data record size requirements for adaptive space time ds cdma signal detection we investigate the data record size requirements of sample matrix inversion based minimum variance distortionless response and maximum signal to interference plus noise ratio adaptive algorithms to meet a given performance objective in joint space time signal detection problems for direct sequence code division multiple access systems we derive closed form expressions that provide the data record size that is necessary to achieve a given performance confidence level in a neighborhood of the optimal performance point as well as expressions that identify the performance level that can be reached for a given data record size this is done by using close approximations of the involved probability density functions the practical significance of the derived expressions lies in the fact that the expressions are functions of the number of antenna elements the number of multipaths and the system spreading gain only while they depend neither on the ideal input covariance matrix which is not known in most realistic applications nor on the exact ideal performance value

multicriteria sorting using a valued indifference relation under a preference disaggregation paradigm abstract most multicriteria decision methods need the definition of a significant amount of preferential information from a decision agent the preference disaggregation analysis paradigm infers the model s parameter values from holistic judgments provided by a decision agent here a new method for inferring the parameters of a fuzzy outranking model for multicriteria sorting is proposed this approach allows us to use most of the preferential information contained in a reference set the central idea is to characterize the quality of the model by measuring discrepancies and concordances amongst i the preference relations derived from the outranking model and ii the preferential information contained in the reference set the model s parameters are inferred from a multiobjective optimization problem according to some additional preferential information from a decision agent once the model has been fitted sorting decisions about new objects are performed by using a fuzzy indifference relation this proposal performs very well in some examples

performance of constrained and unconstrained adaptive multiuser detectors for quasi synchronous cdma it has previously been shown that multiuser interference in a quasi synchronous code division multiple access qs cdma system can be effectively rejected using a nonadaptive decorrelator however the qs decorrelator is orthogonal to the inflated subspace spanned by the undesired users with arbitrary delays in the qs uncertainty interval and hence does not perform as well as a decorrelator with a priori knowledge of the delays here we consider a constrained adaptive linear suppression filter which implicitly estimates the delays of the qs undesired signals and thus approaches the ideal decorrelator of lupas and verdu 1990 for qs cdma it is shown through analysis and simulations that the constrained recursive least squares c rls algorithm converges faster than an unconstrained rls adaptive filter and generally outperforms the nonadaptive qs decorrelator a cellular quasi synchronous system is discussed in the present paper

blind multiuser detection from moe to subspace methods the minimum output energy moe multiuser receiver has been shown to approach the minimum mean square error mmse receiver at high signal to noise ratio snr however performance degradation is incurred by noise induced channel estimation error in this paper we propose a power of r por technique to significantly improve the performance of the moe receiver it is shown that the new receiver asymptotically converges to the mmse receiver without performance penalty the convergence is established either under high snr with large exponent raised in the power of the covariance matrix or with sufficiently large number of data samples connection between our por method and a widely studied subspace method is investigated from the respective optimization criteria asymptotic equivalence between these two methods is also established extensive simulations based on finite data samples show that the proposed method significantly outperforms the subspace method in systems with medium to heavy loading severe multipath distortion or smaller processing gain moreover adaptive implementation of the proposed method exhibits very robust performance in a dynamic loading environment

minimum probability of error for asynchronous gaussian multiple access channels consider a gaussian multiple access channel shared by k users who transmit asynchronously independent data streams by modulating a set of assigned signal waveforms the uncoded probability of error achievable by optimum multiuser detectors is investigated it is shown that the k user maximum likelihood sequence detector consists of a bank of single user matched filters followed by a viterbi algorithm whose complexity per binary decision is o 2 k the upper bound analysis of this detector follows an approach based on the decomposition of error sequences the issues of convergence and tightness of the bounds are examined and it is shown that the minimum multiuser error probability is equivalent in the iow noise region to that of a single user system with reduced power these results show that the proposed multiuser detectors afford important performance gains over conventional single user systems in which the signal constellation carries the entire burden of complexity required to achieve a given performance level

algorithm for generalized co complementarity problems in banach spaces abstract in this paper we introduce a new class of generalized co complementarity problems in banach spaces an iterative algorithm for finding approximate solutions of these problems is considered some convergence results for this iterative algorithm are derived and several existence results are obtained

lms algorithms for tracking slow markov chains with applications to hidden markov estimation and adaptive multiuser detection this paper analyzes the tracking properties of the least mean squares lms algorithm when the underlying parameter evolves according to a finite state markov chain with infrequent jumps first using perturbed liapunov function methods mean square error estimates are obtained for the tracking error then using recent results on two time scale markov chains mean ordinary differential equation and diffusion approximation results are obtained it is shown that a sequence of the centered tracking errors converges to an ordinary differential equation moreover a suitably scaled sequence of the tracking errors converges weakly to a diffusion process it is also shown that iterate averaging of the tracking algorithm results in optimal asymptotic convergence rate in an appropriate sense two application examples analysis of the performance of an adaptive multiuser detection algorithm in a direct sequence code division multiple access ds cdma system and tracking analysis of the state of a hidden markov model hmm with infrequent jumps are presented

performance of blind and group blind multiuser detectors in blind or group blind linear multiuser detection the detector is estimated from the received signals with the prior knowledge of only the signature waveform of the desired user or the signature waveforms of some but not all users the performance of a number of such estimated linear detectors including the direct matrix inversion dmi blind linear minimum mean square error mmse detector the subspace blind linear mmse detector and the form i and form ii group blind linear hybrid detectors are analyzed asymptotic limit theorems for each of the estimates of these detectors when the signal sample size is large are established based on which approximate expressions for the average output signal to interference plus noise ratios sinrs and bit error rates bers are given to gain insights on these analytical results the performance of these detectors in an equicorrelated code division multiple acces cdma system is compared examples are provided to demonstrate the excellent match between the theory developed here and the simulation results

algorithm for generalized multivalued variational inequalities in hilbert spaces abstract we introduce a new class of generalized multivalued variational inequality problems 1 1 which contain several existing variational inequality problems as special cases an iterative algorithm for finding approximate solutions of problem 1 1 is considered several convergence results for this algorithm are derived and in particular several existence results of problems 1 1 are obtained we also introduce a new class of generalized multivalued complementarity problems 5 1 which also contain several known complementarity problems as special cases it is shown that problem 5 1 is equivalent to problem 1 1 of special type from which several existence results of problem 5 1 are obtained

a quadratic programming approach to blind equalization and signal separation blind equalization and signal separation are two well established signal processing problems in this paper we present a quadratic programming algorithm for fast blind equalization and signal separation by introducing a special non mean square error mse objective function we reformulate fractionally spaced blind equalization into an equivalent quadratic programming problem based on a clear geometric interpretation and a formal proof we show that a perfect equalization solution is obtained at every local optimum of the quadratic program because blind source separation is by nature and mathematically a closely related problem we also generalize the algorithm for blind signal separation we show that by enforcing source orthogonalization through successive processing the quadratic programming approach can be applied effectively moreover the quadratic program is easily extendible to incorporate additional practical conditions such as jamming suppression constraints we also provide evidence of good performance through computer simulations

a subspace approach to adaptive narrow band interference suppression in dsss we address the problem of suppression of a digital narrow band interferer in direct sequence spread spectrum dsss communications we focus on the adaptive suppression method proposed by honig madhow and verdti see ieee trans inform theory vol 41 p 944 960 1995 for wide band interference applying it to a narrow band interferer we identify the eigenspaces of the system dynamics to analyze the convergence of the adaptive version of the minimum mean square error mmse algorithm for this application using this subspace approach we are able to 1 significantly decrease the convergence times via a new constraint on the step size in adaptation 2 introduce a simple parameterization of the mean output energy moe and signal to interference ratio sir to compare performance of various receivers and 3 identify modes of operation where the algorithm will cease to effectively cancel interference we propose a new adaptive receiver that avoids the convergence anomalies identified while capitalizing on the new step size for faster convergence simulation results to support theoretical results are presented

statistics of adaptive nulling and use of the generalized eigenrelation ger for modeling inhomogeneities in adaptive processing this paper examines the integrity of the generalized eigenrelation ger which is an approach to assessing performance in an adaptive processing context involving covariance estimation when the adaptive processors are subject to undernulled interference the ger is a mathematical relation which if satisfied often facilitates closed form analysis of adaptive processors employing estimated covariances subject to inhomogeneities the goal of this paper is to determine what impact this constraint has on the integrity of the adaptive nulling process in order to examine the impact of the ger constraint on adaptive nulling we establish fundamental statistical convergence properties of an adaptive null for the sample covariance based scb minimum variance distortionless response mvdr beamformer novel exact expressions relating the mean and variance of an adaptive null of a homogeneously trained beamformer to the mean and variance of a nonhomogeneous trained beamformer are derived in addition it is shown that the reed et al 1974 result for required sample support can be highly inaccurate under nonhomogeneous conditions indeed the required sample support can at times depend directly on the power of the undernulled interference

performance analysis of the minimum variance beamformer we present an analysis of the signal to interference plus noise ratio sinr at the output of the minimum variance beamformer the analysis is based on the assumption that the signals and noise are gaussian and that the number of samples is large compared to the array size and it yields an explicit expression for the sinr in terms of the different parameters affecting the performance including signal to noise ratio snr interference to noise ratio inr signal to interference ratio sir angular separation between the desired signal and the interference array size and shape correlation between the desired signal and the interference and finite sample size

pdf s confidence regions and relevant statistics for a class of sample covariance based array processors we add to the many results on sample covariance matrix scm dependent array processors by i weakening the traditional assumption of gaussian data and ii providing for a class of array processors additional performance measures that are of value in practice the data matrix is assumed drawn from a class of multivariate elliptically contoured mec distributions the performance measures include the exact probability density functions pdfs confidence regions and moments of the weight vector matrix beam response and beamformer output of certain scm based scb array processors the array processors considered include the scb i maximum likelihood ml signal vector estimator ii linearly constrained minimum variance beamformer lcmv iii minimum variance distortionless response beamformer mvdr and iv generalized sidelobe canceller gsc implementation of the lcmv beamformer it is shown that the exact joint pdfs for the weight vectors matrices of the aforementioned scb array processors are a linear transformation from a complex multivariate extension of the standardized t distribution the scb beam responses are generalized t distributed and the pdfs of the scb beamformer outputs are given by kummer s function all but the beamformer outputs are shown to be completely invariant statistics over the class of mecs considered

robust blind multiuser detection based on the worst case performance optimization of the mmse receiver the conventional minimum mean square error mmse multiuser receiver requires that each particular user transmits a sequence of training symbols known to the receiver and the receiver estimates the user signatures using this knowledge however in the presence of multiaccess interference mai during the training period and or in scenarios with short training sequence length the signature estimates can be erroneous and the performance of the mmse multiuser receiver can degrade substantially in this paper we propose a new blind multiuser receiver that is robust against the effects of erroneously presumed desired user signature and short data length our approach is based on the explicit modeling of possible mismatches in the mean square error cost function and worst case performance optimization we show that this approach leads to a multiuser receiver which uses the data covariance matrix with an adaptive diagonal loading the proposed method has simple implementation with a computational complexity comparable with that of the fixed diagonal loading based multiuser receiver simulation results show performance improvements achieved by our approach relative to existing techniques

a multiple criteria sorting method where each category is characterized by several reference actions the electre tri nc method this paper presents electre tri nc a new sorting method which takes into account several reference actions for characterizing each category this new method gives a particular freedom to the decision maker in the co construction decision aiding process with the analyst to characterize the set of categories while there is no constraint for introducing only one reference action as typical of each category like in electre tri c almeida dias et al 2010 as in such a sorting method this new sorting method is composed of two joint rules electre tri nc also fulfills a certain number of natural requirements additional results on the behavior of the new method are also provided in this paper namely the ones with respect to the addition or removal of the reference actions used for characterizing a certain category a numerical example illustrates the manner in which electre tri nc can be used by a decision maker a comparison with some related sorting procedures is presented and it allows to conclude that the new method is appropriate to deal with sorting problems

multicriteria assignment method proaftn methodology and medical application abstract this paper presents a new fuzzy multicriteria classification method called proaftn for assigning alternatives to predefined categories this method belongs to the class of supervised learning algorithms and enables to determine the fuzzy indifference relations by generalising the indices concordance and discordance used in the electre iii method then it assigns the fuzzy belonging degree of the alternatives to the categories we also present a clinical application of the proposed method in the cytopathological diagnosis of acute leukaemia

generalized f complementarity problems in banach spaces abstract in this paper a class of generalized f complementarity problems and three classes of variational inequalities are introduced in real banach spaces and the equivalences among them are established under certain conditions several coercivity conditions are introduced for the existence of solutions of the generalized f complementarity problem under some suitable assumptions it is shown that each of these coercivity conditions is equivalent to the nonemptyness and boundedness of the solution set for the generalized f complementarity problem in infinite dimensional banach spaces and even the nonemptyness and compactness of the solution set for the generalized f complementarity problem in finite dimensional spaces the existence of least elements for the feasible set of the generalized f complementarity problem is also presented under suitable conditions

on the equivalence of three reduced rank linear estimators with applications to ds cdma this correspondence shows the equivalence of three previously proposed reduced rank detection schemes for direct sequence code division multiple access ds cdma communication systems the auxiliary vector filtering avf algorithm is simplified through a key observation on the construction of the auxiliary vectors after simplification it is shown that the avf algorithm is equivalent to the multistage wiener filtering mwf algorithm of honig and goldstein 2002 furthermore these schemes can be shown to be equivalent to the multistage linear receiver scheme based on the cayley hamilton ch theorem when the minimum mean square error mmse criterion is applied to the reduced dimensional space of the received signal

linear mmse multiuser receivers mai conditional weak convergence and network capacity we explore the performance of minimum mean square error mmse multiuser receivers in wireless systems where the signatures are modeled as random and take values in complex space first we study the conditional distribution of the output multiple access interference mai of the mmse receiver by appealing to the notion of conditional weak convergence we find that the conditional distribution of the output mai given the received signatures and received powers converges in probability to a proper complex gaussian distribution that does not depend on the signatures this result indicates that in a large system the output interference of the mmse receiver is approximately gaussian with high probability and that systems with mmse receivers are robust to the randomness of the signatures building on the gaussianity of the output interference we then take the quality of service qos requirements as meeting the signal to interference ratio sir constraints and identify the network capacity of single class systems with random spreading the network capacity is expressed uniquely in terms of the sir requirements and received power distributions compared to the network capacity corresponding to the optimal signature allocation we conclude that at the cost of transmission power the gap between the network capacity corresponding to optimal signatures and that corresponding to random signatures can be made arbitrarily small therefore from the viewpoint of the network capacity systems with mmse receivers are robust to the randomness of signatures

a new approach to multi criteria sorting based on fuzzy outranking relations the theseus method abstract in this paper we propose the theseus method a new approach based on fuzzy outranking relations to multi criteria sorting problems compared with other outranking based methods theseus is inspired by another view of multi criteria classification problems it utilizes a new way of evaluating the assignment of an object to an element of the set of ordered categories that were previously defined this way is based on comparing every possible assignment with the information from various preference relations that are derived from a fuzzy outranking relation defined on the universe of objects the appropriate assignment is determined by solving a simple selection problem the capacity of a reference set for making appropriate assignments is related to a good characterization of the categories a single reference action characterizing a category may be insufficient to achieve well determined assignments in this paper the reference set capacity to perform appropriate assignments is characterized by some new concepts this capacity may be increased when more objects are added to the reference set theseus is a method for handling the preference information contained in such larger reference sets

new user identification in a cdma system we present three detector estimators des which allow multiuser detection and parameter estimation without a side channel in a dynamic asynchronous code division multiple access cdma system in which users are entering and leaving the system these des optimally detect a new user given only the chip rate and the spreading factor of the new user two of these des the maximum likelihood detector estimator mlde and the generalized maximum likelihood detector estimator gmlde produce maximum likelihood estimates of the new user s signature sequence delay and amplitude which are then incorporated into a multiuser detector the third de the cyclic detector estimator cde is the most computationally efficient of the three processors this de detects the new user by testing for cyclostationarity and then uses suboptimal schemes to estimate the new user s signature sequence delay and amplitude simulations indicate that all three des reliably detect a new user for an e sub s spl sigma sup 2 symbol energy to noise ratio of 5 db the mlde and gmlde produce signature sequence and delay estimates with probability of error less than 0 07 for an e sub s spl sigma sup 2 of 10 db and the cde produces signature sequence and delay estimates with probability of error less than 0 13 for an e sub s spl sigma sup 2 of 15 db

an evolutionary approach to construction of outranking models for multicriteria classification the case of the electre tri method outranking methods constitute an important class of multicriteria classification models often however their implementation is cumbersome due to the large number of parameters that the decision maker must specify past studies tried to address this issue using linear and nonlinear programming to elicit the necessary preferential information from assignment examples in this study an evolutionary approach based on the differential evolution algorithm is proposed in the context of the electre tri method computational results are given to test the effectiveness of the methodology and the quality of the obtained models

blind adaptive multiuser detection the decorrelating detector and the linear minimum mean square error mmse detector are known to be effective strategies to counter the presence of multiuser interference in code division multiple access channels in particular those multiuser detectors provide optimum near far resistance when training data sequences are available the mmse multiuser detector can be implemented adaptively without knowledge of signature waveforms or received amplitudes this paper introduces an adaptive multiuser detector which converges for any initialization to the mmse detector without requiring training sequences this blind multiuser detector requires no more knowledge than does the conventional single user receiver the desired user s signature waveform and its timing the proposed blind multiuser detector is made robust with respect to imprecise knowledge of the received signature waveform of the user of interest

large system performance analysis of blind and group blind multiuser receivers we present a large system performance analysis of blind and group blind multiuser detection methods in these methods the receivers are estimated based on the received signal samples in particular we assume binary random spreading and let the spreading gain n the number of users k and the number of received signal samples m all go to infinity while keeping the ratios k n and m n fixed we characterize the asymptotic performance of the direct matrix inversion dmi blind linear minimum mean square error mmse receiver the subspace blind linear mmse receiver and the group blind linear hybrid receiver we first derive the asymptotic average output signal to interference plus noise ratio sinr for each of these receivers our results reveal an interesting saturation phenomenon the output sinr of each of these receivers converges to a finite limit as the signal to noise ratio snr of the desired user increases which is in stark contrast to the fact that the output sinr achieved by the exact linear mmse receiver can get arbitrarily large this indicates that the capacity of a wireless system with blind or group blind multiuser receivers is not only interference limited but also estimation error limited we then show that for both the blind and group blind receivers the output residual interference has an asymptotic gaussian distribution independent of the realizations of the spreading sequences the gaussianity indicates that in a large system the bit error rate ber is related to the sinr simply through the q function

unified large system analysis of mmse and adaptive least squares receivers for a class of random matrix channels we present a unified large system analysis of linear receivers for a class of random matrix channels the technique unifies the analysis of both the minimum mean squared error mmse receiver and the adaptive least squares als receiver and also uses a common approach for both random independent identically distributed i i d and random orthogonal precoding we derive expressions for the asymptotic signal to interference plus noise ratio sinr of the mmse receiver and both the transient and steady state sinr of the als receiver trained using either i i d data sequences or orthogonal training sequences the results are in terms of key system parameters and allow for arbitrary distributions of the power of each of the data streams and the eigenvalues of the channel correlation matrix in the case of the als receiver we allow a diagonal loading constant and an arbitrary data windowing function for i i d training sequences and no diagonal loading we give a fundamental relationship between the transient steady state sinr of the als and the mmse receivers we demonstrate that for a particular ratio of receive to transmit dimensions and window shape all channels which have the same mmse sinr have an identical transient als sinr response we demonstrate several applications of the results including an optimization of information throughput with respect to training sequence length in coded block transmission

an iterative algorithm for the computation of the mvdr filter statistical conditional optimization criteria lead to the development of an iterative algorithm that starts from the matched filter or constraint vector and generates a sequence of filters that converges to the minimum variance distortionless response mvdr solution for any positive definite input autocorrelation matrix computationally the algorithm is a simple noninvasive recursive procedure that avoids any form of explicit autocorrelation matrix inversion decomposition or diagonalization theoretical analysis reveals basic properties of the algorithm and establishes formal convergence when the input autocorrelation matrix is replaced by a conventional sample average positive definite estimate the algorithm effectively generates a sequence of mvdr filter estimators the bias converges rapidly to zero and the covariance trace rises slowly and asymptotically to the covariance trace of the familiar sample matrix inversion smi estimator in fact formal convergence of the estimator sequence to the smi estimate is established however for short data records it is the early nonasymptotic elements of the generated sequence of estimators that offer favorable bias covariance balance and are seen to outperform in mean square estimation error constraint lms rls type orthogonal multistage decomposition as well as plain and diagonally loaded smi estimates an illustrative interference suppression example is followed throughout this presentation

adaptive linear procedures under general conditions under mild conditions on the observation processes the almost sure convergence properties of linear stochastic approximation are summarized for least squares and for some of its applications adaptive filtering echo cancellation detection of binary data in gaussian noise identification and linear classification

performance analysis of beamformers using generalized loading of the covariance matrix in the presence of random steering vector errors robust adaptive beamforming is a key issue in array applications where there exist uncertainties about the steering vector of interest diagonal loading is one of the most popular techniques to improve robustness in this paper we present a theoretical analysis of the signal to interference plus noise ratio sinr for the class of beamformers based on generalized i e not necessarily diagonal loading of the covariance matrix in the presence of random steering vector errors a closed form expression for the sinr is derived that is shown to accurately predict the sinr obtained in simulations this theoretical formula is valid for any loading matrix it provides insights into the influence of the loading matrix and can serve as a helpful guide to select it finally the analysis enables us to predict the level of uncertainties up to which robust beamformers are effective and then depart from the optimal sinr

blind subspace based signature waveform estimation in bpsk modulated ds cdma systems with circular noise a new blind subspace based algorithm for signature waveform estimation in binary phase shift keying bpsk modulated direct sequence code division multiple access ds cdma systems is proposed our approach can be viewed as a modification of the popular blind technique by liu and xu lx which additionally exploits noncircularity of the transmitted signals and circularity of noise to increase the dimension of the observation space twice while keeping the dimension of the signal subspace unchanged this enables us to improve the performance substantially and to apply the proposed algorithm to scenarios with an increased number of active users and lengthier user channels as compared with the original lx algorithm the theoretical analysis of the identifiability of the proposed technique is provided which shows that it enjoys more relaxed identifiability conditions than the lx algorithm analytical expressions for the mean square error mse of the proposed algorithm are also derived numerical examples verify the advantages of the proposed algorithm over the lx technique and validate our analytical results

blind equalization and multiuser detection in dispersive cdma channels the problem of blind demodulation of multiuser information symbols in a high rate code division multiple access cdma network in the presence of both multiple access interference mai and intersymbol interference isi is considered the dispersive cdma channel is first cast into a multiple input multiple output mimo signal model framework by applying the theory of blind mimo channel identification and equalization it is then shown that under certain conditions the multiuser information symbols can be recovered without any prior knowledge of the channel or the users signature waveforms including the desired user s signature waveform although the algorithmic complexity of such an approach is prohibitively high however in practice the signature waveform of the user of interest is always available at the receiver it is shown that by incorporating this knowledge the impulse response of each user s dispersive channel can be identified using a subspace method it is further shown that based on the identified signal subspace parameters and the channel response two linear detectors that are capable of suppressing both mai and isi i e a zero forcing detector and a minimum mean square error mmse detector can be constructed in closed form at almost no extra computational cost data detection can then be furnished by applying these linear detectors obtained blindly to the received signal the major contribution of this paper is the development of these subspace based blind techniques for joint suppression of mai and isi in the dispersive cdma channels

widely linear versus linear blind multiuser detection with subspace based channel estimation finite sample size effects in a recent paper a s cacciapuoti et al ldquofinite sample performance analysis of widely linear multiuser receivers in ds cdma systems ieee transactions on signal processing vol 56 no 4 pp 1572 1588 apr 2008 we presented the finite sample theoretical performance comparison between linear l and widely linear wl minimum output energy moe receivers for direct sequence code division multiple access ds cdma systems worked out under the assumption that the channel impulse response of the desired user is exactly known the main scope of this paper is to extend such an analysis taking into account not only autocorrelation matrix acm estimation effects but also the accuracy of subspace based blind channel estimation ce we aim to answer the two following questions which of the two estimation processes acm or ce is the main source of degradation when implementing the receivers on the basis of a finite sample size compared with the l moe one is the finite sample wl moe receiver with blind ce capable of achieving the performance gains predicted by the theory to this goal simple and easily interpretable formulas are developed for the signal to interference plus noise ratio sinr at the output of the l and wl moe receivers with blind ce when they are implemented using either the sample acm or its eigendecomposition in addition the derived formulas which are validated by simulations allow one to recognize and discuss interesting tradeoffs between the main parameters of the ds cdma system

optimum multiuser asymptotic efficiency the degradation in bit error rate due to the presence of multiple access interference in a white gaussian channel can be measured by the multiuser asymptotic efficiency defined as the ratio between the snr required to achieve the same uncoded bit error rate in the absence of interfering users and the actual snr in this paper the asymptotic efficiency of the optimum multiuser demodulator a bank of matched filters followed by a viterbi algorithm is investigated and compared to that of the conventional single user matched filter receiver the computation of the optimum asymptotic efficiency of any given user is equivalent to the minimization of the euclidean distance between any pair of multiuser signals which differ in at least one of the symbols of that user it is shown that the optimum multiuser efficiency of asynchronous systems is nonzero with probability 1 and therefore the optimum demodulator does not become multiple access limited in contrast to the single user receiver a class of signal constellations with moderate cross correlation requirements is shown to achieve unit optimum multiuser efficiencies and hence to be equivalent to orthogonal signal sets from the viewpoint of performance of the optimum multiuser detector

numerical validation of solutions of linear complementarity problems this paper proposes a validation method for solutions of linear complementarity problems the validation procedure consists of two sufficient conditions that can be tested on a digital computer if the first condition is satisfied then a given multidimensional interval centered at an approximate solution of the problem is guaranteed to contain an exact solution if the second condition is satisfied then the multidimensional interval is guaranteed to contain no exact solution this study is based on the mean value theorem for absolutely continuous functions and the reformulation of linear complementarity problems as nonsmooth nonlinear systems of equations

mmse interference suppression for direct sequence spread spectrum cdma we consider interference suppression for direct sequence spread spectrum code division multiple access cdma systems using the minimum mean squared error mmse performance criterion the conventional matched filter receiver suffers from the near far problem and requires strict power control typically involving feedback from receiver to transmitter for acceptable performance multiuser detection schemes previously proposed mitigate the near far problem but are complex and require explicit knowledge or estimates of the interference parameters in this paper we present and analyze several new mmse interference suppression schemes which have the advantage of being near far resistant to varying degrees depending on their complexity and can be implemented adaptively when interference parameters are unknown and or time varying numerical results are provided that show that these schemes offer significant performance gains relative to the matched filter receiver we conclude that mmse detectors can alleviate the need for stringent power control in cdma systems and may be a practical alternative to the matched filter receiver

linear multiuser detectors for synchronous code division multiple access channels under the assumptions of symbol synchronous transmissions and white gaussian noise the authors analyze the detection mechanism at the receiver comparing different detectors by their bit error rates in the low background noise region and by their worst case behavior in a near far environment where the received energies of the users are not necessarily similar optimum multiuser detection achieves important performance gains over conventional single user detection at the expense of computational complexity that grows exponentially with the number of users it is shown that in the synchronous case the performance achieved by linear multiuser detectors is similar to that of optimum multiuser detection attention is focused on detectors whose linear memoryless transformation is a generalized inverse of the matrix of signature waveform crosscorrelations and on the optimum linear detector it is shown that the generalized inverse detectors exhibit the same degree of near far resistance as the optimum multiuser detectors the optimum linear detector is obtained

a generalized minimum mean output energy strategy for cdma systems with improper mai it has been shown that in a direct sequence code division multiple access ds cdma system employing binary phase shift keying bpsk modulation the baseband equivalent of the cdma multiplex is under very mild assumptions an improper complex random process i e it has a nonzero pseudoautocorrelation function the problem of linear multiuser detection for asynchronous ds cdma systems with improper multiaccess interference mai is considered a new mean output energy moe cost function is introduced whose constrained minimization leads to two new linear multiuser detectors exploiting the information contained in the pseudoautocorrelation of the observables and which generalize the classical decorrelating and minimum mean square error mmse receivers the problem of blind adaptive receiver implementation based on subspace tracking is also tackled finally the superiority of the new detectors with respect to the classical linear detection structures present in the literature is demonstrated through both theoretical considerations and computer simulations

adaptive power techniques for blind channel estimation in cdma systems the problem of blind adaptive channel estimation in code division multiple access cdma systems is considered motivated by the iterative power method which is used in numerical analysis for estimating singular values and singular vectors we develop recursive least squares rls and least mean squares lms subspace based adaptive algorithms in order to identify the impulse response of the multipath channel the schemes proposed in this paper use only the spreading code of the user of interest and the received data and are therefore blind both versions rls and lms exhibit rapid convergence combined with low computational complexity with the help of simulations we demonstrate the improved performance of our methods as compared with the already existing techniques in the literature

blind adaptive constrained constant modulus reduced rank interference suppression algorithms based on interpolation and switched decimation this work proposes a blind adaptive reduced rank scheme and constrained constant modulus ccm adaptive algorithms for interference suppression in wireless communications systems the proposed scheme and algorithms are based on a two stage processing framework that consists of a transformation matrix that performs dimensionality reduction followed by a reduced rank estimator the complex structure of the transformation matrix of existing methods motivates the development of a blind adaptive reduced rank constrained barc scheme along with a low complexity reduced rank decomposition the proposed barc scheme and a reduced rank decomposition based on the concept of joint interpolation switched decimation and reduced rank estimation subject to a set of constraints are then detailed the proposed set of constraints ensures that the multipath components of the channel are combined prior to dimensionality reduction we develop low complexity joint interpolation and decimation techniques stochastic gradient and recursive least squares reduced rank estimation algorithms a model order selection algorithm for adjusting the length of the estimators is devised along with techniques for determining the required number of switching branches to attain a predefined performance an analysis of the convergence properties and issues of the proposed optimization and algorithms is carried out and the key features of the optimization problem are discussed we consider the application of the proposed algorithms to interference suppression in ds cdma systems the results show that the proposed algorithms outperform the best known reduced rank schemes while requiring lower complexity

the use of fuzzy outranking relations in preference modelling this paper deals with preference modelling in the context of decision aid in this framework conflicting systems of logic uncertain knowledge ambiguous positions are always present in order to tackle this problem a multiple criteria methodology is proposed mainly based on fuzzy outranking relations introduced both at one dimensional and multi dimensional levels some properties of outranking relations are investigated such relations are then combined using fuzzy logical connectives to generate relational systems of fuzzy preferences that are shown to be very useful to reflect the vagueness of information in the various preference situations that may be considered in the modelling process

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

low complexity blind detection of ds cdma signals auxiliary vector receivers a fresh look on the design of practical low complexity direct sequence code division multiple access ds cdma receivers is proposed from the wiener reconstruction filter point of view the natural outcome is the emergence of a new class of linear scalar parameterized auxiliary vector receivers filters then the blind optimization of these receivers in the maximum signal to interference plus noise ratio sinr sense becomes a straightforward procedure the conceptual and computational simplicity of this general approach promises immediate practical utility this new generation of receivers exhibits minimal optimization requirements and near matched filter mf operational complexity yet theoretical arguments supported by numerical and simulation results included in this work suggest that the blind auxiliary vector receiver compares favorably both complexity wise and performance wise to multiuser mu detectors such as the minimum output energy moe and the decorrelating receiver although the latter utilizes the assumed known spreading codes of all interfering users

electre tri nb a new multiple criteria ordinal classification method abstract this paper presents a new method for multiple criteria ordinal classification sorting problems in an ordinal classification problem the categories also called classes in related literature are pre defined and ordered from the best to the worst or from the worst to the best the actions not necessarily known a priori are assigned to the different ordered categories several electre type methods were designed to deal with this kind of problem however none of them proposes a characterization of the categories through a set of limiting profiles this is the novelty of the current method which may be considered as an extension of electre tri b it fulfills a set of structural requirements uniqueness of the assignments independence monotonicity homogeneity conformity and stability with respect to merging and splitting operations all these features will be presented in the current paper and illustrated through three examples

electre tri c a multiple criteria sorting method based on characteristic reference actions in this paper a new sorting method following a decision aiding constructive approach is proposed this method is called electre tri c as a sorting method a set of categories must be defined to represent the way in which the actions that are going to be assigned to each of them should further be processed this method is appropriate to deal with decision aiding contexts where the categories are completely ordered and each of them is defined through a single characteristic reference action the set of characteristic actions should be co constructed through an interactive process between the analyst and the decision maker electre tri c has been conceived to verify a set of natural structural requirements conformity homogeneity monotonicity and stability which can be viewed as its fundamental properties this method is composed of two joint rules called descending rule and ascending rule which must be used conjointly and not separately each one of these rules selects only one category or a range of possible categories for a possible assignment of an action this assignment depends on the comparison of such an action to the characteristic actions according to a chosen credibility level numerical examples are also presented in order to illustrate the main theoretical results provided by the method

multicriteria sorting using a valued preference closeness relation abstract to define a metric or a similarity relation with good properties is a crucial issue in most analogy and rule induction oriented methods for multicriteria sorting here we propose a valued indifference closeness relation which is inspired on concordance and discordance measures the criterion weights are obtained from the preferential information embedded in a reference set this proposal performs very well in several practical problems

blind subspace based signature estimation in ds cdma systems with unknown wide sense stationary interference in this paper we propose a new blind subspace based signature waveform estimation technique for direct sequence code division multiple access ds cdma communication systems operating in the presence of unknown wide sense stationary interference unlike the existing algorithms the proposed technique requires just a single receive antenna and is applicable to the case of arbitrary transmitted symbol constellations necessary and sufficient conditions for identifiability of the proposed technique are derived for practical scenarios where the data covariance matrix is estimated using a finite number of samples a closed form expression for the mean squared error mse of the estimated channel is obtained for the high signal to interference ratio sir regime and gaussian interference an approximation of the mse expression is also derived and the effects of different parameters on the performance of the proposed algorithm are analyzed numerical examples validate our analytical results

widely linear equalization and blind channel identification for interference contaminated multicarrier systems this work addresses the problem of designing efficient detection techniques for multicarrier transmission systems operating in the presence of narrowband interference nbi in this case conventional linear receivers such as the zero forcing zf or the minimum mean square error mmse ones usually perform poorly since they are not capable of suppressing satisfactorily the nbi to synthesize interference resistant detection algorithms we resort to widely linear wl filtering which allows one to exploit the noncircularity property of the desired signal constellation by jointly processing the received signal and its complex conjugate version in particular we synthesize new wl zf receivers for multicarrier systems which mitigate in the minimum output energy moe sense the nbi contribution at the receiver output without requiring knowledge of the nbi statistics by exploiting the noncircularity property we also propose a new subspace based blind channel identification algorithm and derive the channel identifiability condition blind identification can be performed satisfactorily also in the presence of nbi requiring only an approximate rank determination of the nbi autocorrelation matrix the performance analysis shows that the proposed moe wl zf receiver even when implemented blindly assures a substantial improvement over the conventional linear zf and mmse ones particularly when the nbi bandwidth is very small in comparison with the intercarrier spacing and the nbi is not exactly located on a subcarrier

multicriteria fuzzy classification procedure procftn methodology and medical application in this paper we introduce a new classification procedure for assigning objects to predefined classes named procftn this procedure is based on a fuzzy scoring function for choosing a subset of prototypes which represent the closest resemblance with an object to be assigned it then applies the majority voting rule to assign an object to a class we also present a medical application of this procedure as an aid to assist the diagnosis of central nervous system tumours the results are compared with those obtained by other classification methods reported on the same data set including decision tree production rules neural network k nearest neighbor multilayer perceptron and logistic regression our results are very encouraging and show that the multicriteria decision analysis approach can be successfully used to help medical diagnosis

exact and approximate maximum likelihood parameter estimation for quasi synchronous cdma signals in order to construct the optimal decorrelator for a quasi synchronous qs code division multiple access receiver it is necessary to estimate the user delays however in a qs system it is shown that delay estimation is equivalent to estimating a parameter vector which is related linearly to the received signal an exact maximum likelihood ml solution using alternating maximization is first developed for joint estimation of the user delay vectors and amplitudes suboptimal recursive least squares rls and least mean square algorithms are then presented which approximate the true ml solution it is shown that the optimal decorrelator and demodulated symbols are also generated by the rls algorithm simulation and analytical results are presented for the bit error rate performance of the adaptive receiver and the average squared error of the estimated delay vectors is compared with the cramer rao bound

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

blind multiuser detection a subspace approach a new multiuser detection scheme based on signal subspace estimation is proposed it is shown that under this scheme both the decorrelating detector and the linear minimum mean square error mmse detector can be obtained blindly i e they can be estimated from the received signal with the prior knowledge of only the signature waveform and timing of the user of interest the consistency and asymptotic variance of the estimates of the two linear detectors are examined a blind adaptive implementation based on a signal subspace tracking algorithm is also developed it is seen that compared with the previous minimum output energy blind adaptive multiuser detector the proposed subspace based blind adaptive detector offers lower computational complexity better performance and robustness against signature waveform mismatch two extensions are made within the framework of signal subspace estimation first a blind adaptive method is developed for estimating the effective user signature waveform in the multipath channel secondly a multiuser detection scheme using spatial diversity in the form of an antenna array is considered a blind adaptive technique for estimating the array response for diversity combining is proposed it is seen that under the proposed subspace approach blind adaptive channel estimation and blind adaptive array response estimation can be integrated with blind adaptive multiuser detection with little attendant increase in complexity

shrinkage linear and widely linear complex valued least mean squares algorithms for adaptive beamforming in this paper shrinkage linear complex valued least mean squares sl clms and shrinkage widely linear complex valued least mean squares swl clms algorithms are devised for adaptive beamforming by exploiting the relationship between the noise free a posteriori and a priori error signals the sl clms method is able to provide a variable step size to update the weight vector for the adaptive beamformer significantly enhancing the convergence speed and decreasing the steady state misadjustment on the other hand besides adopting a variable step size determined by minimizing the square of the augmented noise free a posteriori errors the swl clms approach exploits the noncircular properties of the signal of interest which considerably improves the steady state performance simulation results are presented to illustrate their superiority over the clms complex valued normalized lms variable step size recursive least squares rls algorithms and their corresponding widely linear based schemes additionally our proposed algorithms are more computationally efficient than the rls solutions though they may have a slightly slower convergence rate

an alternate derivation of the distribution of the conditioned signal to noise ratio a result in multiple regression analysis is used to derive the probability distribution of the conditioned signal to noise ratio

data record based criteria for the selection of an auxiliary vector estimator of the mmse mvdr filter when the auxiliary vector av filter generation algorithm utilizes sample average estimated input data statistics it provides a sequence of estimates of the ideal minimum mean square error or minimum variance distortionless response filter for the given signal processing receiver design application evidently early nonasymptotic elements of the sequence offer favorable bias variance balance characteristics and outperform in mean square filter estimation error the unbiased sample matrix inversion smi estimator as well as the constraint least mean square recursive least squares multistage nested wiener filter and diagonally loaded smi filter estimators selecting the most successful in some appropriate sense av filter estimator in the sequence for a given data record is a critical problem that has not been addressed so far we deal exactly with this problem and we propose two data driven selection criteria the first criterion minimizes the cross validated sample average variance of the av filter output and can be applied to general filter estimation problems the second criterion maximizes the estimated j divergence of the av filter output conditional distributions and is tailored to binary phase shift keying type detection problems

an iterative method for a system of linear complementarity problems with perturbations and interval data in this paper we introduce a total step method for solving a system of linear complementarity problems with perturbations and interval data it is applied to two interval matrices a and b and two interval vectors b and c we prove that the sequence generated by the total step method converges to x y which includes the solution set for the system of linear complementarity problems defined by any fixed email protected a email protected b email protected b and email protected c we also consider a modification of the method and show that if we start with two interval vectors containing the limits then the iterates contain the limits we close our paper with two examples which illustrate our theoretical results

towards multicriteria clustering an extension of the k means algorithm abstract the research within the multicriteria classification field is mainly focused on the assignment of actions to pre defined classes nevertheless the building of multicriteria categories remains a theoretical question still not studied in detail to tackle this problem we propose an extension of the well known k means algorithm to the multicriteria framework this extension relies on the definition of a multicriteria distance based on the preference structure defined by the decision maker thus two alternatives will be similar if they are preferred indifferent and incomparable to more or less the same actions armed with this multicriteria distance we will be able to partition the set of alternatives into classes that are meaningful from a multicriteria perspective finally the examples of the country risk problem and the diagnosis of firms will be treated to illustrate the applicability of this method

asymptotic performance analysis of blind minimum output energy receivers for large ds cdma systems the random matrix theory is used to analyze the asymptotic performance of the blind minimum output energy moe receiver in direct sequence code division multiple access ds cdma systems in the presence of unknown multipath channel under the condition that the spreading factor and the number of users go to infinity with the same rate as a special case the asymptotic properties of the blind capon receiver are also studied and the conditions of convergence of the signal to interference plus noise ratio sinr of this receiver to that of the optimal minimum mean square error mmse receiver are discussed in particular it is shown that the sinr performances of the capon and mmse receivers are nearly identical in the uplink scenario while the performance of the capon receiver may be considerably inferior to that of the mmse receiver in the downlink transmission case as the performance of the capon receiver is closely related to the performance of the capon channel estimator the asymptotic properties of the latter estimator are also studied and the conditions of convergence of the capon channel estimate to a scaled version of the channel vector of the user of interest are obtained

design and analysis of supervised and decision directed estimators of the mmse lcmv filter in data limited environments we consider sample matrix inversion smi type estimates of the minimum mean square error mmse and the linearly constrained minimum variance lcmv linear filters obtained from data records of limited size we quantify theoretically the detrimental effect of the desired signal energy level on the mean square ms filter estimation error and the normalized output signal to interference plus noise ratio sinr by deriving a new exact analytical expression and a lower bound respectively for cases where accumulation of pure disturbance observations is not possible we show theoretically how certain intuitive pilot assisted and decision directed adaptive filter implementations that utilize desired signal present data observations perform close to their desired signal absent counterparts simulation studies illustrate our theoretical developments in the context of spread spectrum communications over multipath fading channels under perfect and nonperfect synchronization

adaptive convergence of linearly constrained beamformers based on the sample covariance matrix a statistical analysis of the adaptive convergence behavior of linearly constrained beamformers is given assuming the sample covariance estimator is used to estimate the covariance matrix the sensor data are assumed to be gaussian distributed and independent from data vector to data vector the output power and mean squared error in the absence of the desired signal are shown to be multiples of chi squared random variables the presence of the desired signal results in an excess mean squared error that is beta distributed and depends only on the signal power number of data vectors and number of adaptive degrees of freedom the expected value of the excess mean squared error resulting from the signal presence is directly proportional to the signal power and number of adaptive degrees of freedom but is inversely proportional to the number of data vectors

a multicriteria assignment procedure for a nominal sorting problematic abstract this paper addresses the problem of the assignment of an action in the particular case where the categories defined a priori are not ordered in multicriteria literature it is the nominal sorting problematic we propose a simple and easy method to understand the procedure of assignment to tackle this problematic afterwards we shall illustrate the proposed method by using an example that is inspired by a research carried out the construction sector of the work accident prevention field

blind equalization without gain identification blind equalization up to a constant gain of linear time invariant channels is studied dropping the requirement of gain identification allows equalizer anchoring this results in the elimination of a degree of freedom that causes ill convergence of conventional blind equalizers and affords the possibility of using simple update rules based on the stochastic approximation of output energy unlike conventional blind equalizers truncations of the nonrecursive infinite dimensional realizations of those equalizers inherit the convergence properties of their infinitely parametrized counterparts a globally convergent blind recursive equalizer for channels without all pass sections is obtained based on the exact equalization of the minimum phase part of the channel and the identification of its nonminimum phase zeros

high snr performance analysis of blind minimum output energy receivers for large ds cdma systems high signal to noise ratio snr properties of the minimum output energy moe receiver and the capon channel estimation technique are analyzed in the case of large direct sequence code division multiple access ds cdma systems it is shown that if the noise power tends to zero and the system load is less than one then the signal to interference plus noise ratio sinr of the moe receiver tends to infinity and the capon channel estimate converges to a scaled version of the channel vector of the user of interest for the case when the system load is larger than one an asymptotic sinr expression is obtained furthermore expressions for the efficiency and asymptotic efficiency of the moe receiver are derived simple approximations of and upper lower bounds on these expressions are found and the effects of the system physical parameters on the performance of the moe receiver are discussed