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An efficient Bayesian method for off-line estimation of the position and the path loss model parameters of a base station is presented. Two versions of three different on-line positioning methods are tested using real data collected from a cellular network. The tests confirm the superiority of the methods that use the estimated path loss parameter distributions compared to the conventional methods...
By analyzing information transmission in stable and unstable, open- and closed-loop linear continuous-time Gaussian systems, connections within the MMSE of causal estimation, mutual information rate, and the integral of a Popov function are discussed. Yovits' equality for scalar stable systems and Anderson's equality for scalar unstable systems concerning MMSE are extended to multivariable systems...
This paper introduces a towed-array shape estimation technique that exploits the directional structure of the time-varying acoustic field. Unlike conventional array shape estimation methods that use discrete sources of opportunity, the proposed approach does not assume knowledge of the number of sources in the field or their estimated directions. Instead, the entire time-varying field directionality...
In this paper consensus based algorithms for distributed estimation in sensor networks are discussed and a new algorithm with decentralized adaptation is proposed for solving the problem where the state of a monitored process is observed only by a relatively small percentage of the sensors at each iteration of the algorithm. The given analysis shows that adaptation of the gains in the consensus scheme...
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...
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