The Experts below are selected from a list of 187989 Experts worldwide ranked by ideXlab platform
Robert Schober - One of the best experts on this subject based on the ideXlab platform.
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optimal joint power and subcarrier allocation for full duplex multicarrier non orthogonal multiple access systems
IEEE Transactions on Communications, 2017Co-Authors: Yan Sun, Zhiguo Ding, Robert SchoberAbstract:In this paper, we investigate resource allocation algorithm design for multicarrier non-orthogonal multiple access (MC-NOMA) systems employing a full-duplex (FD) base station for serving multiple half-duplex (HD) downlink and uplink users simultaneously. The proposed algorithm is obtained from the solution of a non-convex optimization problem for the maximization of the weighted sum system throughput. We apply monotonic optimization to develop an optimal joint power and subcarrier allocation policy. The optimal resource allocation policy serves as a system Performance Benchmark due to its high computational complexity. Furthermore, a suboptimal iterative scheme based on successive convex approximation is proposed to strike a balance between computational complexity and optimality. Our simulation results reveal that the proposed suboptimal algorithm achieves a close-to-optimal Performance. In addition, FD MC-NOMA systems employing the proposed resource allocation algorithms provide a substantial system throughput improvement compared with conventional HD multicarrier orthogonal multiple access (MC-OMA) systems and other baseline schemes. In addition, our results unveil that FD MC-NOMA systems enable a fairer resource allocation compared with traditional HD MC-OMA systems.
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optimal joint power and subcarrier allocation for mc noma systems
Global Communications Conference, 2016Co-Authors: Yan Sun, Robert SchoberAbstract:In this paper, we investigate the resource allocation algorithm design for multicarrier non-orthogonal multiple access (MC-NOMA) systems. The proposed algorithm is obtained from the solution of a non-convex optimization problem for the maximization of the weighted system throughput. We employ monotonic optimization to develop the optimal joint power and subcarrier allocation policy. The optimal resource allocation policy serves as a Performance Benchmark due to its high complexity. Furthermore, to strike a balance between computational complexity and optimality, a suboptimal scheme with low computational complexity is proposed. Our simulation results reveal that the suboptimal algorithm achieves a close-to-optimal Performance and MC-NOMA employing the proposed resource allocation algorithm provides a substantial system throughput improvement compared to conventional multicarrier orthogonal multiple access (MC-OMA).
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optimal joint power and subcarrier allocation for full duplex multicarrier non orthogonal multiple access systems
arXiv: Information Theory, 2016Co-Authors: Yan Sun, Zhiguo Ding, Robert SchoberAbstract:In this paper, we investigate resource allocation algorithm design for multicarrier non-orthogonal multiple access (MC-NOMA) systems employing a full-duplex (FD) base station (BS) for serving multiple half-duplex (HD) downlink (DL) and uplink (UL) users simultaneously. The proposed algorithm is obtained from the solution of a non-convex optimization problem for the maximization of the weighted sum system throughput. We apply monotonic optimization to develop an optimal joint power and subcarrier allocation policy. The optimal resource allocation policy serves as a system Performance Benchmark due to its high computational complexity. Furthermore, a suboptimal iterative scheme based on successive convex approximation is proposed to strike a balance between computational complexity and optimality. Our simulation results reveal that the proposed suboptimal algorithm achieves a close-to-optimal Performance. Besides, FD MC-NOMA systems employing the proposed resource allocation algorithms provide a substantial system throughput improvement compared to conventional HD multicarrier orthogonal multiple access (MC-OMA) systems and other baseline schemes. Also, our results unveil that the proposed FD MC-NOMA systems achieve a fairer resource allocation compared to traditional HD MC-OMA systems.
John N Mchenry - One of the best experts on this subject based on the ideXlab platform.
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the new england air quality forecasting pilot program development of an evaluation protocol and Performance Benchmark
Journal of The Air & Waste Management Association, 2005Co-Authors: Daiwen Kang, Brian K Eder, Ariel F Stein, Georg A Grell, Steven E Peckham, John N MchenryAbstract:Abstract The National Oceanic and Atmospheric Administration recently sponsored the New England Forecasting Pilot Program to serve as a “test bed” for chemical forecasting by providing all of the elements of a National Air Quality Forecasting System, including the development and implementation of an evaluation protocol. This Pilot Program enlisted three regional-scale air quality models, serving as prototypes, to forecast ozone (O3) concentrations across the northeastern United States during the summer of 2002. A suite of statistical metrics was identified as part of the protocol that facilitated evaluation of both discrete forecasts (observed versus modeled concentrations) and categorical forecasts (observed versus modeled exceedances/nonexceedances) for both the maximum 1-hr (125 ppb) and 8-hr (85 ppb) forecasts produced by each of the models. Implementation of the evaluation protocol took place during a 25-day period (August 5–29), utilizing hourly O3 concentration data obtained from over 450 monitors...
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the new england air quality forecasting pilot program development of an evaluation protocol and Performance Benchmark
Journal of The Air & Waste Management Association, 2005Co-Authors: Daiwen Kang, Brian K Eder, Ariel F Stein, Georg A Grell, Steven E Peckham, John N MchenryAbstract:The National Oceanic and Atmospheric Administration recently sponsored the New England Forecasting Pilot Program to serve as a "test bed" for chemical forecasting by providing all of the elements of a National Air Quality Forecasting System, including the development and implementation of an evaluation protocol. This Pilot Program enlisted three regional-scale air quality models, serving as prototypes, to forecast ozone (O3) concentrations across the northeastern United States during the summer of 2002. A suite of statistical metrics was identified as part of the protocol that facilitated evaluation of both discrete forecasts (observed versus modeled concentrations) and categorical forecasts (observed versus modeled exceedances/nonexceedances) for both the maximum 1-hr (125 ppb) and 8-hr (85 ppb) forecasts produced by each of the models. Implementation of the evaluation protocol took place during a 25-day period (August 5-29), utilizing hourly O3 concentration data obtained from over 450 monitors from the U.S. Environment Protection Agency's Air Quality System network.
Sebastian Jaimungal - One of the best experts on this subject based on the ideXlab platform.
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outPerformance and tracking dynamic asset allocation for active and passive portfolio management
Applied Mathematical Finance, 2018Co-Authors: Ali Alaradi, Sebastian JaimungalAbstract:Portfolio management problems are often divided into two types: active and passive, where the objective is to outperform and track a preselected Benchmark, respectively. Here, we formulate and solve a dynamic asset allocation problem that combines these two objectives in a unified framework. We look to maximize the expected growth rate differential between the wealth of the investor's portfolio and that of a Performance Benchmark while penalizing risk-weighted deviations from a given tracking portfolio. Using stochastic control techniques, we provide explicit closed-form expressions for the optimal allocation and we show how the optimal strategy can be related to the growth optimal portfolio. The admissible Benchmarks encompass the class of functionally generated portfolios (FGPs), which include the market portfolio, as the only requirement is that they depend only on the prevailing asset values. Finally, some numerical experiments are presented to illustrate the risk-reward profile of the optimal allocation.
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outPerformance and tracking dynamic asset allocation for active and passive portfolio management
arXiv: Portfolio Management, 2018Co-Authors: Ali Alaradi, Sebastian JaimungalAbstract:Portfolio management problems are often divided into two types: active and passive, where the objective is to outperform and track a preselected Benchmark, respectively. Here, we formulate and solve a dynamic asset allocation problem that combines these two objectives in a unified framework. We look to maximize the expected growth rate differential between the wealth of the investor's portfolio and that of a Performance Benchmark while penalizing risk-weighted deviations from a given tracking portfolio. Using stochastic control techniques, we provide explicit closed-form expressions for the optimal allocation and we show how the optimal strategy can be related to the growth optimal portfolio. The admissible Benchmarks encompass the class of functionally generated portfolios (FGPs), which include the market portfolio, as the only requirement is that they depend only on the prevailing asset values. The passive component of the problem allows the investor to leverage the relative arbitrage properties of certain FGPs and achieve outPerformance in a risk-adjusted sense without requiring the difficult task of estimating of asset growth rates. Finally, some numerical experiments are presented to illustrate the risk-reward profile of the optimal allocation.
Yan Sun - One of the best experts on this subject based on the ideXlab platform.
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optimal joint power and subcarrier allocation for full duplex multicarrier non orthogonal multiple access systems
IEEE Transactions on Communications, 2017Co-Authors: Yan Sun, Zhiguo Ding, Robert SchoberAbstract:In this paper, we investigate resource allocation algorithm design for multicarrier non-orthogonal multiple access (MC-NOMA) systems employing a full-duplex (FD) base station for serving multiple half-duplex (HD) downlink and uplink users simultaneously. The proposed algorithm is obtained from the solution of a non-convex optimization problem for the maximization of the weighted sum system throughput. We apply monotonic optimization to develop an optimal joint power and subcarrier allocation policy. The optimal resource allocation policy serves as a system Performance Benchmark due to its high computational complexity. Furthermore, a suboptimal iterative scheme based on successive convex approximation is proposed to strike a balance between computational complexity and optimality. Our simulation results reveal that the proposed suboptimal algorithm achieves a close-to-optimal Performance. In addition, FD MC-NOMA systems employing the proposed resource allocation algorithms provide a substantial system throughput improvement compared with conventional HD multicarrier orthogonal multiple access (MC-OMA) systems and other baseline schemes. In addition, our results unveil that FD MC-NOMA systems enable a fairer resource allocation compared with traditional HD MC-OMA systems.
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optimal joint power and subcarrier allocation for mc noma systems
Global Communications Conference, 2016Co-Authors: Yan Sun, Robert SchoberAbstract:In this paper, we investigate the resource allocation algorithm design for multicarrier non-orthogonal multiple access (MC-NOMA) systems. The proposed algorithm is obtained from the solution of a non-convex optimization problem for the maximization of the weighted system throughput. We employ monotonic optimization to develop the optimal joint power and subcarrier allocation policy. The optimal resource allocation policy serves as a Performance Benchmark due to its high complexity. Furthermore, to strike a balance between computational complexity and optimality, a suboptimal scheme with low computational complexity is proposed. Our simulation results reveal that the suboptimal algorithm achieves a close-to-optimal Performance and MC-NOMA employing the proposed resource allocation algorithm provides a substantial system throughput improvement compared to conventional multicarrier orthogonal multiple access (MC-OMA).
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optimal joint power and subcarrier allocation for full duplex multicarrier non orthogonal multiple access systems
arXiv: Information Theory, 2016Co-Authors: Yan Sun, Zhiguo Ding, Robert SchoberAbstract:In this paper, we investigate resource allocation algorithm design for multicarrier non-orthogonal multiple access (MC-NOMA) systems employing a full-duplex (FD) base station (BS) for serving multiple half-duplex (HD) downlink (DL) and uplink (UL) users simultaneously. The proposed algorithm is obtained from the solution of a non-convex optimization problem for the maximization of the weighted sum system throughput. We apply monotonic optimization to develop an optimal joint power and subcarrier allocation policy. The optimal resource allocation policy serves as a system Performance Benchmark due to its high computational complexity. Furthermore, a suboptimal iterative scheme based on successive convex approximation is proposed to strike a balance between computational complexity and optimality. Our simulation results reveal that the proposed suboptimal algorithm achieves a close-to-optimal Performance. Besides, FD MC-NOMA systems employing the proposed resource allocation algorithms provide a substantial system throughput improvement compared to conventional HD multicarrier orthogonal multiple access (MC-OMA) systems and other baseline schemes. Also, our results unveil that the proposed FD MC-NOMA systems achieve a fairer resource allocation compared to traditional HD MC-OMA systems.
Xining Yu - One of the best experts on this subject based on the ideXlab platform.
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an implementation of real time phased array radar fundamental functions on a dsp focused high Performance embedded computing platform
Aerospace, 2016Co-Authors: Xining Yu, Yan Zhang, Ankit Patel, Allen Zahrai, Mark WeberAbstract:This paper investigates the feasibility of a backend design for real-time, multiple-channel processing digital phased array system, particularly for high-Performance embedded computing platforms constructed of general purpose digital signal processors. First, we obtained the lab-scale backend Performance Benchmark from simulating beamforming, pulse compression, and Doppler filtering based on a Micro Telecom Computing Architecture (MTCA) chassis using the Serial RapidIO protocol in backplane communication. Next, a field-scale demonstrator of a multifunctional phased array radar is emulated by using the similar configuration. Interestingly, the Performance of a barebones design is compared to that of emerging tools that systematically take advantage of parallelism and multicore capabilities, including the Open Computing Language.
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an implementation of real time phased array radar fundamental functions on dsp focused high Performance embedded computing platform
Proceedings of SPIE, 2016Co-Authors: Xining Yu, Yan Zhang, Ankit Patel, Allen Zahrai, Mark E WeberAbstract:This paper investigates the feasibility of real-time, multiple channel processing of a digital phased array system backend design, with focus on high-Performance embedded computing (HPEC) platforms constructed based on general purpose digital signal processor (DSP). Serial RapidIO (SRIO) is used as inter-chip connection backend protocol to support the inter-core communications and parallelisms. Performance Benchmark was obtained based on a SRIO system chassis and emulated configuration similar to a field scale demonstrator of Multi-functional Phased Array Radar (MPAR). An interesting aspect of this work is comparison between “raw and low-level” DSP processing and emerging tools that systematically take advantages of the parallelism and multi-core capability, such as OpenCL and OpenMP. Comparisons with other backend HPEC solutions, such as FPGA and GPU, are also provided through analysis and experiments.
