We give numerically tractable, explicit integral expressions for the distribution of the signal-to-interference-andnoise- ratio (SINR) experienced by a typical user in the downlink channel from the k-th strongest base...
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ISBN:
(纸本)9781479904464
We give numerically tractable, explicit integral expressions for the distribution of the signal-to-interference-andnoise- ratio (SINR) experienced by a typical user in the downlink channel from the k-th strongest base stations of a cellular network modelled by Poisson point process on the plane. Our signal propagation-loss model comprises of a power-law pathloss function with arbitrarily distributed shadowing, independent across all base stations, with and without Rayleigh fading. Our results are valid in the whole domain of SINR, in particular for SINR < 1, where one observes multiple coverage. In this latter aspect our paper complements previous studies reported in [1].
Covering location models consider a demand "covered" if there is at least one facility sited within a preset threshold distance. If more than one facility satisfies this criterion, it is implicitly assumed t...
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Covering location models consider a demand "covered" if there is at least one facility sited within a preset threshold distance. If more than one facility satisfies this criterion, it is implicitly assumed that one of these facilities - usually the closest - will serve the customer, while the remaining ones will have no relation to the demand. However, there are cases in which this multiple coverage has either synergetic or undesired effects. In digital television broadcast networks using Single Frequency Network transmissions, if a customer receives transmissions from more than one transmitter, the strongest transmitter is the main signal source, while the second and following transmitters can either contribute to a good reception or act as sources of interference, depending on the technology and their relative locations. In this case, facilities should be located so as to avoid overlapping coverage if there is interference, or enhancing overlapping coverage if signals are combined constructively. We propose models that are solved using a commercial software, that address this problem. One of these models is used to compare different alternatives of network design for a region in Chile, and to find the best coverage situations. (C) 2011 Elsevier Ltd. All rights reserved.
coverage problems are a flourishing topic in optimization, thanks to the recent advances in the field of wireless sensor networks. The main coverage issue centres around critical conditions that require reliable monit...
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coverage problems are a flourishing topic in optimization, thanks to the recent advances in the field of wireless sensor networks. The main coverage issue centres around critical conditions that require reliable monitoring and prohibit failures. This issue can be addressed by maximal-exposure paths, regarding which this article presents new results. Namely, it shows how to minimize the sensing range of a set of sensors in order to ensure the existence of a k-covered path between two points on a given region. Such a path's coverage depends on k >= 2, which is fixed. The three types of regions studied are: a planar graph, the whole plane and a polygonal region.
Given a set S of n antennas and point q on the plane, q is alpha-covered by S if there exists s(i), s(j) is an element of S such that the angle measured angle(s(i), q, s(j)) >= alpha. It is shown how to minimise th...
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Given a set S of n antennas and point q on the plane, q is alpha-covered by S if there exists s(i), s(j) is an element of S such that the angle measured angle(s(i), q, s(j)) >= alpha. It is shown how to minimise the transmission range of S to alpha-cover a point in O(n) time and space, and how to construct the pi/2-covered region in O(n log n) time and O(n) space. Finally, this paper introduces the coverage Voronoi diagram and an algorithm to construct it in O(n(4) log n) time. (C) 2011 Elsevier B.V. All rights reserved.
Background: Mass spectrometry (MS) based protein profiling has become one of the key technologies in biomedical research and biomarker discovery. One bottleneck in MS-based protein analysis is sample preparation and a...
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Background: Mass spectrometry (MS) based protein profiling has become one of the key technologies in biomedical research and biomarker discovery. One bottleneck in MS-based protein analysis is sample preparation and an efficient fractionation step to reduce the complexity of the biological samples, which are too complex to be analyzed directly with MS. Sample preparation strategies that reduce the complexity of tryptic digests by using immunoaffinity based methods have shown to lead to a substantial increase in throughput and sensitivity in the proteomic mass spectrometry approach. The limitation of using such immunoaffinity-based approaches is the availability of the appropriate peptide specific capture antibodies. Recent developments in these approaches, where subsets of peptides with short identical terminal sequences can be enriched using antibodies directed against short terminal epitopes, promise a significant gain in efficiency. Results: We show that the minimal set of terminal epitopes for the coverage of a target protein list can be found by the formulation as a set cover problem, preceded by a filtering pipeline for the exclusion of peptides and target epitopes with undesirable properties. Conclusions: For small datasets (a few hundred proteins) it is possible to solve the problem to optimality with moderate computational effort using commercial or free solvers. Larger datasets, like full proteomes require the use of heuristics.
In large-scale investigation of electrical structure,magnetotelluric (MT) survey is usually configured along profile orthogonal to regional strike ***,two-dimensional (2D) inversion is now commonly used for the conven...
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In large-scale investigation of electrical structure,magnetotelluric (MT) survey is usually configured along profile orthogonal to regional strike ***,two-dimensional (2D) inversion is now commonly used for the convenience of measurement and ***, our research suggests that 2D MT inversion considering only off-diagonal elements of impedance tensor can not provide off-profile structure which may sometimes imply the variation of resistivity parameter along the direction that parallels strike direction. In this paper,we process and invert 2D MT data set by 3D inversion *** firstly eliminate the correlated noise caused by static effect employing moving window filtering in pseudo-section assisted by artificially recognizing the source of static effect on geology map and satellite image. After de-noising,MT data set becomes redundant for single reconstruction of resistivity model,so we split the whole data set into two distinct subsets and search their respective models *** the same model parameters in a particular area by repeating inversions, this is what we called"multiple coverage"of MT inversion which furnishes interpreters with more models and objective evaluation of reliability for the inversion. Our inversion results indicate that 3D MT inversion of 2D data is able to map the 3D distribution of resistivity on and off the profile;multiple coverage of MT inversion searches the best fitting models along distinct routes in model space and converges at the models close to each other;it also reveals the uncertainty of resistivity parameters in the area data set covers poorly.
Consider the graph G = (V, E) with node set V, edge set E. The subsets D, R subset of V denote the sets of demand and candidate response nodes respectively. A demand i is an element of D that requires l(i) response un...
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Consider the graph G = (V, E) with node set V, edge set E. The subsets D, R subset of V denote the sets of demand and candidate response nodes respectively. A demand i is an element of D that requires l(i) response units is said to be covered, when the j'th response unit to it is within the distance delta(jli), j = 1, 2,..., l(i). The objective under these assumptions is to determine i) the minimum number of response units that cover all the demands, ii) the location of a known number of response units in order to maximize the coverage. We develop a heuristic algorithm that finds a near-optimal solution for the problems described above. Finally a computational and comparative experience is presented.
In this paper we propose a new criterion for coverage which is suitable for two kinds of applications: (i) location of fire trucks in a geographical area in which some demands require multiple fire trucks to be within...
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In this paper we propose a new criterion for coverage which is suitable for two kinds of applications: (i) location of fire trucks in a geographical area in which some demands require multiple fire trucks to be within an acceptable distance standard to achieve coverage; and (ii) location of ambulances in an environment in which a large demand volume often leads to the unavailability of the most desirable response unit. The set covering location problem and the maximal covering location problem are examined in the proposed modeling framework. Properties for these models are developed, and limited computational experience is reported.
The relationship between the maximal covering problem and the P-median problem is reviewed. It is shown that two multiple coverage models, the maximum expected coverage problem (MECP) and the backup coverage problem (...
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作者:
NAUS, JIProfessor
Department of Statistics Rutgers- The State University of New Jersey New Brunswick NJ 08903
Certain statistical applications deal with the extremal distributions of the number of points in a moving interval or window of fixed length. This article gives an approximation that is highly accurate for several of ...
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Certain statistical applications deal with the extremal distributions of the number of points in a moving interval or window of fixed length. This article gives an approximation that is highly accurate for several of these distributions. Applications include the maximum cluster of points on a line or circle, multiple coverage by subintervals or subarcs of fixed size, the length of the longest success run in Bernoulli trials, and the generalized birthday problem.
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