326 research outputs found

    Interference estimation with applications to blind multiple-access communication over fading channels

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    Includes bibliographical references.We consider the detection of nonorthogonal multipulse signals on multiple-access fading channels. The generalized maximum-likelihood rule is employed to decode users whose complex fading gains are unknown. We develop geometrical interpretations for the resulting detectors and their corresponding asymptotic efficiencies. The generalized maximum-likelihood detection rule is then applied to find a matched subspace detector for the frequency-selective fading channel, under the assumption of a short coherence time (or long coherence time without the computational power to track the fading parameters). We propose blind implementations of these detectors for nonorthogonal multipulse signaling on both frequency-nonselective and frequency-selective multiple-access fading channels. These blind detectors extend the results of Wang and Poor to multipulse modulation and fast frequency selective fading. For comparison, the minimum mean-squared error decision rules for these channels are derived and blind implementations of their corresponding detectors are developed.This work was supported by the National Science Foundation under Contract ECS 9979400 and by the Office of Naval Research under Contracts N00014-89-J-1070 and N0014-00-1-0033

    Semiblind Channel Estimation and Data Detection for OFDM Systems With Optimal Pilot Design

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    This paper considers semiblind channel estimation and data detection for orthogonal frequency-division multiplexing (OFDM) over frequency-selective fading channels. We show that the samples of an OFDM symbol are jointly complex Gaussian distributed, where the mean and covariance are determined by the locations and values of fixed pilot symbols. We exploit this distribution to derive a novel maximum-likelihood (ML) semiblind gradient-descent channel estimator. By exploiting the channel impulse response (CIR) statistics, we also derive a semiblind data detector for both Rayleigh and Ricean fading channels. Furthermore, we develop an enhanced data detector, which uses the estimator error statistics to mitigate the effect of channel estimation errors. Efficient implementation of both the semiblind and the improved data detectors is provided via sphere decoding and nulling-canceling detection. We also derive the Cramér-Rao bound (CRB) and design optimal pilots by minimizing the CRB. Our proposed channel estimator and data detector exhibit high bandwidth efficiency (requiring only a few pilot symbols), achieve the CRB, and also nearly reach the performance of an ideal reference receiver

    Convergence behaviours of an adaptive step-size constant modulus algorithm for DS-CDMA receivers

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    A convergence analysis of the blind adaptive step-size constant modulus algorithm (AS-CMA) for direct-sequence code division multiple access (DS-CDMA) receivers is presented. Analytical results show similar convergence behaviours of the AS-CMA receiver and the adaptive step-size stochastic approximation (ASSA) receiver. Simulations show that the blind AS-CMA algorithm performs comparably with the non-blind AS-SA in a Markovian type of nonstationary environment. The robustness of the proposed algorithm to different settings of the initial step-size is also shown

    Blind adaptive constrained reduced-rank parameter estimation based on constant modulus design for CDMA interference suppression

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    This paper proposes a multistage decomposition for blind adaptive parameter estimation in the Krylov subspace with the code-constrained constant modulus (CCM) design criterion. Based on constrained optimization of the constant modulus cost function and utilizing the Lanczos algorithm and Arnoldi-like iterations, a multistage decomposition is developed for blind parameter estimation. A family of computationally efficient blind adaptive reduced-rank stochastic gradient (SG) and recursive least squares (RLS) type algorithms along with an automatic rank selection procedure are also devised and evaluated against existing methods. An analysis of the convergence properties of the method is carried out and convergence conditions for the reduced-rank adaptive algorithms are established. Simulation results consider the application of the proposed techniques to the suppression of multiaccess and intersymbol interference in DS-CDMA systems

    A detection theoretical approach to digital communications using autoregressive process shift keying

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    I klassisk digital kommunikasjon overføres en bitstrøm gjennom en kanal ved å modulere parametrene til en deterministisk bærebølge. Noen kjente eksempler er amplitudemodulasjon (AM), frekvensmodulasjon (FM) og fasemodulasjon (PM). Mottakeren estimerer parametrene til det informasjonsbærende signalet og bruker en deteksjonsregel til å klassifisere den mottatte bølgeformen som en av flere mulige parametriske signaler. Konvensjonelle metoder gir ingen beskyttelse mot at ikke-autoriserte mottakere avlytter og dekoder signalet. Blant ferske metoder som tilbyr en viss beskyttelse mot avlytting finner vi såkalte spredt spektrum-teknikker og kaotiske digitale kodere. Slike teknikker krever nøyakig synkronisering mellom sender og mottaker. Selv små synkroniseringsfeil kan føre til store bitfeilrater hos mottakeren. Denne oppgaven har undersøkt et nytt konsept innen digital kommunikasjon, som er basert på å bruke realisasjoner av stokastiske prosesser som informasjonsbærende signaler. Teknikken har innebygd sikkerhet mot avlytting. Samtidig er det mulig å konstruere dekodere som er enklere enn de som brukes i spredt spektrum og kaotisk kommunikasjon. Målet med prosjektet er å undersøke noen fundamentale egenskaper ved den nye teknikken: 1) Hvordan kan vi finne et statistisk mål på avstand mellom de informasjonsbærende stokastiske prosessene? 2) Hvilken detektor skal vi bruke for å dekode informasjonssekvensen, og hvor god ytelse gir denne? 3) Hvordan skal vi velge de stokastiske prosessene
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