Ioannis N. Psaromiligkos

On adaptive minimum probability of error linear filter receivers for DS-CDMA channels

Receiver architectures in the form of a linear filter front-end followed by a hard-limiting decision maker are considered for DS-CDMA communication systems. Based on stochastic approximation concepts a recursive algorithm is developed for the adaptive optimization of the linear filter front-end in the minimum BER sense. The recursive form is decision driven and distribution free. For additive white Gaussian noise (AWGN) channels, theoretical analysis of the BER surface of linear filter receivers identifies the subset of the linear filter space where the optimal receiver lies and offers a formal proof of guaranteed global optimization with probability one for the two-user case. To the extent that the output of a linear DS-CDMA filter can be approximated by a Gaussian random variable, a minimum-mean-square-error optimized linear filter approximates the minimum BER solution. Numerical and simulation results indicate that for realistic AWGN DS-CDMA systems with reasonably low signature cross-correlations the linear minimum BER filter and the MMSE filter exhibit approximately the same performance. The linear minimum BER receiver is superior, however, when either the signature cross-correlation is high or the background noise is non-Gaussian.

Adaptive robust spread-spectrum receivers

We consider the problem of robust detection of a spread-spectrum (SS) signal in the presence of unknown correlated SS interference and additive non-Gaussian noise. The proposed general SS receiver structure is comprised by a vector of adaptive chip-based nonlinearities followed by an adaptive linear tap-weight filter and combines the relative merits of both nonlinear and linear signal processing. The novel characteristics of our approach are as follows. First, the nonlinear receiver front-end adapts itself to the unknown prevailing noise environment providing robust performance for a wide range of underlying noise distributions. Second, the adaptive linear tap-weight filter that follows the nonlinearly processed chip samples results in a receiver that is proven to be effective in combating SS interference as well. To determine the receiver parameters, we propose, develop, and study three adaptive schemes under a joint mean-square error (MSE), or a joint bit-error-rate (BER), or a joint MSE-BER optimization criterion. As a side result, we derive the optimum decision fusion filter for receivers that utilize hard-limiting (sign) chip nonlinearities. Numerical and simulation results demonstrate the performance of the proposed schemes and offer comparisons with the conventional matched-filter (MF), the decorrelator, the conventional minimum-variance-distortionless-response (MVDR) filter, and the sign-majority vote receiver.

Rapid combined synchronization/demodulation structures for DS-CDMA systems. I. Algorithmic developments

Blind adaptive linear receivers are considered for the demodulation of direct-sequence code-division multiple-access signals in asynchronous transmissions. The proposed structures are self-synchronized in the sense that adaptive synchronization and demodulation are viewed and treated as an integrated receiver operation. Two computationally efficient combined synchronization/demodulation schemes are proposed, developed, and analyzed. The first scheme is based on the principles of minimum-variance distortionless-response processing, while the second scheme follows the principles of auxiliary-vector filtering and exhibits enhanced performance in short data-record scenarios. In both cases, the resulting receiver is a linear structure of order exactly equal to the system processing gain. Simulation studies included in this paper demonstrate the coarse synchronization as well as the bit-error rate performance of the proposed strategies.

Recursive short-data-record estimation of AV and MMSE/MVDR linear filters for DS-CDMA antenna array systems

The presence of the desired signal during estimation of the minimum mean-square error (MMSE)/minimum-variance distortionless-response (MVDR) and auxiliary-vector (AV) filters under limited data support leads to significant signal-to-interference-plus-noise ratio (SINR) performance degradation. We quantify this observation in the context of direct-sequence code-division multiple-access (DS-CDMA) communications by deriving close approximations for the mean-square filter estimation error, the probability density function of the output SINR, and the probability density function of the symbol-error rate (SER) of the sample matrix inversion (SMI) receiver evaluated using both a desired-signal-present and desired-signal-absent input covariance matrix. To avoid such performance degradation, we propose a DS-CDMA receiver that utilizes a simple pilot-assisted algorithm that estimates and then subtracts the desired signal component from the received signal prior to filter estimation. Then, to accommodate decision-directed operation, we develop two recursive algorithms for the on-line estimation of the AV and MMSE/MVDR filter and we study their convergence properties. Finally, simulation studies illustrate the SER performance of the overall receiver structures.

Fast converging minimum probability of error neural network receivers for DS-CDMA communications

We consider a multilayer perceptron neural network (NN) receiver architecture for the recovery of the information bits of a direct-sequence code-division-multiple-access (DS-CDMA) user. We develop a fast converging adaptive training algorithm that minimizes the bit-error rate (BER) at the output of the receiver. The adaptive algorithm has three key features: i) it incorporates the BER, i.e., the ultimate performance evaluation measure, directly into the learning process, ii) it utilizes constraints that are derived from the properties of the optimum single-user decision boundary for additive white Gaussian noise (AWGN) multiple-access channels, and iii) it embeds importance sampling (IS) principles directly into the receiver optimization process. Simulation studies illustrate the BER performance of the proposed scheme.

Rapid combined synchronization/demodulation structures for DS-CDMA systems - part II: finite data-record performance analysis

For pt.I see ibid., vol.51, p.983-94 (2003). We investigate the coarse synchronization performance of blind adaptive linear self-synchronized receivers for asynchronous direct-sequence code-division multiple-access communications under finite data record adaptation. Based on transformation noise modeling techniques, three alternative methods are developed, leading to analytical expressions that approximate the probability of coarse synchronization error of matched-filter-type and minimum-variance distortionless-response-type receivers. The expressions are explicit functions of the data record size and the filter order and reveal the effect of short data-record sample matrix-inversion implementations on the coarse synchronization performance. Besides their theoretical value, the derived expressions provide simple, highly-accurate alternatives to computationally demanding performance evaluation through simulations. The effect of the data record size on the probability of coarse synchronization error is further quantified through the use of a receiver synchronization resolution metric. Numerical and simulation studies examine the accuracy of the theoretical developments and show that the derived expressions approximate closely the actual coarse synchronization performance.

Interference-plus-noise covariance matrix estimation for adaptive space-time processing of DS/CDMA signals

The presence of the desired signal during the estimation of the minimum-variance-distortionless-response (MVDR) or a auxiliary-vector (AV) filter under limited data records leads to significant signal-to-interference-plus-noise ratio (SINR) performance degradation. We quantify this observation in the context of DS/CDMA communications by deriving two new close approximations for the probability density functions (under both desired-signal-present and desired-signal-absent conditions) of the output SINR and bit-error-rate (BER) of the sample-matrix-inversion (SMI) MVDR receiver. To avoid such performance degradation we propose a DS/CDMA receiver that utilizes a simple pilot-assisted algorithm that estimates and then subtracts the desired signal component from the received signal prior to filter estimation. Then, to accommodate decision directed operation we develop two recursive algorithms for the on-line estimation of the MVDR and AV filter and we study their convergence properties. Finally, simulation studies illustrate the BER performance of the overall receiver structures.

Finite data record maximum SINR adaptive space-time processing

The presence of the desired signal during the estimation of the minimum variance distortionless response (MVDR) or auxiliary vector (AV) filter under limited data records leads to significant signal-to-interference-plus-noise ratio (SINR) performance degradation. We quantify this observation in the context of DS/CDMA communications by deriving two new close approximations for the probability density functions (under both desired signal present and absent conditions) of the output SINR and bit error rate (BER) of the sample matrix inversion (SMI) MVDR receiver. To avoid such performance degradation we propose a DS/CDMA receiver that utilizes a simple pilot-assisted algorithm that estimates and then subtracts the desired signal component from the received signal prior to filter estimation. Then, to accomodate decision directed operation we develop two recursive algorithms for the on-line estimation of the MVDR and AV filter and we study their convergence properties. Finally, simulation studies illustrate the BER performance of the overall receiver structure.

Blind self-synchronized receivers for DS/CDMA communications

We consider blind adaptive linear receivers for the demodulation of DS/CDMA signals in asynchronous transmissions. The proposed structures are self-synchronized in the sense that adaptive synchronization and demodulation are viewed and treated as an integrated receiver operation. Two computationally efficient combined synchronization/demodulation schemes are proposed, developed and analyzed. The first scheme is based on the principles of minimum-variance-distortionless-response (MVDR) processing, while the second scheme follows the principles of auxiliary-vector filtering and exhibits enhanced performance in short data record scenarios. The coarse synchronization performance of combined synchronization/demodulation receivers under finite data record adaptation is also investigated. Analytic expressions are derived that approximate closely the probability of coarse synchronization error of the conventional correlator and the MVDR type combined synchronization/demodulation scheme and provide low cost highly accurate alternatives to the computationally demanding performance evaluation through simulations.

Minimum bit-error-rate decision fusion receivers for robust DS spread-spectrum communications

The conventional matched filter (MF) correlation receiver for direct sequence spread spectrum transmissions is reconsidered from the theoretical point of view of robust distributed detection (decision fusion). Separate chip-by-chip decisions on the transmitted information bit of interest are generated. The individual decisions are then optimally fused to produce the final decision on the transmitted bit. It is proven that the majority-vote strategy is the statistically optimal fusion rule for additive white Gaussian noise channels. An exact closed form expression is given for the probability of error induced by the majority-vote receiver. It is shown that the performance is independent of the identity of the active interfering user population, that is signatures and signature cross-correlations, in DS-CDMA environments. This perfect robustness with respect to the identity of the multiuser interference component is coupled by significant resistance toward occasional high-power jamming (equivalently occasional natural severe channel imperfections) or outlier-prone background noise, or both. Some numerical studies illustrate these theoretical findings.