on ppm sequences with good autocorrelation properties the problem of designing sequences of q ary pulse position modulation ppm symbols that have good periodic autocorrelation properties is investigated two cases are considered in the first it is assumed that only slot synchronization is present and thus cyclic shifts are one slot at a time in the second ppm symbol synchronization is present in which case cyclic shifts are by one symbol q slots at a time in both cases upper bounds are derived on the maximum peak to sidelobe distance which are shown through a computer search to be nearly tight when symbol synchronization is present the bound reduces to the plotkin bound but it is slightly tighter in general

an optimal training signal structure for frequency offset estimation this paper addresses an optimal training signal design for frequency offset estimation based on minimizing the cramer rao lower bound for frequency offset estimation with constraints on the peak and the total training signal energies and the training block length the optimal training signal structure is developed an approximate version of the optimal training signal structure is proposed which has practically the same performance as the optimal one and provides convenience in training signal generation and estimator derivation two robust reduced complexity frequency offset estimation methods for the proposed training structures are presented in order to handle larger frequency offsets modified training signal structures are proposed frequency offset estimation methods suitable for these training signals are also derived based on the best linear unbiased estimation principle analytical and simulation results show that the proposed training signal structures improve the estimation performance significantly

efficient estimation of class a noise parameters via the em algorithm the class a middleton noise model is a commonly used statistical physical parametric model for non gaussian interference superimposed on a gaussian background in this study the problem of efficient estimation of the class a parameters for small sample sizes is considered the proposed estimator is based on the em algorithm a two step iterative estimation technique that is ideally suited for the class a estimation problem since the observations can be readily treated as incomplete data for the single parameter estimation problem a closed form expression for the estimator is obtained furthermore for the single parameter estimation problem it is shown that the sequence of estimates obtained via the em algorithm converges and a characterization of the point to which the sequence converges is given in particular it is shown that if the limit point of this convergent sequence is an interior point of the parameter set of interest then it must be a stationary point of the traditional likelihood function in addition for both the single parameter and two parameter estimation problems the small sample size performance of the proposed em algorithm is examined via an extensive simulation study

asymptotic properties of moment estimators for overdispersed counts and proportions summary consistency and asymptotic normality of moment estimates of regression parameters and an overdispersion parameter are shown for data with extra binomial and extrapoisson variation the asymptotic covariance of the regression parameters is found to be unaffected by estimation of the overdispersion parameter the moment estimates may be obtained using iterated weighted least squares

sequence set design with good correlation properties via majorization minimization sets of sequences with good correlation properties are desired in many active sensing and communication systems e g multiple input multiple output mimo radar systems and code division multiple access cdma cellular systems in this paper we consider the problems of designing complementary sets of sequences css and also sequence sets with both good auto and cross correlation properties algorithms based on the general majorization minimization method are developed to tackle the optimization problems arising from the sequence set design problems all the proposed algorithms can be implemented by means of the fast fourier transform fft and thus are computationally efficient and capable of designing sets of very long sequences a number of numerical examples are provided to demonstrate the performance of the proposed algorithms

optimal odd length binary z complementary pairs a pair of sequences is called a golay complementary pair gcp if their aperiodic auto correlation sums are zero for all out of phase time shifts existing known binary gcps only have even lengths in the form of 21026 where are non negative integers to fill the gap left by the odd lengths we investigate the optimal oddlength binary pairs which display the closest correlation property to that of gcps our criteria of closeness is that each pair has the maximum possible zero correlation zone zcz width and minimum possible out of zone aperiodic auto correlation sums such optimal pairs are called optimal odd length binary z complementary pairs ob zcp in this paper we show that each optimal ob zcp has maximum zcz width of n 1 2 and minimum out of zone aperiodic sum magnitude of 2 where n denotes the sequence length odd systematic constructions of such optimal op zcps are proposed by insertion and deletion of certain binary gcps which settle the 2011 li fan tang tu open problem positively the proposed optimal ob zcps may serve as a replacement for gcps in many engineering applications where odd sequence lengths are preferred in addition they give rise to a new family of base two almost difference families adf which are useful in studying partially balanced incomplete block design bibd index terms aperiodic correlation almost difference set ads almost difference families adf golay complementary pair gcp zero correlation zone zcz z complementary pair zcp

on the containment and equivalence problems for two way transducers we look at some classes of two way transducers with auxiliary memory and investigate their containment and equivalence problems we believe that our results are the strongest known to date concerning two way transducers

error performance of multiple symbol differential detection of psk signals transmitted over correlated rayleigh fading channels the error performance of multiple symbol differential detection of uncoded qpsk signals transmitted over correlated rayleigh fading channels is studied the optimal detector is presented along with an exact expression for the corresponding pairwise error event probability it is shown that multiple symbol differential detection is a very effective strategy for eliminating the irreducible error floor associated with a conventional differential detector in all of the cases investigated a detector with an observation interval as small as two symbols is sufficient for this purpose it is also found that the error performance of a multiple symbol differential detector is not sensitive to the mismatch between the decoding metric and the channel fading statistics

efficient computational schemes for the orthogonal least squares algorithm the orthogonal least squares ols algorithm is an efficient implementation of the forward selection method for subset model selection the ability to find good subset parameters with only a linearly increasing computational requirement makes this method attractive for practical implementations we examine the computational complexity of the algorithm and present a preprocessing method for reducing the computational requirement

on ternary complementary sequences a pair of real valued sequences a a sub 1 a sub 2 a sub n and b b sub 1 b sub 2 b sub n is called complementary if the sum r spl middot of their autocorrelation functions r sub a spl middot and r sub b spl middot satisfies r spl tau r sub a spl tau r sub b spl tau spl sigma sub i 1 sup n sup spl tau a sub i a sub i spl tau spl sigma sub j 1 sup n spl tau b sub j b sub j spl tau 0 spl forall spl tau spl ne 0 in this paper we introduce a new family of complementary pairs of sequences over the alphabet spl alpha sub 3 1 1 0 the inclusion of zero in the alphabet which may correspond to a pause in transmission leads both to a better understanding of the conventional binary case where the alphabet is spl alpha sub 2 1 1 and to new nontrivial constructions over the ternary alphabet spl alpha sub 3 for every length n we derive restrictions on the location of the zero elements and on the form of the member sequences of the pair we also derive a bound on the minimum number of zeros necessary for the existence of a complementary pair of length n over spl alpha sub 3 the bound is tight as it is met by some of the proposed constructions for infinitely many lengths

binary and quadriphase sequences with optimal autocorrelation properties a survey time discrete signals with good autocorrelation properties are used in various applications in communications engineering from an implementation point of view usually sequences with a small phase alphabet and a maximal energy efficiency i e a uniform envelope are most favorable for this reason known methods as well as several new construction techniques of binary and quadriphase sequences with optimal or best known autocorrelation properties are discussed in this correspondence in many cases the achievable correlation properties can be improved significantly if a single zero element per sequence is accepted these almost binary and almost quadriphase sequences are considered as well the optimality criteria used include the maximum absolute sidelobe and the merit factor of the periodic and the odd periodic autocorrelation function respectively for sequence lengths of up to 44 in the binary case and up to 32 in the quadriphase case the best known parameters obtained by computer search are compared with the constructed results

a random effects model for binary data from dependent samples a model is proposed for the binary data analog of the paired t situation in this model the success probabilities vary across strata and have a specified probability distribution the parameters can be estimated by moments or likelihood methods various large sample tests are proposed the estimates and tests do not require fixed sample sizes the model can be applied to case control studies in which at least some cases have multiple controls and to other nested designs that have two treatments per stratum and small samples in each treatment stratum combination

a mixed effects model for categorical data a mixed model for categorical data from unbalanced designs which is directly analogous to a two way anova model for quantitative data is proposed an extension of the fitting constants method is developed to estimate model variance components based on appropriate reductions in sums of squares the resulting variance component estimators are incorporated into the covariance structure of a general linear models wald statistic to test for treatment differences these procedures are illustrated with data obtained from a multicenter clinical trial in which the treatments are regarded as fixed effects and the clinics are regarded as random effects

a generalized construction of multiple complete complementary codes and asymptotically optimal aperiodic quasi complementary sequence sets in recent years complete complementary codes cccs and quasi complementary sequence sets qcsss have found many important applications in multi carrier code division multiple access mc cdma systems for their good correlation properties in this paper we propose a generic construction of multiple sets of cccs over mathbb z n consisting of sequences of length n where n geq 3 is an arbitrary odd integer interestingly the maximum inter set aperiodic cross correlation magnitude of the proposed cccs is upper bounded by n it turns out that the combination of the generated cccs results in a new set of sequences to obtain asymptotically optimal and near optimal aperiodic qcsss the proposed construction includes a recent optimal construction of qcsss with prime length as a special case and leads to asymptotically optimal qcsss with new flexible parameters

complementary sets of non power of two length for peak to average power ratio reduction in ofdm golay complementary sequences and complementary sets have been proposed to deal with the high peak to average power ratio papr problem in orthogonal frequency division multiplexing ofdm system the existing constructions of complementary sets based on generalized boolean functions are limited to lengths which are powers of two in this paper we propose novel constructions of binary and nonbinary complementary sets of non power of two length regardless of whether or not the length of the complementary set is a power of two its papr is still upper bounded by the size of the complementary set therefore the constructed complementary sets can be applied in practical ofdm systems where the number of used subcarriers is not a power of two in addition while the binary golay complementary pairs exist only for limited lengths the constructed binary complementary sets of size 4 exist for more lengths with papr at most 4

channel estimation for multicarrier multiple input single output systems using the em algorithm this paper investigates the problem of blindly and semi blindly acquiring the channel gains for an underdetermined synchronous multiuser multicarrier system the special case of a multiple input single output miso channel is considered where the different users transmit at the same time and in the same bandwidth in order to separate the different users blindly techniques exploiting the finite alphabet are used for such techniques and for a general underdetermined mimo system we study conditions under which the channel and the data for each user are blindly and semi blindly identifiable we consider the stochastic maximum likelihood sml criterion in which the unknown input symbols are modeled as discrete random variables we apply the expectation maximization em algorithm in the frequency domain to get blind and semi blind channel estimates for each user in the miso case we also present a recursive em solution that updates the channel and noise estimates at each time instant simulations show that users can be separated even at low snr furthermore semi blind estimation allows for a more robust estimation solution since a possible singularity problem is avoided

complete formal systems for equivalence problems we describe four complete and recursively enumerable formal systems s0 d0 h0 b0 each one of them proves the decidability of some equivalence problem for some class of automata namely the language equivalence problem for simple automata the language equivalence problem for deterministic pushdown automata the function equivalence problem for deterministic pushdown transducers with outputs in an abelian group the bisimulation equivalence problem for loop free pushdown automata

wavelet based sequential monte carlo blind receivers in fading channels with unknown channel statistics recently an adaptive bayesian receiver for blind detection in flat fading channels was developed by the present authors based on the sequential monte carlo methodology that work is built on a parametric modeling of the fading process in the form of a state space model and assumes the knowledge of the second order statistics of the fading channel in this paper we develop a nonparametric approach to the problem of blind detection in fading channels without assuming any knowledge of the channel statistics the basic idea is to decompose the fading process using a wavelet basis and to use the sequential monte carlo technique to track both the wavelet coefficients and the transmitted symbols a novel resampling based wavelet shrinkage technique is proposed to dynamically choose the number of wavelet coefficients to best fit the fading process under such a framework blind detectors for both flat fading channels and frequency selective fading channels are developed simulation results are provided to demonstrate the excellent performance of the proposed blind adaptive receivers

em based recursive estimation of channel parameters recursive online expectation maximization em algorithm along with stochastic approximation is employed in this paper to estimate unknown time invariant variant parameters the impulse response of a linear system channel is modeled as an unknown deterministic vector process and as a gaussian vector process with unknown stochastic characteristics using these models which are embedded in white or colored gaussian noise different types of recursive least squares rls kalman filtering and smoothing and combined rls and kalman type algorithms are derived directly from the recursive em algorithm the estimation of unknown parameters also generates new recursive algorithms for situations such as additive colored noise modeled by an autoregressive process the recursive em algorithm is shown as a powerful tool which unifies the derivations of many adaptive estimation methods

constructions of quasi complementary sequence sets associated with characters an boldsymbol m boldsymbol k boldsymbol n delta max quasi complementary sequence set qcss is referred to as a set of boldsymbol m 2 d matrices of order boldsymbol k times boldsymbol n with periodic tolerance delta max in a multicarrier code division multiple access mc cdma communication system the set size boldsymbol m of a qcss is equal to the maximum number of users it can support and the periodic tolerance delta max determines the interference performance for the application of a qcss it is desirable that the set size should be as large as possible and the periodic tolerance should be as small as possible in this paper a framework of a periodic qcss is proposed from additive and multiplicative characters associated with a specific integer set it is then discovered that the parameters of the obtained qcss are determined by the employed integer set from this discovery new classes of periodic qcsss with large set sizes and low periodic tolerances are constructed and associated with some known integer sets

on the universe disjointness and containment problems for simple machines consider counter machines which are nondeterministic one way finite automata augmented with one counter where at each step the counter can be incremented by 1 decremented by 1 or left unchanged and can be tested for zero acceptance is by accepting state we show that there is a fixed nondeterministic real time i e no e move 1 reversal counter machine a once the counter decrements it can no longer increment such that it is undecidable to determine given an arbitrary positive integer d whether a d which is a with initial counter value d accepts all strings then strengthen the above result by showing that it also holds when a s counter is partially blind in that it cannot be tested for zero the machine aborts when there is an attempt to decrement the counter when it is zero and the only condition for acceptance is for the counter to be zero when the input head falls off the right end of the input we assume that on every input x for which d x the counter is initially set to x we make this assumption since otherwise a d cannot be both real time and satisfy the zero counter requirement for acceptance we also prove a similar result for partially blind 2 head nondeterministic finite automata ally we sharpen the well known results that the disjointness and containment problems for deterministic pushdown automata are undecidable

constructing binary sequences with good correlation properties an efficient analytical computational interplay binary sequence sets with asymptotically optimal auto cross correlation peak sidelobe level psl growth have been known in the literature for a long time and their construction has been studied both analytically and numerically in contrast it has been a long standing problem whether we can construct a family of binary sequences whose auto correlation psl grows in an optimal manner in this paper we devise a construction method of binary sequences with asymptotically optimal psl growth from the sequence sets with good correlation properties a key component of the design follows from the observation that if the psl of the sequence set grows optimally or nearly optimally then the psl of the constructed binary sequence will experience a similar growth as a consequence the proposed construction is simple to implement and is shown to be accomplished in polynomial time with such a construction we not only bridge the gap between analytical construction and computational search but also pave the way to settle the long standing design problem of binary sequences with an optimal growth of the auto correlation psl

longitudinal data analysis using generalized linear models summary this paper proposes an extension of generalized linear models to the analysis of longitudinal data we introduce a class of estimating equations that give consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence the estimating equations are derived without specifying the joint distribution of a subject s observations yet they reduce to the score equations for multivariate gaussian outcomes asymptotic theory is presented for the general class of estimators specific cases in which we assume independence m dependence and exchangeable correlation structures from each subject are discussed efficiency of the proposed estimators in two simple situations is considered the approach is closely related to quasi likelih ood some key ironh estimating equation generalized linear model longitudinal data quasi likelihood repeated measures

almost perfect quadriphase sequences a new class of quadriphase sequences of length n p sup j 1 spl equiv 2 mod 4 p odd prime j 1 2 is presented these almost perfect sequences have a periodic autocorrelation function spl theta spl tau which vanishes for all spl tau spl ne 0mod n 2

channel coding with multilevel phase signals a coding technique is described which improves error performance of synchronous data links without sacrificing data rate or requiring more bandwidth this is achieved by channel coding with expanded sets of multilevel phase signals in a manner which increases free euclidean distance soft maximum likelihood ml decoding using the viterbi algorithm is assumed following a discussion of channel capacity simple hand designed trellis codes are presented for 8 phase shift keying psk and 16 quadrature amplitude shift keying qask modulation these simple codes achieve coding gains in the order of 3 4 db it is then shown that the codes can be interpreted as binary convolutional codes with a mapping of coded bits into channel signals which we call mapping by set partitioning based on a new distance measure between binary code sequences which efficiently lower bounds the euclidean distance between the corresponding channel signal sequences a search procedure for more powerful codes is developed codes with coding gains up to 6 db are obtained for a variety of multilevel phase modulation schemes simulation results are presented and an example of carrier phase tracking is discussed

the expectation maximization algorithm for symbol unsynchronized sequence detection the expectation maximization em algorithm for maximizing likelihood functions combined with the viterbi algorithm is applied to the problem of sequence detection when symbol timing information is not present although the em algorithm is noncausal results obtained using the algorithm on the problem of nonsynchronized sequence detection indicate that it converges most of the time in three iterations making it both of theoretical and of practical interest a practical algorithm based on the em algorithm is introduced it reduces the computational burden and improves performance by making use of timing estimates in previous observation windows

optimal sequences for channel estimation using discrete fourier transform techniques this paper addresses the problem of selecting the optimum training sequence for channel estimation in communication systems over time dispersive channels by processing in the frequency domain a new explicit form of search criterion is found the gain loss factor glf which minimizes the variance of the estimation error and is easy to compute theoretical upper and lower bounds on the glf are derived an efficient directed search strategy and optimal sequences up to length 42 are given these sequences are optimal only for frequency domain estimation not for time domain estimation

application of expectation maximization algorithm to the detection of a direct sequence signal in pulsed noise jamming the detection of a direct sequence spread spectrum signal received in a pulsed noise jamming environment is considered the expectation maximization algorithm is used to estimate the unknown jammer parameters and hence obtain a decision on the binary signal based on the estimated likelihood functions the probability of error performance of the algorithm is simulated for a repeat code and a 7 4 block code simulation results show that at low signal to thermal noise ratio and high jammer power the em detector performs significantly better than the hard limiter and somewhat better than the soft limiter also at low snr there is little degradation as compared to the maximum likelihood detector with true jammer parameters at high snr the soft limiter outperforms the em detector

generic construction of binary sequences of period 2n with optimal odd correlation magnitude based on quaternary sequences of odd period n binary sequences with low odd correlation have important applications in communication systems to reduce interference in this paper using the interleaving technique we present a generic connection between binary sequences with low odd correlation and quaternary sequences with low even correlation as a result some new binary sequences with optimal odd auto correlation magnitude are obtained besides two sets consisting of 2 n 1 binary sequences of period 2 2 n 1 with the maximum odd correlation magnitude 2 n 1 2 2 are derived which are the first two optimal classes of binary sequence sets achieving the sarwate bound on the odd correlation magnitude in the literature

parameter estimation of superimposed signals using the em algorithm a computationally efficient algorithm for parameter estimation of superimposed signals based on the two step iterative em estimate and maximize with an e step and an m step algorithm is developed the idea is to decompose the observed data into their signal components and then to estimate the parameters of each signal component separately the algorithm iterates back and forth using the current parameter estimates to decompose the observed data better and thus increase the likelihood of the next parameter estimates the application of the algorithm to the multipath time delay and multiple source location estimation problems is considered

a maximum likelihood digital receiver using coordinate ascent and the discrete wavelet transform in this paper a maximum likelihood ml method is presented for joint estimation of amplitude phase time delay and data symbols in a single user direct sequence spread spectrum communication system since maximization of the likelihood function is analytically intractable a novel coordinate ascent algorithm is used to obtain sequential updates of the data symbols and all unknown nuisance parameters the novelty of the algorithm is due to the use of a multiresolution expansion of the received signal and the use of polynomial rooting in the complex plane in place of a line search over the signal delay parameter the multiresolution structure of the algorithm is exploited to reduce sensitivity to impulsive noise via wavelet thresholding computer simulations of the single user system show that the algorithm has fast convergence and comparison with theoretical lower bounds establishes that the algorithm achieves nearly optimal error performance

correlated binary regression with covariates specific to each binary observation regression methods are considered for the analysis of correlated binary data when each binary observation may have its own covariates it is argued that binary response models that condition on some or all binary responses in a given block are useful for studying certain types of dependencies but not for the estimation of marginal response probabilities or pairwise correlations fully parametric approaches to these latter problems appear to be unduly complicated except in such special cases as the analysis of paired binary data hence a generalized estimating equation approach is advocated for inference on response probabilities and correlations illustrations involving both small and large block sizes are provided

training sequence optimization in mimo systems with colored interference we address the problems of channel estimation and optimal training sequence design for multiple input multiple output systems over flat fading channels in the presence of colored interference in practice knowledge of the unknown channel is often obtained by sending known training symbols to the receiver during the training period we obtain the best linear unbiased estimates of the channel parameters based on the received training block we determine the optimal training sequence set that minimizes the mean square error of the channel estimator under a total transmit power constraint in order to obtain the advantage of the optimal training sequence design long term statistics of the interference correlation are needed at the transmitter hence this information needs to be estimated at the receiver and fed back to the transmitter obviously it is desirable that only a minimal amount of information needs to be fed back from the receiver to gain the advantage in reducing the estimation error of the short term channel fading parameters we develop such a feedback strategy in this paper

adaptive joint detection and estimation in mimo systems a hybrid systems approach an adaptive receiver based on hybrid system theory is developed for a multiuser multiple input multiple output mimo fading code division multiple access cdma system the basic idea is to treat the transmitted symbols and channel gains as unknown states discrete and continuous within a hybrid systems framework the bayesian inference based state estimation is derived using multiple model theory resulting in an optimal joint sequence estimator which is shown to be intractable in its computational complexity a suboptimal receiver imm sic is then derived based on the well known interacting multiple model imm algorithm and successive interference cancellation sic scheme this paper shows the specific approximations made to the probability densities of the optimal receiver in deriving the imm sic receiver with complexity linear in number of users this receiver design is well suited for online recursive processing of space time coded cdma system where the decoding stage is incorporated within the multiple model framework

large zero autocorrelation zones of golay sequences and their applications golay sequences have been studied for more than five decades since golay first discovered those sequences however the periodic autocorrelation of a single golay sequence is unknown in this paper for h 2 being an arbitrary even integer we show there exist three different constructions of h ary golay sequences with a zero autocorrelation zone zacz of length approximately an half a quarter or one eighth of their period those new discoveries on golay sequences can be explored during synchronization and detection at the receiver end and thus improve the performance of the communication system we present the application of binary golay sequences with zacz for intersymbol interference isi channel estimation compared with m sequences golay sequence aided channel estimation has perfect autocorrelations within the zone compared with frank zadoff chu sequences golay sequence aided channel estimation requires much lower hardware and computational complexity we also discuss the performance of golay sequence aided channel estimation in terms of its error variance finally simulations are conducted to show the performance of our proposed scheme against m sequences and fzc sequences in terms of symbol error rate the simulations also confirm with our theoretical results

periodic complementary binary sequences existence conditions and recursive construction procedures for sets of periodic complementary binary sequences are given relationships to sets of aperiodic complementary binary sequences and to perfect binary arrays whose two dimensional periodic autocorrelation function is a delta function are noted the connections of periodic complementary binary sequences and difference families are given sets of periodic complementary binary sequences which result from computer search are presented a diagram showing what is currently known about the existence of periodic complementary binary sequences with p

estimating efficacy in clinical trials with clustered binary responses when non compliance occurs in a clinical trial it may be of interest to supplement the intent to treat analysis with an analysis of the efficacy or biological effect of therapy sommer and zeger 1991 developed a method for estimating efficacy applicable to the case of a binary response variable and all or none compliance that assumes independent subject responses we extend this approach to accommodate within cluster correlations as may be expected in a cluster randomized design the method is illustrated using data from a controlled village randomized clinical trial conducted in indonesia to investigate the effect of vitamin a supplementation on mortality in children we find that within cluster correlations for these data are very small and that taking into account the clustering does not substantially affect inferences in this case additional calculations show that small within cluster correlations though larger than those found in the vitamin a data may have a large impact on efficacy inferences we also present the results of a simulation study that demonstrates the validness of the proposed approach for finite sample sizes

complementary sequences for isi channel estimation a merit factor based on the sequence autocorrelation function whose minimization leads to the reduction in the cramer rao lower bound crlb for the variance of two sided intersymbol interference isi channel estimation is introduced pairs of binary pilot symbol sequences a preamble and a postamble for channel estimation are jointly designed to minimize this merit factor given that the number of channel taps is l and the length of a pilot symbol sequence is n l 1 where n spl ges l we distinguish between the case when n is even and the case when it is odd for even n we show that complementary sequences not only minimize the merit factor but also the crlb for a subset of odd n we construct almost complementary periodic sequence pairs that minimize the merit factor the optimal pilot symbol block signaling requires alternating between two in most cases different binary sequences that form the merit minimizing pair

a tighter correlation lower bound for quasi complementary sequence sets levenshtein improved the famous welch bound on aperiodic correlation for binary sequences by utilizing some properties of the weighted mean square aperiodic correlation following levenshtein s idea a new correlation lower bound for quasi complementary sequence sets qcsss over the complex roots of unity is proposed in this paper the derived lower bound is shown to be tighter than the welch bound for qcsss when the set size is greater than some value the conditions for meeting the new bound with equality are also investigated

sequence design to minimize the weighted integrated and peak sidelobe levels sequences with low aperiodic autocorrelation sidelobes are well known to have extensive applications in active sensing and communication systems in this paper we first consider the problem of minimizing the weighted integrated sidelobe level wisl which can be used to design sequences with impulse like autocorrelation and a zero or low correlation zone two algorithms based on the general majorization minimization method are developed to tackle the wisl minimization problem with guaranteed convergence to a stationary point the proposed methods are then extended to optimize the ell p norm of the autocorrelation sidelobes which leads to a way to minimize the peak sidelobe level psl criterion all the proposed algorithms can be implemented via the fast fourier transform fft and thus are computationally efficient an acceleration scheme is considered to further accelerate the algorithms numerical experiments show that the proposed algorithms can efficiently generate sequences with virtually zero autocorrelation sidelobes in a specified lag interval and can also produce very long sequences with much smaller psl compared with some well known analytical sequences

on the convergence properties of the em algorithm two convergence aspects of the em algorithm are studied i does the em algorithm find a local maximum or a stationary value of the incomplete data likelihood function ii does the sequence of parameter estimates generated by em converge several convergence results are obtained under conditions that are applicable to many practical situations two useful special cases are a if the unobserved complete data specification can be described by a curved exponential family with compact parameter space all the limit points of any em sequence are stationary points of the likelihood function b if the likelihood function is unimodal and a certain differentiability condition is satisfied then any em sequence converges to the unique maximum likelihood estimate a list of key properties of the algorithm is included

on minimizing the peak to average power ratio for the sum of n sinusoids a new derivation is presented of a previously known relationship for phasing n equal amplitude equally spaced in frequency sinusoids so that the peak to average power ratio of their sum is 2 6 db the method of derivation provides intuitive insight into why this result is possible and shows that the 2 6 db figure is obtained independently of n as long as n is large any phase or frequency modulation can be applied simultaneously to all n sinusoids without altering this result

correlation and set size bounds of complementary sequences with low correlation zone the correlation lower bounds as well as the set size upper bounds of low correlation zone complementary sequences are presented in this paper they can be treated as an extension of tang fan matsufuji bounds in and which considered only the conventional non complementary low correlation zone sequence sets

em based joint data detection and channel estimation of ds cdma signals we present two efficient iterative receiver structures of tractable complexity for joint multiuser detection and multichannel estimation jde of direct sequence code division multiple access signals the schemes result from an application of the expectation maximization em and the space alternating generalized expectation maximization sage algorithms respectively the em jde receiver updates the data bit sequences in parallel while the sage jde receiver reestimates them successively the channel parameters are updated in parallel in both schemes the em algorithm provides a set of free parameters called weight coefficients which can be selected to optimize its performance two optimality criteria are defined and analytical expressions for the corresponding optimized weight coefficients are given monte carlo simulations of a synchronous scenario show that the proposed jde receivers have excellent multiuser efficiency and are robust against errors in the estimation of the channel parameters moreover very short training sequences are required for the jde schemes to converge simulation results further demonstrate that the sage jde receiver exhibits a better performance when the users bit sequences are updated in the order of increasing signal strength i e the bit sequence of the user with the weakest signal strength is updated first at each stage

carrier frequency estimation for transmissions over selective channels this paper deals with carrier frequency estimation for burst transmissions over frequency selective channels three estimation schemes are proposed all based on the use of known training sequences the first scheme employs an arbitrary sequence and provides joint maximum likelihood ml estimates of the carrier frequency and the channel response its implementation complexity is relatively high but its accuracy achieves the cramer rao bound the second scheme is still based on the ml criterion but the training sequence is periodic which helps to reduce the computational load the third scheme also employs periodic sequences but its structure comes from heuristic reasoning theoretical analysis and simulations are employed to assess the performance of the three schemes

the evaluation of error probabilities for intersymbol and cochannel interference an efficient series that can be used to calculate the probability of error in a binary symmetric channel with intersymbol interference and additive noise is derived the series is derived by representing the noise complementary probability distribution function by an exact or approximate fourier series bounds on the accuracy of the estimate are derived for gaussian noise examples show that only a small numerical effort may be required to compute error probabilities of interest using the series applications to both finite and infinite intersymbol interference systems are discussed a similar technique is used to derive series representations for the probability of error of additive noise channels with cochannel interference or with combined intersymbol and cochannel interferences the accuracy of the results is bounded for gaussian noise

on partially blind multihead finite automata this work is concerned with 1 way multihead finite automata fa both deterministic and nondeterministic in which the symbol under only one head controls its move we call such a fa a partially blind multihead fa we show some results regarding the decision problems and closure properties of blind multihead dfa and nfa we also compare these devices with 1 way nfa augmented by reversal bounded counters finally we also present some results regarding the simulation of a partially blind dfa and nfa by a probabilistic finite automaton

synthesizing low autocorrelation and low papr ofdm sequences under spectral constraints through convex optimization and gs algorithm sequences with low autocorrelation ac and low peak to average power ratio papr are desired in many communication or signal processing applications this work investigates the synthesis of ofdm sequences with the desired low ac and low papr under spectral constraints the spectral constraints limit the maximum allowable power on each subcarrier to avoid interference on particular reserved bands and undesirable dc offset the first part of this work discusses the design of sequences with periodic ac property under spectral constraints specifically we present a convex optimization method for synthesizing ofdm sequences with minimized peak sidelobe level psl or weighted sum of sidelobe levels wssl of the periodic ac function within specified time lags the design objective to be minimized can also be a certain convex function of the sequence ac sidelobes furthermore we present methods based on gerchberg saxton gs algorithm to decrease the papr of the sequences while maintaining the optimized ac characteristic the second part of this work investigates the aperiodic ac under spectral constraints in this case the optimal sequence design problem is nonconvex by relaxing the nonconvex problem to a convex problem we provide lower bounds for psl and wssl of the aperiodic ac function based on the optimal solution for the relaxed convex problem we present an efficient algorithm to find sequences with low papr and near optimal aperiodic ac property while the spectral constraints are satisfied

binary odd periodic complementary sequences a pair of binary sequences is called complementary if the sum of their aperiodic autocorrelation functions is zero except for zero shift such sequences are known for relatively few lengths this correspondence therefore introduces pairs of binary odd periodic complementary sequences which can be constructed using q ary m sequences for many more lengths

optimal design and placement of pilot symbols for channel estimation the problem of designing and placing pilot symbols for the estimation of frequency selective random channels is considered the channel is assumed to be a block fading model with finite impulse response fir for both single input single output siso and multiple input multiple output mimo channels under the assumption of independent and identical distributed channel taps the cramer rao bound crb on the mean square error mse of semi blind channel estimators is derived and minimized with respect to pilot symbols and their placement it is shown that the optimal strategy is to place pilot symbols satisfying certain orthogonality condition in such a way that data and pilot symbols with higher power are in the middle of the packet the results also indicate that the optimal pilot placements are independent of channel probability distribution for constant modulus symbols we show that the quasi periodic placement and its generalization in the multiuser case turn out to be optimal we further consider estimating channels with correlated taps and show that the previous placement strategy is also optimal among orthogonal pilot sequences

an accurate and efficient two stage channel estimation method utilizing training sequences with closed form expressions a novel two stage frequency domain channel estimation method especially suitable for the estimation of long channels such as ultra wide band channels is proposed the proposed method can efficiently use the sequences with closed form analytical expressions such as the legendre sequences the suggested method does not require a computationally intense search for good training sequences which is infeasible for long training sequences the method is shown to present a minor improvement in the total estimation error variance when compared with the conventional single stage frequency domain channel estimation in addition the proposed method has a very efficient time domain implementation requiring at most 2n multiplications where n is the training sequence length in comparison to o n log n multiplications required for the conventional method

computational design of sequences with good correlation properties in this paper we introduce a computational framework based on an iterative twisted approximation itrox and a set of associated algorithms for various sequence design problems the proposed computational framework can be used to obtain sequences or complementary sets of sequences possessing good periodic or aperiodic correlation properties and in an extended form to construct zero or low correlation zone sequences furthermore as constrained e g finite alphabets are of interest in many applications we introduce a modified version of our general framework that can be useful in these cases several applications of itrox are studied and numerical examples focusing on the construction of real valued and binary sequences are provided to illustrate the performance of itrox for each application

generalized variance component models for clustered categorical response variables a generalized variance component model is proposed for the analysis of a categorical response variable with extra multinomial variation categorical data obtained from research designs such as randomized multicenter clinical trials or complex sample surveys with clustering frequently exhibit extra variation resulting from intracluster correlation general correlation patterns are accounted for by utilizing a mixed effects modelling approach estimating the cluster variance components through the method of moments and modelling functions of the observed proportions through the use of estimating equations a flexible set of assumptions characterizing the underlying covariance structure for the proportions can be accommodated the importance of accounting for extra variation when performing hypothesis tests is highlighted with an application to data from a multi investigator clinical trial

16 qam almost complementary sequences with low pmepr a pair of sequences is said to be an almost complementary pair acp if they have zero aperiodic autocorrelation sums except at only one position over all the positive negative time shifts having correlation property very close to that of golay complementary pairs gcps acps may be used as an alternative to gcps in many applications in communications and radar for high rate code keying ofdm communication we construct novel 16 qam acps from three new classes of quadratic offsets leading to three large sets of 16 qam almost complementary sequences with maximum peak to mean envelope power ratio pmepr of 2 4

multi image deblurring using complementary sets of fluttering patterns we present a novel coded exposure video technique for multi image motion deblurring the key idea of this paper is to capture video frames with a set of complementary fluttering patterns which enables us to preserve all spectrum bands of a latent image and recover a sharp latent image to achieve this we introduce an algorithm for generating a complementary set of binary sequences based on the modern communication theory and implement the coded exposure video system with an off the shelf machine vision camera to demonstrate the effectiveness of our method we provide in depth analyses of the theoretical bounds and the spectral gains of our method and other state of the art computational imaging approaches we further show deblurring results on various challenging examples with quantitative and qualitative comparisons to other computational image capturing methods used for image deblurring and show how our method can be applied for protecting privacy in videos

binary alexis sequences with perfect correlation binary alexis 1986 sequences are useful signals for fast start up equalization channel estimation synchronization or ranging the aperiodic autocorrelation functions of alexis sequences vanish in a broad window region when correlated using additional binary preamble and postamble sequences originally alexis sequences were found by computer search two methods are presented by which such sequences can be constructed for any length n p sup a and n 2 p sup a 1 where p is an odd prime and a 1 2 3

sequence estimation in the presence of random parameters via the em algorithm the expectation maximization em algorithm was first introduced in the statistics literature as an iterative procedure that under some conditions produces maximum likelihood hit parameter estimates in this paper we investigate the application of the em algorithm to sequence estimation in the presence of random disturbances and additive white gaussian noise as examples of the use of the em algorithm we look at the random phase and fading channels and show that a formulation of the sequence estimation problem based on the em algorithm can provide a means of obtaining ml sequence estimates a task that has been previously too complex to perform