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.     

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.     

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.     

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。     

Symbol-by-symbol MAP demodulation of CPM and PSK signals onRayleigh flat-fading channels

Demodulation using the symbol-by-symbol maximum a posteriori probability (MAP) algorithm is presented. The algorithm is derived for the case of continuous phase modulation (CPM) signals transmitted over Rayleigh flat-fading channels, and a corresponding receiver structure is specified. It is shown that the MAP algorithm requires computing, for each trellis branch, the sum of the products of the weights of all paths through the trellis which pass through that branch, and that this generic computational problem can be solved efficiently by an approach that uses a forward and backward recursion through the trellis. Simulation results are presented which show both the hard and soft decision performance of the MAP receiver to be robust, even in the presence of fade rates of up to 30% of the symbol rate. The application of the receiver concept to phase-shift keying (PSK) signals is also discussed, and then evaluated via simulation. The concept of joint demodulation and decoding using iterative processing techniques is introduced. It is shown that the MAP receiver is well suited for iterative processing applications due to its use of a priori symbol probabilities and its production of optimal soft decisions. Simulation results for the reception of quaternary PSK (QPSK) show that the bit error rate (BER) performance of the iterative MAP receiver can approach that of a receiver operating with perfect knowledge of the fading process     

Turbo equalization of serially concatenated turbo codes using a predictive DFE-based receiver

This paper investigates the performance of various “turbo” receivers for serially concatenated turbo codes transmitted through intersymbol interference (ISI) channels. Both the inner and outer codes are assumed to be recursive systematic convolutional (RSC) codes. The optimum turbo receiver consists of an (inner) channel maximum a posteriori (MAP) decoder and a MAP decoder for the outer code. The channel MAP decoder operates on a “supertrellis” which incorporates the channel trellis and the trellis for the inner error-correcting code. This is referred to as the MAP receiver employing a SuperTrellis (STMAP). Since the complexity of the supertrellis in the STMAP receiver increases exponentially with the channel length, we propose a simpler but suboptimal receiver that employs the predictive decision feedback equalizer (PDFE). The key idea in this paper is to have the feedforward part of the PDFE outside the iterative loop and incorporate only the feedback part inside the loop. We refer to this receiver as the PDFE-STMAP. The complexity of the supertrellis in the PDFE-STMAP receiver depends on the inner code and the length of the feedback part. Investigations with Proakis B, Proakis C (both channels have spectral nulls with all zeros on the unit circle and hence cannot be converted to a minimum phase channel) and a minimum phase channel reveal that at most two feedback taps are sufficient to get the best performance. A reduced-state STMAP (RS-STMAP) receiver is also derived which employs a smaller supertrellis at the cost of performance.     

Soft input soft output Kalman equalizer for MIMO frequency selective fading channels

We consider the Kalman filter for equalization of a multiple-input multiple-output (MIMO), frequency selective, quasi-static fading channel. More specifically, we consider a coded system, where the incoming bit stream is convolutionally encoded, interleaved and then spatially multiplexed across the transmit antennas. Each substream is modulated into M-ary symbols before being transmitted over a frequency selective channel. At the receiver, we propose to use the Kalman filter as a low complexity MIMO equalizer, as opposed to the trellis based maximum a-posteriori (MAP) equalizer whose computational complexity grows exponentially with the channel memory, the number of transmit antennas and the spectral efficiency (bits/s/Hz) of the system. We modify the structure of the Kalman filter and enable it to process the a-priori (soft) information provided by the channel decoder, thereby allowing us to perform iterative (turbo) equalization on the received sequence. The iterative equalizer structure is designed for general M-ary constellations. We also propose a low complexity version of the above algorithm whose performance is comparable to its full complexity counterpart, but which achieves a significant complexity reduction. We demonstrate via simulations that for higher order constellations, when sufficient number of receive antennas are available (e.g. for a 2 transmitter, 3 receiver system, QPSK), the performance of the proposed algorithms after 4 iterations is within 1.5 dB of the non-iterative MAP algorithm with close to an order of magnitude complexity reduction. By objectively quantifying the complexity of all the considered algorithms we show that the complexity reduction for the proposed schemes becomes increasingly significant for practical systems with moderate to large constellation sizes and a large number of transmit antennas     

Iterative receivers for multiuser space-time coding systems

Space-time coding (STC) techniques, which combine antenna array signal processing and channel coding techniques, are very promising approaches to substantial capacity increase in wireless channels. Multiuser detection techniques are powerful signal processing methodologies for interference suppression in CDMA systems. In this paper, by drawing analogies between a synchronous CDMA system and an STC multiuser system, we study the applications of some multiuser detection methods to STC multiuser systems. Specifically, we show that the so-called “turbo multiuser detection” technique, which performs soft interference cancellation and decoding iteratively, can be applied to STC multiuser systems in flat-fading channels. An iterative multiuser receiver and its projection-based variants are developed for both the space-time block coding (STBC) system and the space-time trellis coding (STTC) system. During iterations, extrinsic information is computed and exchanged between a soft multiuser demodulator and a bank of MAP decoders, to achieve successively refined estimates of the users' signals. Computer simulations demonstrate that the proposed iterative receiver techniques provide significant performance improvement over conventional noniterative methods in both single-user and multiuser STC systems. Furthermore, the performance of the proposed iterative multiuser receiver approaches that of the iterative single-user receiver in both STBC and STTC systems     

Belief Propagation over SISO/MIMO Frequency Selective Fading Channels

In this letter, we propose an iterative belief propagation (BP) channel detector (equalizer) over single-input single- output (SISO) and multiple-input multiple-output (MIMO) frequency selective fading channels as an alternative to the typically used maximum a-posteriori (MAP) or maximum likelihood (ML) detectors. The proposed detector has a parallel structure, resulting in fast hardware implementations. Moreover, BP detector is less complex than the MAP detector and it has a short decoding delay. We analyze the bit error rate and the mutual information and show that, over frequency selective fading channels, the proposed BP detector achieves a near-optimal performance, even in the presence of the length 4 cycles in the corresponding channel factor graph.     

Prefiltered space-time M-BCJR equalizer for frequency-selectivechannels

This paper addresses the problem of soft equalization for space-time-coded transmissions over frequency-selective fading channels. The structure of the space-time code is embedded in the channel impulse response for efficient joint equalization and decoding. The proposed equalization/decoding approach uses a prefilter to concentrate the effective channel power in a small number of taps followed by a reduced-complexity maximum a posteriori probability (MAP) equalizer/decoder to produce soft decisions. The prefilter introduces residual intersymbol interference which degrades the performance of MAP when applied to the trellis of the shortened channel. However, the shape of the overall shortened channel impulse response allows the M-algorithm to approximate the prefiltered MAP performance with a small number of states. Based on this general framework, we investigate several enhancements such as using different prefilters for the forward and backward recursions, concatenating two trellis steps during decoding, and temporal oversampling. The performance is evaluated through simulations over the EDGE typical urban channel     

Space-time trellis codes over rapid rayleigh fading channels with channel estimation?part ii: performance analysis and code design for non-identical channels

We consider the maximum likelihood (ML) receiver design, performance analysis and code design for space-time trellis codes (STTC) over non-identical, rapid fading channels with imperfect channel state information (CSI). The exact pairwise error probability (PEP) and PEP bounds for the ML receiver are obtained. A new code design criterion exploiting the statistical information of the channel estimates is proposed, which can minimize the performance loss caused by channel estimation error. New codes are obtained via an iterative search algorithm with reduced complexity. Under actual channel estimation conditions, our codes perform better than the existing codes in the literature which are designed on the assumption of identical channels, and perfect CSI at the receiver. More performance gain can be achieved by our codes when the degree of imbalance among the links is higher.     

An iterative receiver for turbo-coded pilot-assisted modulation infading channels

We introduce an iterative joint channel and data estimation receiver that exploits both the power of pilot-symbol assisted modulation (PSAM) and turbo coding for fading channels. The key innovation is a low-complexity soft channel estimator which divides a processing block into overlapped cells and performs maximum a posteriori (MAP) sequence estimation and MMSE filtering based on the received signal and extrinsic information delivered by the soft channel decoder. Simulation results show that for turbo-coded PSAM systems under time-variant fading the proposed receiver offers significant performance gains over a non-iterative receiver and two other cancellation schemes     

A robust adaptive DFE receiver for DS-CDMA systems under multipathfading channels

This paper presents a novel receiver design from signal processing viewpoint for direct-sequence code-division multiple access (DS-CDMA) systems under multipath fading channels. A robust adaptive decision-feedback equalizer (DFE) is developed by using optimal filtering technique via minimizing the mean-square error (MSE). The multipath fading channels are modeled as tapped-delay-line filters, and the tap coefficients are described as Rayleigh distributions in order to imitate the frequency-selective fading channel. Then, a robust Kalman filtering algorithm is used to estimate the channel responses for the adaptation of the proposed DFE receiver under the situation of partially known channel statistics. The feedforward and feedback filters are designed by using not only the estimated channel responses but the uncertainties and error covariance of channel estimation as well. As shown in the computer simulations, the proposed adaptive DFE receiver is robust against the estimation errors and modeling dynamics of the channels. Hence, it is very suitable for receiver design in data transmissions through multipath fading channels encountered in most wireless communication systems     

Joint Source and Space Time Decoding over Fading Channels

For high data rate communications, variable length codes (VLC) and multiple input multiple output (MIMO) techniques are required in the application layer and the physical layer, respectively. In this paper, we study the joint decoding for systems that consist of reversible VLC (RVLC) as the source codes and recursive space time trellis codes (STTC) as the coded modulation. The maximum a posteriori probability (MAP) decoding algorithm is modified to accommodate issues including the inseparable systematic information, the unsymmetric trellis structure, and information in both bit and symbol domains. Further, by converting extrinsic information based on the modulation mode and the mapping method, iterative information exchange can be performed so as to fully utilize the redundancy in both RVLC and recursive STTC. The performance of the proposed joint decoding is evaluated over both rapid fading and quasi- static flat fading channels, which shows significant improvement in coding gain in comparison with the non-iterative receiver.     

Low-complexity equalization for π/4 DQPSK signals based on themethod of projection onto convex sets

An equalizer adaptation technique for compensation of degradations caused by multipath Rayleigh fading channels to π/4 differential quadrature phase shift keying (DQPSK)-modulated signals is presented. The technique is applied to linear and nonlinear transversal-filter-type equalizers. It is based on the method of projection onto convex sets (POCS), realized in a particular form of the iterative least mean squares (LMS) procedure. The convergence speed of the proposed equalizer coefficient adaptation technique and its computational complexity depend on the newly introduced look-back parameter. Both can be tailored to the characteristics of the channel. For achieving convergence speeds comparable to speeds of recursive least squares (RLS) techniques, the computational load of the presented equalization is of the order of the load required of RLS techniques. However, its algorithmic implementation is notably simpler and its code and storage size requirements are smaller. The technique is numerically stable, and it is suitable for low-power implementations in digital signal processors or custom very large-scale integration (VLSI) circuits. Performed simulations verify good performance of the technique in various channel conditions for 900-MHz multipath fading radio channels     

Iterative multiuser detection for coded CDMA signals in AWGN andfading channels

A new iterative receiver for joint detection and decoding of code division multiple access (CDMA) signals is presented. The new scheme is based on a combination of the minimum mean square error (MMSE) criterion and the turbo processing principle by Hagenauer (see Proc. Int. Symp. Turbo Codes and Related Topics, Brest, France, p.1-9, 1997). The complexity of the new scheme is of polynomial order in the number of users. The new scheme is applicable to two situations: (a) when the receiver is capable of decoding the signals from all users and (b) when the receiver is only capable of decoding the signals from a subset of users. In the first scenario, we establish that the proposed receiver achieves superior performance to the iterative soft interference cancellation technique under certain conditions. On the other hand, in the second scenario, we argue that the proposed receiver outperforms both the iterative soft interference canceler and the iterative maximum a posteriori (MAP) receiver because of its superior near-far resistance. For operation over fading channels, the estimation of the complex fading parameters for all users becomes an important ingredient in any multiuser detector. In our scheme, the soft information provided by the decoders is used to enhance this estimation process. Two iterative soft-input channel estimation algorithms are presented: the first is based on the MMSE criterion, and the second is a lower-complexity approximation of the first. The proposed multiuser detection algorithm(s) are suitable for both terrestrial and satellite applications of CDMA     

Turbo Equalization with Prediction and Iterative Estimation of Time-Varying Frequency-Selective Channels

Turbo equalization that cooperates with channel prediction and iterative channel estimation is investigated for mobile wireless communications. Frames of information bits are encoded, interleaved, and mapped to symbols for transmission over time-varying frequency-selective fading channels. At the receiver, the Turbo equalizer consists of a maximum a posteriori probability equalizer/demapper and a soft-input soft-output maximum a posteriori probability decoder. With initial channel estimates and sparse pilot insertion across a number of frames, the receiver predicts the channel of the current frame. The effect of error propagation of channel prediction is mitigated by the de-interleaver that is embedded in the Turbo equalizer. The predicted and interpolated channel is refined through a channel estimator that uses the soft estimates of data symbols at each Turbo iteration. Due to the bandlimiting feature of channel variation, the channel estimation error can be smoothed by low-pass filters that follow the channel estimator. Simulation results show that incorporating Turbo equalization with channel prediction and iterative channel estimation can combat time- and frequency-selective fading and improve reception performance.     

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.      

Double turbo equalization of continuous phase modulation with frequency domain processing

In this paper, a doubly-iterative linear receiver, equipped with a soft-information aided frequency domain minimum mean-squared error (MMSE) equalizer, is proposed for the combined equalization and decoding of coded continuous phase modulation (CPM) signals over long multipath fading channels. In the proposed receiver architecture, the front-end frequency domain equalizer (FDE) is followed by the soft-input, softoutput (SISO) CPM demodulator and channel decoder modules. The receiver employs double turbo processing by performing back-end demodulation/decoding iterations per each equalization iteration to improve the a priori information for the front-end FDE. As presented by the computational complexity analysis and simulations, this process provides not only a significant reduction in the overall computational complexity, but also a performance improvement over the previously proposed iterative and noniterative MMSE receivers.     

Achieving Single-User Performance in an FEC-Coded DS-CDMA System for Frequency Selective and Flat Fading Channels

This paper presents a reduced-complexity soft-input soft-output trellis/tree multiuser equalizer for an iterative DS-CDMA system undergoing Rayleigh frequency selective fading. The algorithm first expands the equalizer-trellis to an equivalent trellis/tree structure. Then it applies the M-algorithm to the equivalent structure twice, once to reduce the number of states in the trellis and the other to reduce the number of branches emanating from each state. To compute soft-information, the algorithm utilizes not only those fully-extended paths reaching the end of the trellis but also paths that are traversed and discarded in the pruned trellis. Through a simple update-and-discard procedure, reliable soft-information is extracted from discarded paths which enables an extremely large trellis to be successfully decoded with modest complexity. BER performance is presented for a convolutional-coded DS-CDMA system employing random spreading sequences. Our results demonstrate that the proposed algorithm is capable of achieving single-user performance with a much reduced complexity. The proposed algorithm can also be applied to reduce the complexity of multiuser detection where the transmission channel is frequency flat. Single-user performance can also be achieved with the proposed technique.