Block modulus precoding for blind multiuser detection of ds-cdma signals

A code-constrained inverse filter criteria based approach is presented for blind detection of asynchronous short-code DS-CDMA (direct sequence code division multiple access) signals in multipath channels. Only the spreading code of the desired user is assumed to be known; its transmission delay may be unknown. We focus on maximization of the normalized fourth cumulant of inverse filtered (equalized) data w.r.t. the equalizer coefficients subject to the equalizer lying in a subspace associated with the desired user's code sequence. Constrained maximization leads to extraction of the desired user's signal whereas unconstrained maximization leads to the extraction of any one of the existing users. An illustrative simulation example is provided.

Constrained minimum variance (CMV) detection has been proposed for blind multiuser detection of DS/CDMA signals in multipath channels. We suggest a new approach for implementing the CMV detection when an antenna array is used at the receiver. A simple technique is used for restricting the domain of the CMV detector to a smaller subspace based on signals directions of arrivals (DOAs), in a beamformer-like formulation. The proposed technique requires prior knowledge of only the timing of the desired user's signal. It is seen that the proposed subspace restriction is useful for accurate path DOA estimation followed by efficient data detection in heavily loaded systems and over small block sizes of the input signal. This makes this method suitable for slowly time varying channels.

In this paper, we introduce a novel fuzzy adaptive algorithm for blind detection of direct sequence code division multiple access (DS-CDMA) signals in a multiuser communication scenario. We make use of fuzzy control systems to wisely determine the appropriate step size of the adaptive algorithm based on the quality of the received signal. We have used the popular minimum output energy (MOE) blind detector proposed by Honig et al. as our blind adaptive detector whose step size is to be determined by the fuzzy control system. This blind detector requires no more knowledge than does the conventional single-user receiver, i.e. the desired user's signature waveform and its timing. We have proposed to use signal to interference ratio (SIR) and its variations as the key inputs to our fuzzy algorithm. By simulation, we show the competency of our algorithm in terms of the convergence characteristics of the adaptive algorithm. Likewise, by simulation results we show that these convergence improvements yield to a lower bit error rate (BER) for the demodulation process in the receiver.

Blind detection of a desired user's signal in a code-hopping (CH) direct sequence code-division multiple access (CDMA) system is considered. In CH CDMA systems each user switches between a predetermined set of short-code sequences. A user signal in such systems may be treated as the superposition of several virtual short-code signals. A code-constrained inverse filter criterion (IFC)-based blind detector for short-code CDMA signals in asynchronous multipath channels to detect a desired user's signal was recently presented by Tugnait and Li (2001). A novel approach combining the code-constrained IFC and a penalty function is proposed to simultaneously extract all virtual users associated with a given CH user. Global minima of the proposed cost function are analyzed. An extension of an existing subspace-based approach is also investigated. An illustrative simulation example is provided where the proposed algorithm is compared with a clairvoyant matched filter receiver, two linear minimum mean-square error (MMSE) receivers with channels known, and the subspace-based approach.

Noncoherent multiuser detection for nonlinear modulation was previously studied and the idea of phase-independent noncoherent decorrelation was introduced and three post-decorrelative detectors were obtained and analyzed. However, their implementation requires the knowledge of the signature waveforms of all the users, which may be available only for centralized implementation. In this paper, we obtain a blind adaptive noncoherent decorrelative detector for nonlinear modulation that is suitable for distributed implementation with the knowledge of only the normalized signals of the desired user and the additive noise variance. This detector is based on the stochastic approximation method and does not require the overhead of any kind of "training." Two adaptive algorithms are developed, one guided by every signal in the desired user's signal set individually, and the other by the user's entire signal space. While this paper focuses on the particular problem of blind adaptive noncoherent decorrelative detection, it addresses a more general adaptation issue, namely, that of improving the convergence properties of an adaptive scheme by effectively using all the information that is known, and adapting only to the part of the desired solution that is truly unknown. Convergence is shown in the mean squared error sense for both the fixed step-size and time-varying step-size versions of the two algorithms.

This paper studies the performances for wireless communications of the independent component analysis (ICA), and the analytical constant modulus algorithm (ACMA). These algorithms can be used at the base station to separate the received signals. The ICA algorithm aims to statically whiten the data set for second-order statistics, and for higher-order statistics; while ACMA aims to find the solution in a data set which has a constant modulus. The methods are blind beamformers, so no training sequence is required, and the array of sensors requires neither a good calibration, nor the knowledge of the geometry. The main drawback is the prohibitive computational costs. The methods are used for noisy multipath fading channels with a Rayleigh distribution for the amplitude, and a Laplacian distribution for the direction of arrival. Scenarios are simulated for different signal-to-noise ratio (SNR), and bit error rate (BER) is derived. Lastly, utilization of the methods as beamformers/equalizers is shown.

Code-Hopping Multiple Access (CHMA) has been an emerging Multiple Access (MA) technology which offers excellent performance in multipath fading channels with Orthogonal Complementary Codes (OCC). Orthogonality among users is not preserved in multipath channel conditions using the existing orthogonal and semi-orthogonal codes. Further, Multiple Access Interference (MAI) and Multipath Interference (MPI) destroy orthogonality of the code set which in turn increases the error rate during the detection process. An OCC set possesses both ideal auto-correlation and ideal cross-correlation properties for any two codes in the same set. Here, we employ OCC for spreading and prove that the performance of OCC is superior to those of Gold codes in multipath channels where orthogonality does not hold. The error probability expressions for Rayleigh and Nakagami-m fading channels using Maximal Ratio Combining (MRC) are derived for CHMA system using OCCs. We then evaluate the system performance using the proposed technique and show that the new scheme is much better compared to traditional CHMA schemes.

Group-blind multiuser detectors for uplink code-division multiple-access (CDMA) were recently developed by Wang and Host-Madsen. These detectors make use of the spreading sequences of known users to construct a group constraint to suppress the intracell interference. However, such techniques demand the estimation of the multipath channels and the delays of the known users. In this paper, several improved blind linear detectors are developed for CDMA in fading multipath channels. The proposed detectors utilize the correlation information between consecutively received signals to generate the corresponding group constraint. It is shown that by incorporating this group constraint, the proposed detectors can provide different performance gains in both uplink and downlink environments. Compared with the previously reported group-blind detectors, our new methods only need to estimate the multipath channel of the desired user and do not require the channel estimation of other users. Simulation results demonstrate that the proposed detectors outperform the conventional blind linear multiuser detectors.

A new approach for blind multiuser (MU) detection of DS/CDMA signals is proposed. This approach is based on modifying the data spectrum, uniquely for each user, through a two stage coloring-whitening precoding scheme. This enables separation and detection of a desired user's signal in an unknown multipath channel, regardless of the power of the interferers. This technique does not involve any sacrifice in data rate or system bandwidth. The method can be considered as an extension of the approach of J. Xavier et al. (see IEEE Trans. on Sig. Processing, vol.49, p.1073-86, 2001) to the multipath DS/CDMA channel. Detection does not involve channel estimation, and does not use code knowledge. Besides, the proposed method can tolerate severe carrier frequency offsets, with reasonable performance.

We first develop a reduced-rank minimum mean square error (MMSE) detector for direct-sequence (DS) code division multiple access (CDMA) by forcing the linear MMSE detector to lie in a signal subspace of a reduced dimension. While a reduced-rank MMSE detector has lower complexity, it cannot outperform the full-rank MMSE detector. We then concentrate on the blind reduced-rank MMSE detector which is obtained from an estimated covariance matrix. Our analysis and simulation results show that when the desired user's signal is in a low-dimensional subspace, there exists an optimal subspace so that the blind reduced-rank MMSE detector lying in this subspace has the best performance. By properly choosing a subspace, we guarantee that the optimal blind reduced-rank MMSE detector is obtained. An adaptive blind reduced-rank MMSE detector, based on a subspace tracking algorithm, is developed. The adaptive blind reduced-rank MMSE detector exhibits superior steady-state performance and fast convergence speed.

A new stable blind multiuser detector based on signal subspace orthogonal projection is presented. By carrying out a pseudo-eigendecomposition (PED) analysis, a technique proposed for the first time, the signal of the interested user can be approximated by the orthogonal projection of a received multiuser signal onto the related subspace of the interested user. Simulations show that compared with the previous subspace-based MMSE blind multiuser detector, the new detector offers better performance without leading to an increase in the computational complexity.

In this paper, we propose a generic receiver based on optimum maximum likelihood sequence estimation (MLSE) employing a generalized Ungerboeck metric with significantly reduced complexity for the general class of M-ary quasi orthogonal signaling (MOS) in severe multipath fading channels. First, by using the factor graph (FG) of the obtained generalized Ungerboeck metric for MOS and sum-product algorithm (SPA) framework, a highly efficient reduced state sequence estimation (RSSE) algorithm is proposed that operates on forward and backward directions and is directly applied to unwhitened channel matched filter (CMF) and code matched filter outputs at symbol rate. The proposed structure, generating the a posteriori probabilities (APP) by bidirectional RSSE recursions, are substantiated with symbol rate bidirectional decision feedback (BDF) based on surviving paths in order to eliminate the post- and pre-cursor inter-symbol interference (ISI) as well as multi code interference (MCI) due to the non-ideal properties of the signaling waveforms and multipath channel. It appears as the unification of Ungerboeck type reduced trellis equalization framework for MOS and achieves near-optimum performance especially for channels with large dispersion. Second, we identify a bias term through an error probability analysis which helps us improve the proposed receiver's performance. Furthermore, a tight approximation for the bit error rate (BER) of the proposed receiver is derived. These analyses lead to significant insight on the selection of system parameters and clearly demonstrate the high performance and efficiency of the proposed scheme by a proper choice of the signaling parameters.

Blind adaptive multiuser detection based on the constant modulus algorithm (CMA) has received a lot of attention. In the blind detectors proposed previously, the CMA is applied to the output of the chip match filters. In this paper, we consider the use of the CMA at the output of a bank of filters matched to the signature waveforms of each user. For simplicity, a synchronous code division multiple access (CDMA) system is adopted. The convergence performance of the blind detector is also analyzed and the results indicate that the CMA does not have the stable undesired equilibrium, which has been proven to exist for the practical Goddard algorithm with the finite tap equalizer when used in intersymbol interference (ISI) channels. However, the permutation ambiguity and the phase ambiguity occur. To avoid the permutation and phase ambiguities, some constraints are introduced into the CMA and their validity is also proven by analysis and simulations. When the CMA for each user converges to the desired solution, the blind detector is approaching to the decorrelating detector.

This paper addresses the problem of blind estimation of CDMA signals in multipath channel based on MMSE criterion. We formulate the asynchronous CDMA model into the framework of multiple input multiple output (MIMO) system and developed a new blind equalization and user separation algorithm based on second order statistics to cancel ISI and MUI. We also give the conditions for detecting a desired user from the received signal.

Orthogonal frequency-division multiplexing (OFDM) is a popular transmission technology in cognitive radio (CR) networks, because the correlation of cyclic prefix (CP) in OFDM signals can be utilized to improve the reliability of spectrum sensing of secondary users (SUs). However, the optimal spectrum sensing over multipath fading channels remains an important and challenging issue. Therefore, this work proposes an optimal Neyman- Pearson (NP) detector for spectrum sensing using CP. To detect the OFDM signal of primary users (PUs), the log- likelihood ratio (LR) test is formulated by using the correlation characteristics of the redundancy of CP. Analytical results indicate that the LR of received samples is equivalent to their log- likelihood function (LF) plus LR of an energy detector (ED), subsequently allowing us to gain insights on the optimal NP detector. Since many unknown parameters need to be resolved, a practical generalized log-likelihood ratio test (GLRT) is presented. Moreover, to achieve a good performance over multipath fading channels, a channel- independent GLRT (CI-GLRT) is employed to derive an estimation of correlation coefficient independent of multipath channel profiles. Simulations confirm the advantages of the proposed detectors compared with state-of-the-art detectors.