基于噪声预测的低复杂度判决反馈均衡

针对散射通信系统多径效应严重，常用的频域非线性均衡算法复杂度过高的情况，提出了一种基于噪声预测的低复杂度判决反馈均衡方法。根据常用散射通信多径信道模型，在时延功率谱呈指数衰减的情况下，通过曲线拟合的方法预测非线性判决反馈均衡器的部分系数，从而达到降低算法复杂度的目的。仿真结果表明，所提方法不仅具有较低的复杂度，也具备良好的误码性能，在合适的阈值下，与原有算法的性能损失可控制在0.1 dB以内。     

Reduced complexity decision feedback equalization for digitalsubscriber loops

Decision feedback equalizers (DFEs) are widely used in modern local network digital transmission systems to remove the intersymbol interference caused by slowly decaying pulse tails. A gradient descent algorithm for adapting a coefficient to model the slowly decaying portion of the tail is described. An equalization strategy is described that exploits prior knowledge of the nature of the subscriber loop channel, together with the new adaptation algorithm, to give reduced complexity DFE structures. The use of this algorithm in FIR and IIR equalizer structures is described. The use of this algorithm in FIR and IIR equalizers is quantitatively compared to a conventional DFE in terms of performance and implementation complexity. An analysis is presented describing the operation of the adaptation algorithm in the presence of noise. Simulation results illustrate the training of the algorithm and its stability in the presence of near-end crosstalk noise     

Low-complexity soft-input soft-output demodulation of orthogonal modulation

This letter is concerned with the soft-input soft-output (SISO) demodulation of M-ary (M = 2^r) orthogonal modulation. We prove that the SISO orthogonal demodulation (SISO-OD) is equivalent to the SISO decoding of orthogonal Hadamard codes, for which we deduct a posteriori probability fast Hadamard transform (APP-FHT) algorithm. With FHT and the proposed APP-FHT, the demodulation complexity can be reduced from O(r2^r) to O(2^r) exponential/logarithm operations and O(r²2^r) to O(2^r) additions, respectively.     

Reduced complexity decision feedback equalization for multipathchannels with large delay spreads

Two modified decision feedback equalization (DFE) structures are presented for the efficient equalization of long sparse channels with strong precursor, such as those encountered in high-speed communications over multipath channels with large delay spread. Unlike the conventional DFE, these structures allow the channel's sparseness to be exploited by simple tap allocation, before the sparseness is degraded by feedforward filtering. Both structures yield large reductions in complexity while maintaining performance comparable to the conventional DPE, hence overcoming a key computational bottleneck when equalizers are implemented in hardware for speed. Fast channel estimate-based algorithms for computing the modified DFE coefficients are derived. Simulation results are presented for data rates and channel profiles of the type considered for the proposed North American high definition television (HDTV) terrestrial broadcast mode     

Low complexity turbo equalization based on soft feedback interference cancellation

This letter presents a new soft feedback interference cancellation (SFIC) based equalizer suitable for iterative receivers applying turbo equalization. SFIC offers a very low computational complexity depending only linearly on the channel memory length. Despite its low complexity, SFIC shows a very good BER performance. Simulation results for the severely intersymbol interference distorted Proakis C channel show, that our approach performs within 0.5 dB to the powerful turbo equalization scheme based on MMSE linear filtering with time-varying coefficients and fails the mathematical optimum maximum a-posteriori (MAP) equalizer only by 1.2 dB.     

联合均衡块迭代软判决反馈干扰抵消接收机

CDMA扩频通信系统在低扩频比时,路径间干扰(IPI, inter-path interference)变得非常严重。本文将块迭代干扰抵消同MMSE均衡器相结合,提出了一种适用于CDMA扩频通信系统低扩频比情况下的联合均衡块迭代软判决反馈干扰抵消(MMSE-BIIC)接收机结构。理论分析与计算机仿真表明,本文提出的MMSE-BIIC接收机同传统的Rake接收机、线性MMSE均衡器以及多级干扰抵消接收机相比在性能上有较大改善。     

基于PR—QMF理论的判决反馈均衡器

根据完全重构正交镜像滤波器（PR-QMF）的理论,我们构造了一类正交变换并且用于交换域判决反馈均衡器（OFE）的设计。在此基础上我们进一步讨论了该类DFE的优化设计。通过与卡胡南一洛也夫变换（KLT）和离散余弦变换（DCT）比较得出这样的结论：经过最优化设计,本文提出的算法具有更快的收敛速度,同时,它还具有复杂程度低和设计灵活的优点。     

A soft-input soft-output APP module for iterative decoding ofconcatenated codes

Concatenated coding schemes consist of the combination of two or more simple constituent encoders and interleavers. The parallel concatenation known as “turbo code” has been shown to yield remarkable coding gains close to theoretical limits, yet admitting a relatively simple iterative decoding technique. The recently proposed serial concatenation of interleaved codes may offer superior performance to that of turbo codes. In both coding schemes, the core of the iterative decoding structure is a soft-input soft-output (SISO) a posteriori probability (APP) module. In this letter, we describe the SISO APP module that updates the APP's corresponding to the input and the output bits, of a code, and show how to embed it into an iterative decoder for a new hybrid concatenation of three codes, to fully exploit the benefits of the proposed SISO APP module     

基于LSQR算法和加窗技术的判决反馈均衡器

在正交频分复用(OFDM)系统中,高速移动造成的多普勒效应破坏了子载波间的正交性并产生载波间干扰(ICI).为了消除ICI,确保快时变信道下的可靠通信,该文提出了一种低复杂度加窗LSQR(least square QR)判决反馈均衡器(Decision Feedback Equalization,DFE).借助加窗技术和时域LSQR迭代计算,该算法减少了残存的ICI,有效克服了"地板效应";此外,该算法还利用带状矩阵分解降低了计算复杂度.理论分析和仿真结果表明,在快时变信道下与已有的块状线性均衡(Block Linear Equalization,BLE)算法比较,该算法在复杂度相当的情况下可以进一步改善系统的误码率性能.     

A soft-output bidirectional decision feedback equalizationtechnique for TDMA cellular ratio

Issues encountered in the design of reliable narrowband time-division multiple access (TDMA) digital cellular mobile communication systems are considered. In particular, the problem of compensating for the harsh multipath fading environment in systems whose transmission bandwidth is commensurate with the coherence bandwidth of the fading channel is considered. A TDMA channel characterization parameter, the slot-normalized fade rate, is introduced, and an adaptive bidirectional equalization technique, which estimates the location of a deep fade within a time slot, is proposed. The simulation results show that the carrier-to-noise ratio requirement is only 15.5 dB when this equalization technique is used. This is achieved without diversity, and with low complexity. An equivalent equalized land mobile radio channel model and the analytical solution for the optimal bit likelihood calculation for π/4-shift quadrature differential phase-shift keying (QDPSK) modulation are also derived under certain channel conditions. The results are used as soft decisions for the convolutional decoder     

Adaptive soft-input soft-output algorithms for iterative detection with parametric uncertainty

The soft-input soft-output (SISO) module is the basic building block for established iterative detection (ID) algorithms for a system consisting of a network of finite state machines. The problem of performing ID for systems having parametric uncertainty has received relatively little attention in the open literature. Previously proposed adaptive SISO (A-SISO) algorithms are either based on an oversimplified channel model, or have a complexity that grows exponentially with the observation length N (or the smoothing lag D). In this paper, the exact expressions for the soft metrics in the presence of parametric uncertainty modeled as a Gauss-Markov process are derived in a novel way that enables the decoupling of complexity and observation length. Starting from these expressions, a family of suboptimal (practical) algorithms is motivated, based on forward/backward adaptive processing with linear complexity in N. Previously proposed A-SISO algorithms, as well as existing adaptive hard decision algorithms are interpreted as special cases within this framework. Using a representative application-joint iterative equalization-decoding for trellis-based codes over frequency-selective channels-several design options are compared and the impact of parametric uncertainty on previously established results for ID with perfect channel state information is assessed.     

On soft-input soft-output decoding using "box and match" techniques

The box and match decoding algorithm (BMA) significantly reduces the computational complexity of the ordered statistic decoding algorithm at the expense of increased memory requirements. A soft-input/soft-output version of the BMA is developed. Additional complexity-reduction techniques are also described.     

Blind decision feedback equalization for terrestrial televisionreceivers

In December 1996 the Federal Communications Commission (FCC) adopted the Grand Alliance (GA) system as the digital television broadcasting standard for the United States ending a seven-year-long search for a fully digital television standard. MPEG-2 was chosen as the video compression standard, and trellis-coded 8-vestigial sideband (VSB) with a training sequence was chosen as the transmission standard. The laboratory tests that were performed on the final two competing systems, 8-VSB with training sequence and 32-quadrature amplitude modulation (QAM) with blind equalization, showed a need for blind equalization in dynamic channels that could not be adequately handled by an equalizer training on the training sequence alone. Hence, the final GA system recommended the use of blind equalization in the receiver. In this paper, we describe the U.S. digital television transmission standard as it pertains to the equalization problem, typical transmission channel characteristics and the need for blind equalization in terrestrial television receivers     

多进制部分响应Multi-h CPM的软输出维特比算法

为降低多调制指数连续相位调制(Multi-h CPM)信号解调和级联译码的复杂度和时延,提出了一种适用于多进制部分响应Multi-h CPM信号的低复杂度软输出维特比(LC-SOVA)算法。针对倾斜相位(TP)+频率脉冲截断(FPT)低复杂度Multi-h CPM解调,在维特比检测中对每个状态存储并不断更新符号软信息,通过舍弃度量较小的路径来降低更新软信息的运算量,且软信息更新过程可以并行处理,复杂度降低一半,时延与维特比算法等价。仿真结果表明,所提LC-SOVA算法具有通用性,适用于多进制部分响应Multi-h CPM信号的软信息计算,在级联低密度奇偶校验码(LDPC)系统中,该算法与Max-log-MAP算法相比信噪比损失几乎可以忽略不计。     

Decision-feedback soft-input/soft-output multiuser detector foriterative decoding of coded CDMA

The optimal decoding scheme for a code-division multiple-access (CDMA) system that employs convolutional codes results in a prohibitive computational complexity. To reduce the computational complexity, an iterative receiver structure was proposed for decoding multiuser data in a convolutional coded CDMA system. At each iteration, extrinsic information is exchanged between a soft-input/soft-output (SISO) multiuser detector and a bank of single-user SISO channel decoders. However, a direct implementation of the full-complexity SISO multiuser detector also has the exponential computational complexity in terms of the number of users. This paper proposes a low-complexity SISO multiuser detector based on tentative hard decisions that are made and fed back from the channel decoders in the previous iteration. The computational complexity of the proposed detector is linear in terms of the number of users and can be adjusted according to the complexity/performance tradeoff. Simulation results show that even with this simple feedback scheme, the performance of the coded multiuser system approaches that of the single-user system for moderate to high signal-to-noise ratios (SNRs)     

The effect of microreflections on decision feedback equalization

In coaxial cable modems and terrestrial broadcasting, the appearance and disappearance of microreflections cause a temporary drop in SNR at the equalizer output. We describe mathematically the effect of the appearance/disappearance of a microreflection on the performance of a previously trained fractionally spaced equalizer     

Efficient decision feedback equalization for sparse wireless channels

A new efficient decision feedback equalizer (DFE) appropriate for channels with long and sparse impulse response (IR) is proposed. Such channels are encountered in many high-speed wireless communications applications. It is shown that, in cases of sparse channels, the feedforward and feedback (FB) filters of the DFE have a particular structure, which can be exploited to derive efficient implementations of the DFE, provided that the time delays of the channel IR multipath components are known. This latter task is accomplished by a novel technique, which estimates the time delays based on the form of the channel input-output cross-correlation sequence in the frequency domain. A distinct feature of the resulting DFE is that the involved FB filter consists of a reduced number of active taps. As a result, it exhibits considerable computational savings, faster convergence, and improved tracking capabilities as compared with the conventional DFE. Note that faster convergence implies that a shorter training sequence is required. Moreover, the new algorithm has a simple form and its steady-state performance is almost identical to that of the conventional DFE.     

基于符号判决反馈均衡的联合检测算法

传统的联合检测算法使用的块线性均衡和块判决反馈均衡,它们是以整个数据块为单位进行均衡和检测的,导致系统矩阵比较庞大,计算复杂度较高.本文将系统矩阵分成可检测的最小单位--数据符号,来进行逐个符号的联合检测,产生基于符号线性均衡的联合检测.并且将块判决反馈均衡原理应用其中,得到基于符号判决反馈均衡的联合检测算法.此算法系统矩阵尺寸小得多,因此复杂度也小得多.符号判决反馈均衡既能减小噪声项,又能减小前一符号判决误差项,因此总体的性能接近于块判决反馈均衡.仿真实验表明了这一点.本文还讨论了不同用户不同扩频因子情形下该算法的改造,并提出按用户扩频因子大小排列用户数据符号的改进,仿真实验验证了这个改进的好处.