New results about analysis and design of TCM for ISI channels andcombined equalization/decoding

New upper bounds for the performance of the optimum combined symbol-by-symbol (SbS) Abend-Fritchman-like equalizer and decoder are presented, and a related criterion for the actual design of good trellis-coded-modulated (TCM) schemes effectively matched to the distortion introduced by the intersymbol interference (ISI)-corrupted transmission channel is developed. The actual application of the proposed design criterion is also addressed     

SNR-Invariant Importance Sampling for Hard-Decision Decoding Performance of Linear Block Codes

We present an importance sampling (IS) technique for evaluating the word-error rate (WER) and bit-error rate (BER) performance of binary linear block codes under hard-decision decoding. This IS technique takes advantage of the invariance of the decoding outcome to the transition probability of the binary symmetric channel given a received error pattern, and is equivalent to the method of stratification for variance reduction. A thorough analysis of the accuracy of the proposed signal-to-noise-ratio-invariant IS (IIS) estimator based on computing its relative bias and standard deviation is provided. Under certain conditions, which may be achieved fairly easily for certain code and decoder combinations, we demonstrate that it is possible to use the proposed IIS technique to accurately evaluate the WER and BER to arbitrarily low values. Further, in all cases, the probability estimates obtained via IIS always serve as a lower bound on the true probability values     

Importance sampling simulation for evaluating the lower-bound BERof the Bayesian DFE

An importance sampling (IS) simulation technique, originally derived by Iltis (1995) for Bayesian equalizers, is extended to evaluate the lower-bound bit error rate of the Bayesian decision feedback equalizer (under the assumption of correct decisions being fed back). Using a geometric translation approach, it is shown that the two subsets of opposite-class channel states are always linearly separable. A design procedure is presented, which chooses appropriate bias vectors for the simulation density to ensure asymptotic efficiency of the IS simulation     

IDMA水声多用户下行通信链路迭代接收算法

水声通信网络的快速发展对多用户水声物理层通信技术提出了迫切的需求。本文主要针对水声多用户下行通信链路中存在严重码间干扰和多址干扰的问题,提出了一种交织多址（IDMA）水声多用户下行通信链路迭代接收算法,能够根据译码器输出的软信息对估计的信道进行迭代更新,同时根据信道估计结果重建各用户对当前用户的多址干扰（MAI）,并使用干扰抵消器予以抵消,通过在均衡器、译码器和干扰抵消器之间的迭代逐次提高当前用户信息的输出信噪比,最终实现正确解调。其中,信道估计算法采用LMMSE初始化的分簇OMP稀疏信道估计算法,多普勒估计采用时频二维搜索结合自相关相位估计的方法,计算机仿真结果表明该接收机具有与已知信道时接近或相当的性能。进行了多用户水声通信海上试验,在4.5km、6km和7km三个距离实现了对2个用户、3个用户和4个用户的同时通信,每个用户的通信净速率约为500bps,证明了本文所提出的方法能够有效应用在多用户水声通信中,为水声通信网络的发展提供了一种重要的物理层通信技术手段。      

Orthogonal-transformed variable-gain least mean squares (OVLMS)algorithm for fractional tap-spaced adaptive MLSE equalizers

A fast channel-estimation scheme for adaptive maximum-likelihood sequence-estimation (MLSE) equalizers called the orthogonal-transformed variable-gain least mean squares (OVLMS) algorithm is proposed. This algorithm requires only as many operations as the least mean squares algorithm in spite of its excellent performance. Furthermore, an operational complexity reduction method is proposed in which the orthogonal matrix is reconfigured as eigenvectors with valid eigenvalues. The OVLMS algorithm is theoretically analyzed and is shown to have both a fast acquisition and a good tracking performance. An equalizer using OVLMS (OVLMS-MLSE) experimentally attains a 5-dB improvement in bit-error rate (BER) performance at BER of 1.0×10 ^-4 over coherent detection. The OVLMS-MLSE is found to be free of the degradation caused by sampling phase error. Finally, the OVLMS-MLSE equalizer is experimentally verified to synchronize within five symbols     

MLSE and soft-output equalization for trellis-coded continuousphase modulation

This paper presents two equalizer structures for trellis-coded continuous phase modulation (TC-CPM) on multipath fading intersymbol interference (ISI) channels. An equivalent discrete-time (DT) model is developed by combining the tapped-delay-line (TDL) model of the frequency-selective channel and by oversampling at the receiver. The (noninterleaved) fractionally spaced maximum-likelihood sequence estimation (MLSE) equalizer performs continuous phase modulation (CPM) demodulation, trellis-coded modulation (TCM) decoding, and channel equalization by exploiting the finite state nature of the ISI-corrupted TC-CPM signal. Both simulation and analytical results show diversity-like improvement when performing joint MLSE decoding and equalization. For the interleaved soft-output equalizer, the soft symbol metric is delivered to the TCM decoder by using a forward and backward recursion algorithm. Three variants of the soft-output equalizer are examined. We conclude that the backward recursion is essential to partial response CPM schemes, and with moderate complexity, the soft-output equalizer can have a substantial advantage over a noninterleaved MLSE equalizer     

A fixed-lag particle smoother for blind SISO equalization of time-varying channels

We introduce a new sequential importance sampling (SIS) algorithm which propagates in time a Monte Carlo approximation of the posterior fixed-lag smoothing distribution of the symbols under doubly-selective channels. We perform an exact evaluation of the optimal importance distribution, at a reduced computational cost when compared to other optimal solutions proposed for the same state-space model. The method is applied as a soft input?soft output (SISO) blind equalizer in a turbo receiver framework and simulation results are obtained to show its outstanding BER performance.     

Viterbi-based algorithm for side-match vector quantization overnoisy channels

Side-match vector quantization is a finite-state technique for image coding. This research shows that the side-match vector quantization is an error-propagating code and it is similar to a catastrophic convolutional code. Here, we propose a Viterbi-based algorithm to solve this problem. Various noise detection algorithms are integrated into the Viterbi algorithm (to yield the Viterbi-based algorithm) for a much better performance. According to the simulation of a binary symmetric channel with random bit-error rate (BER) 0.1%-0.01%, the Viterbi-based algorithm provides 2.8-9.6 dB and 2.3-8.4 dB gain compared with the conventional side-match vector quantization decoder and the Viterbi decoder, respectively. In addition, the proposed algorithm requires much fewer computations than the Viterbi algorithm     

Performance of digital DECT radio links based on semianalyticalmethods

We report a very efficient semianalytical approach for the performance evaluation of differential detection schemes for GMSK signals of the DECT standard. Precisely, for a given channel, the performance is determined by means of an analytical procedure which includes the saddlepoint approximation. We consider both static channels (with impulse response generated by the simulation program SIRCIM) and two-ray Rayleigh and log-normal fading channels. As a departure from previous works, our receiver includes an all-digital part after the analog differential detection scheme. The digital part includes: (1) a block for the estimation of both the optimum sampling phase and the nonlinear channel coefficients (by making use of the DECT training sequence), (2) a one-tap decision feedback (DF) equalizer, and (3) a block for the evaluation of the approximate optimum bias level (γ _e) in the threshold detector. Both the DF equalizer coefficient and γ_e are based on the nonlinear channel coefficients estimate. For channels with a normalized delay spread up to 0.2, the use of the optimum threshold together with the DF equalizer permits a gain of about 2 dB at BER=10^-6 with respect to a receiver without equalization and a zero-level decision threshold. In addition, we discover that, in indoor environments, the 2-bit GMSK detector performs roughly the same as the 1-bit detector. The threshold optimization is also effective in the presence of channels affected by fading. To support this statement, we report the performance of the 1-bit differential detection scheme combined with antenna selection diversity in the presence of a two-ray log-normal and Rayleigh fading channel     

Combining PSA fading estimation techniques for TCM and diversity reception in Rician fading channels

In this paper, a novel pilot‐symbol‐aided (PSA) technique is proposed for fading estimation in the land mobile satellite fading channels. The proposed technique combines the fading estimates obtained from a bandwidth‐efficient technique and a conventional technique according to the signal‐to‐noise ratios (SNRs) of the fading estimates. To enhance the transmission quality, trellis‐coded modulation (TCM) and diversity reception are employed in the system, and the combined estimates are subsequently used to correct the channel fading effects, to weight the signals from different diversity branches, and to provide channel state information to the Viterbi decoder. Monte Carlo computer simulation has been used to study the bit‐error‐rate (BER) performance of the proposed technique on trellis‐coded 16‐ary quadrature amplitude modulation in the frequency non‐selective Rician fading channels. Results have shown that the proposed PSA technique requires a very low bandwidth redundancy to provide satisfactory BER performance at low SNRs, and thus is suitable for use with TCM and diversity reception to achieve both bandwidth and power‐efficient transmission. Copyright © 2002 John Wiley & Sons, Ltd.     

Optimal <Emphasis Type="Italic">M</Emphasis>-PAM Spread-Spectrum Data Embedding with Precoding

We consider M-level pulse amplitude modulation (M-PAM) spread-spectrum (SS) data embedding in transform domain host data. The process of data embedding can be viewed as delivering information through the channel including additive interference from host that is known to the embedder. We first utilize the knowledge of second-order statistics of host to design optimal carrier that maximizes the signal-to-interference-plus-noise ratio at the decoder end. Then, inspired by Tomlinson–Harashima precoding used in communication systems, a symbol-by-symbol precoding scheme is developed for M-PAM SS embedding to alleviate the impact of the interference which is explicitly known to embedder. For any given embedding carrier and host data, we aim at designing precoding algorithm to minimize the receiver bit error rate (BER) with any given host distortion budget, and conversely minimize the distortion at any target BER. Experimental studies demonstrate that the proposed precoded SS embedding approach can significantly improve BER performance over conventional SS embedding schemes.     

一种空时分组码预编码的均衡算法研究

为了提高正交空时分组码的MIMO系统性能,提出了采用预编码的空时分组码信号检测方案,该方案在发射端将正交分组编码和预编码矩阵相结合,在接收端采用MMSE均衡译码算法。分析了最小均方误差(MMSE)均衡译码算法和最大似然(ML)译码算法,将此两种算法的性能与最大比值合并(MRC)的性能进行了仿真和比较。仿真结果表明,MMSE算法与ML算法性能相比在误比特率为10-5时有约0.5 dB的增益。     

Split soft-decision equalization for wireless channels with large delay spread

A novel split soft-decision equalizer (SSE) with near-optimum performance is proposed for wireless multipath channels with large delay spread. The concept of SSE is significantly different from the traditional notions of the Viterbi algorithm and decision-feedback equalizer. Instead of dealing with received sequence as a combined sequence, it splits the received sequence into its constituent paths. Using an iterative soft-decision algorithm, reliability of the soft decisions on each decomposed element is improved iteratively. The major advantage of SSE is the independence of computation complexity on channel time dispersion. Joint design of SSE with a soft-decision decoder is also considered in this paper. Performance analysis and simulation results show that performance of the proposed algorithm comes very close to that of the logarithmic maximum a posteriori decoder.     

Neural network decoding of the block Markov superposition transmission

A neural network (NN)-based decoding algorithm of block Markov superposition transmission (BMST) was researched.The decoders of the basic code with different network structures and representations of training data were implemented using NN.Integrating the NN-based decoder of the basic code in an iterative manner,a sliding window decoding algorithm was presented.To analyze the bit error rate (BER) performance,the genie-aided (GA) lower bounds were presented.The NN-based decoding algorithm of the BMST provides a possible way to apply NN to decode long codes.That means the part of the conventional decoder could be replaced by the NN.Numerical results show that the NN-based decoder of basic code can achieve the BER performance of the maximum likelihood (ML) decoder.For the BMST codes,BER performance of the NN-based decoding algorithm matches well with the GA lower bound and exhibits an extra coding gain.     

A Proof of Convergence of the MAP Turbo-Detector to the AWGN Case

In this paper, we consider a coded transmission over a frequency-selective channel. We propose to study analytically the convergence of the turbo-detector using a maximum a posteriori (MAP) equalizer and a MAP decoder. We show that the densities of the extrinsic log likelihood ratios (LLRs) exchanged during the iterations are e-symmetric and output-symmetric. Under the Gaussian approximation, this property allows to perform a one-dimensional (1-D) analysis of the turbo-detector. By deriving the analytical expressions of the extrinsic LLR distributions under the Gaussian approximation, we prove that the bit error rate (BER) performance of the turbo-detector converges to the BER performance of the coded additive white Gaussian noise (AWGN) channel at high signal to noise ratio (SNR), for any frequency-selective channel.     

MLSE and MAP Equalization for Transmission Over Doubly Selective Channels

In this paper, equalization for transmission over doubly selective channels is discussed. The symbol-by-symbol maximum a posteriori probability (MAP) equalizer and the maximum-likelihood sequence estimation (MLSE) are discussed. The doubly selective channel is modeled using the basis expansion model (BEM). Using the BEM allows for an easy and low-complexity mechanism for constructing the channel trellis to implement the MLSE and the MAP equalizer. The MLSE and the MAP equalizer are implemented for single-carrier transmission and for multicarrier transmission implemented using orthogonal frequency-division multiplexing (OFDM). In this scenario, a complexity-diversity tradeoff can be observed. In addition, we propose a joint estimation and equalization technique for doubly selective channels. In this joint estimation and equalization technique, the channel state information (CSI) is obtained in an iterative manner. Simulation results show that the performance of the joint channel estimation and equalization approaches the performance when perfect CSI is available at the receiver.     

New Syndrome Check Error Estimation and Its Concatenated Coding

A low-complexity and high performance SCEE (Syndrome Check Error Estimation) decoding method for convolutional codes and its concatenated SCEE/RS (Reed–Solomon) coding scheme are proposed. First, we describe the operation of the decoding steps in the proposed algorithm. Then deterministic values on the decoding operation are derived when some combination of predecoder-reencoder is used. Computer simulation results show that the computational complexity of the proposed SCEE decoder is significantly reduced compared to that of conventional Viterbi decoder without degradation of the P_e performance. Also, simulation results of BER performance of the concatenated SCEE/Hard Decision Viterbi (HD-Viterbi) and SCEE/RS (Reed–Solomon) codes are presented.     

A hardware-efficient technique to implement a trellis code modulation decoder

This brief presents a new technique in implementing a very large-scale integration trellis code modulation (TCM) decoder. The technique aims to reduce hardware complexity and increase decoding throughput. The technique is introduced in the design of a Viterbi decoder. To simplify the decoding algorithm and calculation, branch cost distances are pre-calculated and stored in a distance look-up table (DLUT). The concept of DLUT significantly reduces hardware requirements as this table eliminates the need for calculation circuitry. In addition, an output LUT (OLUT) is constructed based on the trellis diagram of the code. This table generates the decoding output using information provided by the algorithm. The use of this OLUT reduces the amount of storage requirement. The technique was used to design a 16-state, radix-4 codec for two-dimensional and four-dimensional TCM. The decoder was implemented in hardware after functional simulation. The tested ASIC has a core area of 1.1 mm/sup 2/ in 0.18-/spl mu/m CMOS. A decoding speed of 1 Gbps was achieved. Implementation results have shown that LUTs can be used to decrease hardware requirement and increase decoding speed.     

Multichannel MLSE equalizer with parametric FIR channelidentification

We propose a parametric finite impulse response (FIR) channel identification algorithm, apply the algorithm to a multichannel maximum likelihood sequential estimation (MLSE) equalizer using multiple antennas, and investigate the improvement in the overall bit error rate (BER) performance. By exploring the structure of the specular multipath channels, we are able to reduce the number of channel parameters to provide a better channel estimate for the MLSE equalizer. The analytic BER lower bounds of the proposed algorithm as well as those of several other conventional MLSE algorithms in the specular multipath Rayleigh-fading channels are derived. In the derivation, we consider the channel mismatch caused by the additive Gaussian noise and the finite-length channel approximation error. A handy-to-use simplified BER lower bound is also derived. Simulation results that illustrate the BER performance of the proposed algorithm in the global system for mobile communications (GSM) system are presented and compared to the analytic lower bounds