Wavelet-based sequential Monte Carlo blind receivers in fading channels with unknown channel statistics

Recently, an adaptive Bayesian receiver for blind detection in flat-fading channels was developed by the present authors, based on the sequential Monte Carlo methodology. That work is built on a parametric modeling of the fading process in the form of a state-space model and assumes the knowledge of the second-order statistics of the fading channel. In this paper, we develop a nonparametric approach to the problem of blind detection in fading channels, without assuming any knowledge of the channel statistics. The basic idea is to decompose the fading process using a wavelet basis and to use the sequential Monte Carlo technique to track both the wavelet coefficients and the transmitted symbols. A novel resampling-based wavelet shrinkage technique is proposed to dynamically choose the number of wavelet coefficients to best fit the fading process. Under such a framework, blind detectors for both flat-fading channels and frequency-selective fading channels are developed. Simulation results are provided to demonstrate the excellent performance of the proposed blind adaptive receivers.     

Sampling-based soft equalization for frequency-selective MIMO channels

We consider the problem of channel equalization in broadband wireless multiple-input multiple-output (MIMO) systems over frequency-selective fading channels, based on the sequential Monte Carlo (SMC) sampling techniques for Bayesian inference. Built on the technique of importance sampling, the stochastic sampler generates weighted random MIMO symbol samples and uses resampling to rejuvenate the sample streams; whereas the deterministic sampler, a heuristic modification of the stochastic counterpart, recursively performs exploration and selection steps in a greedy manner in both space and time domains. Such a space-time sampling scheme is very effective in combating both intersymbol interference and cochannel interference caused by frequency-selective channel and multiple transmit and receiver antennas. The proposed sampling-based MIMO equalizers significantly outperform the decision-feedback MIMO equalizers with comparable computational complexity. More importantly, being soft-input soft-output in nature, these sampling-based MIMO equalizers can be employed as the first-stage soft demodulator in a turbo receiver for coded broadband MIMO systems. Such a turbo receiver successively improves the receiver performance through iterative equalization, channel re-estimation, and channel decoding. Finally, computer simulation results are provided to demonstrate the performance of the proposed sampling-based soft MIMO equalizers in both uncoded and turbo coded systems.     

Bayesian Monte Carlo multiuser receiver for space-time codedmulticarrier CDMA systems

We consider the design of optimal multiuser receivers for space-time block coded (STBC) multicarrier code-division multiple-access (MC-CDMA) systems in unknown frequency-selective fading channels. Under a Bayesian framework, the proposed multiuser receiver is based on the Gibbs sampler, a Markov chain Monte Carlo (MCMC) method for numerically computing the marginal a posteriori probabilities of different users' data symbols. By exploiting the orthogonality property of the STBC and the multicarrier modulation, the computational complexity of the receiver is significantly reduced. Furthermore, being a soft-input soft-output algorithm, the Bayesian Monte Carlo multiuser detector is capable of exchanging the so-called extrinsic information with the maximum a posteriori (MAP) outer channel code decoders of all users, and successively improving the overall receiver performance. Several practical issues, such as testing the convergence of the Gibbs sampler in fading channel applications, resolving the phase ambiguity as well as the antenna ambiguity, and adapting the proposed receiver to multirate MC-CDMA systems, are also discussed. Finally, the performance of the Bayesian Monte Carlo multiuser receiver is demonstrated through computer simulations     

Monte Carlo Bayesian Signal Processing for Wireless Communications

Many statistical signal processing problems found in wireless communications involves making inference about the transmitted information data based on the received signals in the presence of various unknown channel distortions. The optimal solutions to these problems are often too computationally complex to implement by conventional signal processing methods. The recently emerged Bayesian Monte Carlo signal processing methods, the relatively simple yet extremely powerful numerical techniques for Bayesian computation, offer a novel paradigm for tackling wireless signal processing problems. These methods fall into two categories, namely, Markov chain Monte Carlo (MCMC) methods for batch signal processing and sequential Monte Carlo (SMC) methods for adaptive signal processing. We provide an overview of the theories underlying both the MCMC and the SMC. Two signal processing examples in wireless communications, the blind turbo multiuser detection in CDMA systems and the adaptive detection in fading channels, are provided to illustrate the applications of MCMC and SMC respectively.     

A sequential Monte Carlo blind receiver for OFDM systems infrequency-selective fading channels

We consider the application of the sequential Monte Carlo (SMC) methodology to the problem of blind symbol detection in a wireless orthogonal frequency-division multiplexing (OFDM) system over a frequency-selective fading channel. Bayesian inference of the unknown data symbols in the presence of an unknown multipath fading channel is made only from the observations over one OFDM symbol duration. A novel blind SMC detector built on the techniques of importance sampling and resampling is developed for differentially encoded OFDM systems. The performance of different schemes of delayed-weight estimation methods is studied. Furthermore, being soft-input and soft-output in nature, the proposed SMC detector is employed as the first-stage demodulator in a turbo receiver for a coded OFDM system. Such a turbo receiver successively improves the receiver performance by iteratively exchanging the so-called extrinsic information with the maximum a posteriori (MAP) outer channel decoder. Finally, the performance of the proposed sequential Monte Carlo receiver is demonstrated through computer simulations     

Bayesian blind turbo receiver for coded OFDM systems with frequencyoffset and frequency-selective fading

The design of a blind receiver for coded orthogonal frequency-division multiplexing communication systems in the presence of frequency offset and frequency-selective fading is investigated. The proposed blind receiver iterates between a Bayesian demodulation stage and a maximum a posteriori channel decoding stage. The extrinsic a posteriori probabilities of data symbols are iteratively exchanged between these two stages to achieve successively improved performance. The Bayesian demodulator computes the a posteriori data symbol probabilities, based on the received signals (without knowing or explicitly estimating the frequency offset and the fading channel states), by using Markov chain Monte Carlo (MCMC) techniques. In particular, two MCMC methods-the Metropolis-Hastings algorithm and the Gibbs sampler-are studied for this purpose. Computer simulation results show that the proposed Bayesian blind turbo receiver can achieve good performance and is robust against modeling mismatch     

Maximum likelihood decoding of uncoded and coded PSK signalsequences transmitted over Rayleigh flat-fading channels

The problem of maximum likelihood (ML) detection for uncoded and coded M-PSK signals on Rayleigh fading channels is investigated. It is shown that, if the received signal is sampled at baud-rate, a ML receiver employing per-survivor processing can be implemented. The error rate performance of this receiver is evaluated by means of computer simulations and its limitations are discussed. In addition, it is shown that, on a fast fading channel, the error floor in the BER curve can be appreciably lowered if more than one received signal sample per symbol interval is processed by the receiver algorithm, Finally, a sub-optimum two-stage receiver structure for interleaved coded PSK systems is proposed. Its error rate performance is assessed for simple trellis-coded modulation schemes and compared to that provided by other receiver structures     

Blind detection in MIMO systems via sequential Monte Carlo

We provide a novel sequential estimation and detection approach for multiple-input-multiple-output (MIMO) systems. The basic idea is to design a probabilistic approximation method for the computation of the maximum a posterior distribution (MAP) via the sequential Monte Carlo methods (SMC). The SMC method has two advantages over the other methods in that it is a blind method and can be computed in parallel. Furthermore, the SMC has characteristics of soft-input and soft-output in nature and, thus, it can be employed as the first stage demodulator in a turbo receiver for a coded MIMO system. Such a turbo receiver successively improves the receiver performance by iteratively exchanging the so-called extrinsic information with the MAP outer channel decoder. Finally, the performance of the proposed sequential Monte Carlo receiver is demonstrated through computer simulations for MIMO systems over single-path and multipath fading channels.     

A Bayesian Multiuser Detection Algorithm for MIMO-ODFM Systems Affected by Multipath Fading, Carrier Frequency Offset, and Phase Noise

We derive a novel Bayesian algorithm for multiuser detection in the uplink of a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system employing stacked space-time block codes, such as the stacked Alamouti code with two transmit antennas, and a stacked quasi-orthogonal code with four transmit antennas. The proposed technique accomplishes joint estimation of the carrier frequency offset, phase noise, channel impulse response and data of each active user. Its derivation relies on the specific structure of the transmitted signal and on efficient Markov chain Monte Carlo (MCMC) methods. Simulation results evidence the robustness of the proposed algorithm in both uncoded and coded systems.     

Maximum-likelihood differential detection of uncoded and trelliscoded amplitude phase modulation over AWGN and fading channels-metricsand performance

This paper derives metrics for maximum-likelihood differential detection of uncoded and trellis coded MPSK and QAM transmitted over Rayleigh and Rician fading channels. Receiver structures based on these metrics are proposed and their error probability performance analyzed and/or simulated. The results represent a generalization of the notion of multiple symbol differential detection, previously introduced by the authors for MPSK over an AWGN, to the fading channel and other modulations. For the coded cases, ideal interleaving/deinterleaving is assumed and furthermore the presence or absence of channel state information. An interesting side result is that for a constant envelope modulation transmitted over a fading channel with unknown but rapidly-varying phase error (the other extreme to the slowly-varying phase error case normally assumed for differential detection), under certain practical assumptions, it is shown that the optimum receiver is of the limiter-discriminator type     

Multisampling receivers for uncoded and coded PSK signal sequencestransmitted over Rayleigh frequency-flat fading channels

An algorithm, based on previous work [Vitetta and Taylor 1994, 1995], for the detection of coded and uncoded PSK sequences transmitted on a frequency-flat fading channel is investigated. It is based on the Viterbi algorithm and processes more than one signal sample per signaling interval. Its performance is evaluated by means of computer simulations for both uncoded and coded systems     

Double-filtering receivers for PSK signals transmitted overRayleigh frequency-flat fading channels

This paper describes novel detection algorithms for coded and uncoded M-ary phase shift keying (M-PSK) signals transmitted over frequency-flat fading channels. Fading distortion is estimated with per-survivor methods using the sampled outputs of two receive filters. Some of the proposed algorithms do not require information on the fading statistics and are dubbed blind algorithms. The error rate performance of blind and nonblind algorithms is assessed by simulation for uncoded and trellis-coded phase shift keying (PSK) and is compared to the performance of other detection schemes proposed in the literature     

Fast convergent monte carlo receiver for OFDM systems

The paper investigates the problem of the design of an optimal Orthogonal Frequency Division Multiplexing (OFDM) receiver against unknown frequency selective fading. A fast convergent Monte Carlo receiver is proposed. In the proposed method, the Markov Chain Monte Carlo (MCMC) methods are employed for the blind Bayesian detection without channel estimation. Meanwhile, with the exploitation of the characteristics of OFDM systems, two methods are employed to improve the convergence rate and enhance the efficiency of MCMC algorithms.One is the integration of the posterior distribution function with respect to the associated channel parameters, which is involved in the derivation of the objective distribution function; the other is the intra-symbol differential coding for the elimination of the bimodality problem resulting from the presence of unknown fading channels. Moreover, no matrix inversion is needed with the use of the orthogonality property of OFDM modulation and hence the computational load is significantly reduced. Computer simulation results show the effectiveness of the fast convergent Monte Carlo receiver.     

“Turbo DPSK”: iterative differential PSK demodulationand channel decoding

Multiple symbol differential detection is known to fill the gap between conventional differential detection of MPSK (M-DPSK) and coherent detection of M-PSK with differential encoding (M-DEPSK). Emphasis has been so far on soft-input/hard-output detectors applied in uncoded systems. In this paper, we investigate a receiver structure suitable for coded DPSK signals on static and time-varying channels. The kernel is an a posteriori probability (APP) DPSK demodulator. This demodulator accepts a priori information and produces reliability outputs. Due to the availability of reliability outputs, an outer soft-decision channel decoder can be applied. Due to the acceptance of a priori information, if the outer channel decoder also outputs reliability information, iterative (“turbo”) processing can be done. The proposed “APP DPSK demodulator” uses linear prediction and per-survivor processing to estimate the channel response. The overall transmission scheme represents a type of serial “turbo code,” with a differential encoder concatenated with a convolutional code, separated by interleaving. The investigated system has the potential to improve the performance of coherent PSK without differential encoding and perfect channel estimation for fading cases! Only a small number of iterations are required. The receiver under investigation can be applied to several existing standards without changing the transmission format. Results are presented for uncoded and convolutionally coded 4-DPSK modulation transmitted over the Gaussian channel and the Rayleigh flat-fading channel, respectively     

Effects of LDPC Code on the BER Performance of MPSK System with Imperfect Receiver Components over Rician Channels

In this letter, we study the influence of receiver imperfections on bit error rate (BER) degradations in detecting low‐density parity‐check coded multilevel phase‐shift keying signals transmitted over a Rician fading channel. Based on the analytical system model which we previously developed using Monte Carlo simulations, we determine the BER degradations caused by the simultaneous influences of stochastic phase error, quadrature error, in‐phase‐quadrature mismatch, and the fading severity.     

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     

非频率选择性衰落MIMO信道上基于序列蒙特卡罗的数字调制识别方法

该文针对非频率选择性衰落多输入多输出(MIMO)信道提出了一种基于序列蒙特卡罗(SMC)方法的幅度-相位调制方式识别方法。首先将MIMO系统等效为一个动态状态空间模型,然后利用序列重要性采样和模式转移步骤估计每根发送天线采用的各种可能调制方式的概率,最后利用各个信道上发送符号的不相关性在长为N的观测信道上进行噪声平均。该方法能够在识别数字调制方式的同时估计发送数据符号。其复杂度是信道观测长度、发送天线数、采样大小、调制星座大小的线性函数。仿真结果表明提出的数字调制识别方法在各种调制星座上具有良好的性能。     

Maximum likelihood sequence estimation of differentially encoded PSK signals transmitted over Rayleigh frequency-flat fading channels

The problem of maximum likelihood (ML) detection of differentially encodedM-PSK signals on Rayleigh fading channels is investigated. It is shown that the solution to this problem can be easily related to previous results [1] and leads to the implementation of a receiver structure based on the Viterbi algorithm and employing per-survivor processing. The error rate performance of this receiver is evaluated by means of computer simulations for both coded and uncoded systems.     

Performance of Adaptive Transmission for FH/MFSK Signaling Over Jammed Fading Channels

This paper gives an evaluation of the performance of adaptive signaling techniques for jammed fading channels. These techniques perform remarkably well for fading channels with AWGN. The performance of both uncoded and coded systems is examined in the presence of jamming. Adaptive signaling schemes are shown to offer little improvement for uncoded antijam systems. However, for coded antijam systems, they provide improvements in the performance and, in some cases, simplify the receiver implementation.     

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