Time-varying FIR equalization for doubly selective channels

We propose a time-varying (TV) finite impulse response (FIR) equalizer for doubly selective (time- and frequency-selective) channels. We use a basis expansion model (BEM) to approximate the doubly selective channel and to design the TV FIR equalizer. This allows us to turn a complicated equalization problem into an equivalent simpler equalization problem, containing only the BEM coefficients of both the doubly selective channel and the TV FIR equalizer. The minimum mean-square error (MMSE) as well as the zero-forcing (ZF) solutions are considered. Comparisons with the block linear equalizer (BLE) are made. The TV FIR equalization we propose here unifies and extends many previously proposed serial equalization approaches. In contrast to the BLE, the proposed TV FIR equalizer allows a flexible tradeoff between complexity and performance. Moreover, through computer simulations, we show that the performance of the proposed MMSE TV FIR equalizer comes close to the performance of the ZF and MMSE BLE, at a point where the design as well as the implementation complexity are much lower.     

Joint MAP equalization and channel estimation forfrequency-selective and frequency-flat fast-fading channels

This paper presents a new fractionally-spaced maximum a posteriori (MAP) equalizer for data transmission over frequency-selective fading channels. The technique is applicable to any standard modulation technique. The MAP equalizer uses an expanded hypothesis trellis for the purpose of joint channel estimation and equalization. The fading channel is estimated by coupling minimum mean square error techniques with the (fixed size) expanded trellis. The new MAP equalizer is also presented in an iterative (turbo) receiver structure. Both uncoded and conventionally coded systems (including iterative processing) are studied. Even on frequency-flat fading channels, the proposed receiver outperforms conventional techniques. Simulations demonstrate the performance of the proposed equalizer     

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.     

Iterative Estimation and Equalization for SCCP Over Doubly Selective Channels

In time varying channels, symbol recovery for single carrier cyclic prefix (SCCP) systems becomes complicated, because the orthogonality of channel frequency response (CFR) matrix is destroyed. In response, we propose a block turbo equalization algorithm in the time domain for SCCP to cope with channel time variations. In particular, the band structure of the channel time response (CTR) matrix is exploited to reduce the computational complexity of matrix inversion. In order to use this equalization scheme, accurate channel state information (CSI) must be available. Accordingly, we present a doubly selective channel estimation method for SCCP block transmissions with the aid of a Karhunen-Loeve basis expansion model (KL-BEM). In this method, the channel estimates are firstly obtained by using the cyclic prefix (CP) of each block, and then further refined by employing an expectation maximization (EM) based iterative algorithm. Combining the iterative estimator with the proposed equalizer naturally results in a doubly iterative receiver, the performance of which is shown to come close to the performance with perfect CSI.     

Adaptive maximum-likelihood sequence estimation by means ofcombined equalization and decoding in fading environments

This paper proposes an adaptive maximum-likelihood sequence estimation (MLSE) by means of combined equalization and decoding, i.e., adaptive combined MLSE, which employs separate channel estimation for respective states in the Viterbi algorithm. First, an approximate metric including channel estimation is derived analytically for this proposed adaptive combined MLSE. Secondly, procedures to accomplish blind equalization are investigated for the proposed MLSE. Finally, its excellent BER performance on fast time-varying fading channels is confirmed by computer simulation, when the proposed MLSE operates as a blind equalizer     

Iterative Channel Estimation and Successive ICI Cancellation for OFDM Systems over Doubly Selective Channels

In orthogonal frequency division multiplexing systems, significant inter-carrier interference (ICI) caused by doubly selective channels make challenge for reliable reception. In this paper, channel estimation and ICI cancellation are considered jointly. Relying on the basis expansion model (BEM) of time-varying channel, the linear system model of transceiver is established, and the corresponding joint optimization of the transmitted data and BEM coefficients is formulated. Due to the separability of the data and BEM coefficients, we use cyclic minimizing technique to perform channel estimation and equalization alternately. This yields a linear minimum mean square-error (LMMSE) channel estimator and a block MMSE equalizer respectively. The block MMSE equalizer has complexity O(N ³), where N is the number of data subcarriers. To reduce the complexity, instead of equalizing all the data simultaneously, we consider estimating each data symbol successively. This idea results in the per subcarrier interference canceller with lower complexity O(N ²). Finally, an iterative receiver consisting of the data-aided LMMSE channel estimator and the successive interference canceller is developed. Simulation results show the scheme is effective over the channel with relatively large Doppler spread.     

MLSE and soft-output equalization for trellis-coded continuousphase modulation

This paper presents two equalizer structures for trellis-coded continuous phase modulation (TC-CPM) on multipath fading intersymbol interference (ISI) channels. An equivalent discrete-time (DT) model is developed by combining the tapped-delay-line (TDL) model of the frequency-selective channel and by oversampling at the receiver. The (noninterleaved) fractionally spaced maximum-likelihood sequence estimation (MLSE) equalizer performs continuous phase modulation (CPM) demodulation, trellis-coded modulation (TCM) decoding, and channel equalization by exploiting the finite state nature of the ISI-corrupted TC-CPM signal. Both simulation and analytical results show diversity-like improvement when performing joint MLSE decoding and equalization. For the interleaved soft-output equalizer, the soft symbol metric is delivered to the TCM decoder by using a forward and backward recursion algorithm. Three variants of the soft-output equalizer are examined. We conclude that the backward recursion is essential to partial response CPM schemes, and with moderate complexity, the soft-output equalizer can have a substantial advantage over a noninterleaved MLSE equalizer     

Space–Time Turbo Equalization With Successive Interference Cancellation for Frequency-Selective MIMO Channels

This paper addresses the issue of iterative space–time equalization for multiple-input–multiple-output (MIMO) frequency-selective fading channels. A new soft equalization concept based on successive interference cancellation (SIC) is introduced for a space–time bit-interleaved coded modulation (STBICM) transmission. The proposed equalizer allows us to separate intersymbol interference (ISI) and multiantenna interference (MAI) functions. Soft ISI is successively suppressed using a low-complexity suboptimum minimum mean square error (MMSE) criterion. The decoupling of ISI and MAI offers more flexibility in the design of the whole space–time equalizer. Different multiantenna detection criteria can be considered, ranging from simple detectors to the optimal maximum a posteriori (MAP) criterion. In particular, we introduce two soft equalizers, which are called SIC/SIC and SIC/MAP, and we show that they can provide a good performance-to-complexity tradeoff for many system configurations, as compared with other turbo equalization schemes. This paper also introduces an MMSE-based iterative channel state information (CSI) estimation algorithm and shows that attractive performance can be achieved when the proposed soft SIC space–time equalizer iterates with the MMSE-based CSI estimator.      

Iterative MAP Equalization and Decoding in Wireless Mobile Coded OFDM

Orthogonal frequency division multiplexing (OFDM) system suffers extra performance degradation in fast fading channels due to intercarrier interference (ICI). Combining frequency domain equalization and bit-interleaved coded modulation (BICM), the iterative receiver is able to harvest both temporal and frequency diversity. Realizing that ICI channels are intrinsically ISI channels, this paper proposes a soft-in soft-out (SISO) maximum a posteriori (MAP) equalizer by extending Ungerboeck's maximum likelihood sequence estimator (MLSE) formulation to ICI channels. The SISO MAP equalizer employs BCJR algorithm and computes the bit log-likelihood ratios (LLR) for the entire received sequence by efficiently constructing a trellis that takes into account of the ICI channel structure. A reduced state (RS) formulation of the SISO MAP equalizer which provides good performance/complexity tradeoff is also described. Utilizing the fact that ICI energy is clustered in adjacent subcarriers, frequency domain equalization is made localized. This paper further proposes two computational efficient linear minimum mean square error (LMMSE) based equalization methods: recursive q-tap SIC-LMMSE equalizer and recursive Sliding-Window (SW) SIC-LMMSE equalizer respectively. Simulations results demonstrate that the iterative SISO RS-MAP equalizer achieves the performance of no ICI with normalized Doppler frequency f_dT_s up to 20.46% in realistic mobile WiMAX environment.     

Receiver Design for Single-Carrier Block Transmission Over Doubly Selective Channels

Single-carrier block transmission is an alternative scheme to orthogonal frequency-division multiplexing (OFDM) for wireless broadband communications. In this paper, a receiver is designed for single-carrier block transmission with cyclic prefix for mobile broadband communications. As the wireless transmission is over doubly selective channels, a basis expansion model is used to capture both the time- and frequency-selectivity of the channel and is parameterized for the receiver design. The receiver estimates the channel model coefficients in the time domain and uses these coefficients for equalization in the frequency domain. The channel estimation is assisted by time-domain pilot insertion. The structure of the frequency-domain channel matrix is exploited and a linear minimum mean-square error equalizer is used for the equalization. When the basis expansion model well matches the physical channel, simulation results show superior receiving performance of the proposed system compared with the OFDM system with a similar complexity.     

Turbo equalization of doubly selective channels

In this paper, turbo equalization for transmission over doubly selective channels is proposed. The maximum a posteriori probability (MAP) algorithm is used for channel detection as well as for channel decoding. The detection/decoding constituents can exchange soft information in an iterative manner resulting in the so‐called turbo equalization. The time‐varying multi‐path fading channel is modeled using the basis expansion model (BEM). In this BEM, the time‐varying channel is viewed as a bank of time‐invariant finite impulse response filters, and the time variation is captured by means of time‐varying complex exponential basis functions. Therefore, the time‐varying transition tables that characterize the time‐varying channel can also follow a similar BEM. The complexity of the MAP channel detector is rather prohibitive for practical applications. This motivates the search for lower‐complexity soft‐output channel detectors. For this purpose, soft‐output linear minimum‐mean square error (LMMSE)‐based channel detectors are proposed for single carrier as well as for multi‐carrier systems. With the use of Gaussian approximation, expressions for the a posteriori and extrinsic log‐likelihood ratios have been derived. The performance of the proposed turbo equalization schemes are evaluated using numerical simulations. Copyright © 2012 John Wiley & Sons, Ltd.     

On the least-squares performance of a novel efficient center estimation method for clustering-based MLSE equalization

Recently, a novel maximum-likelihood sequence estimation (MLSE) equalizer was reported that avoids the explicit estimation of the channel impulse response. Instead, it is based on the fact that the (noise-free) channel outputs, needed by the Viterbi algorithm, coincide with the points around which the received (noisy) samples are clustered and can thus be estimated directly with the aid of a supervised clustering method. Moreover, this is achieved in a computationally efficient manner that exploits the channel linearity and the symmetries underlying the transmitted signal constellation. The resulting computational savings over the conventional MLSE equalization scheme are significant even in the case of relatively short channels where MLSE equalization is practically applicable. It was demonstrated, via simulations, that the performance of this algorithm is close to that using a least-squares (LS) channel estimator, although its computational complexity is even lower than that of the least-mean squares (LMS)-trained MLSE equalizer. This paper investigates the relationship of the center estimation (CE) part of the proposed equalizer with the LS method. It is proved that, when using LS with the training sequence employed by CE, the two methods lead to the same solution. However, when LS is trained with random data, it outperforms CE, with the performance difference being proportional to the channel length. A modified CE method, called MCE, is thus developed, that attains the performance of LS with perfectly random data, while still being much simpler computationally than classical LS estimation. Through the results of this paper, CE is confirmed as a methodology that combines high performance, simplicity, and low computational cost, as required in a practical equalization task. An alternative, algebraic viewpoint on the CE method is also provided.     

Performance analysis of an adaptive receiver structure for digital mobile communications

In this paper we investigate the performance of a combined estimation/equalization technique for the mobile radio channel, assuming a GSM-recommended transmission format (narrowband TDMA with midamble, recommendation 5.04) and MSK modulation scheme. Channel estimation is performed via correlation of the received signal with a suitably modulated replica of the transmitted midamble. Equalization is then obtained by means of a maximum likelihood sequence estimation (MLSE) scheme in the form of a so-called Viterbi equalizer. Our analysis provides theoretical results concerning the bit error rate (BER) attained by the receiver for a given stationary multipath channel model. Simulation results are also presented in order to integrate and validate the theory.     

双选择性信道下发射分集MISO OFDM系统基于BEM的低复杂度信道均衡

在高速移动环境下,无线信道会同时经历时间选择性和频率选择性衰落,即所谓的快速时变信道,也称之为双选择性信道。最初的发射分集Alamouti编码方案是针对时不变平坦信道提出的,不能直接应用于快速时变信道。此外,OFDM 系统在双选信道下遭受的载波间干扰(ICI)不可忽视。因此,发射分集MISO OFDM系统在双选择性信道下既节能又有效的信号恢复是有挑战的。本文基于双选择性信道的基扩展模型(BEM)表示,研究了一种有效的可动态分组的混合干扰消除(HIC)信道均衡方案。仿真结果表明,提出的方案,与传统的MMSE均衡相比,计算复杂度大大降低的同时性能显著提高,计算量的降低减少了能量消耗,达到节能的目的;与现有的关于发射分集的信道均衡方案相比,表现出性能和复杂度的较好折中;此外,在信道信息完美已知的假设下,随着移动速度的提高,误码性能没有损失。      

Performance of trellis-coded modulation for equalized multipathfading ISI channels

The performance of TCM on equalized multipath fading ISI channels with different equalization schemes is examined. Trellis codes that are effective for AWGN channels and flat fading channels with interleaving are evaluated for equalized multipath fading channels. For joint MLSE equalization and decoding the equivalent uncoded system outperforms all the trellis-coded systems that are examined. Trellis codes that are designed for flat fading channels with interleaving perform well if interleaving is used and an MLSE equalizer is used before deinterleaving. An effective interleaver-deinterleaver is identified that allows joint DDFSE equalization and decoding to be used without the need for equalization before decoding     

Estimation and equalization of doubly selective channels using known symbol padding

This paper considers the situation where users that experience high-mobility transmit data over frequency-selective channels, resulting in a doubly selective channel model (i.e., time- and frequency-selective channels) and this within the framework of Known Symbol Padding (KSP) transmission. KSP is a recently proposed block transmission technique where short sequences of known symbols acting as guard bands are inserted between successive blocks of data symbols. This paper proposes three novel channel estimation methods that allow for an accurate estimation of the time-varying transmission channel solely relying on the knowledge of the redundant symbols introduced by the KSP transmission scheme. The first method is a direct adaptive one while the others rely on a recently proposed model, the Basis Expansion Model (BEM), where the doubly selective channel is approximated with high accuracy using a limited number of complex exponentials. An important characteristic of the proposed methods is that they exploit all the received symbols that contain contributions from the training sequences and blindly filter out the contribution of the unknown surrounding data symbols. Besides these channel identification methods, the classical KSP equalizers are adapted to the context of doubly selective channels, which allows evaluation of the bit-error-rate (BER) performance of a KSP transmission system relying on the proposed channel estimation methods in the context of doubly selective channels. Simulation results show that KSP transmission is indeed a suitable transmission technique toward the delivery of high data rates to users experiencing a high mobility, when adapted KSP equalizers are used in combination with the proposed channel estimation methods.     

Doubly Iterative Equalization of Continuous-Phase Modulation

In this paper, a doubly iterative receiver is proposed for joint turbo equalization, demodulation, and decoding of coded binary continuous-phase modulation (CPM) in multipath fading channels. The proposed receiver consists of three soft-input soft-output (SISO) blocks: a front-end soft-information-aided minimum mean square error (MMSE) equalizer followed by a CPM demodulator and a back-end channel decoder. The MMSE equalizer, combined with an a priori soft-interference canceler (SIC) and an a posteriori probability mapper, forms a SISO processor suitable for iterative processing that considers discrete-time CPM symbols which belong to a finite alphabet. The SISO CPM demodulator and the SISO channel decoder are both implemented by the a posteriori probability algorithm. The proposed doubly iterative receiver has a central demodulator coupled with both the front-end equalizer and the back-end channel decoder. A few back-end demodulation/decoding iterations are performed for each equalization iteration so as to improve the a priori information for the equalizer. As presented in the extrinsic information transfer (EXIT) chart analysis and simulation results for different multipath fading channels, this provides not only faster convergence to low bit error rates, but also lower computational complexity.     

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.     

瑞利衰落信道下的Turbo均衡

Turbo均衡是一种将Turbo原理和均衡技术结合起来的技术。他通过反复均衡和信道译码来提高接收机性能。针时瑞利衰落信道，采用基于线性滤波器的软输入／软输出均衡器来消除码间干扰，其系数由最小均方误差准则确定。译码器采用最大后验概率算法时卷积码译码。考虑到瑞利衰落信道为随机信道，用非相干检测时信道进行估计。接收机通过联合均衡和译码以充分利用已经获得的信息，实现信道估计及信道均衡与信道译码的迭代更新。仿真结果表明其性能不仅远远优于非迭代系统．而且在信噪比高于4dB时几乎可以完全消除符号间干扰的影响，与MAPSE相比其复杂度大大降低。     

A robust noncoherent equalizer receiver for fading channels with short memory . II. Modified structure

For pt. I see ibid., vol.5, no.5, p.1040-54 (2002). In Part I, we introduced a robust noncoherent maximum likelihood sequence estimation (MLSE) equalizer receiver structure applicable to radio channels with impulse responses spanning less than two bit intervals. The distinct characteristic of this receiver was its robustness to carrier frequency offsets. However, due to the differential operation prior to the MLSE equalization, we observed some performance degradation, resulting in a delay spread range significantly smaller than an equivalent coherent MLSE equalizer. We propose techniques to significantly improve the performance of the noncoherent equalizer by using a second, complementary differential processor. The performance assessment of the new receiver is presented. In particular, using the Digital Enhanced Cordless Telecommunications system as an example, it is shown that the modified receiver's dispersive channel operation range is almost twice as much as the basic structure, with a multipath diversity gain comparable to a coherent equalizer receiver. On the other hand, unlike coherent structures, it retains low sensitivity to both frequency offsets and modulation index drifts. Finally, we introduce an approach to further extend the receiver's frequency offset tolerance to that of a standard differential detector receiver.