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

a chip based multiuser detector for the downlink of a ds cdma system using a folded state transition trellis the maximum likelihood sequence estimation mlse multiuser detector has very good performance but at the expense of high computational complexity the viterbi algorithm is employed to implement the mlse in the asynchronous uplink in this scheme the various bit combinations are taken to be the different states in the decoding trellis however the number of states increases exponentially with the number of active users we propose a scheme that exploits the feature of power equality in the downlink to reduce the number of states involved each transmitted chip value can only take a certain number of possible discrete values using these discrete values as the states in the transition trellis diagram and operating the viterbi algorithm at the chip level the number of states is reduced from 4 sup k to k 1 sup l where k is the number of users and l is the number of paths in the multipath channel

new algorithms for euclidean distance transformation of an n dimensional digitized picture with applications abstract in this paper we propose a new method to obtain the euclidean distance transformation and the voronoi diagram based on the exact euclidean metric for an n dimensional picture we present four algorithms to perform the transformation which are constructed by the serial composition of n dimensional filters when performed by a general purpose computer they are faster than the method by h yamada for a two dimensional picture those algorithms require only one n dimensional array for storing input output pictures and a single one dimensional array for a work area if an input picture needs not be preserved

a recursive linear detection algorithm for asynchronous cdma communication system a recursive linear detection algorithm is proposed for the detection of signals from an asynchronous direct sequence code division multiple access ds cdma communication system this algorithm works for short as well as long codes under some reasonable conditions this algorithm is proved to be stable and converges to the ideal decorrelating detector idd with a sufficiently large memory length the performance of the algorithm is analyzed in some detail upper and lower bounds for the bit error probabilities are developed it is demonstrated that the two bounds converge to the bit error probabilities of the idd as the large memory length increases simulation results show that the recursive detector proposed outperforms the truncated decorrelating detector with less memory and less computational complexity

performance analysis for the improved linear multiuser detectors in bpsk modulated ds cdma systems recently a new class of linear multiuser receivers for direct sequence code division multiple access cdma systems employing binary phase shift keying modulation has been introduced unlike classical decorrelating and minimum mean square error linear multiuser detectors the new receivers exploit the information contained in the pseudo autocorrelation of the observables and are thus capable of achieving much better performance we present new results on the performance analysis of this class of new receivers in particular with reference to a cdma system with deterministic spreading codes we show that the new receivers outperform the classical ones in terms of both error probability and near far resistance with regard instead to cdma systems with random spreading we compute the average system near far resistance showing that the new receivers can accommodate twice the number of users accommodated by the classical linear multiuser receivers

indirectly estimated adaptive detectors for code division multiple access signals this paper presents the development of indirectly estimated adaptive idea detectors for code division multiple access cdma signals in wireless communication systems multiuser cdma detection is formulated as an inverse problem in the presence of noise and the estimation of the detector parameters is accomplished using elements of regularization theory the development of autonomous cdma detectors that are capable of adjusting to the channel characteristics with the support of training sequences relies on data dependent procedures designed to reduce the effect of noise and interfering users on the performance of the detector the detector parameters can be computed by adaptive algorithms that require no matrix inversion the proposed idea detector is evaluated and compared with existing multiuser cdma detectors in terms of their robustness to noise resistance to the near far problem and ability to handle multipath signals

an efficient code timing estimator for ds cdma signals we present an efficient algorithm for estimating the code timing of a known training sequence in an asynchronous direct sequence code division multiple access ds cdma system the algorithm is a large sample maximum likelihood lsml estimator that is derived by modeling the known training sequence as the desired signal and all other signals including the interfering signals and thermal noise as unknown colored gaussian noise that is uncorrelated with the desired signal the lsml estimator is shown to be robust against the near far problem and is also compared with several other code timing estimators via numerical examples it is found that the lsml approach can offer noticeable performance improvement especially when the loading of the system is heavy

deblurring saturated night image with function form kernel deblurring saturated night images are a challenging problem because such images have low contrast combined with heavy noise and saturated regions unlike the deblurring schemes that discard saturated regions when estimating blur kernels this paper proposes a novel scheme to deduce blur kernels from saturated regions via a novel kernel representation and advanced algorithms our key technical contribution is the proposed function form representation of blur kernels which regularizes existing matrix form kernels using three functional components 1 trajectory 2 intensity and 3 expansion from automatically detected saturated regions their skeleton brightness and width are fitted into the corresponding three functional components of blur kernels such regularization significantly improves the quality of kernels deduced from saturated regions second we propose an energy minimizing algorithm to select and assign the deduced function form kernels to partitioned image regions as the initialization for non uniform deblurring finally we convert the assigned function form kernels into matrix form for more detailed estimation in a multi scale deconvolution experimental results show that our scheme outperforms existing schemes on challenging real examples

penrose demosaicking the penrose pixel layout an aperiodic pixel layout in rhombus penrose tiling has been shown to substantially outperform the existing square pixel layout in super resolution however it was tested only on grayscale images to study its performance on color images we have to reconstruct regular color images from penrose raw images i e images with only one color component at each penrose pixel resulting in the problem of demosaicking from penrose pixels penrose demosaicking is more difficult than regular demosaicking because none of the color components of the reconstructed regular color images are available therefore most of the traditional demosaicking methods do not apply we develop a sparse representation based method for penrose demosaicking extensive experiments show that penrose pixel layout outperforms regular pixel layouts in terms of both perceptual evaluation and s cielab the penrose pixel layout is unique among all irregular layouts because it is uniformly three colorable and it has only two pixel shapes thick and thin rhombi making its manufacturing relatively easy

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

automated graph based analysis and correction of cortical volume topology the human cerebral cortex is topologically equivalent to a sheet and can be considered topologically spherical if it is closed at the brainstem low level segmentation of magnetic resonance mr imagery typically produces cerebral volumes whose tessellations are not topologically spherical the authors present a novel algorithm that analyzes and constrains the topology of a volumetric object graphs are formed that represent the connectivity of voxel segments in the foreground and background of the image these graphs are analyzed and minimal corrections to the volume are made prior to tessellation the authors apply the algorithm to a simple test object and to cerebral white matter masks generated by a low level tissue identification sequence the authors tessellate the resulting objects using the marching cubes algorithm and verify their topology by computing their euler characteristics a key benefit of the algorithm is that it localizes the change to a volume to the specific areas of its topological defects

convergence analysis of self adaptive equalizers a theoretical analysis of self adaptive equalization for data transmission is carried out starting from known convergence results for the corresponding trained adaptive filter the development relies on a suitable ergodicity model for the sequence of observations at the output of the transmission channel thanks to the boundedness of the decision function used for data recovery it can be proved that the algorithm is bounded strong convergence results can be reached when a perfect noiseless equalizer exists the algorithm will converge to it if the eye pattern is initially open otherwise convergence may take place towards certain other stationary points of the algorithm for which domains of attraction have been defined some of them will result in a poor error rate the case of a noisy channel exhibits limit points for the algorithm that differ from those of the classical trained algorithm the stronger the noise the greater the difference is one of the principal results of this study is the proof of the stability of the usual decision feedback algorithms once the learning period is over

a multiuser receiver for code division multiple access communications over multipath channels a multiuser communication system is considered where k users share a channel with multipath propagation by using code division for multiple access data modulation is carried out by binary phase shift keying and direct sequence spread spectrum signaling the micro cellular communication media is modeled as a frequency selective fading channel with multipath propagation the multipath diversity of the received signals from the k users is exploited by a bank of k rake correlators algorithms based on the maximum likelihood rule have been developed for estimating the complex channel coefficients as well as for detection of the desired data packets from the sufficient statistics provided by the rake correlators the performance of the resulting multiuser detector is evaluated analytically and via monte carlo simulations the results indicate that the estimator of the channel coefficients has a variance close to the cramer rao lower bound and that the proposed multiuser detector is capable of eliminating the near far effect as well as processing the signals propagated through multiple paths

strongly normal sets of contractible tiles in n dimensions the second and third authors and others have studied collections of usually convex tiles a generalization of pixels or voxels in r 2 and r 3 that have a property called strong normality sn for any tile p only finitely many tiles intersect p and any nonempty intersection of those tiles also intersects p this paper extends basic results about strong normality to collections of contractible polyhedra in r n whose nonempty intersections are contractible we also give sufficient and trivially necessary conditions on a locally finite collection of contractible polyhedra in r 2 or r 3 for their nonempty intersections to be contractible

tracking properties and steady state performance of rls adaptive filter algorithms adaptive signal processing algorithms derived from ls least squares cost functions are known to converge extremely fast and have excellent capabilities to track an unknown parameter vector this paper treats analytically and experimentally the steady state operation of rls recursive least squares adaptive filters with exponential windows for stationary and nonstationary inputs a new formula for the estimation noise has been derived involving second and fourth order statistics of the filter input as well as the exponential windowing factor and filter length furthermore it is shown that the adaptation process associated with lag effects depends solely on the exponential weighting parameter in addition the calculation of the excess mean square error due to the lag for an assumed markov channel provides the necessary information about tradeoffs between speed of adaptation and steady state error it is also the basis for comparison to the simple lms algorithm in a simple case of channel identification it is shown that the lms and rls adaptive filters have the same tracking behavior finally in the last part we present new rls restart procedures applied to transversal structures for mitigating the disastrous results of the third source of noise namely finite precision arithmetic

windowing for multicarrier cdma systems the windows for achieving good multiple access performance of multicarrier code division multiple access mccdma systems employing minimum mean squared error receivers are studied the mean squared error mse is used as the performance metric for the optimization in a simplified two user system the rectangular window is found to be optimum while regarded as an inferior window in orthogonal frequency division multiplexing systems because of its spectral inefficiency necessary conditions are given for improving the performances of spectrally efficient windows by exploiting the cyclic prefix and oversampling in the frequency domain

linear multiuser detectors for incompletely known symmetric signals in cdma systems in this paper we consider a synchronous code division multiple access cdma system with a multiuser receiver all users are assumed to have symmetric signature sequences but the presence of a subset of the users is unknown to the receiver we first calculate the signal to interference ratio sir in this environment for the matched filter receiver the decorrelating receiver and the linear minimum mean square error mmse detector we then identify the user capacity for a single class system and the effective bandwidth for a multiple class system the result is compared to the case of random sequences and of optimum sequences for symmetric sequences the effective bandwidth cannot be expressed by a scalar as in because two constraints have to be satisfied simultaneously to satisfy the sir requirement we introduce a two dimensional 2 d vector notion of effective bandwidth with and without unknown users for both the decorrelator and the mmse detector the user capacity is 1 when all users are known to the receivers and is reduced to 1 n l when n users are unknown with l the processing gain the performance of these three linear detectors with and without unknown users is compared

automatic design of high sensitivity color filter arrays with panchromatic pixels in most of existing digital cameras color images have to be reconstructed from raw images which only have one color sensed at each pixel as their imaging sensors are covered by color filter arrays cfas at each pixel a cfa usually allows only a portion of the light spectrum to pass through and thereby reduces the light sensitivity of pixels to address this issue previous works have explored adding panchromatic pixels into cfas however almost all existing methods assign panchromatic pixels empirically making the designed cfas prone to aliasing artifacts in this paper based on a mathematical model we propose a fully automatic approach to designing high sensitivity cfas using panchromatic pixels by the frequency structure representation of cfas we formulate high sensitivity cfa design as a continuous multi objective optimization problem where robustness to aliasing artifacts and percentage of panchromatic pixels are simultaneously maximized we analyze the characteristics of our new formulation according to the analysis we develop a new method to propose frequency structure candidates which can produce cfas that reach a desired percentage of panchromatic pixels then for each candidate we optimize parameters to obtain the final cfa which is an appropriately balanced solution to the multi objective optimization problem we formulate the two design procedures as constrained optimization problems and solve them using the alternating direction method extensive experiments confirm the advantage of the proposed method in both low light and normal light conditions

joint demosaicing and denoising via learned nonparametric random fields we introduce a machine learning approach to demosaicing the reconstruction of color images from incomplete color filter array samples there are two challenges to overcome by a demosaicing method 1 it needs to model and respect the statistics of natural images in order to reconstruct natural looking images and 2 it should be able to perform well in the presence of noise to facilitate an objective assessment of current methods we introduce a public ground truth data set of natural images suitable for research in image demosaicing and denoising we then use this large data set to develop a machine learning approach to demosaicing our proposed method addresses both demosaicing challenges by learning a statistical model of images and noise from hundreds of natural images the resulting model performs simultaneous demosaicing and denoising we show that the machine learning approach has a number of benefits 1 the model is trained to directly optimize a user specified performance measure such as peak signal to noise ratio psnr or structural similarity 2 we can handle novel color filter array layouts by retraining the model on such layouts and 3 it outperforms the previous state of the art in some setups by 0 7 db psnr faithfully reconstructing edges textures and smooth areas our results demonstrate that in demosaicing and related imaging applications discriminatively trained machine learning models have the potential for peak performance at comparatively low engineering effort

mlse for an unknown channel i optimality considerations the problem of performing joint maximum likelihood ml estimation of a digital sequence and unknown dispersive channel impulse response is considered starting from a continuous time ct model previous investigations of this problem have not considered the front end fe processing in detail rather a discrete time signal model has been assumed we show that a fractionally spaced whitened matched filter matched to the known data pulse provides a set of sufficient statistics when a tapped delay line channel model is assumed and that the problem is ill posed when the channel impulse response is generalized to a ct finite length model practical approximations are considered that circumvent this ill posed condition recursive computation of the joint ml metric is developed together the fe processing and metric recursion provide a receiver structure which may be interpreted as the theoretical foundation for the previously introduced technique of per survivor processing and they lead directly to generalizations several fe processors representative of those suggested in the literature are developed and related to the practically optimal fe

iterative detection in block orthogonal and spatially multiplexed multisensor signaling schemes the impact of iterative minimum mean square error mmse detection on multisensor signaling schemes in frequency selective media is considered the suitability of a decision feedback mmse df mmse front end relative to a linear mmse lmmse front end is examined using two case studies namely layered spatial multiplexing and block orthogonal space time signaling iterative mmse detection is observed to afford near optimal performance further in channels with large delay spreads a combination of the lmmse and df mmse front ends seems appropriate the former in earlier iterations and the latter in concluding iterations

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

a proof of the spherical homeomorphism conjecture for surfaces the human cerebral cortex is topologically equivalent to a sphere when it is viewed as closed at the brain stem due to noise and or resolution issues magnetic resonance imaging may see handles that need to be eliminated to reflect the true spherical topology shattuck and leahy 2001 present an algorithm to correct such an image the basis for their correction strategy is a conjecture which they call the spherical homeomorphism conjecture stating that the boundary between the foreground region and the background region is topologically spherical if certain associated foreground and background multigraphs are both graph theoretic trees in this paper we prove the conjecture and its converse under the assumption that the foreground background boundary is a surface

adaptive bayesian multiuser detection for synchronous cdma with gaussian and impulsive noise we consider the problem of simultaneous parameter estimation and data restoration in a synchronous cdma system in the presence of either additive gaussian or additive impulsive white noise with unknown parameters the impulsive noise is modeled by a two term gaussian mixture distribution bayesian inference of all unknown quantities is made from the superimposed and noisy received signals the gibbs sampler a markov chain monte carlo procedure is employed to calculate the bayesian estimates the basic idea is to generate ergodic random samples from the joint posterior distribution of all unknown and then to average the appropriate samples to obtain the estimates of the unknown quantities adaptive bayesian multiuser detectors based on the gibbs sampler are derived for both the gaussian noise synchronous cdma channel and the impulsive noise synchronous cdma channel a salient feature of the proposed adaptive bayesian multiuser detectors is that they can incorporate the a priori symbol probabilities and they produce as output the a posteriori symbol probabilities that is they are soft input soft output algorithms hence these methods are well suited for iterative processing in a coded system which allows the adaptive bayesian multiuser detector to refine its processing based on the information from the decoding stage and vice versa a receiver structure termed the adaptive turbo multiuser detector

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

signal separation using fractional sampling in multiuser communications described is a decorrelating filter that separates signals in a multiuser environment by relying on the relative delays to be sufficiently distinct the input signal is fractionally sampled to allow for the differentiation of the user delays both zero forcing and minimum mean square error versions of this filter are derived and probability of error expressions are given the algorithm successfully separates unknown digital signals by using the known received pulse shapes and the symbol rate a delay division multiple access ddma scheme based on this signal decorrelator is proposed that will allow signals to be transmitted without spreading the signal spectrum it is shown that in a noisy environment the signal to noise ratio penalty for ddma can be severe yet the bandwidth advantage is very pronounced compared to spread spectrum systems and is similar to other bandwidth efficient schemes the performance of a code division multiple access cdma system using this signal decorrelator is also given the decorrelator can be used as a blind multiuser detector or as a preprocessor to enhance the performance of a cdma system

multiuser detection of quasisynchronous cdma signals using linear decorrelators a linear decorrelator detector is proposed for a quasisynchronous code division multiple access qs cdma cellular system it is assumed that each of n users has a global positioning system gps generated local clock and attempts to transmit synchronously with the other users in its cell the base station thus receives n signature waveforms which are approximately synchronized but with a small timing error due to local oscillator drift doppler shifts and variable distances from the mobiles to the base the residual timing offset is discretized and a decorrelator is constructed which attempts to reject the multiuser interference vectors corresponding to the set of possible offsets a noncoherent version of the decorrelator detector is presented along with a maximum likelihood scheme for synchronizing to the desired signal bounds and analytical results for the bit error rate ber are obtained for various interferer conditions

interior point least squares estimation transient convergence analysis and application to mmse decision feedback equalization in many communication systems training sequences are used to help the receiver identify and or equalize the channel the amount of training data required depends on the convergence properties of the adaptive filtering algorithms used for equalization in this paper we propose the use of a new adaptive filtering method called interior point least squares ipls for adaptive equalization first we show that ipls converges exponentially fast in the transient phase then we use the ipls algorithm to update the weight vector for a minimum mean square error decision feedback equalizer mmse dfe in a cdma downlink scenario numerical simulations show that when training sequences are short ipls consistently outperforms rls in terms of system bit error rate and packet error rate as the training sequence gets longer ipls matches the performance of the rls algorithm

color demosaicking via directional linear minimum mean square error estimation digital cameras sample scenes using a color filter array of mosaic pattern e g the bayer pattern the demosaicking of the color samples is critical to the image quality this paper presents a new color demosaicking technique of optimal directional filtering of the green red and green blue difference signals under the assumption that the primary difference signals pds between the green and red blue channels are low pass the missing green samples are adaptively estimated in both horizontal and vertical directions by the linear minimum mean square error estimation lmmse technique these directional estimates are then optimally fused to further improve the green estimates finally guided by the demosaicked full resolution green channel the other two color channels are reconstructed from the lmmse filtered and fused pds the experimental results show that the presented color demosaicking technique outperforms the existing methods both in psnr measure and visual perception

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

determining simplicity and computing topological change in strongly normal partial tilings of r2 or r3 abstract a convex polygon in r2 or a convex polyhedron in r3 will be called a tile a connected set p of tiles is called a partial tiling if the intersection of any two of the tiles is either empty or is a vertex or edge in r3 or face of both p is called strongly normal sn if for any partial tiling p p and any tile p p the neighborhood n p p of p the union of the tiles of p that intersect p is simply connected let p be sn and let n p p be the excluded neighborhood of p in p i e the union of the tiles of p other than p itself that intersect p we call p simple in p if n p p and n p p are topologically equivalent this paper presents methods of determining for an sn partial tiling p whether a tile p p is simple and if not of counting the numbers of components and holes in r3 components tunnels and cavities in n p p

an efficient code timing estimator for receiver diversity ds cdma systems we propose an efficient algorithm for estimating the code timing of direct sequence code division multiple access ds cdma systems that consist of an arbitrary antenna array at the receiver and work in a flat fading and near far environment the algorithm is an asymptotic for large number of data samples maximum likelihood ml estimator that is derived by modeling the known training sequence as the desired signal and all other signals including the interfering signals and the additive noise as unknown colored gaussian noise the algorithm does not require the search over a parameter space and the code timing is obtained by rooting a second order polynomial which is computationally very efficient simulation results show that the algorithm is quite robust against the near far problem and channel fading it requires a shorter training sequence than the single antenna based estimators

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

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

maximum likelihood based multipath channel estimation for code division multiple access systems the problem of estimating the channel parameters of a new user in a multiuser code division multiple access cdma communication system is addressed it is assumed that the new user transmits training data over a slowly fading multipath channel the proposed algorithm is based on maximum likelihood estimation of the channel parameters first an asymptotic expression for the likelihood function of channel parameters is derived and a re parametrization of this likelihood function is proposed in this re parametrization the channel parameters are combined into a discrete time channel filter of symbol period length then expectation maximization algorithm and alternating projection algorithm based techniques are considered to extract channel parameters from the estimated discrete channel filter to maximize the derived asymptotic likelihood function the performance of the proposed algorithms is evaluated through simulation studies in addition the proposed algorithms are compared to previously suggested subspace techniques for multipath channel estimation

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

minimal non deletable sets and minimal non codeletable sets in binary images the concepts of strongly 8 deletable and strongly 4 deletable sets of 1s in binary images on the 2d cartesian grid were introduced by ronse in the mid 1980s to formalize the connectivity preservation conditions that parallel thinning algorithms are required to satisfy in this paper we call these sets deletable and codeletable respectively to establish that a proposed parallel thinning algorithm for binary images on the 2d cartesian grid preserves 8 4 connected foreground components and 4 8 connected background components it is enough to prove that the set of 1s which are changed to 0s at each pass of the algorithm is always a deletable codeletable set ronse established results that are very useful in this context for proving that a finite set d of 1s is deletable or codeletable in particular he showed that d and its proper subsets are all codeletable in a binary image if each singleton and each pair of 8 adjacent pixels in d is codeletable he further showed that d and its proper subsets are all deletable in a binary image if 1 each singleton and each pair of 4 adjacent pixels in d is deletable and 2 no set of 2 3 or 4 pairwise 8 adjacent pixels that is an 8 connected foreground component of the image is entirely contained in d in the 1990s and early 2000s analogous results were obtained by hall ma gau and the author for binary images on the 2d hexagonal grid the 3d cartesian and face centered cubic grids and the 4d cartesian grid this paper extends the above mentioned work to binary images on almost any polytopal complex whose union is n dimensional euclidean space for n 4 our main results generalize and unify the corresponding results of the earlier work

sequential amplitude estimation in multiuser communications considers the problem of multiuser amplitude estimation i e the problem of estimating the amplitudes of several digital communications signals superimposed in the same channel this problem is of importance in communications environments such as spread spectrum radio networks in which nonorthogonal multiplexing is used multiuser amplitude estimation is a critical prerequisite to the optimum demodulation of such signals using for example verdu s algorithm in the present paper a sequential detection estimation approach is applied to this problem and several estimation paradigms including the method of moments and likelihood based estimators are considered the consistency asymptotic variance and complexity of these estimators are examined a new method of constructing a recursive consistent and asymptotically efficient estimation algorithm out of a consistent estimator sequence is also suggested and is applied to the current setup it is seen that detector estimators that use these estimators in verdu s algorithm result asymptotically in known amplitude optimum error probabilities with little relative increase in complexity per demodulated bit

on chip matched filtering and discrete sufficient statistics for asynchronous band limited cdma systems the problem of generating discrete sufficient statistics for signal processing in code division multiple access cdma systems is considered in the context of underlying channel bandwidth restrictions discretization schemes are identified for approximately bandlimited cdma systems and a notion of approximate sufficiency is introduced the role of chip matched filtering in generating accurate discrete statistics is explored the impact of approximate sufficiency on performance is studied in three cases conventional matched filter mf detection minimum mean squared error detection and delay acquisition it is shown that for waveforms limited to a chip interval sampling the chip mf output at the chip rate can lead to a significant degradation in performance then with equal bandwidth and equal rate constraints the performance with different chip waveforms is compared in all three cases above it is demonstrated that multichip waveforms that approximate nyquist sine pulses achieve the best performance with the commonly used rectangular chip pulse being severely inferior however the results also indicate that it is possible to approach the best performance with well designed chip waveforms limited to a chip interval as long as the chip mf output is sampled above the nyquist rate

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

fast recursive least squares transversal filters for adaptive filtering fast transversal filter ftf implementations of recursive least squares rls adaptive filtering algorithms are presented in this paper substantial improvements in transient behavior in comparison to stochastic gradient or lms adaptive algorithms are efficiently achieved by the presented algorithms the true not approximate solution of the rls problem is always obtained by the ftf algorithms even during the critical initialization period first n iterations of the adaptive filter this true solution is recursively calculated at a relatively modest increase in computational requirements in comparison to stochastic gradient algorithms factor of 1 6 to 3 5 depending upon application additionally the fast transversal filter algorithms are shown to offer substantial reductions in computational requirements relative to existing fast rls algorithms such as the fast kalman algorithms of morf ljung and falconer 1976 and the fast ladder lattice algorithms of morf and lee 1977 1981 they are further shown to attain steady state unnormalized or improve upon first n initialization steps the very low computational requirements of the efficient rls solutions of carayannis manolakis and kalouptsidis 1983 finally several efficient procedures are presented by which to ensure the numerical stability of the transversal filter algorithms including the incorporation of soft constraints into the performance criteria internal bounding and rescuing procedures and dynamic range increasing square root normalized variations of the transversal filters

local and global topology preservation in locally finite sets of tiles abstract this paper deals with sets p of tiles compact convex sets in r 2 or r 3 tiles are a generalization of pixels or voxels they can have arbitrary shapes are allowed to have overlapping interiors and need not cover the space the union of all the tiles of p is denoted by u p the neighborhood n p p of a tile p is the union of the tiles of p that intersect p p is called simple if deletion of p from p does not change the topology in the homotopy sense of u p we show in this paper that if p satisfies a property called strong normality sn and deletion of p preserves the topology of n p p then p is simple this may not be true if p is not sn and even if p is sn p may be simple even if deletion of p does not preserve the topology of n p p

local sparse structure denoising for low light level image sparse and redundant representations perform well in image denoising however sparsity based methods fail to denoise low light level lll images because of heavy and complex noise they consider sparsity on image patches independently and tend to lose the texture structures to suppress noises and maintain textures simultaneously it is necessary to embed noise invariant features into the sparse decomposition process we therefore used a local structure preserving sparse coding lspsc formulation to explore the local sparse structures both the sparsity and local structure in image it was found that with the introduction of spatial local structure constraint into the general sparse coding algorithm lspsc could improve the robustness of sparse representation for patches in serious noise we further used a kernel lspsc k lspsc formulation which extends lspsc into the kernel space to weaken the influence of linear structure constraint in nonlinear data based on the robust lspsc and k lspsc algorithms we constructed a local sparse structure denoising lssd model for lll images which was demonstrated to give high performance in the natural lll images denoising indicating that both the lspsc and k lspsc based lssd models have the stable property of noise inhibition and texture details preservation

a new color filter array with optimal properties for noiseless and noisy color image acquisition digital color cameras acquire color images by means of a sensor on which a color filter array cfa is overlaid the bayer cfa dominates the consumer market but there has recently been a renewed interest for the design of cfas however robustness to noise is often neglected in the design though it is crucial in practice in this paper we present a new 2 3 periodic cfa which provides by construction the optimal tradeoff between robustness to aliasing chrominance noise and luminance noise moreover a simple and efficient linear demosaicking algorithm is described which fully exploits the spectral properties of the cfa practical experiments confirm the superiority of our design both in noiseless and noisy scenarios

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

breadth first maximum likelihood detection in multiuser cdma in this letter we derive a recursive additive metric for complexity constrained maximum likelihood detection for multiuser cdma using breadth first detection algorithms the metric requires linear filtering of the matched filtered received signal vector it is shown that a class of filters fulfilling certain requirements lead to identical performance

error probability for direct sequence spread spectrum multiple access communications part i upper and lower bounds upper and lower bounds on the average probability of error are obtained for direct sequence spread spectrum multipleaccess communications systems with additive white gaussian noise channels the bounds which are developed from convexity properties of the error probability function are valid for systems in which the maximum multiple access interference does not exceed the desired signal and the signature sequence period is equal to the duration of the data pulse the tightness of the bounds is examined for systems with a small number of simultaneously active transmitters this is accomplished by comparisons of the upper and lower bounds for several values of the system parameters the bounds are also compared with an approximation based on the signal to noise ratio and with the chernoff upper bound

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

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

on minimum ber linear multiuser detection for ds cdma channels the minimum bit error rate mber linear multiuser detection of direct sequence code division multiple access ds cdma communications is considered it is shown that the problem of mber linear multiuser detection is equivalent to a constrained optimization problem where the constrained space is the surface and interior of a hyperellipsoid it is further shown that any solution of the constrained optimization problem must be a solution of a set of nonlinear equations based on these the mber linear multiuser detector of the two user case is obtained for general cases we propose a convex subspace of the constrained space and show that the ber cost function is convex on the subspace and therefore has a unique solution some sufficient conditions that guarantee the convex subspace always contains the global minimizer are provided which show that if the signal to noise ratio snr is sufficiently large the convex subspace always contains the global minimizer a newton method is developed for the set of nonlinear equations and computer simulation gives some illustrative examples

computationally efficient angle estimation for signals with known waveforms this paper presents a large sample decoupled maximum likelihood deml angle estimator for uncorrelated narrowband plane waves with known waveforms and unknown amplitudes arriving at a sensor array in the presence of unknown and arbitrary spatially colored noise the deml estimator decouples the multidimensional problem of the exact ml estimator to a set of 1 d problems and hence is computationally efficient we shall derive the asymptotic statistical performance of the deml estimator and compare the performance with its cramer rao bound crb i e the best possible performance for the class of asymptotically unbiased estimators we will show that the deml estimator is asymptotically statistically efficient for uncorrelated signals with known waveforms we will also show that for moderately correlated signals with known waveforms the deml estimator is no longer a large sample maximum likelihood ml estimator but the deml estimator may still be used for angle estimation and the performance degradation relative to the crb is small we shall show that the deml estimator can also be used to estimate the arrival angles of desired signals with known waveforms in the presence of interfering or jamming signals by modeling the interfering or jamming signals as random processes with an unknown spatial covariance matrix finally several numerical examples showing the performance of the deml estimator are presented in this paper

blind adaptive multiuser detection in multipath cdma channels based on subspace tracking a blind adaptive technique for signal demodulation in multipath code division multiple access cdma communication channels is proposed this technique is based on signal subspace estimation the receiver employs a bank of linear filters decorrelating filters or linear mmse filters at the front end to mitigate the multiple access interference and the multipath interference a channel estimator is used to estimate the channel state for diversity combining it is shown that through the use of signal subspace estimation both the decorrelating filterbank and the linear mmse filterbank can be obtained blindly i e they can be estimated from the received signal with the prior knowledge of only the signature waveform of the desired user two forms of the subspace based linear filterbanks are developed and their equivalence in terms of the interference suppression capability is established these subspace based blind adaptive interference suppression techniques require at each symbol epoch the eigenvalues and the eigenvectors of an appropriate signal subspace which ran be obtained using computationally efficient sequential adaptive eigendecomposition subspace tracking algorithms moreover a blind adaptive method for estimating the channel state is developed which also produces the postcombining decision statistic as a byproduct

on parameter estimation in long code ds cdma systems cramer rao bounds and least squares algorithms the problem of parameter estimation in direct sequence code division multiple access ds cdma systems employing long aperiodic spreading codes is considered in particular for an asynchronous network the problem of estimating the amplitudes phase offsets propagation delays and directions of arrival doas for the cdma signals transmitted by the active users is examined first formulas are provided for the cramer rao bound crb on the error variance of any joint multiuser parameter estimation procedure exploiting a known training sequence further least squares adaptive algorithms are derived which based on the transmission of known pilot symbols enable adaptive estimation of the parameters with a computational complexity that is only quadratic in the processing gain in particular the cases where either the parameters from all of the active users are to be estimated or the relevant parameters of only one user are to be acquired based on the knowledge of its spreading code and training sequence only are considered this study is completed by an analysis of the convergence properties of the proposed adaptive algorithms and by extensive computer simulation results illustrating the performance of the estimation procedures also in comparison with the crb and the impact of the estimation errors on the performance of the linear minimum mean square error lmmse multiuser detector

integer forcing linear receivers linear receivers are often used to reduce the implementation complexity of multiple antenna systems in a traditional linear receiver architecture the receive antennas are used to separate out the codewords sent by each transmit antenna which can then be decoded individually although easy to implement this approach can be highly suboptimal when the channel matrix is near singular this paper develops a new linear receiver architecture that uses the receive antennas to create an effective channel matrix with integer valued entries rather than attempting to recover transmitted codewords directly the decoder recovers integer combinations of the codewords according to the entries of the effective channel matrix the codewords are all generated using the same linear code which guarantees that these integer combinations are themselves codewords provided that the effective channel is full rank these integer combinations can then be digitally solved for the original codewords this paper focuses on the special case where there is no coding across transmit antennas and no channel state information at the transmitter s which corresponds either to a multiuser uplink scenario or to single user v blast encoding in this setting the proposed integer forcing linear receiver significantly outperforms conventional linear architectures such as the zero forcing and linear minimum mean squared error receiver in the high signal to noise ratio regime the proposed receiver attains the optimal diversity multiplexing tradeoff for the standard multiple input multiple output mimo channel with no coding across transmit antennas it is further shown that in an extended mimo model with interference the integer forcing linear receiver achieves the optimal generalized degrees of freedom

joint channel estimation partial successive interference cancellation and data decoding for ds cdma based on the sage algorithm this paper deals with the derivation and optimization of an iterative receiver architecture performing joint multiuser decoding and channel estimation we consider an asynchronous multirate convolutional coded ds cdma system that communicates over quasi static flat rayleigh fading channels the proposed receiver is derived within the space alternating generalized expectation maximization sage framework in connection with the noise splitting approach the used theoretical framework guarantees convergence of the receiver as opposed to many other iterative receiver structures furthermore the noise splitting approach provides a set of noise weighting coefficients that can be optimized under weak constraints the inputs to the single user decoders are linear combinations of two kinds of soft values with weights determined by the noise weighting coefficients these two kinds of soft values can be interpreted as a priori information and extrinsic information respectively if the channels are known in the case of unknown channels they are asymptotically a priori and asymptotically extrinsic i e they become a priori and extrinsic when the length of the observed frame tends to infinity in most cases the optimum coefficients lead to extrinsic or asymptotically extrinsic values fed to the input of the single user decoders monte carlo simulations show that the proposed receiver is resistant to channel estimation errors and supports high system loads

near optimum tree search detection schemes for bit synchronous multiuser cdma systems over gaussian and two path rayleigh fading channels simple reduced tree search detection schemes of the breadth first type are applied to suboptimal joint multiuser detection in bit synchronous code division multiple access cdma systems over both gaussian and two path rayleigh fading channels it is pointed out that in contrast to the case of the optimal multiuser detector the choice of the receiver filter severely influences the performance of suboptimal multiuser detectors simulation results supported by analysis show that breadth first tree search algorithms using a decorrelating noise whitening receiver filter perform better than similar receivers which solely use a matched filter mf for virtually all nonsingular spreading code sets studied most of the code sets are randomly generated the m and t algorithm detectors based on decorrelating noise whitening filter wf outputs can achieve near optimum performance at a very low complexity compared to the optimal detector although the proposed detectors are more complex than some known suboptimum detectors furthermore the use of combining techniques is considered for a two path rayleigh fading channel and a semi synchronous cdma structure is proposed it is shown that if maximum ratio combining mrc is employed the decorrelating noise wf still exists the corresponding suboptimal combining detector with a decorrelating noise wf outperforms a similar noncombining detector

decision feedback multiuser detection a systematic approach a systematic approach to decision feedback multiuser detection is introduced for the joint detection of symbols of k simultaneously transmitting users of a synchronous correlated waveform multiple access cwma channel with gaussian noise a new performance criterion called symmetric energy is defined which is a low noise indicator of the joint error rate that at least one user is detected erroneously even the best linear detectors can perform poorly in terms of symmetric energy compared to the maximum likelihood detector a general class of decision feedback detectors dfds is defined with o k implementational complexity per user the symmetric energy of arbitrary dfd and bounds on their asymptotic effective energy aee performance are obtained along with an exact bit error rate and aee analysis for the decorrelating dfd the optimum dfd that maximizes symmetric energy is obtained each one of the k optimum decorrelating and conventional dfds that correspond to the k orders in which the users can be detected are shown to outperform the linear optimum decorrelating and conventional detectors respectively in terms of symmetric energy moreover algorithms are obtained for determining the choice of order of detection for the three dfds which guarantee that they uniformly user wise outperform their linear counterparts in addition to optimality in symmetric energy it is also shown that under certain conditions the optimum dfd achieves the aee performance of the exponentially complex maximum likelihood detector for all users simultaneously none of the results of this paper make the perfect feedback assumption the implications of our work on power control for multiuser detection are also discussed

a geometric method for optimal design of color filter arrays a color filter array cfa used in a digital camera is a mosaic of spectrally selective filters which allows only one color component to be sensed at each pixel the missing two components of each pixel have to be estimated by methods known as demosaicking the demosaicking algorithm and the cfa design are crucial for the quality of the output images in this paper we present a cfa design methodology in the frequency domain the frequency structure which is shown to be just the symbolic dft of the cfa pattern one period of the cfa is introduced to represent images sampled with any rectangular cfas in the frequency domain based on the frequency structure the cfa design involves the solution of a constrained optimization problem that aims at minimizing the demosaicking error to decrease the number of parameters and speed up the parameter searching the optimization problem is reformulated as the selection of geometric points on the boundary of a convex polygon or the surface of a convex polyhedron using our methodology several new cfa patterns are found which outperform the currently commercialized and published ones experiments demonstrate the effectiveness of our cfa design methodology and the superiority of our new cfa patterns

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

a moment based blind method for identification of fir down link ds cdma channels in order to achieve lower bit error rates bers multiuser detection techniques have been proposed generally multiuser detectors can provide excellent performance only when channel parameters are precisely known in this paper we propose a moment based blind method to estimate down link channels precisely the mean square error mse expression of the channel vector estimate has been derived through simulations we show the effect of the channel estimation error on the performance of a multiuser detector in this paper we also show that finite impulse response fir channels can be blindly identified by using the proposed method and the spreading operation since the spreading operation of the code division multiple access cdma can induce cyclostationarity any fir channel can be identified by the proposed method of course in order to guarantee identifiability some conditions on the spreading codes will be satisfied in this paper these conditions are also found

convergence analysis of chip and fractionally spaced lms adaptive multiuser cdma detectors this paper analyzes the convergence behavior of the least mean square lms filter when used in an adaptive code division multiple access cdma detector consisting of a tapped delay line with adjustable tap weights the sampling rate may be equal to or higher than the chip rate and these correspond to chip spaced cs and fractionally spaced fs detection respectively it is shown that cs and fs detectors with the same time span exhibit identical convergence behavior if the baseband received signal is strictly bandlimited to half the chip rate even in the practical case when this condition is not met deviations from this observation are imperceptible unless the initial tap weight vector gives an extremely large mean squared error mse this phenomenon is carefully explained with reference to the eigenvalues of the correlation matrix when the input signal is not perfectly bandlimited the inadequacy of the eigenvalue spread of the tap input correlation matrix as an indicator of the transient behavior and the influence of the initial tap weight vector on convergence speed are highlighted specifically a initialization within the signal subspace or to the origin leads to very much faster convergence compared with initialization in the a noise subspace

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

decorrelating multiuser code timing estimation for long code cdma with bandlimited chip waveforms this paper addresses the problem of multiuser code timing estimation for asynchronous uplink code division multiple access cdma systems with aperiodic spreading codes and bandlimited chip waveforms two decorrelating code timing estimation schemes namely the frequency domain least squares fls and frequency domain weighted least squares fwls estimators are developed the two proposed estimators offer different tradeoffs between complexity and estimation accuracy a critical step for decorrelating based estimation is to decompose the received signal into subsignals of shorter duration we discuss how to perform the decomposition to ensure improved identifiability and statistical stability of the proposed schemes due to a unique signal structure in the frequency domain both the fls and fwls estimators admit efficient implementations that result in significant complexity reductions the crame spl acute r rao bound for the estimation problem under study is derived and used as an assessment tool for the proposed estimators numerical results show that both of the proposed estimators can support overloaded systems with more users than the processing gain in multipath fading environments and significantly outperform a conventional technique based on matched filter processing

recursive code timing estimation for ds cdma signals in a time varying environment through a stochastic optimization approach a modified simulated annealing method is proposed for recursively minimizing the nonlinear cost function in the subspace based code timing estimation for direct sequence code division multiple access signals over a multipath fading channel the new algorithm has low complexity because of the recursive updating of the final code timing estimates together with the noise subspace tracking

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

detection of 3 d simple points for topology preserving transformations with application to thinning the problems of 3 d digital topology preservation under binary transformations and 3 d object thinning are considered in this correspondence first the authors establish the conditions under which transformation of an object voxel to a non object voxel or its inverse does not affect the image topology an efficient algorithm to detect a simple point has been proposed on the basis of those conditions in this connection some other interesting properties of 3 d digital geometry are also discussed using these properties and the simple point detection algorithm the authors have proposed an algorithm to generate a surface skeleton so that the topology of the original image is preserved the shape of the image is maintained as much as possible and the results are less affected by noise

the khalimsky topologies are precisely those simply connected topologies on z n whose connected sets include all 2 n connected sets but no 3 n 1 disconnected sets we give a proof of the result stated in the title here the concepts of 2n and 3n 1 dis connected sets are the natural generalizations to zn of the standard concepts of 4 and 8 dis connected sets in 2d digital topology suppose we have an n dimensional scanner that digitizes n dimensional objects to subsets of zn we are interested in topological spaces zn that might allow standard concepts and methods of general topology to be directly and usefully applied to good digitizations produced by the scanner but our result suggests that if a topological space zn is not a khalimsky space then it will not satisfy our requirement our proof involves some purely discrete arguments and a fact about simply connected polyhedra that is a well known consequence of the simplicial approximation theorem but also uses the following fact which was one of the main results in an earlier paper in r m shortt ed general topology and applications proc 1988 northeast conf marcel dekker new york 1990 pp 153 164 by the author and khalimsky for any t0 topological space in which each point lies in a finite open set and a finite closed set there exists a polyhedron whose vertices are in 1 1 correspondence with the points of the space such that the homotopy classes of continuous maps into the topological space from any metric space are in 1 1 correspondence with the homotopy classes of continuous maps from that metric space into the polyhedron

joint signal detection and parameter estimation in multiuser communications the problem of simultaneously detecting the information bits and estimating signal amplitudes and phases in a k user asynchronous direct sequence spread spectrum multiple access communication system is addressed the joint maximum likelihood ml estimator has a computational complexity that is exponential in the total number of bits transmitted and thus does not represent a practical solution to the problem an estimator that combines a suboptimum tree search algorithm with a recursive least squares estimator of complex signal amplitude is considered the complexity of this estimator is o k sup 2 computations per decoded bit and its performance is very close to that of the joint ml receiver this receiver has the advantage that the transmitted signal powers and phases are extracted from the received signal in an adaptive fashion without using a test sequence

the generalized spherical homeomorphism theorem for digital images the spherical homeomorphism conjecture proposed by shattuck and leahy in 2001 serves as the backbone of their algorithm to correct the topology of magnetic resonance images of the human cerebral cortex using a canonical image thickening technique and the authors previously proven spherical homeomorphism theorem for surfaces we formulate and prove a spherical homeomorphism theorem which is valid for all digital images when utilizing the 26 6 connectivity rule

a novel adaptive antenna array for ds cdma code acquisition equipped with an adaptive beamformer existing adaptive array code acquisition still relies on the correlator structure due to the inherent property of the associated serial search scheme its mean acquisition time is large especially in strong interference environments in this paper we propose a novel adaptive filtering scheme to solve the problem the proposed scheme comprises two adaptive filters an adaptive spatial and an adaptive temporal filter with a specially designed structure the spatial filter can act as a beamformer suppressing interference while the temporal filter can act as a code delay estimator a mean squared error mse criterion is proposed such that these filters can be simultaneously adjusted by a stochastic gradient descent method the performance as well as the convergence behavior of the proposed algorithm are analyzed in detail closed form expressions for optimum filter weights optimum beamformer signal to interference plus noise ratio sinr steady state mse and mean acquisition time are derived for the additive white gaussian noise awgn channel computer simulations show that the mean acquisition time of the proposed algorithm is much shorter than that of the correlator based approach and the derived theoretical expressions are accurate

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

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

a near ideal noise whitening filter for an asynchronous time varying cdma system a near ideal noise whitening filter for a time varying code division multiple access cdma system is examined first the structure of the ideal noise whitening filter is determined the ideal noise whitening filter for a time varying cdma system is dependent on unknown future system parameters and is therefore impractical a near ideal realizable whitening filter is introduced as a solution the convergence of the factorization method for a time varying cdma system is considered the truncation of the number of taps of the ideal noise whitening filter is studied and a metric function based on the near ideal noise whitening filter for a tree search detection algorithm is formulated simulation results are obtained for five and ten user time varying cdma systems with binary random signature sequences of length 10 and a rectangular chip waveform the results show that the near ideal noise whitening filter can accurately approximate the ideal noise whitening filter at a low complexity level the performance degradation of a suboptimal tree search detector for a time varying asynchronous cdma system using a typical near ideal noise whitening filter is minimal compared to an identical system using the ideal noise whitening filter

reduced state sequence estimation with set partitioning and decision feedback a reduced state sequence estimator for linear intersymbol interference channels is described the estimator uses a conventional viterbi algorithm with decision feedback to search a reduced state subset trellis that is constructed using set partitioning principles the complexity of maximum likelihood sequence estimation mlse due to the length of the channel memory and the size of the signal set is systematically reduced an error probability analysis shows that a good performance complexity tradeoff can be obtained in particular the results indicate that the required complexity to achieve the performance of mlse is independent of the size of the signal set for large enough signal sets simulation results are provided for two partial response systems a simple technique for quadrature partial response signaling qprs is described that eliminates the quasicatastrophic nature of the ml trellis