一种用于无线信道的逐幸存处理均衡器

提出了一种适用于无线时变信道的逐幸存处理均衡器。通过训练序列得到信道参数的初始估计值,此后在Viterbi算法进行网格搜索的过程中,使得每一条幸存路径维持各自的信道参数,并在确定幸存分支后利用历史幸存序列对信道参数值进行更新,实现了信道参数的无时延估计。仿真结果表明,在无线时变信道环境下,逐幸存处理均衡器的性能明显优于其他传统均衡器。     

A decision feedback equalizer with time-reversal structure

This work describes the use of a receiver with a time-reversal structure for low-complexity decision feedback equalization of slowly fading dispersive indoor radio channels. Time-reversal is done by storing each block of received signal samples in a buffer and reversing the sequential order of the signal samples in time prior to equalization. As a result, the equivalent channel impulse response as seen by the equalizer is a time-reverse of the actual channel impulse response. Selective time-reversal operation, therefore, allows a decision feedback equalizer (DFE) with a small number of forward filter taps to perform equally well for both minimum-phase and maximum-phase channel characteristics. The author evaluates the theoretical performance bounds for such a receiver and quantifies the possible performance improvement for discrete multipath channels with Rayleigh fading statistics. Two extreme cases of DFE examples are considered: an infinite-length DFE; and a DFE with a single forward filter tap. Optimum burst and symbol timing recovery is addressed and several practical schemes are suggested. Simulation results are presented. The combined use of equalization and diversity reception is considered     

A Maximum-Likelihood Sequence Estimator with Decision-Feedback Equalization

A decision-feedback equalizer (DFE) is proposed as a prefilter which limits the complexity of a maximum-likelihood sequence estimator (MLSE) implemented by the Viterbi algorithm (VA) for channels having a long impulse response. By imbedding a DFE into the structure of the MLSE, the overall impulse response of the system is truncated to a short duration. With this practical receiver, a compromise may be made between performance and complexity by properly choosing the duration of a desired impulse response. A technique is also developed to estimate the performance of the receiver numerically, taking into account the effect of incorrect decision feedback on the VA. Analysis and computer simulation over a single-pole channel show that the proposed scheme can reduce the complexity of the MLSE while retaining much of its performance advantages.     

Adaptive Equalization Techniques for HF Channels

Data transmission at rates of 1.2 kbits/s or higher through voiceband ionospheric channels is subject to impairment from severe linear distortion, fast channel time variations, and severe fading. In this paper, we have focused on the performance of DFE (decision feedback equalization) receivers for communication over 3 kHz bandwidth HF channels. We describe the results of simulations for a wide range of fading rates on simulated and real recorded HF channels, using fractionally spaced DFE receivers. Both LMS (least mean square) and FRLS (fast recursive least squares) adaptation algorithms with periodic restart were evaluated, and both ideal-reference and decision-directed operation was observed. The results indicate that FRLS adaptation yields superior performance to LMS in rapid fading conditions, but that this performance advantage diminishes at low signal-to-noise ratios. Also, fade rates greater than about 1 Hz produced relatively high error rates, irrespective of which adaptation method was employed. Finally, a novel modification of the simple LMS algorithm which improves its tracking ability was evaluated. This involved preceding the LMS DFE receiver with an adaptive lattice whitening filter.     

Performance of sequence estimation scheme of narrowband digital FMsignals with limiter-discriminator detection

A communication scheme using binary FM with noncoherent limiter-discriminator detection has been well known. Up to now, the improvement of bit error rate at the receiver side has been carried out through the bandwidth optimization of the IF filter, the decision feedback equalization (DFE), or simple two-state maximum likelihood sequence estimator (MLSE). This channel is inherently the intersymbol interference (ISI) channel due to the premodulation baseband filtering as well as the narrowband IF filtering. So the sequence estimation scheme using the Viterbi algorithm can be applied successfully, although the channel is not additive white Gaussian and maximum likelihood in the strict sense. In this paper, through computer simulations, we examine the actual BER improvement of the sequence estimation scheme with multiple-state trellis especially for MSK and GMSK signals. We mainly consider static AWGN and frequency nonselective Rician fading channels. Consequently, by adjusting the IF filter bandwidth, very large estimation gains are obtained compared to the conventional DFE or MLSE detector for AWGN and Rician fading channels. This scheme does not produce large demodulation delay and is implemented only by adding the signal processing part to the final stage of the receiver. This scheme seems to be very useful for any applications including satellite mobile channels     

Fast adaptive equalization/diversity combining for time-varyingdispersive channels

We examine adaptive equalization and diversity combining methods for fast Rayleigh-fading frequency selective channels. We assume a block adaptive receiver in which the receiver coefficients are obtained from feedforward channel estimation. For the feedforward channel estimation, we propose a novel reduced dimension channel estimation procedure, where the number of unknown parameters are reduced using a priori information of the transmit shaping filter's impulse response. Fewer unknown parameters require a shorter training sequence. We obtain least-squares, maximum-likelihood, and maximum a posteriori (MAP) estimators for the reduced dimension channel estimation problem. For symbol detection, we propose the use of a matched filtered diversity combining decision feedback equalizer (DFE) instead of a straightforward diversity combining DFE. The matched filter form has lower computational complexity and provides a well-conditioned matrix inversion. To cope with fast time-varying channels, we introduce a new DFE coefficient computation algorithm which is obtained by incorporating the channel variation during the decision delay into the minimum mean square error (MMSE) criterion. We refer to this as the non-Toeplitz DFE (NT-DFE). We also show the feasibility of a suboptimal receiver which has a lower complexity than a recursive least squares adaptation, with performance close to the optimal NT-DFE     

On the distribution of zeros of mobile channels with application toGSM/EDGE

The distribution of zeros of mobile channels is investigated and the results obtained are applied to the GSM/EDGE system. The taps of the discrete-time overall impulse response can be modeled as correlated complex Gaussian random variables, where the correlations depend on the transmit filter, the power delay profile of the channel, and the receiver input filter. For calculation of the density of zeros of the overall transfer function, a result from the mathematical literature is used. From this density, two cumulative distributions which are relevant for the design of suboptimum receivers are derived. Our investigations show that for the power delay profiles specified for GSM/EDGE, an allpass prefilter which transforms the impulse response in its minimum phase equivalent should be employed if decision-feedback equalization (DFE) or reduced-state sequence estimation (RSSE) are used at the receiver. On the other hand, if impulse response truncation using a linear prefilter is applied, the truncated impulse response should have a length of three as shown     

A new adaptive equalizer with channel estimator for mobile radiocommunication

For unknown mobile radio channels with severe intersymbol interference (ISI), a maximum likelihood sequence estimator, such as a decision feedback equalizer (DFE) having both feedforward and feedback filters, needs to handle both precursors and postcursors. Consequently, such an equalizer is too complex to be practical. This paper presents a new reduced-state, soft decision feedback Viterbi equalizer (RSSDFVE) with a channel estimator and predictor. The RSSDFVE uses maximum likelihood sequence estimation (MLSE) to handle the precursors and truncates the overall postcursors with the soft decision of the MLSE to reduce the implementation complexity. A multiray fading channel model with a Doppler frequency shift is used in the simulation. For fast convergence, a channel estimator with fast start-up is proposed. The channel estimator obtains the sampled channel impulse response (CIR) from the training sequence and updates the RSSDFVE during the bursts in order to track changes of the fading channel. Simulation results show the RSSDFVE has nearly the same performance as the MLSE for time-invariant multipath fading channels and better performance than the DFE for time-variant multipath fading channels with less implementation complexity than the MLSE. The fast start-up (FS) channel estimator gives faster convergence than a Kalman channel estimator. The proposed RSSDFVE retains the MLSE structure to obtain good performance and only uses soft decisions to subtract the postcursor interference. It provides the best tradeoff between complexity and performance of any Viterbi equalizers     

Adaptive combined DFE/MLSE techniques for ISI channels

By embedding a decision-feedback equalizer (DFE) into the structure of a maximum-likelihood sequence estimator (MLSE), an adaptive combined DFE/MLSE scheme is proposed. In this combined DFE/MLSE, the embedded DFE has three functions: (i) prefiltering the received signals and truncating the equivalent channel response into the desired one, (ii) compensating for channel distortions, and (iii) providing the MLSE detector with predicted values of input signals. Since the embedded MLSE detector operates on the predicted signals the detected symbols at the output of the DFE/MLSE do not suffer any delay and can be directly fed back into the embedded DFE so that the error propagation, which usually takes place in a conventional DFE, can be greatly reduced. Analytical and simulation results indicate that the performance is significantly improved by the DFE/MLSE compared to the conventional DFE while its computation complexity is much less than that of the conventional MLSE receiver. The combined DFE/MLSE can use different adaptive structures (block-updating, sliding window updating or symbol-by-symbol updating) to meet different performance objectives. Moreover, the proposed DFE/MLSE provides a trade-off between performance and complexity with a parameter m representing the MLSE detection depth as well as the number of predicting steps of the embedded DFE. For some particular values of m, this scheme is capable of emulating the conventional DFE, MLSE-VA, adaptive LE-MLSE equalizer, adaptive DDFSE, and adaptive BDFE without detection delay     

一种短波信道自适应均衡算法的研究

基于逐幸存路径处理(PSP)的思想,研究了一种减少状态序列估计(RSSE)的短波信道自适应均衡算法.该算法首先通过训练序列估计信道的参数,然后利用RLS算法对信道参数和输入数据的估计值同时进行逐幸存路径地更新.数值仿真表明,在短波信道环境下,RSSE-PSP算法在减小计算复杂度的同时最大限度地保持了性能增益,其性能明显优于其他均衡算法.     

Performance of a nonlinear adaptive SBS-MAP detector usingsoft-statistics for digital transmissions over HF channels

The effectiveness of the adaptive maximum a posteriori (MAP) receiver in Cusani and Mattila is verified for digital HF links between mobile and/or fixed units. Following Cusani and Mattila (1998), a suitable MAP algorithm is employed to compute symbol-by-symbol (SBS) the a posteriori probabilities (APPs) of the channel state; from these, the detected data stream is obtained. The same APPs are employed by an adaptive nonlinear Kalman-like filter to estimate recursively the time-varying channel with fast convergence and good tracking properties, overcoming the delay problem suffered by conventional adaptive MLSE-VA detectors. Computer simulations allow to compare the adaptive SBS-MAP with other receivers (DFE, MLSE) and verify its effectiveness in the HF environment     

On optimum detection of linearly filtered CPM signals

A novel structure of the MLSE receiver for linearly filtered CPM (continuous phase modulation) signals is derived. It is shown that the correlator bank required in the works of Svensson (1987) can equivalently be replaced by a reduced correlator bank, preceded by a linear filter with impulse response h*(-t) [channel matched filter]. The reduced correlator bank only incorporates characteristics of the CPM signals and is independent of the channel impulse response. This implies that the complexity of the modified correlator bank depends only linearly on the channel filter impulse response length. The proposed receiver structure permits considerable complexity reduction when compared to the currently known solution     

Adaptive Bayesian decision feedback equalizer for dispersive mobileradio channels

The paper investigates adaptive equalization of time-dispersive mobile radio fading channels and develops a robust high performance Bayesian decision feedback equalizer (DFE). The characteristics and implementation aspects of this Bayesian DFE are analyzed, and its performance is compared with those of the conventional symbol or fractional spaced DFE and the maximum likelihood sequence estimator (MLSE). In terms of computational complexity, the adaptive Bayesian DFE is slightly more complex than the conventional DFE but is much simpler than the adaptive MLSE. In terms of error rate in symbol detection, the adaptive Bayesian DFE outperforms the conventional DFE dramatically. Moreover, for severely fading multipath channels, the adaptive MLSE exhibits significant degradation from the theoretical optimal performance and becomes inferior to the adaptive Bayesian DFE     

A study of analog decision feedback equalization for ADC-Based serial link receivers

High-speed serial link receivers based on analog-to-digital converters (ADCs) provide better programmability with different channel characteristics and the possibility of employing powerful signal equalization techniques in the digital domain. However, complexity and power consumption are still major issues in adopting such receivers in high-speed applications when compared to traditional binary or mixed-signal approaches. Embedded decision feedback equalization (DFE) before ADC quantization can relax the design requirements of both the ADC and post-ADC digital processing. This paper studies the impact of embedded analog DFE on voltage margin improvement of an ADC-based receiver through worst-case analysis. An analytical expression for the link bit-error-rate (BER) with analog DFE is derived and validated through simulations. An empirical study is conducted that evaluates the achievable BER of embedded analog DFE as a function of the channel inter-symbol interference (ISI) and ADC resolution. A channel-dependent parameter is introduced and employed to quantify the BER improvement achieved by embedding analog DFE in a receiver. A prototype receiver with embedded DFE is designed and laid out in a 130 nm CMOS process and achieves 4.64-bits peak ENOB and 4.08 pJ/conv.-step FOM at a 1.6-GS/s sampling rate. The BER performance of the receiver over high-loss FR4 channels at 1.6 Gb/s is evaluated and used to validate the simulation results.     

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.     

Statistical Estimation of Fast Varying Channels for Cellular Mobile Telecommunications Systems

The time variant environment in fast channels severely impacts on the performances of classical equalization techniques. A method is proposed here to circumvent this problem, particularly in the severe channel with fast behaviour. To improve the Bit Error Rate (BER) at the receiver, a new approach is proposed for the channel impulse response (CIR) estimation in the Enhanced Data rates for GSM Evolution (EDGE)cellular system. The computation of the CIR h(t) (finite impulse response filter) is performed by using the Least Squares algorithm. Then, a statistical estimation of the CIR is achieved to update the coefficients of the equalizer filter. Computer simulation results show that statistical estimation (CIR re-estimation) provides significant improvement with 250 km/h vehiclespeed (RA250): the bit error rate (BER) is 20% lowered for data bits far from the middle of the burst.     

基于快速信道捕获与系数映射均衡的流星通信接收机

针对流星余迹通信原理及信道特点,构造了基于自适应编码调制的变速率通信机制,提出了有效利用传输帧结构的快速信道估计及系数映射均衡的流星余迹通信接收机.在利用时域相关运算快速捕获流星信道冲击响应的基础上,推导出信道参数与均衡器系数之间的映射关系,直接计算出判决反馈均衡器的抽头系数,从而实现流星余迹通信自适应编码调制方式数据的可靠接收.该接收机在信道变化的情况下具有较快的收敛速度,和较好的抗噪声性能.仿真结果和复杂度分析验证了算法的有效性.     

Reduced-complexity equalization techniques for broadband wirelesschannels

This paper presents reduced-complexity equalization techniques for broadband wireless communications, both outdoors (fixed or mobile wireless asynchronous transfer mode (ATM) networks) and indoors [high-speed local-area networks (LANs)]. The two basic equalization techniques investigated are decision-feedback equalization (FE) and delayed decision-feedback sequence estimation (DDFSE). We consider the use of these techniques in highly dispersive channels, where the impulse response can last up to 100 symbol periods. The challenge is in minimizing the complexity as well as providing fast equalizer start-up for transmissions of short packets. We propose two techniques which, taken together, provide an answer to this challenge. One is an open-loop timing recovery approach (for both DFE and DDFSE) which can be executed prior to equalization; the other is a modified DFE structure for precanceling postcursors without requiring training of the feedback filter. Simulation results are presented to demonstrate the feasibility of the proposed techniques for both indoor and outdoor multipath channel models. The proposed open-loop timing recovery technique plays a crucial role in maximizing the performance of DFE and DDFSE with short feedforward spans (the feedforward section of DDFSE is a Viterbi sequence estimator). A feedforward span of only five is quite sufficient for channels with symbol rate-delay spread products approaching 100. The modified DFE structure speeds up the training process for these channels by 10-20 times, compared to the conventional structure without postcursor precancellation. The proposed techniques offer the possibility of practical equalization for broadband wireless systems     

Joint array combining and MLSE for single-user receivers inmultipath Gaussian multiuser channels

The well-known structure of an array combiner along with a maximum likelihood sequence estimator (MLSE) receiver is the basis for the derivation of a space-time processor presenting good properties in terms of co-channel and intersymbol interference rejection. The use of spatial diversity at the receiver front-end together with a scalar MLSE implies a joint design of the spatial combiner and the impulse response for the sequence detector. This is faced using the MMSE criterion under the constraint that the desired user signal power is not cancelled, yielding an impulse response for the sequence detector that is matched to the channel and combiner response. The procedure maximizes the signal-to-noise ratio at the input of the detector and exhibits excellent performance in realistic multipath channels     

Multi-input multi-output fading channel tracking and equalizationusing Kalman estimation

This paper addresses the problem of channel tracking and equalization for multi-input multi-output (MIMO) time-varying frequency-selective channels. These channels model the effects of inter-symbol interference (ISI), co-channel interference (CCI), and noise. A low-order autoregressive model approximates the MIMO channel variation and facilitates tracking via a Kalman filter. Hard decisions to aid Kalman tracking come from a MIMO finite-length minimum-mean-squared-error decision-feedback equalizer (MMSE-DFE), which performs the equalization task. Since the optimum DFE for a wide range of channels produces decisions with a delay Δ > 0, the Kalman filter tracks the channel with a delay. A channel prediction module bridges the time gap between the channel estimates produced by the Kalman filter and those needed for the DFE adaptation. The proposed algorithm offers good tracking behavior for multiuser fading ISI channels at the expense of higher complexity than conventional adaptive algorithms. Applications include synchronous multiuser detection of independent transmitters, as well as coordinated transmission through many transmitter/receiver antennas, for increased data rate