Blind Channel Estimation Research Articles

A Novel Self-Pilot-Based Transmit-Receive Architecture for Multipath-Impaired UWB Systems

In the last few years, ultra-wideband (UWB) systems became an appealing technology for wireless communication applications. Unfortunately, when the transmission channel is affected by intersymbol interference (ISI), system performance of UWB systems equipped with receivers based on conventional matched filters presents error-floor phenomena. Aimed by these considerations, in this letter, we present a novel transmit-receive scheme allowing blind channel estimation and minimum mean-square error linear channel equalization. Essentially, the proposed scheme exploits a very short duration of the UWB pulse for achieving reliable blind deconvolution of the received signal. A nice feature of the resulting system is that blind deconvolution of the received signal is achieved without power and throughput losses. Simulation results support the effectiveness of the proposed scheme, and show that it is able to gain about 8 dB over current UWB receivers based on matched filtering on several test channels impaired by ISI.

A trellis-based technique for blind channel estimation and equalization

In this paper, we present a trellis-based blind channel estimation and equalization technique coupling two kinds of adaptive Viterbi algorithms. First, the initial blind channel estimation is accomplished by incorporating the list parallel Viterbi algorithm with the least mean square (LMS) updating approach. In this operation, multiple trellis mappings are preserved simultaneously and ranked in terms of path metrics. Equivalently, multiple channel estimates are maintained and updated once a single symbol is received. Second, the best channel estimate from the above operation will be adopted to set up the whole trellis. The conventional adaptive Viterbi algorithm is then applied to detect the signal and further update the channel estimate alternately. A small delay is introduced for the symbol detection and the decision feedback to smooth the noise impact. An automatic switch between the above two operations is also proposed by exploiting the evolution of path metrics and the linear constraint inherent in the trellis mapping. Simulation has shown an overall excellent performance of the proposed scheme in terms of mean square error (MSE) for channel estimation, robustness to the initial channel guess, computational complexity, and channel equalization.

Blind OFDM Channel Estimation Through Simple Linear Precoding

A novel approach of blind channel estimation for orthogonal frequency-division multiplexing (OFDM) systems is proposed. A linear transformation is applied on each block before it enters the OFDM system. The transform imposes a correlation structure on the transmitted blocks, which is exploited at the receiver to recover the channel via simple cross-correlation operations. The proposed approach is computationally simple and converges fast, which makes it a good candidate for estimation of fast-varying channels. Its performance is tested analytically, through a mean-square error analysis, and also via simulations. Results show that it compares favorably to the training-based scheme used in the IEEE 802.11a wireless standard.

Stochastic channel-adaptive rate control for wireless video transmission

In this paper, an empirically optimized channel-matched quantizer, and a joint stochastic-control based rate controller and channel estimator for H.261 based video transmission over a noisy channel is proposed. The rate controller adaptively learns to choose the correct channel matched quantizer using a stochastic learning algorithm. The stochastic automaton based learning algorithm aids in estimating the channel bit error rate based on a one bit feedback from the decoder. The algorithm is observed to converge to the optimal choice of the quantizer very quickly for various channel bit error probabilities and for different video sequences. When compared to traditional channel estimation schemes the proposed technique has several advantages. First, the proposed method results in a significant reduction in the delay and bandwidth requirement for channel estimation when compared to pilot symbol aided channel estimation schemes. Next, the stochastic learning algorithm used to estimate the channel bit error rate has simple computations. This makes it attractive for low power applications such as wireless video communications. This is in contrast to traditional blind channel estimation schemes that are computationally expensive, in general.

Blind Channel Estimation in Multicode CDMA Using Multiantenna Receiver

In this paper blind channel estimation methods for long code CDMA system with multicode transmission are proposed. By allocating multiple codes, higher data rates may be provided to a user. Blind channel estimation allows reducing pilot signaling. Hence, higher effective data rates may be achieved and larger sample support may be obtained by using both the information symbols and known pilot symbols for channel estimation. Algorithms are extended to multi-antenna receiver which further improves the performance. The performance of the algorithms is studied in extensive simulations using WCDMA system model. The effects of code selection, interference and noise, number of antennas, antenna correlation are considered using frequency selective channel models. The proposed methods are more robust in the face of interference and code selection than the well-known subspace method in \cite{WF99}. The computational complexity is lower as well.

STAR channel estimation in DS-CDMA communication systems

A novel blind DS-CDMA array channel estimator is presented which is capable of handling severe frequency-selective channels, where the multipath delay spread can be comparable with the data symbol period. By employing the concept of the spatiotemporal array (STAR) manifold, a subspace-type estimation algorithm is proposed, in conjunction with an one- dimensional temporal smoothing procedure, to jointly estimate the spatiotemporal multipath- channel parameters associated with the desired user. Close examination of the proposed STAR channel estimator reveals that it is 'near-far' resistant and the total number of signal paths can be more than the number of antenna elements. The effectiveness of the proposed approach is supported by computer simulation results.

Totally blind APP channel estimation for mobile OFDM systems

A new two-dimensional blind channel estimation scheme for coherent detection of orthogonal frequency-division multiplexing (OFDM) signals in a mobile environment is presented. The channel estimation is based on the a posteriori probability (APP) calculation algorithm. The time-variant channel transfer function is completely recovered without phase ambiguity with no need for any pilot or reference symbols, thus maximizing the spectral efficiency of the underlying OFDM system. The phase ambiguity problem is solved by using a 4-QAM (quadrature amplitude modulation) scheme with asymmetrical arrangement. The results clearly indicate that totally blind channel estimation is possible for virtually any realistic time-variant mobile channel.

Blind channel estimation in delay diversity for frequency selective channels

Delay diversity is an effective transmit diversity technique to combat adverse effects of fading. Thus far, previous work in delay diversity assumed that perfect estimates of current channel fading conditions are available at the receiver and training symbols are required to estimate the channel from the transmitter to the receiver. However, increasing the number of the antennas increases the required training interval and reduces the available time within which data may be transmitted. Learning the channel coefficients becomes increasingly difficult for the frequency selective channels. In this paper, with the subspace method and the delay character of delay diversity, a channel estimation method is proposed, which does not use training symbols. It addresses the transmit diversity for a frequency selective channel from a single carrier perspective in the form of a simple equivalent flat fading model. Monte Carlo simulations give the performance of channel estimation and the performance comparison of our channel-estimation-based detector with decision feedback equalization, which uses the perfect channel information.

A new method for channel estimation and data detection in the context of turbo equalisation

In this paper, we propose a new turbo equaliser which outputs marginal a-posteriori probabilities of each symbol. These marginal a-posteriori probabilities can be used directly by the decoder in the turbo process. We show how this equaliser is particularly interesting in the context of turbo decoding and also allows to perform blind channel estimation. We will finally show that this new method brings out significant improvements over the classixal Interference Canceller (lower SNR threshold or trigger point) with an acceptable computational cost.

Blind direct DFE estimation using multistep prediction

We propose a blind decision feedback equalizer (DFE) that is characterized by the fact that it does not require channel estimation. Because the output of the optimized multistep prediction error filter (PEF) can be represented as a product of the channel partial impulse response and the transmitted sequence, a backward multistep PEF can be used as the blind DFE feedforward filter. The corresponding feedback filter is obtained from the symbol-rate partial channel impulse response. The proposed algorithm has several advantages over existing blind channel estimation techniques, including stable performance without the necessity of exact channel order estimation.

Blind channel estimation for multicarrier systems with narrowband interference suppression

We present herein a novel blind channel estimator for multicarrier (MC) systems in the presence of unmodeled narrowband interference. A generalized multichannel minimum variance principle is invoked to design an equalizing filterbank that preserves desired signal components and suppresses the overall interference. While a channel estimate may be obtained by directly maximizing the filterbank output power through multidimensional nonlinear searches, such an approach is computationally prohibitive and suffers local convergence. To overcome this difficulty, we derive an asymptotically (in SNR) tight lower bound of the filterbank output power and use it for channel estimation, which reduces the problem to a quadratic minimization. Numerical examples show that the proposed scheme compares favorably with a subspace blind channel estimator in the presence of unknown narrowband interference.

Blind SOS subspace channel estimation and equalization techniques exploiting spatial diversity in OFDM systems

In this paper, we present second-order-statistics (SOS) subspace-based blind channel estimation techniques, which exploit the receive antenna diversity in each of the following situations: cyclic prefix-OFDM (CP-OFDM), zero padded-OFDM (ZP-OFDM), and bandwidth efficient-OFDM (BWE-OFDM) systems. We also propose a number of combinations of pre-FFT equalizer, post-FFT equalizer, zero-forcing (ZF) equalizer, and minimum-mean-square-error (MMSE) equalizer. For any number of receive antennas, the pre-FFT equalizers require only one FFT at the receiver. As a result, a considerable reduction in hardware complexity and power saving may be obtained especially for systems with higher number of sub-carriers. In contrast, post-FFT equalizers result in considerable reduction in processing complexity at the cost of one FFT for each antenna. Adaptive linear-complexity implementations of the proposed receivers are considered, along with some modifications in the presence of null side carriers. The effectiveness of the new techniques is demonstrated through simulations.

Blind channel order estimation based on second-order statistics

For many existing blind channel estimation algorithms, accurate estimates of the channel order are a prerequisite. A novel scheme for blind channel order estimation using exclusively second-order statistics of the received signal is proposed, which can be embedded in channel estimation and is based on the examination of an indicator function constructed from initial channel estimates with overestimated order. It is demonstrated that significantly better order estimates can be obtained than by information-theoretic criteria like the minimum description length criterion.

Space-Time Coded MC-CDMA: Blind Channel Estimation, Identifiability, and Receiver Design

Integrating the strengths of multicarrier (MC) modulation and code division multiple access (CDMA), MC-CDMA systems are of great interest for future broadband transmissions. This paper considers the problem of channel identification and signal combining/detection schemes for MC-CDMA systems equipped with multiple transmit antennas and space-time (ST) coding. In particular, a subspace-based blind channel identification algorithm is presented. Identifiability conditions are examined and specified which guarantee unique and perfect (up to a scalar) channel estimation when knowledge of the noise subspace is available. Several popular single-user based signal combining schemes, namely the maximum ratio combining (MRC) and the equal gain combining (EGC), which are often utilized in conventional single-transmit-antenna-based MC-CDMA systems, are extended to the current ST-coded MC-CDMA (STC-MC-CDMA) system to perform joint combining and decoding. In addition, a linear multiuser minimum mean square error (MMSE) detection scheme is also presented, which is shown to outperform the MRC and EGC at some increased computational complexity. Numerical examples are presented to evaluate and compare the proposed channel identification and signal detection/combining techniques.

Adaptive Transmitter Precoding for Time Division Duplex CDMA in Fading Multipath Channels: Strategy and Analysis

The recently developed blind adaptive techniques for multiuser detection in code division multiple access (CDMA) systems offer an attractive compromise of performance and complexity. However, the desire to further reduce complexity at the mobile unit has led to the investigation of techniques that move signal processing from the mobile unit to the base station. In this paper, we investigate transmitter precoding for downlink time division duplex (TDD) code division multiple access (CDMA) communications. In particular, we develop a linear minimum mean square error precoding strategy using blind channel estimation for fading multipath channels that allows for simple matched filtering at the mobile unit and is easy to make adaptive. We also present a performance analysis using tools developed for the analysis of conventional (receiver-based) linear blind multiuser detection in unknown channels. We compare the analytical and simulation results to traditional receiver-based blind multiuser detection. It is seen that transmitter precoding offers a reasonable alternative for TDD-mode CDMA when minimizing computational complexity at the mobile unit is a priority.

Subspace-based blind channel estimation for OFDM by exploiting virtual carriers

Reliable channel estimation is indispensable for orthogonal frequency-division multiplexing (OFDM) systems employing coherent detection and adaptive loading in order to achieve high data rate communications. Several options exist in practical OFDM systems-including training symbols, cyclic prefix, virtual carriers, pilot tones, and receiver diversity-to facilitate channel estimation. In this paper, a subspace blind channel estimation method based on exploiting the presence of virtual carriers is proposed for OFDM systems over a time-dispersive channel. The method can be applied to conventional OFDM systems with cyclic prefix as well as OFDM systems with no cyclic prefix. The reduction/elimination of cyclic prefix thereby provides the OFDM systems the potential to achieve higher channel utilization than most previously reported cyclic prefix based estimators. Sufficient channel identifiability condition is developed as well. Comparison with two other recently reported subspace methods is presented via computer simulations to support the effectiveness of the proposed method.

Matched filtering for CMA-based blind channel estimation

A novel blind matched filter receiver (MFR) is presented. The development depends on rearrangement of the optimum MFR and the use of the constant modulus algorithm (CMA) to estimate the matched filter. Using the blind MFR and CMA together, a novel blind channel estimation technique is presented.

Joint blind and semi-blind detection and channel estimation for space–time trellis coded modulation over fast faded channels

A method for decoding of space–time trellis coded modulation (STTCM) without a need to transmit separate training sequences is developed. The novel technique uses only a single initial estimate to acquire and track multiple-input multiple-output (MIMO) channels while performing STTCM detection. The technique is akin to blind trellis search techniques (per-survival processing, PSP) and adaptive Viterbi. The solution consists of the deployment of a bank of Kalman filters. The bank of Kalman filters is coupled with Viterbi-type decoders, which produce tentative decisions based on Kalman channel predictions. In return the bank of Kalman filters use the tentative decisions to update and track the MIMO channels corresponding to a number of tracked hypotheses. The proposed technique is applicable to space–time single carrier systems in rapidly fading environments, and also to space–frequency coded MIMO-OFDM.

A space-time channel estimator and single-user receiver for code-reuse ds-cdma systems

A blind asynchronous single-user code-reuse direct sequence code division multiple access (CDMA) array receiver is proposed for the uplink. By assigning each short PN-code more than once, code reuse allows the number of active users to be increased beyond the spreading gain. The proposed receiver is based on a blind single-code multipath joint space-time channel estimation technique that utilizes the concept of the spatio-temporal array manifold, in conjunction with a novel preprocessor, to deal with the multipath problem. From the estimated space-time channel parameters of a particular active code, the subset of parameters of a specific co-code user is then identified, and a single-user receiving weight vector is finally formed. The proposed approach is a subspace type method, and therefore, it is "near-far" resistant. Furthermore, in contrast to existing receivers such as the space-time decorrelating detector, the proposed receiver weight vector is tolerant to partial channel estimation errors and the incomplete estimation of channel parameters. The theoretical framework is supported by computer simulation studies.

On CDMA with space--time codes over multipath fading channels

We explore code-division multiple-access systems with multiple transmitter and receiver antennas combined with algebraic constellations over a quasi-static multipath fading channel. We first propose a technique to obtain transmit diversity for a single user over quasi-static fading channels by combining algebraic constellations with full spatial diversity and spreading sequences with good cross-correlation properties. The proposed scheme is then generalized to a multiuser system using the same algebraic constellation and different spreading sequences. We also propose a linear multiuser detector based on the combination of linear decorrelation with respect to all users, and the application of the sphere decoder to decode each user separately. Finally, we consider the generalization to multipath fading channels where the additional diversity advantage due to multipath is exploited by the sphere decoder, and a method of blind channel estimation based on subspace decomposition is examined.