems employ forward error correction (FEC) encoding followed by a form of DQPSK modulation. In this letter, we derive the maximum a posteriori (MAP) bit detector for DQPSK modulation in non-ISI channels for a coherent receiver with one or more antennas. The MAP detector forms a bit log-likelihood ratio, which provides the optimal “soft information” for MLSE or MAP convolutional decoding. MAP detection requires exponentiation and logarithm operations, as well as knowledge of the noise covariance. To avoid these operations, two approximate forms are developed, which do not require the noise covariance value under certain assumptions. Both approximate approaches, when used with soft FEC decoding, are within 0.5 dB of the optimal approach     

CPM调制的迭代检测技术

CPM信号具有包络恒定、峰均比小、功率利用率高的优点。针对CPM信号的特征,比较了最大似然序列检测Viterbi算法和逐符号的最大后验概率(MAP)解调算法的特点,重点研究了使用迭代检测技术进行软输入输出解调及译码的MAP解调方法。在AWGN信道条件下对CPM全响应和部分响应信号进行了误码性能仿真,结果表明采用相干解调和译码,迭代检测方案可得到较高的编码增益。     

Spectrum estimation of short-time stationary signals in additivenoise and channel distortion

In this work, spectrum estimation of a short-time stationary signal that is degraded by both channel distortion and additive noise is addressed. A maximum likelihood estimation (MLE) algorithm is developed to jointly identify the degradation system and estimate short-time signal spectra. The source signal is assumed to be generated by a hidden Markov model (HMM) with state-dependent short-time spectral distributions described by mixtures of Gaussian densities. The distortion channel is linear time-invariant, and the noise is Gaussian. The algorithm is derived by using the principle of expectation-maximization (EM), where the unknown parameters of channel and noise are estimated iteratively, and the short-time signal power spectra are obtained from the posterior sufficient statistics of the source signal. Other spectral representation parameters, such as autoregressive model parameters or cepstral parameters, are obtained by minimum mean-squared error (MMSE) estimation from the power spectral estimates. The estimation algorithm was evaluated on simulated signals at the signal-to-noise ratios (SNRs) of 20 dB down to 0 dB, where it produced convergent estimation and significantly reduced spectral distortion     

Comments on "A Map Symbol Synchronizer Implemented with Charge-Coupled Devices"

We show that the synchronizer described in the above paper is not a maximum a posteriori (MAP) synchronizer, as it searches the minimum instead of the maximum of the log likelihood ratio. Only a slight modification is required to transform it into a MAP synchronizer. By a theoretical analysis, we show that this modification substantially reduces the rms timing error.     

Performance of MAP Reconstruction for Hot Lesion Detection in Whole-Body PET/CT: An Evaluation With Human and Numerical Observers

For positron emission tomography (PET) imaging, different reconstruction methods can be applied, including maximum likelihood (ML ) and maximum a posteriori (MAP) reconstruction. Postsmoothed ML images have approximately position and object independent spatial resolution, which is advantageous for (semi-) quantitative analysis. However, the complex object dependent smoothing obtained with MAP might yield improved noise characteristics, beneficial for lesion detection. In this contribution, MAP and postsmoothed ML are compared for hot spot detection by human observers and by the channelized Hotelling observer (CHO). The study design was based on the “multiple alternative forced choice” approach. For the MAP reconstruction, the relative difference prior was used. For postsmoothed ML, a Gaussian smoothing kernel was used. Both the human observers and the CHO performed slightly better on MAP images than on postsmoothed ML images. The average CHO performance was similar to the best human performance. The CHO was then applied to evaluate the performance of priors with reduced penalty for large differences. For these priors, a poorer detection performance was obtained.      

Detection of binary Markov sources over channels with additiveMarkov noise

We consider maximum a posteriori (MAP) detection of a binary asymmetric Markov source transmitted over a binary Markov channel. The MAP detector observes a long (but finite) sequence of channel outputs and determines the most probable source sequence. In some cases, the MAP detector can be implemented by simple rules such as the “believe what you see” rule or the “guess zero (or one) regardless of what you see” rule. We provide necessary and sufficient conditions under which this is true. When these conditions are satisfied, the exact bit error probability of the sequence MAP detector can be determined. We examine in detail two special cases of the above source: (i) binary independent and identically distributed (i.i.d.) source and (ii) binary symmetric Markov source. In case (i), our simulations show that the performance of the MAP detector improves as the channel noise becomes more correlated. Furthermore, a comparison of the proposed system with a (substantially more complex) traditional tandem source-channel coding scheme portrays superior performance for the proposed scheme at relatively high channel bit error rates. In case (ii), analytical as well as simulation results show the existence of a “mismatch” between the source and the channel (the performance degrades as the channel noise becomes more correlated). This mismatch is reduced by the use of a simple rate-one convolutional encoder     

BAD: bidirectional arbitrated decision-feedback equalization

The bidirectional arbitrated decision-feedback equalizer (BAD), which has bit-error rate performance between a decision-feedback equalizer (DFE) and maximum a posteriori (MAP) detection, is presented. The computational complexity of the BAD algorithm is linear in the channel length, which is the same as that of the DFE, and significantly lower than the exponential complexity of the MAP detector. While the relative performance of BAD to those of the DFE and the MAP detector depends on the specific channel model, for an error probability of 10/sup -2/, the performance of BAD is typically 1-2 dB better than that of the DFE, and within 1 dB of the performance of MAP detection.     

Sequence MAP decoding of trellis codes for Gaussian and Rayleighchannels

This paper considers the use of sequence maximum a posteriori (MAP) decoding of trellis codes. A MAP receiver can exploit any “residual redundancy” that may exist in the channel encoded signal in the form of memory and/or a nonuniform distribution, thereby providing enhanced performance over very noisy channels, relative to maximum likelihood (ML) decoding. The paper begins with a first-order two-state Markov model for the channel encoder input. A variety of different systems with different source parameters, different modulation schemes, and different encoder complexities are simulated. Sequence MAP decoding is shown to substantially improve performance under very noisy channel conditions for systems with low-to-moderate redundancy, with relative gain increasing as the rate increases. As a result, coding schemes with multidimensional constellations are shown to have higher MAP gains than comparable schemes with two-dimensional (2-D) constellations. The second part of the paper considers trellis encoding of the code-excited linear predictive (CELP) speech coder's line spectral parameters (LSPs) with four-dimensional (4-D) QPSK modulation. Two source LSP models are used. One assumes only intraframe correlation of LSPs while the second one models both intraframe and interframe correlation. MAP decoding gains (over ML decoding) as much as 4 dB are achieved. Also, a comparison between the conventionally designed codes and an I-Q QPSK scheme shows that the I-Q scheme achieves better performance even though the first (sampler) LSP model is used     

A Bayesian estimation approach for speech enhancement using hiddenMarkov models

A Bayesian estimation approach for enhancing speech signals which have been degraded by statistically independent additive noise is motivated and developed. In particular, minimum mean square error (MMSE) and maximum a posteriori (MAP) signal estimators are developed using hidden Markov models (HMMs) for the clean signal and the noise process. It is shown that the MMSE estimator comprises a weighted sum of conditional mean estimators for the composite states of the noisy signal, where the weights equal the posterior probabilities of the composite states given the noisy signal. The estimation of several spectral functionals of the clean signal such as the sample spectrum and the complex exponential of the phase is also considered. A gain-adapted MAP estimator is developed using the expectation-maximization algorithm. The theoretical performance of the MMSE estimator is discussed, and convergence of the MAP estimator is proved. Both the MMSE and MAP estimators are tested in enhancing speech signals degraded by white Gaussian noise at input signal-to-noise ratios of from 5 to 20 dB     

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.     

基于改进传感器模式噪声提取模型的源相机识别

针对当前基于传感器模式噪声(sensor pattern noise,SPN)提取模型处理压缩 视频来源检测的识别效果较差问题,提出一种基 于多尺度变换域自适应维纳滤波和一种加权最大似然估计的改进SPN提取模型。 首先干预视 频的编解码过程,在编解码器的环路滤波模块前提取视频帧,然后将视频帧输入双密度双树 复小波变换 自适应维纳滤波模型中提取噪声残差,最后使用加权最大似然估计从噪声残差中估计得到SPN。在公共视频源取证数据库VISION上进行测试比较,实验结果表明所提出的改进SPN提取 模型在ROC曲线和Kappa统计系数两种评价指标上的识别效果优于 传统SPN提取算法。     

Analysis and design of trellis codes optimized for a binarysymmetric Markov source with MAP detection

We consider the problem of transmitting a binary symmetric Markov source (BSMS), over the additive white Gaussian noise (AWGN) channel. The coding technique considered is trellis-coded modulation (TCM), where we utilize decoders which implement the maximum-likelihood (ML) and maximum a posteriori (MAP) criteria. Employing 8-PSK Ungerboeck codes on a BSMS with state transition probability 0.1, we first show that the MAP decoder realizes a 0.8-2.1-dB coding gain over the ML decoder. Motivated by these gains, we consider the design of trellis codes optimized for the BSMS/AWGN/MAP system. An approximate union bound is established for this system. Using this bound, we found codes which exhibit additional 0.4-1.1-dB gains over Ungerboeck codes. Finally, we compare the proposed TCM system with a tandem coding system. At normalized signal-to-noise ratio (SNR) of 10.8 dB and below, the proposed system significantly outperforms the tandem system     

Terra MODIS第5波段红外遥感影像条带噪声的探测与校正

由于Terra MODIS传感器第5波段（1.230~1.250 m）中部分探测元件出现故障,从而导致整幅影像上存在明显的条带噪声。对于地理校正后的MODIS影像数据,其条带噪声的分布并不是完全规则的,还可能存在不连续的现象,加大了对噪声进行处理的难度。提出一种对条带噪声进行检测与去除的方法,首先利用局部梯度对条带噪声的位置进行探测。然后在基于最大后验概率的框架下结合噪声模型与Huber-Markov先验,并通过梯度下降算法进行噪声的去除。使用真实的遥感数据进行了实验,所展示的恢复后数据和对应的频谱图都证明了文中方法的有效性。     

An Optimal Chip-Level OCDMA Detector by Using Photon Counting

This paper studies the optimal bit error rate (BER) performance of chip-level detection for optical code division multiple-access (OCDMA) systems in the presence of shot noise. To attain the optimal BER of chip-level detection, a chiplevel detector that uses a limiter on the photon counts at each weighted chip is first proposed. Then, the monotonicity of the likelihood ratio used in the maximum a posteriori (MAP) probability criterion is established. With this monotonicity, a sufficient condition characterized by the cap levels of the limiters and the average photon counts per pulse is obtained, under which the detector is simply an AND detector to attain the optimal BER of chip-level detection. The detector?s performance and its comparison to those of other detectors are also studied by numerical studies.     

An error resilient scheme for image transmission over noisychannels with memory

This article addresses the use of a joint source-channel coding strategy for enhancing the error resilience of images transmitted over a binary channel with additive Markov noise. In this scheme, inherent or residual (after source coding) image redundancy is exploited at the receiver via a maximum a posteriori (MAP) channel detector. This detector, which is optimal in terms of minimizing the probability of error, also exploits the larger capacity of the channel with memory as opposed to the interleaved (memoryless) channel. We first consider MAP channel decoding of uncompressed two-tone and bit-plane encoded grey-level images. Next, we propose a scheme relying on unequal error protection and MAP detection for transmitting grey-level images compressed using the discrete cosine transform (DCT), zonal coding, and quantization. Experimental results demonstrate that for various overall (source and channel) operational rates, significant performance improvements can be achieved over interleaved systems that do not incorporate image redundancy.     

Experimental Performance of Point Process Estimators of Optical Pulse Delay

Experimental results of estimating the delay of optical pulses in the presence of background noise based on the occurrence times of photoelectrons emitted by a direct detection photoelectric effect receiver are presented. Both minimum mean square error (MMSE) and maximum likelihood estimation techniques were used. The MMSE estimates of the delay of both Gaussian and rectangular optical pulses were obtained from the evolution of the posterior conditional probability density of the pulse delay given the photocount occurrence times. For signal to noise intensity ratios as low as 10 dB, it was found that the experimental performance of the MMSE delay estimates remained near performance lower bounds and that a rectangular pulse gave better performance than a Gaussian pulse of equal signal energy and equal peak signal intensity. At lower signal to noise ratios, the performance of the estimates for both pulse shapes deteriorated rapidly. It is shown that, in the absence of background noise, MMSE and ML estimation are equivalent.     

On the partial MAP detection with applications to MIMO channels

We investigate a multidimensional detection problem with a partial information of the a posteriori probability, which is referred to as the partial maximum a posteriori probability (MAP) detection problem. We show that the maximum likelihood (ML) detection of a higher dimension can be reduced to the ML detection of a lower dimension with cancellation under a certain condition through the formulation of the partial MAP detection problem. Using this, we can propose a computationally efficient algorithm to apply to the detection problem for multiple input multiple output (MIMO) channels including multiple transmit and multiple receive antenna (MTMR) channels and intersymbol interference (ISI) channels. It is shown that the proposed method has less error propagation effect, and its performance is close to that of the full ML detection with a lower computational complexity.     

A monolithically integrated HEMT-HBT low noise high linearityvariable gain amplifier

We report on a 1-6 GHz HEMT-HBT three-stage variable gain amplifier (VGA), which is realized using selective molecular beam epitaxy (MBE). The VGA integrates an HEMT low noise amplifier with an HBT analog current-steer variable gain cell and output driver stage to achieve a combination of low noise figure, wide gain control, and high linearity. The HEMT-HBT VGA MMIC obtains a maximum gain of 21 dB with a gain control range >30 dB, a minimum noise figure of 4.3 dB, and an input IP3 (IIP3) greater than -4 dBm over 25 dB of gain central range. By integrating an HEMT instead of on HBT preamplifier stage, the VGA noise figure is improved by as much as 2 dB compared to an all-HBT single-technology design. The HEMT-HBT MMIC demonstrates the functional utility and RF performance advantage of monolithically integrating both HEMT and HBT devices on a single substrate