Optimal Channel Switching Over Gaussian Channels Under Average Power and Cost Constraints

Tutay, Mehmet Emin; Gezici, Sinan; Soğancı, Hamza; Arıkan, Orhan

doi:10.1109/tcomm.2015.2418252

Cited by 10 publications

(51 citation statements)

References 31 publications

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“…and channel switching problems such as [4,[20][21][22], there exist no studies in the literature that consider the optimization of both centralized and decentralized detection systems in the presence of cost constrained measurements based on a specific cost function as in [3]. In this study, we first consider the centralized detection problem and propose a general formulation for allocating the cost budget to measurement devices in order to achieve the optimum performance according to the Bayesian criterion.…”

Section: Although Costs Of Measurements Have Been Considered In Variomentioning

confidence: 99%

“…On the other hand, [21] investigates the tradeoff between reducing the measurement cost and keeping the estimation accuracy within acceptable levels in continuous time linear filtering problems. In [22], the channel switching problem is studied, where the aim is to minimize the probability of error between a transmitter and a receiver that are connected via multiple channels and only one channel can be used at a given time. In that study, a logarithmic cost function similar to that in [3] is employed for specifying the cost of using a certain channel.…”

Section: Introductionmentioning

confidence: 99%

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Centralized and decentralized detection with cost-constrained measurements

Laz

Gezici

2017

Signal Processing

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In this thesis, optimal detection performance of centralized and decentralized detection systems is investigated in the presence of cost constrained measurements. For the evaluation of detection performance, Bayesian, Neyman-Pearson and Jdivergence criteria are considered. The main goal for the Bayesian criterion is to minimize the probability of error (more generally, the Bayes risk) under a constraint on the total cost of the measurement devices. In the Neyman-Pearson framework, the probability of detection is to be maximized under a given cost constraint. In the distance based criterion, the J-divergence between the distributions of the decision statistics under different hypotheses is maximized subject to a total cost constraint. The probability of error expressions are obtained for both centralized and decentralized detection systems, and the optimization problems are proposed for the Bayesian criterion. The probability of detection and probability of false alarm expressions are obtained for the Neyman-Pearson strategy and the optimization problems are presented. In addition, J-divergences for both centralized and decentralized detection systems are calculated and the corresponding optimization problems are formulated. The solutions of these problems indicate how to allocate the cost budget among the measurement devices in order to achieve the optimum performance. Numerical examples are presented to discuss the results. Gezici for his guidance, suggestions and encouragement throughout this work. KeywordsHe is a modest, kind and considerate academician having a great personality.Working with him was a great privilege and honor for me.

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Section: Although Costs Of Measurements Have Been Considered In Variomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Centralized and decentralized detection with cost-constrained measurements

Laz

Gezici

2017

Signal Processing

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“…By choosing aλ ∈ (0, 1) such thatλP + (1 −λ)P − av = P av and considering the expressions in (25) and (26), the same approach employed in the previous part of the proof (see (22)- (24)) can be applied to show that the optimal channel switching strategy outperforms the optimal single channel strategy. Thus, it is concluded that when the condition in Proposition 2 is not satisfied, the optimal single channel strategy achieves a smaller average capacity than the optimal channel switching strategy, which implies that the condition in the proposition is necessary to achieve the same maximum average capacity for both strategies.…”

Section: A Optimal Channel Switching Versus Optimal Single Channel Smentioning

confidence: 99%

“…In the presence of multiple channels between a transmitter and a receiver, it may be beneficial to perform channel switching; that is, to transmit over one channel for a certain fraction of time, and then switch to another channel for the next transmission period [7], [19]- [22]. In [7], the channel switching problem is investigated in the presence of an average 0090-6778 © 2015 IEEE.…”

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confidence: 99%

“…Although the optimal channel switching problem is studied thoroughly in terms of average probability of error minimization (e.g., [7], [21], [22]) and in the context of opportunistic spectrum access (e.g., [23]- [26]), no studies in the literature have considered the channel switching problem for maximization of data rates by jointly optimizing time sharing (channel switching) factors and corresponding power levels (please see [1] for the conference version of this study). In this paper, the average Shannon capacity is considered as the main metric since it gives the maximum achievable data rates with low probability of decoding errors.…”

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confidence: 99%

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Optimal Channel Switching Strategy for Average Capacity Maximization

Sezer

Gezici

İnaltekin

2015

IEEE Trans. Commun.

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Abstract-In this study, an optimal channel switching strategy is proposed for average capacity maximization in the presence of average and peak power constraints. Necessary and sufficient conditions are derived to determine when the proposed optimal channel switching strategy can or cannot outperform the optimal single channel strategy, which performs no channel switching. Also, it is obtained that the optimal channel switching strategy can be realized by channel switching between, at most, two different channels. In addition, a low-complexity optimization problem is derived to obtain the optimal channel switching strategy. Furthermore, based on some necessary conditions that need to be satisfied by the optimal channel switching solution, an alternative approach is proposed for calculating the optimal channel switching strategy. Numerical examples are provided to exemplify the derived theoretical results and to provide intuitive explanations.

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A Markovian analytical framework for public‐safety video sharing by device‐to‐device communications

Zhao

Han

Mao

et al. 2017

Concurrency and Computation

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Monitoring video of city surveillance camera plays an important role in public security and disaster relief, which is often used by first responder teams, such as firefighters and police officers.The first responders in emergency situations require consistent connection with one another and request the remote real-time monitoring video for effective cooperation and coordination.However, the capacity and privacy of public wireless networks fail to satisfy the requirements in many emergency scenarios, which often leads to exceptionally high traffic loads and insecurity.Device-to-device (D2D) communications have been deemed a key solution for this problem, as responders can use D2D links for traffic offloading and secure communications. To investigate the D2D-based solution for public safety video sharing, this paper focuses on the Focus Geographical Area (FGA) video consisting of multiple camera streams requiring higher bandwidth consumption than that of the traditional single-camera stream, which attracts a large number of contents delivery requests in emergency situations. This paper develops a new Traffic Burden Switching Markovian (TBSM) model to evaluate the performance of transmitting real-time FGA video in wireless networks with D2D communications. First, a novel D2D area model is introduced to characterize link-switching in wireless D2D communication networks. Based on the proposed D2D area model, the state and transition matrix of TBSM model are then derived by jointly considering user mobility, link-switching, and FGA video view-switching. Thereafter, some key performance metrics including system offloading ratio, D2D link-switching ratio, and view-switching ratio are derived on the basis of coverage probability and ergodic rate. The performance results show the significant varying performance among D2D areas with different geographical locations in D2D enabled wireless networks, which is referred to as multi-D2D-area diversity. The excellent match between simulation and model results validates the accuracy of the TBSM model, which can be used to provide guidelines for the deployment and optimization of future wireless video networks with D2D communications. KEYWORDS Device-to-device area, Camera view switching, Markovian model, Traffic burden switching 1 tional bandwidth-limited wireless networks with the following characteristics: (1) provision of more than one camera stream, (2) permission Concurrency Computat: Pract Exper. 2017;29:e4078.wileyonlinelibrary.com/journal/cpe

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Optimal Channel Switching Over Gaussian Channels Under Average Power and Cost Constraints

Cited by 10 publications

References 31 publications

Centralized and decentralized detection with cost-constrained measurements

Centralized and decentralized detection with cost-constrained measurements

Optimal Channel Switching Strategy for Average Capacity Maximization

A Markovian analytical framework for public‐safety video sharing by device‐to‐device communications

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