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

on the relationship between robust minimum variance beamformers with probabilistic and worst case distortionless response constraints an interesting relationship between the probability constrained and worst case optimization based robust minimum variance mv beamformers has been discovered it is shown that both in the cases of circularly symmetric gaussian and worst case distributions of the steering vector mismatch the probability constrained robust mv beamforming problem can be tightly approximated as a convex second order cone programming socp problem the latter problem is mathematically equivalent to that resulting from the deterministic worst case approach and therefore probability constrained beamformers can be interpreted and implemented using their deterministic worst case counterparts however an important advantage of the developed probability constrained mv beamformers with respect to their standard worst case counterparts is that the former approaches enable to explicitly quantify the parameters of the uncertainty region in terms of the beamformer outage probability

detection of signals by information theoretic criteria a new approach is presented to the problem of detecting the number of signals in a multichannel time series based on the application of the information theoretic criteria for model selection introduced by akaike aic and by schwartz and rissanen mdl unlike the conventional hypothesis testing based approach the new approach does not requite any subjective threshold settings the number of signals is obtained merely by minimizing the aic or the mdl criteria simulation results that illustrate the performance of the new method for the detection of the number of signals received by a sensor array are presented

a subspace method for signature waveform estimation in synchronous cdma systems synchronous code division multiple access cdma techniques possess intrinsic protection against co channel interference due to orthogonal codes employed and thus offers higher capacity than existing frequency division multiple access fdma or time division multiple access tdma systems in the presence of multipath however each signal is subject to frequency selective fading and the orthogonality condition does not necessarily hold leading to increased cross correlation in these scenarios multiuser detection need to be performed to suppress interference and recover the message symbols to implement such a technique explicit knowledge of the nonorthogonal signature waveforms of all users is required we propose a blind estimation scheme that provides closed form estimates of the signature waveforms by exploiting the structure information of the data output in particular we show that the subspace of the data matrix contains sufficient information for unique determination of the signature waveforms based on this observation a multiple signal classification music like algorithm is derived performance analysis of the new approach is also presented

subspace based channel estimation for code division multiple access communication systems we consider the estimation of channel parameters for code division multiple access cdma communication systems operating over channels with either single or multiple propagation paths the multiuser channel estimation problem is decomposed into a series of single user problems through a subspace based approach by exploiting the eigenstructure of the received signal s sample correlation matrix the observation space can be partitioned into a signal subspace and a noise subspace without prior knowledge of the unknown parameters the channel estimate is formed by projecting a given user s spreading waveform into the estimated noise subspace and then either minimizing the likelihood or minimizing the euclidean norm of this projection both of these approaches yield algorithms which are near far resistant and do not require a preamble

robust constrained optimization based linear receiver for high rate mimo ofdm against channel estimation errors we consider multi input multi output orthogonal frequency division multiplexing mimo ofdm transmission in a scenario that the adopted cyclic prefix cp length is shorter than the channel delay spread for boosting data rate and moreover the channel parameters are not exactly known but are estimated using the least squares ls training technique by exploiting the receiver spatial resource we propose a constrained optimization based linear equalizer which can mitigate inter symbol interference and inter carrier interference incurred by insufficient cp interval and is robust against the net detrimental effects caused by channel estimation errors the optimization problem is formulated in an equivalent unconstrained generalized sidelobe canceller gsc setup the channel parameter error is explicitly incorporated into the constraint free gsc system model through the perturbation technique this allows us to exploit the presumed ls channel error property for deriving a closed form solution and can also facilitate an associated analytic performance analysis a closed form approximate signal to interference plus noise ratio sinr expression for the proposed robust scheme is given and an appealing formula of the achievable sinr improvement over the nonrobust counterpart is further specified our analytic results bring out several intrinsic features of the proposed solution simulation study confirms the effectiveness of the proposed method and corroborates the predicted sinr results

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

on information theoretic criteria for determining the number of signals in high resolution array processing an important problem in high resolution array processing is the determination of the number of signals arriving at the array information theoretic criteria provide a means to achieve this two commonly used criteria are the akaike information criterion aic and minimum descriptive length mdl criterion while the aic tends to overestimate even at a high signal to noise ratio snr the mdl criterion tends to underestimate at low or moderate snr by excluding irrelevant parameters a new log likelihood function has been chosen utilizing this new log likelihood function gives a set of more accurate estimates of the eigenvalues and in the establishment of modified information theoretic criteria which moderate the performance of the aic and the mdl criterion computer simulations confirm that the modified criteria have superior performance

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

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

detection of the number of coherent signals by the mdl principle an approach is presented to the problem of detecting the number of sources impinging on a passive sensor array that is based on j rissanen s 1983 minimum description length mdl principle the approach is applicable to any type of sources including the case of sources which are fully correlated referred to as the coherent signals case two slightly different detection criteria are derived both requiring the estimation of the locations of the sources the first is tailored to the detection problem per se whereas the second is tailored to the combined detection estimation problem consistency of the two criteria is proved and their performance is demonstrated by computer simulations

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

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

on the second order statistics of the weighted sample covariance matrix the second order statistics of the sample covariance are encountered in many covariance based processing algorithms this paper derives closed form expressions for the covariance of the weighted sample covariance matrix with an arbitrary weight for both a real system and complex system given a system model the results explicitly rely on the second order and fourth order statistics of the channel noise and inputs they are shown to coincide with the existing results when the channel inputs and noise are gaussian distributed our results can be directly applied to analyze the statistical properties of subspace based channel estimation methods for single input multiple output simo systems and code division multiple access cdma systems numerical examples are provided to further verify analyses

blind startup of mmse receivers for cdma systems this paper presents a novel technique for blindly starting up a minimum mean squared error mmse receiver for a user newly entering a code division multiple access cdma system it is assumed that only one user at a time is admitted into the system and that data before and after the onset of the new transmission are available the technique is based on the generalized eigendecomposition of the two corresponding autocorrelation matrices before and after the new user is admitted in general the two autocorrelation matrices differ by a low rank matrix contributed by the autocorrelation of the new user signal this fact yields the useful property that the generalized eigenvectors corresponding to the minimum eigenvalue span the noise subspace of the low rank signal term exploiting this subspace relation the signature of the new user can be identified if in particular the difference between the two autocorrelation matrices is exactly a rank one matrix then there is only one maximum eigenvalue and the corresponding eigenvector coincides with the mmse receiver corresponding to the rank one signal term these properties are also applicable to long code cdma systems to provide an optimal multipath combining method

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

robust adaptive beamforming for general rank signal models the performance of adaptive beamforming methods is known to degrade severely in the presence of even small mismatches between the actual and presumed array responses to the desired signal such mismatches may frequently occur in practical situations because of violation of underlying assumptions on the environment sources or sensor array this is especially true when the desired signal components are present in the beamformer training data snapshots because in this case the adaptive array performance is very sensitive to array and model imperfections the similar phenomenon of performance degradation can occur even when the array response to the desired signal is known exactly but the training sample size is small we propose a new powerful approach to robust adaptive beamforming in the presence of unknown arbitrary type mismatches of the desired signal array response our approach is developed for the most general case of an arbitrary dimension of the desired signal subspace and is applicable to both the rank one point source and higher rank scattered source fluctuating wavefront desired signal models the proposed robust adaptive beamformers are based on explicit modeling of uncertainties in the desired signal array response and data covariance matrix as well as worst case performance optimization simple closed form solutions to the considered robust adaptive beamforming problems are derived our new beamformers have a computational complexity comparable with that of the traditional adaptive beamforming algorithms while at the same time offer a significantly improved robustness and faster convergence rates

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

detecting the number of signals in wireless ds cdma networks in this paper a new information theoretic algorithm is proposed for signal enumeration in ds cdma networks the approach is based on the predictive description length pdl of the observation vector the pdl is the length of a predictive code of observations for signal detection the pdl criterion is computed for the candidate models and is minimized to determine the number of signals the proposed technique uses the maximum likelihood ml estimate of the correlation matrix the only information used in the ml estimation of the correlation matrix is the multiplicity of the smallest eigenvalue the pdl algorithm has a signal to noise ratio resolution threshold that is smaller than that of the minimum description length mdl the proposed method can be used on line and can be applied to time varying and non stationary systems

filtering design for two dimensional markovian jump systems with state delays and deficient mode information this paper is concerned with the problem of h filtering for a class of two dimensional markovian jump linear systems described by the fornasini marchesini local state space model the systems under consideration are subject to state delays and deficient mode information in the markov chain the description of deficient mode information is comprehensive that simultaneously includes the exactly known partially unknown and uncertain transition probabilities by invoking the properties of the transition probability matrix together with the convexification of uncertain domains a new h performance analysis criterion for the filtering error system is firstly derived then via some matrix inequality linearisation procedures two approaches for the filter synthesis are proposed it is shown that both the full order and reduced order filters can be constructed by solving a set of linear matrix inequalities finally simulation studies are provided to illustrate the effectiveness of the proposed design methods

traveling salesman games in this paper we discuss the problem of how to divide the total cost of a round trip along several institutes among the institutes visited we introduce two types of cooperative games fixed route traveling salesman games and traveling salesman games as a tool to attack this problem under very mild conditions we prove that fixed route traveling salesman games have non empty cores if the fixed route is a solution of the classical traveling salesman problem core elements provide us with fair cost allocations a traveling salesman game may have an empty core even if the cost matrix satisfies the triangle inequality in this paper we introduce a class of matrices defining ts games with non empty cores

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

robust linear receivers for space time block coded multiaccess mimo systems with imperfect channel state information recently several linear receiver algorithms have been developed for space time block coded multiaccess multiple input multiple output mimo wireless communication systems all these techniques are based on the assumption that the channel state information csi at the receiver side is perfect however in practical situations the available csi may be imperfect because of channel estimation errors and or outdated training in this paper we develop new robust linear receiver techniques for joint space time decoding and interference rejection in multiaccess mimo systems that use orthogonal space time block codes and erroneous csi the proposed receivers are based on worst case performance optimization they are shown to provide a substantially improved robustness against csi mismatches as compared with the existing linear multiaccess mimo receivers

gaussian process regressors for multiuser detection in ds cdma systems in this paper we present gaussian processes for regression gpr as a novel detector for cdma digital communications particularly we propose gpr for constructing analytical nonlinear multiuser detectors in cdma communication systems gpr can easily compute the parameters that describe its nonlinearities by maximum likelihood thereby no cross validation is needed as it is typically used in nonlinear estimation procedures the gpr solution is analytical given its parameters and it does not need to solve an optimization problem for building the nonlinear estimator these properties provide fast and accurate learning two major issues in digital communications the gpr with a linear decision function can be understood as a regularized mmse detector in which the regularization parameter is optimally set we also show the gpr receiver to be a straightforward nonlinear extension of the linear minimum mean square error mmse criterion widely used in the design of these receivers we argue the benefits of this new approach in short codes cdma systems where little information on the users codes users amplitudes or the channel is available the paper includes some experiments to show that gpr outperforms linear mmse and nonlinear svm state ofthe art solutions

robust constrained linear receivers for cdma wireless systems for code division multiple access cdma communication systems many constrained linear receivers have been developed to suppress multiple access interference the linearly constrained formulations are generally sensitive to multipath fading and other types of signal mismatch we develop robust linear receivers by exploring appropriate constraints multiple linear constraints are exploited to preserve the output energy that is scattered in multipath channels in addition a quadratic inequality constraint on the weight vector norm is used to improve robustness with respect to imprecise signal modeling these constraints can be applied to the minimum output energy moe detector to mitigate the signal mismatch problem and to the decision directed minimum mean square error mmse detector to prevent error propagation and eliminate the need for training sequences at startup adaptive implementations for the proposed detectors are presented using recursive least square rls updating in both the direct form and the partitioned linear interface canceller plic structure simulations are performed in a multipath propagation environment to illustrate the performance of the proposed detectors

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