基于快衰落信道的一种新型自适应MLSE接收器

在移动通信系统中,由于衰落和多普勒效应,为了实现基于Viterbi算法的极大似然序列估计(MLSE),需要不断跟踪信道参数变化.本文首先提出了一种新的基于插值的信道估计方法ICP(Interpolating channel processing),并给出了该方法的两种实现形式,同已有的一些算法的比较结果表明:新方法具有更小的计算复杂度,误码率更低.同时,本文对如何降低Viterbi算法(VA)的计算复杂度也作了探讨.通过采用自适应减小计算复杂度的算法(ATA),本文提出的ICP算法具有更优的性能.     

On Optimal Detection of Band-Limited PAM Signals with Excess Bandwidth

PAM data transmission receivers accomplishing maximum likelihood sequence detection (MLSD) usually require a matched filter prefilter, a sampler at the symbol rate, and a Viterbi algorithm detector. When the channel is unknown or slowly changing, one must use an adaptive matched filter prefilter. We examine an alternative optimum receiver whose optimality is independent of the matched filter prefilter and which is applicable when the channel is effectively band-limited. The sampler in the proposed receiver operates at a rate faster than the data symbol rate, enabling one to replace the matched filter by a fixed low-pass filter and still ensure that the maximum likelihood detector is supplied with a set of sufficient statistics. It is shown that the matched filter is incorporated within a modified Viterbi detector without increasing the number of states in the algorithm, although the Viterbi detector must perform computations at approximately twice the usual rate. Simulations support the optimality of the new receiver and quantitatively indicate the degradation in performance experienced by some adaptive receivers previously proposed.     

Mitigation of channel estimation error in TR–UWB system based on a novel MMSE equalizer

The time reversal (TR) technique combined with the ultra-wideband (UWB) system offers a new potential for decreasing the cost and complexity of the UWB receivers. In spite of TR–UWB's good performance in perfect channel state information (CSI), it is very sensitive to the channel estimation error. The effect of channel imperfection on the TR–UWB system is considered in this paper. At first, based on a minimum mean square error (MMSE) equalizer receiver, a prefilter is calculated in closed form to improve the performance of the TR–UWB system in an imperfect CSI scenario. Furthermore, for comparison purposes, a similar calculation for prefilter is carried out based on a simple matched filter (MF) receiver. Then, in order to improve the MF receiver performance, a two-stage iteration-based algorithm is developed. The initial value for this iteration-based improved algorithm is considered to be a prefilter which is calculated in the TR–UWB system with MMSE equalizer. This optimized algorithm causes the channel estimation error in the TR–UWB system to become zero in some steps. Finally, exhaustive simulations are done to demonstrate the performance advantage attained by the improved algorithm.     

Equalization concepts for EDGE

An equalization concept for the novel radio access scheme Enhanced Data rates for GSM Evolution (EDGE) is proposed by which high performance can be obtained at moderate computational complexity. Because high-level modulation is employed in EDGE, optimum equalization as usually performed in Global System for Mobile Communications (GSM) receivers is too complex and suboptimum schemes have to be considered. It is shown that delayed decision-feedback sequence estimation (DDFSE) and reduced-state sequence estimation (RSSE) are promising candidates. For various channel profiles, approximations for the bit error rate of these suboptimum equalization techniques are given and compared with simulation results for DDFSE. It turns out that a discrete-time prefilter creating a minimum-phase overall impulse response is indispensable for a favorable tradeoff between performance and complexity. Additionally, the influence of channel estimation and of the receiver input filter is investigated and the reasons for performance degradation compared to the additive white Gaussian noise channel are indicated. Finally, the overall system performance attainable with the proposed equalization concept is determined for transmission with channel coding     

MIMO Receiver Using Reduced Complexity Sequence Estimation With Channel Estimation and Tracking

A sequence-based multiple-input–multiple-output receiver incorporating channel estimation and tracking for a frequency selective fading environment is developed. It employs near-maximum likelihood sequence estimation using the partitioned Viterbi algorithm and offers linearly increasing complexity with the number of transmit antennas. The receiver implements channel estimation and tracking using a vector-polynomial-based generalized recursive least squares algorithm. The resulting integrated receiver can operate in a continuously time-varying Rayleigh or Rician fading environment. Simulation results show that it offers a good tradeoff between complexity and performance. Further complexity reduction can be achieved using tentative decisions as reference signals to the estimator and a reduced complexity form of the estimator.      

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     

Decision feedback sequence estimation for continuous phasemodulation on a linear multipath channel

An approach to reduced-complexity detection of partial response continuous phase modulation (CPM) on a linear multipath channel is presented. The method, referred to as decision feedback sequence estimation (DFSE), is based on a conventional Viterbi algorithm (VA) using a reduced-state trellis combined with decision feedback (DF). By varying the number of states in the VA, the receiver structure can be changed gradually from a DF receiver to the optimal maximum-likelihood sequence estimator (MLSE). In this way different tradeoffs between performance and complexity can be obtained. Results on the receiver performance, based on minimum distance calculations and bit error rate simulations, are given for Gaussian minimum-shift keying modulation on typical mobile radio channels. It is shown that for channels with a long memory, a significant complexity reduction can be achieved at the cost of a moderate degradation in performance     

Improving error probability of the prefiltered Viterbi equalizer

The article deals with the design of suboptimal data detectors for binary transmission over frequency selective channels. A detector consisting of a prefilter followed by a Viterbi processor with a number of states lower than that needed for maximum likelihood sequence estimation is considered. Often the parameters of the receiver are optimized according to the minimum mean square error criterion. Here a stochastic approximation algorithm that optimizes the parameters of the receiver according to a measure of the error probability is introduced. Simulation results show that the proposed design gives substantial benefits at moderate to high signal to noise ratio     

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.     

Application of Sequential Estimation Algorithm Based on Branch Metric to Frequency-Selective Channel Equalization

In this work, a sequential estimation algorithm based on branch metric is used as channel equalizer to combat intersymbol interference in frequency-selective wireless communication channels. The bit error rate (BER) and computational complexity of the algorithm are compared with those of the maximum likelihood sequence estimation (MLSE), the recursive least squares (RLS) algorithm, the Fano sequential algorithm, the stack sequential algorithm, list-type MAP equalizer, soft-output sequential algorithm (SOSA) and maximum-likelihood soft-decision sequential decoding algorithm (MLSDA). The BER results have shown that whilst the sequential estimation algorithm has a close performance to the MLSE using the Viterbi algorithm, its performance is better than the other algorithms. Beside, the sequential estimation algorithm is the best in terms of computational complexity among the algorithms mentioned above, so it performs the channel equalization faster. Especially in M-ary modulated systems, the equalization speed of the algorithm increases exponentially when compared to those of the other algorithms.     

Simplified Viterbi processors for the GSM Pan-European cellularcommunication system

The GSM cellular system provides the European countries with a common digital mobile radio structure for overland communications. This paper illustrates an implementation of a GSM receiver in which two reduced complexity Viterbi processors are used: the first one for the demodulation of the GMSK signal and the second one for the decoding operations. The performance of the receiver is evaluated through a channel simulator for mobile communications. The results show that in many cases the proposed receiver allows the significant reduction of the computation complexity with respect to the classical Viterbi processor. In particular, for mean and high signal-to-noise ratios, a reduction of four times in the computational burden is obtained     

Decision-feedback differential demodulation of bit-interleavedcoded MDPSK

A novel simple receiver structure for M-ary differential phase shift keying (MDPSK) transmission over flat Rayleigh fading channels without channel state information is proposed. Convolutional codes are used for error correction and bit-interleaving as an appropriate means to combat the effects of fading, and the hard decisions of the Viterbi algorithm are fed back during the decoding process in order to improve the calculated bit metric. Iterative decoding with this decision-feedback differential demodulation, (DF-DM) results in significant power efficiency gains compared to those achieved using conventional differential demodulation, while the computational complexity remains low     

一种新的未知信道参数下的次最优分集合并接收机

本文推导了衰落信道中未知信道参数情况下相移键控信号多信道分集合并的最大似然序列估计算法,并在此最优方案的基础上提出了两新的次最优维持比算法,将该算法用于扩系统的ＲＡＫＥ接收机的模拟结果表明,对ＤＱＰＳＫ和编码的ＱＰＳＫ信号的接收民理想接收十分接近。     

A suboptimal approach to channel equalization based on the nearestneighbor rule

Applications of clustering and neural network techniques to channel equalization have revealed the classification nature of this problem. This paper illustrates an implementation of a global system for mobile communications (GSM) receiver in which channel equalization and demodulation are realized by means of the nearest neighbor (NN) classifier algorithm. The most important advantage in using such techniques is the significant reduction in terms of the computational complexity compared with the maximum likelihood sequence estimation (MLSE) equalizer. The proposed approach involves symbol-by-symbol interpretation and the knowledge of the channel is embedded in the mapping process of the received symbols over the symbols of the training sequence. This means that no explicit channel estimation need be carried out, either with correlative blocks or using neural networks thus speeding up the entire process. The performance of the proposed receiver, evaluated through a channel simulator for mobile radio communications, is compared with the results obtained by means of a 16-state Viterbi algorithm and other suboptimal receivers. It is shown that the presented algorithm increases the bit error rate (BER) compared with the MLSE demodulator, but the performance degradation, despite the simplicity of the receiver, is kept within the limits imposed by the GSM specifications     

基于快速贝叶斯匹配追踪的激光大气信道估计

信道估计是指接收机获知信道状态信息的方法和过程。信道估计的准确度决定了接收机的工作性能,所以均衡之前,必须先进行信道估计。目前,激光光学传输信道估计成为多输入多输出正交频分复用的自由空间光通信系统的关键技术。传统的压缩感知方法作为一种信道估计的有效方法,具有恢复和重构原始信号的能力,但在计算复杂度上付出了一定的代价。快速贝叶斯匹配追踪算法克服了现有方法重构精度低和复杂度高缺点。通过先验模型选择和近似的最小均方误差的参数向量的估计,快速贝叶斯匹配追踪算法提供了估计信道冲激响应的一种有效方式。仿真结果表明,与传统的基于压缩感知的方法相比,该方法能显著提高系统的性能。     

Iterative decoding and channel estimation for space-time BICM over MIMO block fading multipath AWGN channel

In this paper, we consider a generic model of space-time bit-interleaved coded modulation (ST-BICM) on a multiple-input multiple-output (MIMO) Rayleigh fading multipath channel. A practical low-complexity receiver structure performing iteratively MIMO data detection, channel decoding and channel estimation, is presented. The MIMO data detection, employing a reduced-state list-type soft output Viterbi algorithm enables to cope with severe channel intersymbol interference (ISI) without MIMO prefiltering. Among other results, simulations show that our approach can dramatically improve the downlink performance of time-division multiple access (TDMA) systems with high order modulation, keeping a reasonable complexity at the receiver side.     

Parallel structures for joint channel estimation and data detectionover fading channels

Joint data and channel estimation for mobile communication receivers can be realized by employing a Viterbi detector along with channel estimators which estimate the channel impulse response. The behavior of the channel estimator has a strong impact on the overall error rate performance of the receiver. Kalman filtering is an optimum channel estimation technique which can lead to significant improvement in the receiver bit error rate (BER) performance. However, a Kalman filter is a complex algorithm and is sensitive to roundoff errors. Square-root implementation methods are required for robustness against numerical errors. Real-time computation of the Kalman estimator in a mobile communication receiver calls for parallel and pipelined structures to take advantage of the inherent parallelism in the algorithm. In this paper different implementation methods are considered for measurement update and time update equations of the Kalman filter. The unit-lower-triangular-diagonal (LD) correction algorithm is used for the time update equations, and systolic array structures are proposed for its implementation. For the overall implementation of joint data and channel estimation, parallel structures are proposed to perform both the Viterbi algorithm and channel estimation. Simulation results show the numerical stability of different implementation techniques and the number of bits required in the digital computations with different estimators     

Soft-output demodulator in space-time-coded continuous phase modulation

Space-time coding has shown great promise for digital transmission in wireless communication links, especially when the channel response is known at the receiver. Space time coding combined with continuous phase modulation (CPM) can offer better tradeoffs in bandwidth and power efficiency. Because of the memory inherent in CPM, channel estimation is often harder than for linear modulations. We present an adaptive soft algorithm that performs joint channel estimation and data detection for space-time CPM systems. Properly designed pilot symbols are inserted at the very beginning to give good initial estimates of the channels. This soft receiver is further applied to the interleaved space-time CPM system to yield better performance with moderate complexity through iterative processing. Simulation results show that the receiver can often achieve near-coherent performance in quasistatic fading as well as in time-varying fading.     

Evaluation of Decision Feedback Equalization and Viterbi Algorithm Detection for Voiceband Data Transmission--Part I

The application of QAM receivers employing passband decision feedback equalization or Viterbi algorithm detection is considered for high-speed data transmission in voiceband telephone channels. Analytical results for the Viterbi receiver indicate that it can permit digital data transmission with symbol rates exceeding the nominal bandwidth capabilities of the channel. However, it is also shown that the minimum distance of partial response-type impulse responses can substantially decrease due to small demodulation phase errors. Thus, decision feedback receivers may offer more robust performance on channels with phase jitter.     

基于PSP均衡技术的CPM检测算法

针对时变频率选择性衰落信道,研究了连续相位调制（CPM）信号的逐幸存检测算法。该算法在未知信道状态的条件下,利用训练序列对信道参数进行初始估计。在对CPM信号进行Viterbi解调过程中,采用PSP技术实现信道的无延时跟踪。基于频域均衡的CPM检测算法虽然可以有效抗多径干扰且计算复杂度较低,但不能对时变信道进行跟踪。仿真结果表明,在时变多径信道下,基于PSP均衡的CPM检测算法能有效地进行信道参数估计,比频域均衡算法具有更好的误码性能。