The Experts below are selected from a list of 183 Experts worldwide ranked by ideXlab platform
Robe W Heath - One of the best experts on this subject based on the ideXlab platform.
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delay constrained video Transmission Quality driven resource allocation and scheduling
IEEE Journal of Selected Topics in Signal Processing, 2015Co-Authors: Amin Abdel Khalek, Constantine Caramanis, Robe W HeathAbstract:Real-time video demands Quality-of-service (QoS) guarantees such as delay bounds for end-user satisfaction. Furthermore, the tolerable delay varies depending on the use case such as live streaming or two-way video conferencing. Due to the inherently stochastic nature of wireless fading channels, deterministic delay bounds are difficult to guarantee. Instead, we propose providing statistical delay guarantees using the concept of effective capacity. We consider a multiuser setup whereby different users have (possibly different) delay QoS constraints. We derive the resource allocation policy that maximizes the sum video Quality and applies to any Quality metric with concave rate-Quality mapping. We show that the optimal operating point per user is such that the rate-distortion slope is the inverse of the supported video source rate per unit bandwidth, a key metric we refer to as the source spectral efficiency. We extend the resource allocation policy to capture video Quality-driven adaptive user-subcarrier assignment in wideband channels as well as capture the impact of adaptive modulation and coding. We also solve the alternative problem of fairness-based resource allocation whereby the objective is to maximize the minimum video Quality across users. Finally, we derive user admission and scheduling policies that enable selecting a maximal user subset such that all selected users can meet their statistical delay requirement. Results show that video users with differentiated QoS requirements can achieve similar video Quality with vastly different resource requirements. Thus, QoS-aware scheduling and resource allocation enable supporting significantly more users under the same resource constraints.
Amin Abdel Khalek - One of the best experts on this subject based on the ideXlab platform.
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delay constrained video Transmission Quality driven resource allocation and scheduling
IEEE Journal of Selected Topics in Signal Processing, 2015Co-Authors: Amin Abdel Khalek, Constantine Caramanis, Robe W HeathAbstract:Real-time video demands Quality-of-service (QoS) guarantees such as delay bounds for end-user satisfaction. Furthermore, the tolerable delay varies depending on the use case such as live streaming or two-way video conferencing. Due to the inherently stochastic nature of wireless fading channels, deterministic delay bounds are difficult to guarantee. Instead, we propose providing statistical delay guarantees using the concept of effective capacity. We consider a multiuser setup whereby different users have (possibly different) delay QoS constraints. We derive the resource allocation policy that maximizes the sum video Quality and applies to any Quality metric with concave rate-Quality mapping. We show that the optimal operating point per user is such that the rate-distortion slope is the inverse of the supported video source rate per unit bandwidth, a key metric we refer to as the source spectral efficiency. We extend the resource allocation policy to capture video Quality-driven adaptive user-subcarrier assignment in wideband channels as well as capture the impact of adaptive modulation and coding. We also solve the alternative problem of fairness-based resource allocation whereby the objective is to maximize the minimum video Quality across users. Finally, we derive user admission and scheduling policies that enable selecting a maximal user subset such that all selected users can meet their statistical delay requirement. Results show that video users with differentiated QoS requirements can achieve similar video Quality with vastly different resource requirements. Thus, QoS-aware scheduling and resource allocation enable supporting significantly more users under the same resource constraints.
Hsiaohwa Chen - One of the best experts on this subject based on the ideXlab platform.
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energy constrained distortion reduction optimization for wavelet based coded image Transmission in wireless sensor networks
IEEE Transactions on Multimedia, 2008Co-Authors: Wei Wang, Dongming Peng, Hamid Sharif, Honggang Wang, Hsiaohwa ChenAbstract:Image Transmissions in wireless multimedia sensor networks (WMSNs) are often energy constrained. They also have requirement on distortion minimization, which may be achieved through unequal error protection (UEP) based communication approaches. In related literature with regard to wireless multimedia Transmissions, significantly different importance levels between image-pixel-position information and image-pixel-value information have not been fully exploited by existing UEP schemes. In this paper, we propose an innovative image-pixel-position information based resource allocation scheme to optimize image Transmission Quality with strict energy budget constraint for image applications in WMSNs, and it works by exploring these uniquely different importance levels among image data streams. Network resources are optimally allocated cross PHY, MAC and APP layers regarding inter-segment dependency, and energy efficiency is assured while the image Transmission Quality is optimized. Simulation results have demonstrated the effectiveness of the proposed approach in achieving the optimal image Quality and energy efficiency. The performance gain in terms of distortion reduction is especially prominent with strict energy budget constraints and lower image compression ratios.
Xiaoqin Song - One of the best experts on this subject based on the ideXlab platform.
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joint video packet scheduling subchannel assignment and power allocation for cognitive heterogeneous networks
IEEE Transactions on Wireless Communications, 2017Co-Authors: Lei Xu, Arumugam Nallanathan, Xiaoqin SongAbstract:In this paper, a joint video scheduling, subchannel assignment, and power allocation problem in cognitive heterogeneous networks are modeled as a mixed integer non-linear programming (MINLP), which maximizes the minimum video Transmission Quality among different secondary mobile terminals (MTs) subject to the total available energy at each secondary, the total interference power at each primary base station, the total available capacity at each radio interface of each secondary MTs, and the video sequence encoding characteristic. In order to solve it, we decompose the original MINLP as joint subchannel and power allocation problem and video packet scheduling problem. Then, we model the joint subchannel and power allocation problem as a max–min fractional programming, and transform it as a convex optimization problem. Finally, we utilize dual decomposition method to design a joint subchannel and power allocation algorithm, and propose a video packet scheduling scheme based on auction theory to maximize the video Quality for each secondary MT. Simulation results demonstrate that the proposed framework not only improves the video Transmission Quality significantly, but also guarantees the fairness among different secondary MTs.
Constantine Caramanis - One of the best experts on this subject based on the ideXlab platform.
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delay constrained video Transmission Quality driven resource allocation and scheduling
IEEE Journal of Selected Topics in Signal Processing, 2015Co-Authors: Amin Abdel Khalek, Constantine Caramanis, Robe W HeathAbstract:Real-time video demands Quality-of-service (QoS) guarantees such as delay bounds for end-user satisfaction. Furthermore, the tolerable delay varies depending on the use case such as live streaming or two-way video conferencing. Due to the inherently stochastic nature of wireless fading channels, deterministic delay bounds are difficult to guarantee. Instead, we propose providing statistical delay guarantees using the concept of effective capacity. We consider a multiuser setup whereby different users have (possibly different) delay QoS constraints. We derive the resource allocation policy that maximizes the sum video Quality and applies to any Quality metric with concave rate-Quality mapping. We show that the optimal operating point per user is such that the rate-distortion slope is the inverse of the supported video source rate per unit bandwidth, a key metric we refer to as the source spectral efficiency. We extend the resource allocation policy to capture video Quality-driven adaptive user-subcarrier assignment in wideband channels as well as capture the impact of adaptive modulation and coding. We also solve the alternative problem of fairness-based resource allocation whereby the objective is to maximize the minimum video Quality across users. Finally, we derive user admission and scheduling policies that enable selecting a maximal user subset such that all selected users can meet their statistical delay requirement. Results show that video users with differentiated QoS requirements can achieve similar video Quality with vastly different resource requirements. Thus, QoS-aware scheduling and resource allocation enable supporting significantly more users under the same resource constraints.
