Optimum Power Allocation in Sensor Networks for Active Radar Applications

Alirezaei, Gholamreza; Taghizadeh, Omid; Mathar, Rudolf

doi:10.1109/twc.2015.2396052

Cited by 35 publications

(23 citation statements)

References 15 publications

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“…where (a) is because all entries ofP d − p d p T d are less that 1, (b) is found using Cauchy-Schwarz inequality, (c) comes from the inequality in IPC, and (d) is due to ξ 1. This implies that when ξ 1, (O 3 ) can be approximated with (O l 3 ) in (18). min…”

Section: Maximizing MDC In (15) Under Ipcmentioning

confidence: 99%

On Power Allocation for Distributed Detection With Correlated Observations and Linear Fusion

Ahmadi¹,

Maleki

Vosoughi

2018

IEEE Trans. Veh. Technol.

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We consider a binary hypothesis testing problem in an inhomogeneous wireless sensor network, where a fusion center (FC) makes a global decision on the underlying hypothesis. We assume sensors' observations are correlated Gaussian and sensors are unaware of this correlation when making decisions. Sensors send their modulated decisions over fading channels, subject to individual and/or total transmit power constraints. For parallel-access channel (PAC) and multiple-access channel (MAC) models, we derive modified deflection coefficient (MDC) of the test statistic at the FC with coherent reception. We propose a transmit power allocation scheme, which maximizes MDC of the test statistic, under three different sets of transmit power constraints: total power constraint, individual and total power constraints, individual power constraints only. When analytical solutions to our constrained optimization problems are elusive, we discuss how these problems can be converted to convex ones. We study how correlation among sensors' observations, reliability of local decisions, communication channel model and channel qualities and transmit power constraints affect the reliability of the global decision and power allocation of inhomogeneous sensors.

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Section: Maximizing MDC In (15) Under Ipcmentioning

confidence: 99%

On Power Allocation for Distributed Detection With Correlated Observations and Linear Fusion

Ahmadi¹,

Maleki

Vosoughi

2018

IEEE Trans. Veh. Technol.

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“…For the cooperative network of spectrum sharing, by solving the convex optimization problem, the optimal power allocation strategy with minimum energy consumption under the requirements of QoS was obtained in [11]. For the symbol programming problem of target detection in distributed radar sensor network, the closed-form expression of optimal power allocation by establishing the optimal linear unbiased estimation model was obtained in [12]. In [13], based on the received signal interference plus noise ratio, Markov chain was adopted to obtain the dynamic power control method with the minimum packet error rate (PER).…”

Section: Introductionmentioning

confidence: 99%

Transmit Power Allocation with Connectivity Probability for Multi-QoS in Cluster Flight Spacecraft Network

Yan

et al. 2020

Wireless Communications and Mobile Computing

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In this paper, we investigate the transmit power allocation problem to minimize the average packet error rate at the access point in the cluster flight spacecraft network, which adopts the CSMA/CA channel access mechanism. First, the node mobility, nodal distance distribution, and probabilistic adjacency matrix were formulated for cluster flight spacecraft network based on twinsatellite mode. en, the optimization-theoretic model described the optimized transmit power allocation strategy and its implementation algorithm was proposed. And the problem of minimizing the packet error rate of the cluster flight spacecraft network system can be converted into maximizing the expectation of the binary probabilistic adjacency matrix, i.e., maximizing the sum of the nondiagonal elements in the probabilistic adjacency matrix. Due to discreteness of nodal distance distribution, Monte Carlo method was applied to solve the transmit power allocation problem. Yet importantly, the influence of node transmit power on the QoS performance of cluster flight spacecraft network was simulated and analyzed under the assumption of finite overall network transmit power and low traffic load. Finally, the results show that the pocket error rate increases with the provided traffic load, but the pocket error rate hardly changes with the same traffic load in different sequential time slots of any orbital hyperperiod or in the same time slot of different orbital hyperperiods, and by maximizing the sum of the nondiagonal elements in the probabilistic adjacency matrix, the pocket error rate minimum is achieved for a given total network transmit power at any time slot for cluster flight spacecraft network.

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“…Examples include, but are not limited to, industrial automation, military surveillance, information collection, and environmental monitoring. [1][2][3] One of the major lines of investigation on sensor networks is the so-called distributed estimation/filtering issue that aims to design filtering schemes at each sensing nodes by using measurements information not only from the individual sensor itself but also from its neighbors according to certain topology. 4 In comparison to the conventional centralized mechanism, 5,6 the distributed filtering techniques have shown many advantages (eg, robustness, flexibility) and, accordingly, have attracted an ever-increasing research interest.…”

Section: Introductionmentioning

confidence: 99%

Distributed filtering for nonlinear time‐delay systems over sensor networks subject to multiplicative link noises and switching topology

Wang

Liu

et al. 2019

Intl J Robust & Nonlinear

137

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Summary This paper is concerned with the distributed filtering problem for a class of nonlinear time‐delay system over sensor networks subject to multiplicative link noises and switching topology. Both discrete and distributed time delays are included in the system model. Each sensor estimates the system state by means of the measurements not only from itself but also from its neighboring nodes according to an interactive topology. The multiplicative stochastic link noises are taken into consideration to reflect the random perturbations during the information exchanges between sensor nodes. The considered communication topology is switching according to certain predetermined rules. The purpose of the addressed problem is to develop a distributed filtering strategy such that, in the presence of multiplicative stochastic link noises and switching topology, the resulting filtering error dynamics is exponentially stable in the mean square sense and also satisfies the prespecified weighted disturbance attenuation level. In light of the average dwell time technique in combination with stochastic analysis, sufficient conditions are derived for the solvability of the addressed distributed filtering problem, and the desired filtering gains are then obtained through solving certain convex optimization problems. An illustrative simulation example is presented to demonstrate the correctness and applicability of the obtained theoretical results.

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Optimum Power Allocation in Sensor Networks for Active Radar Applications

Cited by 35 publications

References 15 publications

On Power Allocation for Distributed Detection With Correlated Observations and Linear Fusion

On Power Allocation for Distributed Detection With Correlated Observations and Linear Fusion

Transmit Power Allocation with Connectivity Probability for Multi-QoS in Cluster Flight Spacecraft Network

Distributed filtering for nonlinear time‐delay systems over sensor networks subject to multiplicative link noises and switching topology

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