Bayesian techniques for blind deconvolution

This paper introduces extended Bayesian filters (EBFs), a new family of blind deconvolution filters for digital communications. The blind deconvolution problem is formulated as a nonlinear and non-Gaussian fixed-lag minimum mean square error filtering problem, and the EBF is derived as a suboptimal recursive estimator. The model-based setting makes extensive use of the transmitted symbol and noise distributions. A key feature of the EBF is that the filter lag can be chosen to be larger than the channel length, while the complexity is exponential in a parameter which is typically chosen to be smaller than both the channel length and the filter lag. Extensive simulations characterizing the performance of EBFs in severe intersymbol interference channels are presented. The fast convergence and robust equalization of the EBFs are demonstrated for uncoded linearly modulated signals [e.g., differentially encoded quaternary phase shift keying (QPSK)] transmitted over unknown channels. Comparisons are made to other blind symbol-by-symbol demodulation algorithms. The results show that the EBF provides much better performance (at increased complexity) compared to the constant modulus algorithm and the extended Kalman filter, and achieves a better performance-complexity trade-off than other Bayesian demodulation algorithms. The simulations also show that the EBF is applicable with large constellations and shaped modulations     

Bayesian decision feedback techniques for deconvolution

There has been great interest in reduced complexity suboptimal MAP symbol-by-symbol estimation for digital communications. We propose a new suboptimal estimator suitable for both known and unknown channels. In the known channel case, the MAP estimator is simplified using a form of conditional decision feedback, resulting in a family of Bayesian conditional decision feedback estimators (BCDFEs); in the unknown channel case, recursive channel estimation is combined with the BCDFE. The BCDFEs are indexed by two parameters: a “chip” length and an estimation lag. These algorithms can be used with estimation lags greater than the equivalent channel length and have a complexity exponential in the chip length but only linear in the estimation lags. The BCDFEs are derived from simple assumptions in a model-based setting that takes into account discrete signalling and channel noise. Extensive simulations characterize the performance of the BCDFE and BCDPE for uncoded linear modulations over both known and unknown (nonminimum phase) channels with severe ISI. The results clearly demonstrate the significant advantages of the proposed BCDFE over the BCDFE in achieving a desirable performance/complexity tradeoff. Also, a simple adaptive complexity reduction scheme can be combined with the BCDFE resulting in further substantial reductions in complexity, especially for large constellations. Using this scheme, we demonstrate the feasibility of blind 16QAM demodulation with 10^-4 bit error probability at E _b/N₀≈ 18.5 dB on a channel with a deep spectral null     

Information-Bearing Noncoherently Modulated Pilots for MIMO Training

In this correspondence, we deal with noncoherent communications over multiple-input-multiple-output (MIMO) wireless links. For a Rayleigh flat block-fading channel with M transmit- and N receive-antennas and a channel coherence interval of length T, it is well known that for TGtM, or, at high signal-to-noise-ratio (SNR) rhoGt1 and Mlesmin{N,lfloorT/2rfloor}, unitary space-time modulation (USTM) is capacity-achieving, but incurs exponential demodulation complexity in T. On the other hand, conventional training-based schemes that rely on known pilot symbols for channel estimation simplify the receiver design, but they induce certain SNR loss. To achieve desirable tradeoffs between performance and complexity, we propose a novel training approach where USTM symbols over a short length T_tau(tau is a small fraction of T, and recovers part of the SNR loss experienced by the conventional training-based schemes. When rhorarrinfin and TgesT_tau ges2M=2Nrarrinfin, but the ratios alpha=M/T, alpha₁ =T_tau/T are fixed, we obtain analytical expressions of the asymptotic SNR loss for both the conventional and new training-based approaches, serving as a guideline for practical designs     

A novel correlation adaptive receiver structure for high speed transmissions in ultra wide band systems with realistic channel estimation

Impulse radio ultra wide band (UWB) communications require robust receivers; typically Rake receivers are required to capture a large number of resolvable paths, (even hundred of paths), so large number of correlators are needed; otherwise, adaptive receivers use complex filters and channel estimation algorithms. Therefore, traditional Impulse radio receivers demand non-practical implementation structures. In this paper we propose a novel correlation-adaptive receiver structure with low complexity for indoor high speed ultra wide band systems. This novel structure combines correlation characteristics from Rake receivers with recursive filters from adaptive receivers. The receiver includes a low complexity recursive channel estimation filter capable of estimating hundreds of channel impulse responses, and a single filter-correlation filter used for coherent bit demodulation. Furthermore, we derive by simulations the bit error rate for high density multipath environments for several impulse radio modulations like TH-PPM, DS-BPSK and TH-BPSK and we compare the performance of the proposed structure with typical Rake receivers.     

A Practical Optimization Approach for QPSK/TDMA Satellite Channel Filtering

This paper reports the results of computer and laboratory hardware simulation studies concerning optimum pulseshaping filter characteristics and configurations to be employed with conventional QPSK signaling in a nonlinear channel. An understanding of the factors and issues contributing to transmission impairments was obtained through an initial hardware simulation which was confirmed and extended with computer simulation. Based on this understanding, the critical characteristics of the channel pulseshaping transmit and receive filters were determined, promising filter candidates were implemented, and a complete system laboratory hardware simulation study was configured to evaluate the candidate filters using an INTELSAT IV satellite. This study emphasizes the performance tradeoff between the nonlinear channel-induced bit-error-rate impairment and the adjacent channel interference levels caused by HPA spectrum regeneration of filtered QPSK as a function of filter configuration. The results show that a more gentle rolloff Nyquist or wider bandwidth non-Nyquist transmit filter produces similar significantly improved performance compared to a conventional sharp rolloff Nyquist transmit filter in nonlinear satellite channels. For the wider non-Nyquist filter case, employing a Nyquist filter at the demodulation also benefits performance.     

Bayesian sequential state estimation for MIMO wireless communications

This paper explores the use of particle filters, rooted in Bayesian estimation, as a device for tracking statistical variations in the channel matrix of a narrowband multiple-input, multiple-output (MIMO) wireless channel. The motivation is to permit the receiver to acquire channel state information through a semiblind strategy and thereby improve the receiver performance of the wireless communication system. To that end, the paper compares the particle filter as well as an improved version of the particle filter using gradient information, to the conventional Kalman filter and mixture Kalman filter with two metrics in mind: receiver performance curves and computational complexity. The comparisons, also including differential phase modulation, are carried out using real-life recorded MIMO wireless data.     

The design and operation of practical charge-transfer transversal filters

Some of the design considerations for charge-transfer split-electrode transversal filters are discussed. Clock frequency, filter length, and chip area are important design parameters. The relationship of these parameters to filter performance and accuracy is described. Both random and tap weight quantization errors are considered, and the optimum filter length is related to tap weight error. A parallel charge-transfer channel, which balances both capacitance and background charge, and a coupling diffusion between split electrodes greatly improves accuracy. A one-phase clock is used to simplify the readout circuitry. Two off-chip readout circuits are described, and the performance of two low-pass filters using these readout circuits is given. Signal to noise ratios of 90 dB/kHz and an overall linearity of 60 dB have been achieved with this readout circuitry.     

The design and operation of practical charge-transfer transversal filters

Some of the design considerations for charge-transfer split-electrode transversal filters are discussed. Clock frequency, filter length, and chip area are important design parameters. The relationship of these parameters to filter performance and accuracy is described. Both random and tap weight quantization errors are considered, and the optimum filter length is related to tap weight error. A parallel charge-transfer channel, which balances both capacitance and background charge, and a coupling diffusion between split electrodes greatly improves accuracy. A one-phase clock is used to simplify the readout circuitry. Two off-chip readout circuits are described, and the performance of two low-pass filters using these readout circuits is given. Signal to noise ratios of 90 dB/kHz and an overall linearity of 60 dB have been achieved with this readout circuitry.     

Globally convergent adaptive IIR filters based on fixed polelocations

A new class of adaptive filters, dubbed fixed pole adaptive filters (FPAF's), is introduced. These adaptive filters have infinite impulse responses, yet their adaptation exhibits provable global convergence. Good filter performance with a relatively small number of adapted parameters is permitted by the new filter structure, thus reducing the computational burden needed to implement adaptive filters. The implementation and computational complexity of the FPAF is described, and its modeling capabilities are determined. Excitation conditions on the filter input are established that guarantee global convergence of a standard set of adaptive algorithms. Some methods are described for selecting the fixed pole locations based on a priori information regarding the operating environment of the adaptive filter. The FPAF is tailored to applications by such a procedure, enabling improved performance. In examples, the FPAF is shown to achieve a smaller minimum mean square error, given an equal number of adapted parameters, in comparison with adaptive FIR filters and adaptive filters based on Laguerre and Kautz models     

Gaussian particle filtering

Sequential Bayesian estimation for nonlinear dynamic state-space models involves recursive estimation of filtering and predictive distributions of unobserved time varying signals based on noisy observations. This paper introduces a new filter called the Gaussian particle filter. It is based on the particle filtering concept, and it approximates the posterior distributions by single Gaussians, similar to Gaussian filters like the extended Kalman filter and its variants. It is shown that under the Gaussianity assumption, the Gaussian particle filter is asymptotically optimal in the number of particles and, hence, has much-improved performance and versatility over other Gaussian filters, especially when nontrivial nonlinearities are present. Simulation results are presented to demonstrate the versatility and improved performance of the Gaussian particle filter over conventional Gaussian filters and the lower complexity than known particle filters.     

Block demodulation of MDPSK with low complexity

A new block demodulation (NBD) of MDPSK with low complexity is proposed. The error patterns of conventional differential detection (CDD) are analysed, and the decisions of CDD and the knowledge of error patterns are employed to reduce the complexity of optimum block demodulation (OBD). The complexity of NBD increases in a roughly linear fashion with block length N, while OBD increases exponentially with N. Simulations show almost the same performance     

Universal Filtering Via Hidden Markov Modeling

The problem of discrete universal filtering, in which the components of a discrete signal emitted by an unknown source and corrupted by a known discrete memoryless channel (DMC) are to be causally estimated, is considered. A family of filters are derived, and are shown to be universally asymptotically optimal in the sense of achieving the optimum filtering performance when the clean signal is stationary, ergodic, and satisfies an additional mild positivity condition. Our schemes are comprised of approximating the noisy signal using a hidden Markov process (HMP) via maximum-likelihood (ML) estimation, followed by the use of the forward recursions for HMP state estimation. It is shown that as the data length increases, and as the number of states in the HMP approximation increases, our family of filters attains the performance of the optimal distribution-dependent filter. An extension to the case of channels with memory is also established.     

Adaptive joint multiuser detection and channel estimation in multipath fading CDMA channels

The problem of joint multiuser detection and channel estimation in frequency-selective Rayleigh fading CDMA channels is considered. First the optimal multiuser detector for such channels is derived, which is seen to have a computational complexity exponential in the product of the number of users and the length of the transmitted data sequence. Two suboptimal detectors are then developed and analyzed, both of which employ decorrelating filters at the front-ends to eliminate the multiple-access interference and the multipath interference. The symbol-by-symbol detector uses a Kalman filter and decision feedback to track the fading channel for diversity combining. The per-survivor sequence detector is in the form of the Viterbi algorithm with the trellis updates being computed by a bank of Kalman filters in the per-survivor fashion. Both suboptimal detectors require the knowledge of all waveforms of all users in the channel and the channel fading model parameters. Adaptive versions of these suboptimal detectors that require only the knowledge of the waveform of the user of interest are then developed. The adaptive receivers employ recursive-least-squares (RLS) minimum-mean-square-error (MMSE) filters at the front-end to mitigate the interference, and use a bank of linear predictors to track the fading channels. It is shown that the front-end RLS-MMSE filters can be implemented using systolic arrays to exploit massively parallel signal processing computation, and to achieve energy efficiency. Finally, the performance of the suboptimal detectors and their adaptive versions are assessed by simulations. This revised version was published online in July 2006 with corrections to the Cover Date.     

Soft-Output Demodulation on Frequency-Selective Rayleigh Fading Channels Using AR Channel Models

This paper is a study of high-performance soft-output demodulation for slow or moderate frequency-selective and flat Rayleigh fading using an autoregressive (AR) channel model. For channel taps modeled as AR processes, the discrete-time-equivalent channel model is derived for a matched filter (matched to the transmit pulse) and symbol rate-sampled receiver front end. The optimum symbol-by-symbol demodulator is then derived and shown to consist of a joint data and Kalman filter (KF) channel estimator. Additionally, a symbol-by-symbol demodulator with an extended KF is proposed that jointly identifies and tracks the channel and the unknown parameters in AR channel models. A simulation study shows that the proposed algorithms offer significant advantages in performance or complexity compared to several previously proposed algorithms. The algorithms do not exhibit a significant error floor, provide soft-output metrics needed for interleaved coded modulation, provide high performance with a blind initialization, are capable of blind operation with fast acquisition though compatible with pilot-symbol-assisted modulation, and are robust to parameter mismatch.     

Soft output interference suppression in TDMA wireless communications

We present a novel symbol-by-symbol Bayesian multiuser detector for cochannel interference cancellation in TDMA cellular communications. To begin with, we present the usual composite signal model consisting of the desired signal, interferer, channel parameters and channel noise. Then, we derive the soft output interference cancellation algorithm (SICA) to compute fixed-lag maximum a posteriori (MAP) estimates of the data symbols of the desired user, using a fixed lookahead of D observations. In the process, the interferer symbols are treated as nuisance parameters and averaged out. The complexity of the SICA is exponential in the length of the combined channel at the receiver. Subsequently, we present a simple, yet effective, technique for complexity reduction without significant performance degradation. We apply the algorithm to some typical scenarios, using the IS-136 TDMA standard, to demonstrate its interference suppression capabilities. In this paper, we assume that all relevant channel parameters are known. Hence, our results should be viewed as representing the best possible performance that can be obtained with the SICA in the scenarios considered. This revised version was published online in July 2006 with corrections to the Cover Date.     

Modified Metaheuristic Algorithms for the Optimal Design of Multiplier-Less Non-uniform Channel Filters

Reconfigurable non-uniform channel filters are now being widely used in software define radio (SDR). The hardware implementation of these filters requires low complexity, low chip area and low power consumption. The frequency response masking (FRM) approach is proved to be a good candidate for the realization of a sharp digital finite impulse response (FIR) filter with low complexity. To reduce the complexity further, this paper gives an optimal design method which makes the channel filters totally multiplier-less. This is done in two steps. The channel filters are designed using the FRM approach with continuous filter coefficients. To obtain multiplier-less design, these filter coefficients are converted to finite-precision coefficients using signed power of two (SPT) space and the filter coefficients are synthesized in the canonic signed-digit (CSD) format. But this may lead to degradation of the filter performance. Hence the filter coefficients synthesis in the CSD format is formulated as an optimization problem. Several meta-heuristic algorithms like Differential Evolution (DE), Artificial Bee Colony (ABC), Harmony Search Algorithm (HSA) and Gravitational Search Algorithm (GSA) are modified and deployed and the best one is selected.     

A simple and efficient design of variable fractional delay FIR filters

In this paper, a simple and efficient approach for designing one-dimensional variable fractional delay finite impulse response digital filters is proposed. Two matrix equations, based respectively on the weighted least-squares function of the optimum fixed fractional delay filter and the filter coefficient polynomial fitting, are formulated in tandem to form the design algorithm, which only has the computation complexity comparable with that of designing fixed finite impulse response digital filters. A design example is also given to justify the effectiveness and advantages of the proposed design method.     

基于粒子滤波算法的DS-CDMA多用户检测

粒子滤波算法是一种基于贝叶斯估计的蒙特卡罗方法,尤其适用于处理非线性、非高斯系统的状态估计问题。该算法应用于DS-CDMA系统的多用户检测中,检测器能在检测性能和计算复杂度之间取得很好的平衡。基于粒子滤波算法的多用户检测器在性能上逼近于最优多用户检测器,而计算复杂度远低于最优多用户检测器,与次优多用户检测器相当。利用白化匹配滤波器的输出可以建立同步DS-CDMA系统的状态空间方程,使得粒子滤波算法应用于多用户检测中。仿真实例证明了基于粒子滤波算法的多用户检测器在等功率和远近效应的情况下的性能优势。     

A family of pulse-shaping filters with ISI-free matched andunmatched filter properties

The raised-cosine pulse-shaping filter plays an important role in digital communications due to its intersymbol interference (ISI)-free property. The ISI-free property holds after matched filtering is performed. In this letter, we propose a new family of pulse-shaping filters. These filters are ISI free with or without matched filtering. Using these new pulse-shaping filters, the computational load, and therefore the hardware cost in demodulation for modem design, might be reduced in some applications