复值的MBER非线性均衡器用于QAM信号

本文提出一种复值的最低误码率非线性滤波器用于非线性信道中QAM信号的均衡.推导了针对QAM信号的最低误码率准则训练算法的目标函数,并用Voherra序列来实现复值的非线性均衡器.为使非线性均衡器能在线自适应训练并增加训练算法的数值稳定性,提出～种滑窗随机梯度算法.大量仿真表明,对于非线性信道中QAM信号的均衡,最低误码率非线性均衡器的性能优于最小均方误差准则.     

Combined equalization and differential detection using precoding

A new transceiver for data transmission over multipath fading channels employing precoding and differential detection is investigated. This precoding scheme effectively functions as a decision feedback equalizer (DFE) for differentially coherent demodulation. The main advantage of the proposed scheme over the conventional DFE is its ability to compensate for fast channel phase variations     

A NEW ADAPTIVE EQUALIZER STRUCTURE FOR NONLINEAR CHANNELS

Based on the analysis of nonlinear channel models,a new connectionist model ofadaptive equalizer is constructed.Comparing with the connectionist model using the Volterraseries to extend the input vector space,the number of weights with the new structure is reducedsignificantly.It is shown by simulations that the weight values of the new scheme converge to theoptimal values closely for non-minimum phase channels as well minimum phase channels,if thechannel noise is small enough.Testing results of the BER(Bit Error Rate)tell us that the newadaptive equalizer for nonlinear channels is superior to the conventional linear equalizers in theequalization performances.     

Efficient bad equalizer in two-ray multipath fading channels

An efficient bidirectional arbitrated decision feedback (BAD) equalizer is presented in single-carrier block transmission system in the Two-Ray multipath fading channels, where the output from the bidirectional equalizers are combined together directly using maximal ratio combining (MRC) rule to improve the signal-to-noise ratio (SNR) before demodulation. The computational complexity of the BAD equalizer presented is linear with the channel length, which is the same as conventional decision feedback equalizer (DFE) and is significantly lower than that of conventional BAD equalizer as well as the maximum likelihood (ML) algorithm. While the performance of the new scheme depends on the specific channel characteristics, it is shown by simulation results that the performance of the new BAD can surpass the one of DFE dramatically in the minimum or non-minimum phase Two-Ray multipath fading channels.     

Complex noncoherent receivers for GMSK signals

Noncoherent demodulators are very attractive for high performance radio LAN (HIPERLAN) systems because of their low implementation costs and their inherent robustness against frequency and carrier phase offsets. However, when the channel is time dispersive, the nonlinear intersymbol interference (ISI) introduced by these demodulators precludes the use of conventional linear equalization strategies. We present an alternative noncoherent receiver structure followed by a nonlinear equalizer, which includes a RAM and a Viterbi detector, capable of equalizing nonlinear multipath fading channels. In addition, we also present a new algorithm specifically for noncoherent demodulators, which allows estimation of all useful signal values at the input of the equalizer to be stored in the RAM. By means of computer simulations, we report the performance and computational complexity tradeoffs of the receiver/equalizer structure, including antenna diversity. We show that demodulators which consist of a complex receiver and a Viterbi detector are much more robust against multipath fading channels than traditional real noncoherent demodulators. The results suggest that in a typical HIPERLAN scenario, where the channel delay spread is less than 50 ns and a reliable line of sight component exists, it is feasible to combat multipath effects using noncoherent demodulation     

An adaptive algorithm for differentially coherent detection in the presence of intersymbol interference

An adaptive equalization method is proposed for use with differentially coherent detection of M-ary differential phase-shift keying (DPSK) signals in the presence of unknown carrier frequency offset. A decision-feedback or a linear equalizer is employed, followed by the differentially coherent detector. The equalizer coefficients are adjusted to minimize the post-detection mean squared error. The error, which is a quadratic function of the equalizer vector, is used to design an adaptive algorithm of stochastic gradient type. The approach differs from those proposed previously, which linearize the post-detection error to enable the use of least mean squares (LMS) or recursive least squares (RLS) adaptive equalizers. The proposed quadratic-error (Q) algorithm has complexity comparable to that of LMS, and equal convergence speed. Simulation results demonstrate performance improvement over methods based on linearized-error (L) algorithm. The main advantages of the technique proposed are its simplicity of implementation and robustness to carrier frequency offset, which is maintained for varying modulation level.     

Low-complexity equalization for π/4 DQPSK signals based on themethod of projection onto convex sets

An equalizer adaptation technique for compensation of degradations caused by multipath Rayleigh fading channels to π/4 differential quadrature phase shift keying (DQPSK)-modulated signals is presented. The technique is applied to linear and nonlinear transversal-filter-type equalizers. It is based on the method of projection onto convex sets (POCS), realized in a particular form of the iterative least mean squares (LMS) procedure. The convergence speed of the proposed equalizer coefficient adaptation technique and its computational complexity depend on the newly introduced look-back parameter. Both can be tailored to the characteristics of the channel. For achieving convergence speeds comparable to speeds of recursive least squares (RLS) techniques, the computational load of the presented equalization is of the order of the load required of RLS techniques. However, its algorithmic implementation is notably simpler and its code and storage size requirements are smaller. The technique is numerically stable, and it is suitable for low-power implementations in digital signal processors or custom very large-scale integration (VLSI) circuits. Performed simulations verify good performance of the technique in various channel conditions for 900-MHz multipath fading radio channels     

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     

An efficient low-complexity technique for MLSE equalizers for linear and nonlinear channels

In this paper, a novel sequence equalizer, which belongs to the family of cluster-based sequence equalizers, is presented. The proposed algorithm achieves the maximum likelihood solution to the equalization problem in a fraction of computational load, compared with the classic maximum likelihood sequence estimation (MLSE) equalizers. The new method does not require the estimation of the channel impulse response. Instead, it utilizes the estimates of the cluster centers formed by the received observations. Furthermore, a new cluster center estimation scheme, which exploits the intrinsic dependencies among the cluster centers, is proposed. The new center estimation method exhibits enhanced performance with respect to convergence speed, compared with an LMS-based channel estimator. Moreover, this gain in performance is obtained at substantially lower computational load. The method is also extended in order to cope with nonlinear channels. The performance of the new equalizer is tested with several simulation examples, using both the quadrature phase shift keying (QPSK) and the 16-quadrature amplitude modulated (QAM) signaling schemes for linear and nonlinear communication channels.     

Blind equalizer for constant-modulus signals based on Gaussian process regression

A new blind equalization method for constant modulus (CM) signals based on Gaussian process for regression (GPR) by incorporating a constant modulus algorithm (CMA)-like error function into the conventional GPR framework is proposed. The GPR framework formulates the posterior density function for weights using Bayes' rule under the assumption of Gaussian prior for weights. The proposed blind GPR equalizer is based on linear-in-weights regression model, which has a form of nonlinear minimum mean-square error solution. Simulation results in linear and nonlinear channels are presented in comparison with the state-of-the-art support vector machine (SVM) and relevance vector machine (RVM) based blind equalizers. The simulation results show that the proposed blind GPR equalizer without cumbersome cross-validation procedures shows the similar performances to the blind SVM and RVM equalizers in terms of intersymbol interference and bit error rate.     

Grouped signed power-of-two algorithms for low-complexity adaptive equalization

With increasing demand for higher data rate, modern communication systems have grown more complex. Equalization has become more and more important as it is effective in mitigating the multipath fading often occurred in high-data-rate communication systems. However, the implementation complexity of adaptive equalizers is usually too high for mobile communication applications. In this paper, a novel adaptive equalization algorithm and its low-complexity architecture are proposed. This algorithm employs a new grouped signed power-of-two (GSPT) number representation. The GSPT algorithm and several enhanced versions are simulated as adaptive equalizers in a phase-shift keying communication receiver for several practical channels and the GSPT-based equalizers perform as well as the least mean square (LMS) equalizer. Moreover, for comparison, two GSPT-based equalizers and two other equalizers are implemented in field-programmable gate arrays. The GSPT-based equalizers require only about 25%-30% of the hardware resources needed in the LMS equalizer. Also the GSPT-based equalizers are more than twice as fast as the LMS equalizer.     

Reconstruction of chaotic signals with application to channel equalization in chaos‐based communication systems

A number of schemes have been proposed for communication using chaos over the past years. Regardless of the exact modulation method used, the transmitted signal must go through a physical channel which undesirably introduces distortion to the signal and adds noise to it. The problem is particularly serious when coherent‐based demodulation is used because the necessary process of chaos synchronization is difficult to implement in practice. This paper addresses the channel distortion problem and proposes a technique for channel equalization in chaos‐based communication systems. The proposed equalization is realized by a modified recurrent neural network (RNN) incorporating a specific training (equalizing) algorithm. Computer simulations are used to demonstrate the performance of the proposed equalizer in chaos‐based communication systems. The Hénon map and Chua's circuit are used to generate chaotic signals. It is shown that the proposed RNN‐based equalizer outperforms conventional equalizers as well as those based on feedforward neural networks for noisy, distorted linear and non‐linear channels. Copyright © 2004 John Wiley & Sons, Ltd.     

基于最低误码率准则及Volterra序列的几何特征均衡器

针对通信系统中带内噪声及干扰的滤波问题,提出一种基于最低误码率准则的非线性几何特征均衡器.考虑到噪声与干扰具有不同的统计特性,本文所建立的均衡模型把匹配滤波器输出映射到特征空间,使信号与干扰在特征空间形成不同的几何特征,再用Volterra序列予以分离,而分离是基于最低误码率准则.仿真表明:对于扩展的二元相移键控信号,在相对强的调频信号、调幅信号及噪声的联合干扰下,匹配滤波器和基于最小均方误差准则的线性均衡器均已失效,而几何特征均衡器仍能表现出良好的性能,并且基于奇次三阶Volterra序列的几何特征均衡器更具实用价值.     

Blind equalization for short burst wireless communications

In this paper, we propose a dual mode blind equalizer based on the constant modulus algorithm (CMA). The blind equalizer is devised for short burst transmission formats used in many current wireless TDMA systems as well as future wireless packet data systems. Blind equalization is useful for such short burst formats, since the overhead associated with training can be significant when only a small number of bits are transmitted at a time. The proposed equalizer overcomes the common problems associated with classic blind algorithms, i.e., slow convergence and ill-convergence, which are detrimental to applying blind equalization to short burst formats. Thus, it can eliminate the overhead associated with training sequences. Also, the blind equalizer is extended to a two branch diversity combining blind equalizer. A new initialization for fractionally spaced CMA equalizers is introduced. This greatly improves the symbol timing recovery performance of fractionally spaced CMA equalizers with or without diversity, when applied to short bursts. Through simulations with quasi-static or time-varying frequency selective wireless channels, the performance of the proposed equalizer is compared to selection diversity and conventional equalizers with training sequences. The results indicate that its performance is far superior to that of selection diversity alone and comparable to the performance of equalizers with short training sequences. Thus, training overhead can be removed with no performance degradation for fast time-varying channels, and with slight performance degradation for static channels     

Differential modulation techniques for a 34 MBit/s radio channel using orthogonal frequency division multiplexing

The orthogonal frequency division multiplexing (OFDM) technique has been proposed for terrestrial digital transmission systems due to its high spectral efficiency, its robustness in different multipath propagation environments and the ability of avoiding intersymbol interference (ISI). Our studies consider a radio channel bandwidth of 8 MHz and a data rate of 34 Mbit/s.In the case of the OFDM transmission system a coherent 64-QAM requires a channel estimation process and a channel equalization in frequency-selective interference situations [4]. The equalization process can be realized by a multiplier bank at the FFT output in the receiver, a so-called frequency-domain equalizer. Alternatively, a multilevel differential modulation technique, the so-called differential amplitude and phase shift keying (64-DAPSK) considering the phase and simultaneously the amplitude for differential modulation, is proposed and presented in this paper. Differential modulation/demodulation techniques do not require any explicit knowledge about the radio channel properties in the differential channel equalization. It is therefore not necessary to implement a frequency-domain equalizer in an OFDM/64-DAPSK receiver, which reduces the computation complexity. The performance of both modulation techniques has been analysed in the uncoded and coded case referring to Gaussian and frequency-selective Rayleigh fading channels. Simulation results are presented in this paper.The OFDM signal has a non-constant envelope with large instantaneous power spikes possible primarily resulting in an overdriving of the high power amplifier (HPA) at the transmitter. This leads to nonlinear distortion causing intermodulation noise and spectral spreading. Both effects can be limited by introducing an appropriate input backoff (IBO). In this paper the performance of OFDM signals in the presence of nonlinearities is analysed quantitatively.     

Efficient reinitialization of the prewhitened constant modulusalgorithm

We present a reinitialization scheme for blind equalizers adapted via the constant modulus algorithm (CMA) when an all-pole prefilter is included to whiten the received signal. The mechanism exploits the special structure of the minimum mean squared error (MMSE) equalizers and their relation with CMA equalizers. A heuristic rule for blind determination of the best equalization delay is also provided. Using these guidelines, the equalizer is capable of finding the optimal setting in an online and computationally efficient fashion. In particular, estimation and inversion of the channel output autocorrelation matrix is not needed, in contrast with previous approaches     

Adaptive noncoherent linear minimum ISI equalization for MDPSK andMDAPSK signals

A novel noncoherent linear equalization scheme is introduced and analyzed. In contrast to previously proposed noncoherent equalization schemes, the proposed scheme is not only applicable for M-ary differential phase-shift keying (MDPSK) but also for M-ary differential amplitude/phase-shift keying (MDAPSK). The novel scheme minimizes the variance of intersymbol interference (ISI) in the equalizer output signal. The optimum equalizer coefficients may be calculated directly from an eigenvalue problem. For an efficient recursive adaptation of the equalizer coefficients, a modified least-mean-square (LMS) and a modified recursive least-squares (RLS) algorithm are proposed. It is shown that the corresponding cost function has no spurious local minima that ensures global convergence of the adaptive algorithms. Simulations confirm the good performance of the proposed noncoherent equalization scheme and its robustness against frequency offset     

基于概率软切换的两级双模盲均衡器

文中提出一种基于概率软切换的两级双模盲均衡器。它实时统计两级盲均衡器输出硬判决值相同的概率,并利用它切换盲均衡算法。该均衡器结合了级联两级均衡结构和双模算法的优点。仿真表明,它能够纠正相位偏移,相对于波特间隔（BSE）的并发常模＋判决导引（CMA＋DD）盲均衡器,以非常小的计算复杂度代价,获得稳态均方误差（MSE）性能和误比特率（BER）性能的较大提高。     

Adaptive Equalization of the Slow Fading Channel

This paper considers equalization of the slow fading channel for a serial data transmission application. Linear and decision-feedback adaptive equalization techniques are contrasted. The error propagation effect in decision-feedback equalizers is analyzed by a Markov process model. The error probability magnification is computed for both fixed and fading channels and for both binary and quaternary phase-shift-keying (PSK) transmission. The results show that the error propagation effect is small and in regions of practical error probabilities the decision-feedback equalizer is superior to its linear counterpart. Parameters of a practical decisionfeedback equalizer are estimated and a performance evaluation is performed. The implicit diversity gain is shown to be significant and the intersymbol interference penalty is found to be less than 1 dB. Because the intersymbol interference penalty is small, more complex nonlinear processors such as the Viterbi algorithm cannot be recommended for this application. Time jitter effects for the equalizer are included in a calculation of average error probability.     

Monte carlo equalization for nonlinear dispersive satellite channels

Satellite channels are generally nonlinear and dispersive in nature, due to amplifiers being driven close to saturation. These effects can cause significant degradations when they are not taken into account at either the receiver (equalization) or at the transmitter (pre-distortion). State-of-the-art equalizers rely on the forward-backward algorithm and yield excellent performance. However, they have unreasonable complexity and storage requirements, especially for highly dispersive channels and/or large constellations. In this paper, we derive an equalization strategy for nonlinear channels based on Monte Carlo methods. We present a detailed performance, complexity and storage analysis. A significant performance gain compared to the linear equalizer is reported, and the proposed technique results in a significant reduction in both complexity and storage, compared to the forward-backward equalizer.