The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper we present two real-time methods for estimating surface normals from organized point cloud data. The proposed algorithms use integral images to perform highly efficient border- and depth-dependent smoothing and covariance estimation. We show that this approach makes it possible to obtain robust surface normals from large point clouds at high frame rates and therefore, can be used in...
In this paper, an algorithm is proposed for the joint phase noise (PN) estimation and data detection in or- thogonal frequency division multiplexing signals pertaining to spatially multiplexed multiple-input multiple-output channels. Severe oscillator PN gives rise to inter-carrier interference that becomes a limiting factor in sustaining reliable communication link. Considering a received signal...
This paper presents a novel ‘Energy Efficient Tracking’ (EET) algorithm that tries to meet the localization accuracy requirement, Pa, imposed by a generic location-based application while the energy consumption for ranging and communication is optimized. More specifically, given the set of range measurements performed by a mobile node with respect to its neighboring anchors (i.e., nodes whose exact...
This paper suggests the calculation methodology of univariate and multivariate absolute risk aversion based on asymptotic analysis of conditional expectation and future excess return variance. In the paper we provide modification of the multivariate econometric algorithm on the assumption of weakly time-varying correlation matrices for which the conditions of positive definiteness were received. We...
The interference rejection combining (IRC) receiver, which can suppress inter-cell interference, is effective in improving the cell edge user throughput, and is required to function effectively in various development scenarios, e.g., in both closed-loop and open-loop multiple input multiple output (MIMO) multiplexing. The IRC receiver is typically based on the minimum mean square error (MMSE) criteria,...
The estimation of carrier frequency offset (CFO) is an important issue for OFDM systems. Many CFO estimation methods have been proposed in the past. In particular, two ESPRIT-based methods were introduced for blind CFO estimations. These ESPRIT-based methods can provide satisfactory performance at a reasonable implementation cost. In this paper, we propose a least-squares (LS) algorithm for improving...
In the context of wireless networks, a new technique is proposed for the estimation of the Collision Multiplicity (CM), i.e., the number of packets involved in a collision. The collision signals are observed and a sample covariance matrix of the observations is computed first. Then, an eigenvalue decomposition of this matrix is performed and the eigenvalues are sorted in descending order. Our approach...
The aim of this paper is to get an insight of the interference estimation for multi-layer multi-user multiple-input and multiple-output (ML-MU-MIMO) transmission for LTE-Advanced (long term evolution) systems. Different interference-aware receivers have been investigated in ML-MU-MIMO with the presence of co-layer, intra-cell and inter-cell interferences. User-specific reference signal (UE-RS) based...
The performance of any transmission scheme is coupled with the receive strategy. Herein the behavior of transmissions based on interference alignment scheme is investigated under different receive strategies. Moreover, interference alignment is compared with different state-of-art transmission schemes under the assumption of intrabase station and inter-base station coordination. The performance of...
This paper deals with distributed information processing in sensor networks. We propose the Hypothesizing Distributed Kalman Filter that incorporates an assumption of the global measurement model into the distributed estimation process. The procedure is based on the Distributed Kalman Filter and inherits its optimality when the assumption about the global measurement uncertainty is met. Recursive...
A novel approach to estimate localizability for mobile robots is presented based on probabilistic grid map (PGM). Firstly, a static localizability matrix is proposed for off-line estimation over the priori PGM. Then a dynamic localizability matrix is proposed to deal with unexpected dynamic changes. These matrices describe both localizability index and localizability direction quantitatively. The...
We cast the problem of reverse-engineering the connectivity matrix of genetic regulatory networks from a limited number of measurements as a regularized multivariate regression problem. The regularization term incorporates the prior knowledge of sparsity of genetic regulatory networks. Moreover, the genetic profiles within a measurement are assumed to be correlated with a full covariance structure...
The paper proposes a joint precoding algorithm for cyclic prefix (CP) orthogonal frequency-division multiplexing (OFDM) system that enables blind channel estimation. The study analyzes the impact of the precoding algorithm for channel estimation error and data detection error. Instead of only considering one aspect of channel estimation, as done in previous works where a fixed precoding matrix is...
This paper describes a Multiscale Online Union of Sub-Spaces Estimation (MOUSSE) algorithm for online tracking of a time-varying manifold. MOUSSE uses linear subsets of low-dimensional hyperplanes to approximate a manifold embedded in a high-dimensional space. Each subset corresponds to the leaf node in a binary tree which encapsulates the multiresolution analysis underlying the proposed algorithm...
The minimum variance distortionless response (MVDR) beamformer is a classical filter to reduce the interference plus noise energy without distorting the desired signal. Semidefinite programming (SDP) is a subfield of convex optimization concerned with the optimization of a linear objective function over the intersection of the cone of positive semidefinite matrices. In this paper, we will show MVDR...
Coordinated multi-point transmission (CoMP) allows to deal with interference limitation in cellular systems by acting as a distributed antenna system across cell boundaries. In order to successfully enable CoMP, accurate channel knowledge is required. In our work we focus on uplink joint reception, using linear MMSE combining, suppressing interference. We use LTE-Advanced signal formats together with...
The conventional linear minimum mean square error estimator (LMMSE) suffers a severe performance degradation whenever the sample size is comparable to the observation dimension. In order to tackle this problem, we propose an optimal linear correction of the conventional LMMSE, which minimizes the average mean square error (MSE) by using the moments of the complex inverse Wishart distribution. Numerical...
In classical estimation usually unbiased estimators are used. This is mainly because the bias term in classical biased estimators in general depends on the parameter to be estimated. However, recently a considerable amount of research has been spent on improving unbiased estimators by introducing a bias, e.g. based on a minimax optimization strategy. In this work we follow this idea of introducing...
A subset of long-range dependent FARIMA processes is considered. A method for estimating the parameter that describes the long-range dependency of such a process is suggested. The method is based on an asymptotic expression for the covariance function of the process and gives a closed form solution by means of a weighted linear least squares estimate. The variance of the estimate given by themethod...
This paper presents an adaptive filtering algorithm based on random weighting estimation method to improve the Kalman filtering algorithm's accuracy for dynamic navigation positioning. The method involves the concept of fading filtering algorithm. Theories of random weighting estimation and windowing algorithms are proposed for estimating adaptive fading factors based on innovation vectors and estimating...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.