A blind channel estimation and equalisation scheme is given for orthogonal frequency-division multiplexing systems with unmodelled interference. The approach uses a generalised multichannel minimum variance principle to design an equalising filterbank that preserves the desired signal components and suppresses the overall interference. A channel estimate is then obtained by deriving an asymptotically tight lower bound of the filterbank output power, which reduces the problem to a quadratic minimisation. By imposing a special structure on the received signal, the performance is shown to be significantly increased. To assess the performance of the proposed scheme, an unconditional Cramér–Rao bound (CRB) is derived which, similar to the proposed blind channel estimator, does not assume knowledge of the transmitted information symbols. The CRB serves as a lower bound for all unbiased blind channel estimation schemes. Numerical examples show that the proposed scheme approaches the CRB as the SNR increases. It also exhibits low sensitivity to unknown narrowband interference and compares favourably with a subspace blind channel estimator.

Multiuser detection (MUD) for code-division multiple-access (CDMA) systems usually relies on some a priori channel estimates, which are obtained either blindly or by using training sequences, and the covariance matrix of the received signal, usually replaced by the sample covariance matrix. However, such prior estimates are often affected by errors that are typically ignored in subsequent detection. In this paper, we present robust channel estimation and MUD techniques for multicarrier (MC) CDMA by explicitly taking into account such estimation errors. The proposed techniques are obtained by optimizing the worst case performance over two bounded uncertainty sets pertaining to the two types of estimation errors. We show that although the estimation errors associated with the prior channel estimate and the sample covariance matrix are generally not bounded, it is beneficial to optimize the worst case performance over properly chosen bounded uncertainty sets determined by a parameter called bounding probability. At a slightly higher computational complexity, our proposed robust detectors are shown to yield improved performance over the standard detectors that ignore the prior estimation errors.

In this paper, we present a blind code-timing estimator for asynchronous code-division multiple-access (CDMA) systems that use bandlimited chip waveforms. The proposed estimator first converts the received signal to the frequency domain, followed by a frequency deconvolution to remove the convolving chip waveform, and then calculates the code-timing estimate from the output of a narrowband filter with a sweeping center frequency, which is designed to suppress the overall interference in the frequency domain. The proposed estimator is near-far resistant, and can deal with time- and frequency-selective channel fading. It uses only the spreading code of the desired user, and can be adaptively implemented for both code acquisition and tracking. We also derive an unconditional Crame/spl acute/r-Rao bound (CRB) that is not conditioned on the fading coefficients or the information symbols. It is a more suitable lower bound than a conditional CRB for blind code-timing estimators which do not assume knowledge of the channel or information symbols. We present numerical examples to evaluate and compare the proposed and several other code-timing estimators for bandlimited CDMA systems.

In this paper, we present a deterministic multiuser code-timing estimator for asynchronous direct-sequence (DS) code-division multiple-access (CDMA) systems with aperiodic long spreading codes and bandlimited chip waveforms. A key feature of the proposed estimator is that it captures and capitalizes on a deterministic structure of the overall interference, namely multi-access interference (MAI) and inter-symbol interference (ISI), in the frequency domain. This allows complete interference elimination in a deterministic manner, which is in general more effective and data-efficient than stochastic approaches. Numerical results show that the proposed estimator can achieve fast acquisition; it is also near-far resistant, providing accurate code acquisition for even overloaded systems (i.e., systems with more users than the processing gain) in multipath fading environments.

In this paper, we present a novel code-timing estimator for uplink asynchronous direct-sequence code-division multiple-access systems utilizing bandlimited chip waveforms. The proposed estimator requires only the spreading code and training of the desired user. We start from a maximum likelihood (ML) approach that models the intersymbol interference and multiple-access interference as a colored Gaussian process with unknown covariance matrix in the frequency domain. The exact ML estimator is highly nonlinear and requires iterative searches over multi-dimensional parameter space that is impractical to implement. To deal with this difficulty, we invoke asymptotic (large-sample) approximations of the ML criterion and reparameterization techniques, which lead to an asymptotic ML estimator that yields code-timing and channel estimates via efficient noniterative quadratic optimizations. To benchmark the proposed estimator, we provide Crame/spl acute/r-Rao bound analysis for the code-timing estimation problem. Numerical simulation results are presented, which show that the proposed scheme is resistant to interference, fading, and modeling errors (e.g., sampling position errors), and compares favorably to several competing schemes in multipath fading channels.

In this paper, we present a code-timing estimation scheme for asynchronous direct-sequence (DS) code-division multiple-access (CDMA) systems with aperiodic (long) spreading codes and bandlimited chip waveforms. The proposed scheme first converts the observed signal to the frequency domain by fast Fourier transform (FFT). Then, a nonlinear least-squares (NLS) criterion is invoked to fit the unknown parameters to the frequency-domain data. While the exact minimizer of the NLS criterion requires computationally prohibitive searches over a multidimensional parameter space, we propose an efficient approach that iteratively estimates one user/path at a time via simple linear processing and, furthermore, combines successive interference suppression (SIC) with parameter re-estimation for improved code acquisition performance. Simulation results show that the proposed scheme achieves a significantly larger user capacity and faster acquisition time than the SIC and standard matched-filter based code acquisition techniques in time-varying fading channels.

In this paper, we present a novel code-timing estimation for asynchronous direct-sequence (DS) code-division multiple-access (CDMA) systems utilizing bandlimited chip waveforms. We start from a maximum likelihood (ML) approach that model the inter-symbol interference (ISI) and multiple-access interference (MAI) as a colored Gaussian process with unknown covariance matrix in the frequency domain. The exact ML estimator is highly nonlinear and requires iterative searches over multidimensional parameter space that is impractical to implement. To deal with this difficulty, we invoke asymptotic approximations of the ML criterion and reparameterization techniques, which lead to an asymptotic ML estimator that yields code-timing and channel estimates via efficient non-iterative quadratic optimizations. To benchmark the proposed estimator, we provide Cramer-Rao bound (CRB) analysis for the code-timing estimation problem. Numerical simulation results are presented to illustrate the performance of the proposed code-timing estimator for bandlimited CDMA in multipath fading channels.

In this paper, we present a blind code-timing estimator for asynchronous DS (direct-sequence) CDMA (code-division multiple-access) systems. that utilize bandlimited chip waveforms. The received signal is first Fourier-transformed to the frequency domain, followed by a frequency deconvolution to remove the effect of the chip waveform. The code-timing is next derived from the output of a narrowband filter with a sweeping center frequency, which is designed to suppress interference of various sources, including, e.g., MUI (multiuser interference), ISI (inter-symbol interference), CCI (co-channel interference), and narrowband interference. The proposed estimator requires only the spreading code of the desired user. It can be used in frequency-flat or frequency-selective, time-invariant or time-varying fading channels. Moreover, the proposed estimator can be readily implemented using standard adaptive schemes, making it appealing not only for acquisition but also for tracking. Numerical results are presented to illustrate the performance of the proposed scheme.

We present a blind code synchronization scheme, referred to as the Capon algorithm, for DS (direct sequence) CDMA (code division multiple access) systems. The only required knowledge of the proposed scheme is the spreading code of the desired user, so that it is appealing for a decentralized implementation. The Capon algorithm can be used in frequency-flat or frequency-selective, time-invariant or time-varying fading channels; it is able to deal with colored channel noise and unknown interference of various origins, such as inter-cell interference and interference in cellular overlay systems. The Capon algorithm can be readily implemented using standard adaptive schemes, making it amenable to not only acquisition but tracking as well. An additional advantage enjoyed by Capon is that it does not need to know the number of active transmissions, a knowledge usually indispensable for some blind algorithms to function properly. Numerical simulations are presented to illustrate the performance of the proposed Capon scheme.

In this paper, we present a novel blind code synchronization algorithm, referred to as the Capon algorithm, for direct-sequence (DS) code division multiple access (CDMA) systems. The idea is to design a bank of filters, each of which passes one user signal of interest without distortion (unit-gain), meanwhile suppressing the overall interference as much as possible. The only required knowledge of the proposed scheme is the spreading code of the desired user; therefore, it is appealing to a decentralized implementation. The Capon algorithm is able to mitigate not only interference signals originated within the same cell (i.e., intra-cell interference), but also unknown interference of various origins, such as unmodeled inter-cell interference and narrowband interference in cellular overlay systems. It can be readily implemented using standard adaptive schemes, making it amenable to both acquisition and tracking. An additional advantage enjoyed by Capon is that it does not need to know the number of active transmissions, a knowledge usually indispensable for some blind algorithms to function properly. Numerical simulations are presented to illustrate the performance of the proposed Capon scheme.