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The mathematical models of populations of mutually coupled oscillators having self-synchronization capabilities are a powerful tool for designing sensor networks with high energy efficiency, fault tolerance and scalability. In this work, we derive the conditions for the existence the asymptotic stability of the equilibrium of a system capable to provide maximum likelihood estimates through only local...
In this paper, we propose a semi-blind MAP (maximum "a posteriori") channel estimation method based on an expectation-maximization block algorithm (EM-MAP-block). In the OFDM communication context, our algorithm still have a linear arithmetical complexity. However, it yields to an SNR improvement going up to 3.5 dB compared to classical training sequences based channel estimation method...
For MIMO systems operating over frequency-selective channels, we establish the Cramer-Rao bound (CRB) for the CFO and channel parameters. We derive training sequences so that the resulting CRB on the CFO is independent of the channel. We show that these designs lead to simple implementation of the maximum likelihood estimators of the CFO and channel parameters, Simulation results illustrate the performance...
In this paper we present a new source separation method based on dynamic sparse source signal models. Source signals are modeled in frequency domain as a product of a Bernoulli selection variable with a deterministic but unknown spectral amplitude. The Bernoulli variables are modeled in turn by first order Markov processes with transition probabilities learned from a training database. We consider...
Mobile location using time of arrival (TOA), time difference of arrival (TDOA) or angle of arrival (AOA) measurements has received considerable attention over the last years. Several closed-form algorithms have been presented for the TOA and TDOA case based on approximations of the maximum-likelihood (ML) estimator. In the case of AOA measurements, only ad-hoc estimators have been presented in order...
In this paper, we consider the localization of a source from quantized measurements of time of arrivals (TOA) or time difference of arrivals (TDOA). Applications include, as particular examples, acoustic source localization from a network of microphones under communication constraints, and the localization of a base station using a geolocalized mobile station using tuning advance measurements. We...
We propose a low complexity H-ARQ utilizing bit interleaved coded modulation (BICM). Our aim is to improve the reliability and bandwidth efficiency of wireless communications using high rate H-ARQ enabled by the proposed BICM option. This type-II hybrid ARQ generates incremental redundancy and diversity by varying the bit-to-symbol mapping during retransmission without relying on FEC design. The joint...
We propose a novel algorithm employing particle filters for acoustic source tracking in a reverberant environment. By incorporating the likelihood function computed through approximate maximum-likelihood (AML) method, the proposed algorithm is applicable to wideband sources and can be implemented for multiple sources tracking. Both computer simulation and experimental results show the effectiveness...
In cooperative wireless networks, virtual antenna arrays formed by distributed network nodes can provide cooperative diversity. Obviating channel estimation, differential schemes have long been appreciated in conventional multi-input multi-output (MIMO) communications. However, distributed differential schemes for general cooperative network setups have not been thoroughly investigated. In this paper,...
We present multichannel speech enhancement method based on MAP speech spectral magnitude estimation using a generalized gamma model of speech prior distribution, where the model parameters are adapted from actual noisy speech in a frame-by-frame manner. The utilization of a more general prior distribution with its online estimation is shown to be effective for speech spectral estimation. We tested...
This paper focuses on the development of a radio localization technique for a wireless sensor network infrastructure where a large number of simple power-aware nodes are spread in indoor environments. Fixed and moving nodes exchange radio messages but can only measure mutual power figures such as the received signal strength (RSS) indicator. Local maximum likelihood estimation from propagation models...
For a number of training samples T that do not exceed the number of antenna elements M, we propose a non-degenerate normalized LR test that can be used in various detection-estimation problems. For the null hypothesis this test is described by a scenario-free probability density function
Mobile positioning has drawn significant attention in recent years. In dealing with the non-line-of-sight (NLOS) propagation error, the dominant error source in the mobile positioning, most previous research in this area has focused on the NLOS identification and mitigation. In this paper, we investigate new positioning algorithms to take advantage of the NLOS propagation paths rather than cancelling...
This paper presents an optimum power allocation strategy for the maximum likelihood based channel estimation in the space-time coded multiple-input multiple-output systems employing a data-bearing approach for pilot-embedding. The corresponding channel estimation error, the Chernoff's upper bound on the detection error probability, and a lower bound on channel capacity of such systems are analyzed...
In this paper we propose an extended differential unitary space-time modulation (xDUSTM) scheme that can offer improved error performance over the differential unitary space-time modulation (DUSTM) scheme. DUSTM is well suited to rapidly time-varying unknown channels. It has a simple structure, but incurs an error performance penalty of about 3 dB compared to its coherent counterpart. The xDUSTM scheme...
This contribution proposes a new joint estimation method of multiple carrier frequency offsets (CFOs) and channels in the uplink of multiuser orthogonal frequency division multiplexing (OFDM) systems. The estimators are derived from the optimal maximum-likelihood (ML) principle. Complexity reductions are achieved by exploiting the correlation properties of the training-sequence. The grid search algorithm...
This paper considers the problem of decentralized data fusion (DDF) for large wireless sensor networks with stringent bandwidth requirements. To reduce the power and bandwidth costs of wireless transmissions, each sensor node is confined to quantize its sensing data and send 1-bit information only. Under this setting, we derive the maximum likelihood (ML) data fusion rule for decentralized parameter...
In this paper, we propose a new method for practical non-Gaussian and non-stationary underwater ambient noise modeling and direction-finding approach. In this application, measurement of ambient noise in natural environment shows that noise can sometimes be significantly non-Gaussian and time-varying features such as variances. Therefore, signal processing algorithms such as direction-finding that...
A method is derived for passively locating wide-band targets (typically acoustic targets) which may be moving at speeds sufficient to produce significant Doppler shift. The method involves a generalisation of standard beam forming techniques. It is shown that conventional beam forming techniques have less discrimination in the direction of motion of the sources, whereas the proposed technique exhibits...
This paper introduces a novel ML based approach to channel identification for time variant SIMO (single input multiple output) systems fed by a stochastic process. We focus on the particular case where the unknowns are represented by the channels phases, that find applications in radar interferometry. Starting from the rigorous formulation of the ML estimator, we derive an approximation that makes...
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