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.     

Column-anchored zeroforcing blind equalization for multiuserwireless FIR channels

We propose a direct blind zeroforcing approach to cancel intersymbol interference (ISI) in multiple user finite impulse response (FIR) channels. By selectively anchoring columns of the channel convolution matrix, we present two column-anchored zeroforcing equalizers (CAZE), one without output delay and one with a chosen delay. Unlike many known blind identification algorithms, these equalizers do not need an accurate estimate of the channel orders. Exploiting second-order statistics (SOS) of the received signals, they can retain preselected d columns in the channel convolution matrix (d is the number of users) and force the remaining columns to zero. CAZE can effectively equalize single-input-multiple-output (SIMO) systems and can reduce dynamic multiple-input-multiple-output (MIMO) systems into a memoryless signal mixing system for source separation. Simulation results show that the CAZE is not only effective for blind equalization of linear quadrature amplitude modulation (QAM) systems, but it is also applicable to the nonlinear GMSK modulation in the popular wireless GSM systems when computational cost severely limits the use of nonlinear methods such as the Viterbi algorithm     

利用无约束函数的QAM信号自适应盲均衡方法

本文针对正交幅度调制(QAM)信号的盲均衡与载波相位恢复问题,首先在对现有的基于功率最大化盲均衡算法分析的基础上,依据向量范数间的关系,给出了一种QAM信号盲均衡与载波相位恢复的无约束代价函数;然后对代价函数的收敛性和解的唯一性进行严格论证,证明代价函数在取得最优解时能够同时实现盲均衡与载波相位恢复;之后将其转化为采用随机梯度法实现的自适应算法。相对CMA、MMA等其他自适应算法,新算法可获得更好的性能,通过对高阶QAM信号的均衡仿真,进一步验证了算法的有效性。      

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.     

Evaluation of channel coding, modulation and interference ofdigital ATV terrestrial transmission systems

This paper presents results of computer simulations and laboratory tests to investigate various digital techniques (i.e., trellis coded QAM, vestigial sideband (VSB) modulation, orthogonal frequency division multiplexing (OFDM), and adaptive equalization) proposed for Advanced Television (ATV) terrestrial broadcasting. The performance of these channel coding and modulation techniques, in the presence of various interferences (i.e., Gaussian noise, ATV and NTSC co-channel interference) and in a multipath distortion environment, is evaluated and compared. The effects of ATV interference into NTSC systems are also investigated     

用于多电平QAM调制的新型的自恢复均衡技术的研究

本文对一种新的代阶函作了研究，提出一种适用于多民平ＱＡＭ（ＭＱＡＭ）信号的自恢复的均衡算法，克服了ＣＭＡ算法对相位不敏感的缺点，并在此基础上提出了两种改进的均衡算法，概率算法和混合算法，理论分析和计算机模拟表明这两种算法的收敛性能优越，而且误码性能与传统的ＬＭＳ均衡算法一致，是两种很实用的均衡算法。     

Set-membership adaptive equalization and an updator-sharedimplementation for multiple channel communications systems

This paper considers the problems of channel estimation and adaptive equalization in the novel framework of set-membership parameter estimation. Channel estimation using a class of set-membership identification algorithms known as optimal bounding ellipsoid (OBE) algorithms and their extension to tracking time-varying channels are described. Simulation results show that the OBE channel estimators outperform the least-mean-square (LMS) algorithm and perform comparably with the RLS and the Kalman filter. The concept of set-membership equalization is introduced along with the notion of a feasible equalizer. Necessary and sufficient conditions are derived for the existence of feasible equalizers in the case of linear equalization for a linear FIR additive noise channel. An adaptive OBE algorithm is shown to provide a set of estimated feasible equalizers. The selective update feature of the OBE algorithms is exploited to devise an updator-shared scheme in a multiple channel environment, referred to as updator-shared parallel adaptive equalization (USHAPE). U-SHAPE is shown to reduce the hardware complexity significantly. Procedures to compute the minimum number of updating processors required for a specified quality of service are presented     

快速收敛的正交振幅调制信号半盲均衡算法

针对传输正交幅度调制信号的多输入多输出频率选择性衰落无线通信系统中的信号间干扰与信号内部的码间干扰问题, 提出了一种改进的软决策算法.该方法精确地利用了正交振幅调制(Quadrature Amplitude Modulation, QAM)信号星座图信息, 避免了经典恒模算法、多模算法中存在的误调问题, 提高了均衡性能.对代价函数采用梯度牛顿法进行优化, 与常用的梯度类算法相比, 其具有更快的收敛速度.通过均方误差和最大信道扭曲分析和验证了该算法的可靠性和有效性.     

Reduced Complexity Implementation of Passband Adaptive Equalizers

High-speed modems typically employ quadrature amplitude modulation (QAM) so that two signal paths, in-phase and quadrature, are simultaneously being used. The standard receiver structure has, in effect, four adaptive equalizers, one for each of the two signal paths and two to correct for cross coupling between signal paths. As a result, equalization normally requires8Nmultiplications per baud interval, whereNis the number of taps, to perform the needed signal processing including adaptive updating of the weights., In this correspondence, we present a new signal processing algorithm which requires only6Nmultiplications per baud interval. For fractionally spaced equalization and adaptive cancellation,Nis quite large so that this saving can be of practical value in improwng throughput capability of custom chips, or depending on the architecture, with programmable signal processor chips. Specifically, the algorithm is advantageous for implementations where multiplications require a longer execution time than additions.     

含软方向判决的修正CMA盲均衡新算法

提出了一种新颖的盲均衡算法MCMA SDD,它一方面在代价函数中同时包含了幅度和相位的信息,另一方面,增加了并行的软方向判决(SDD)盲均衡算法,使得MCMA SDD算法无需载波跟踪环就能够纠正相位的失真;在低信噪比条件下具有较快的收敛速度和较低的稳态均方误差。     

Minimum Bayes Risk Adaptive Linear Equalizers

This paper introduces Bayes risk (expected loss) as a criterion for linear equalization. Since the probability of error is equal to the Bayes risk (BR) for a particular binary loss function, this work is a natural generalization of previous works on minimum probability of error (PE) equalizers. Adaptive equalization algorithms are developed that minimize the BR. Like the minimum PE equalizers, the BR algorithms have low computational complexity which is comparable to that of the LMS algorithm. The advantage of the BR criterion is that the loss function can be specified in a manner that accelerates adaptive equalizer convergence relative to the minimum PE adaptive algorithm as illustrated in simulation examples. Besides introducing a new criterion, this paper provides another independent contribution to the field of PE minimizing equalization. While most prior works focus on $M$-ary QAM type modulations with rectangular decision regions, this paper uses upper bounds on the probabilities of certain events to yield tractable mathematics that apply to two-dimensional constellations with arbitrarily shaped decision regions. The resulting adaptive algorithm use the full information available in the phase of the error signal, whereas previous algorithms use a quantized version of this error phase.      

A comparison of QAM and VSB for hybrid fiber/coax: digitaltransmission

There are two competing transmission systems for downstream digital transmission on hybrid fiber/coax cable networks: quadrature amplitude modulation (QAM), and vestigial sideband modulation (VSB). Both QAM and VSB are bandwidth efficient, and have the same bandwidth efficiency. Detailed calculations and simulations of QAM and VSB transmission on hybrid fiber/coax are reported here. It is shown that, since VSB has a higher symbol rate, it has at most 1/2 dB less received SNR than QAM at low frequencies because of dispersion and symbol timing jitter. This difference is negligible. Vendors proposing VSB recover the carrier with a pilot tone and a PLL, and vendors proposing QAM use all-digital data-directed carrier recovery. Simulations reported here show that QAM and VSB have very similar carrier recovery performance. It is concluded that for hybrid fiber/coax, VSB and QAM have practically the same overall performance, and the choice between these transmission systems should be based on considerations other than performance     

A hybrid adaptive blind equalization algorithm for QAM signals in wireless communications

A hybrid adaptive channel equalization technique for quadrature amplitude modulation (QAM) signals is proposed. The proposed algorithm, which is referred to as the modified constant modulus algorithm (MCMA), minimizes an error cost function that includes both amplitude and phase of the equalizer output. In addition to the amplitude-dependent term that is provided by the conventional constant modulus algorithm (CMA), the cost function includes an additive signal constellation matched error (CME) term. This term can be designed to satisfy a set of desirable properties. The MCMA is compared with the CMA for blind equalization. The performance is measured for wireless channels using both transient and steady-state behavior of the mean square error (MSE). It is shown that MCMA is superior and more robust in low signal-to-noise ratio (SNR) environments. Simulation results demonstrate that using MCMA improves adaptive channel equalization by increasing the convergence rate and decreasing the steady-state mean square error.     

Normalized sliding window constant modulus and decision-directedalgorithms: a link between blind equalization and classical adaptivefiltering

By minimizing a deterministic criterion of the constant modulus (CM) type or of the decision-directed (DD) type, we derive normalized stochastic gradient algorithms for blind linear equalization (BE) of QAM systems. These algorithms allow us to formulate CM and DD separation principles, which help obtain a whole family of CM or DD BE algorithms from classical adaptive filtering algorithms. We focus on the algorithms obtained by using the affine projection adaptive filtering algorithm (APA). Their increased convergence speed and ability to escape from local minima of their cost function make these algorithms very promising for BE applications     

On Blind Equalization of Biorthogonal Signaling

Motivated by increasing interest in energy efficient modulations, we provide the first look at adaptive equalization of biorthogonal signaling. While this modulation has historically been considered only for use in narrowband systems without intersymbol interference (ISI), recent attention has been given to its use in ISI channels. Due to the fact that biorthogonal modulation (BOM) results in a source that is not i.i.d., however, classical blind adaptive equalization techniques cannot be directly applied to equalization of BOM signals. We first examine minimum mean-squared error (MMSE) and least mean squares (LMS)-based equalizers, and identify some peculiarities that arise in equalization of BOM signals when compared to more traditional modulations like binary phase shift keying (BPSK). Next, we present two novel blind algorithms for the adaptive equalization of BOM signals: LTBOMB and TROMBONE. We discuss the convergence properties of these algorithms, and demonstrate their performance with numerical simulations     

Blind equalization based on prediction and polycepstra principles

The polycepstra and prediction equalization algorithm (POPREA) is proposed for blind equalization of nonminimum phase channels. The algorithm equalizes the amplitude and phase of the channel independently by employing linear prediction and tricepstrum principles, respectively. It guarantees convergence to a global solution. The tracking and cancellation of phase due to carrier frequency offset is carried out independently of equalization. It is demonstrated, by means of computer simulations, that the proposed POPREA is able to open the eye pattern of QAM signal constellations faster than existing polyspectra-based equalizers. The complexity of the algorithm is high but comparable to that of polyspectra equalizers     

Deterministic approaches for blind equalization of time-varyingchannels with antenna arrays

In this paper, we study the blind equalization problem of time-varying (TV) systems where the channel variations are too rapid to be tracked with conventional adaptive equalizers. We show that using a finite Fourier basis expansion, a TV antenna array system can be cast into a time-invariant multi-input, multi-output (MIMO) framework. The multiple inputs are related through the bases, thereby allowing blind equalization to be accomplished without the use of higher order statistics. Two deterministic blind equalization approaches are presented: one determines the channels first and then the equalizers, whereas the other estimates the equalizers directly. Related issues such as order determination are addressed briefly. The proposed algorithms are illustrated using simulations     

一种适用于高阶QAM系统Bussgang类盲均衡新方法

该文提出一种适用于高阶QAM系统的新Bussgang类多模盲均衡算法。将新的代价函数与星座匹配误差函数结合,给出一种瞬时双模切换混合算法,然后设计了一种基于判决圆的模式切换准则,从而达到进一步有效降低新算法稳态误差的效果。最后,仿真结果以高阶256QAM信号为例,验证了该算法对于高阶QAM信号的盲均衡能力和良好效果。     

组合半盲均衡算法及其在半盲均衡中的应用

针对传输正交幅度调制信号的多输入多输出卷积通信系统中的码间干扰和共信道干扰问题,利用软决策算法的选择性以及QAM信号星座图的几何特征,提出一种组合的半盲均衡算法。该算法不仅克服了传统恒模算法,多模算法在稳态下的误调问题,而且避免了SDD算法在高阶QAM系统中运算量急剧增加的问题。采用梯度牛顿法优化CSBEA算法代价函数,与常用的梯度类算法相比,其具有收敛速度快,稳态性能好的特点。通过仿真实验证明了所提算法的有效性。     

一种复杂星座信号的盲均衡新方法

基于高阶统计量(HOS)盲均衡算法虽可适用于单人单出(SISO)系统,但HOS算法均依赖大数据量而无法满足高速信号传输的时变要求,该类算法对于高阶正交幅度调制(QAM)信号系统的盲均衡能力偏弱.该文在较小数据量的前提下,提出一种适用于SISO系统的高阶QAM信号盲均衡的新算法.算法运用支持向量回归框架,根据有序风险最小...