The Experts below are selected from a list of 86745 Experts worldwide ranked by ideXlab platform
Jianwei Huang - One of the best experts on this subject based on the ideXlab platform.
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Spatial Spectrum Access Game
IEEE Transactions on Mobile Computing, 2015Co-Authors: Xu Chen, Jianwei HuangAbstract:A key feature of wireless communications is the Spatial reuse. However, the Spatial aspect is not yet well understood for the purpose of designing efficient Spectrum sharing mechanisms. In this paper, we propose a framework of Spatial Spectrum access games on directed interference graphs, which can model quite general interference relationship with Spatial reuse in wireless networks. We show that a pure Nash equilibrium exists for the two classes of games: (1) any Spatial Spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the Spatial Spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We also quantify the price of anarchy of the Spatial Spectrum access game. We then propose a distributed learning algorithm, which only utilizes users’ local observations to adaptively adjust the Spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any Spatial Spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to $100$ percent performance improvement over a random access algorithm.
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Spatial Spectrum Access Game
arXiv: Networking and Internet Architecture, 2014Co-Authors: Xu Chen, Jianwei HuangAbstract:A key feature of wireless communications is the Spatial reuse. However, the Spatial aspect is not yet well understood for the purpose of designing efficient Spectrum sharing mechanisms. In this paper, we propose a framework of Spatial Spectrum access games on directed interference graphs, which can model quite general interference relationship with Spatial reuse in wireless networks. We show that a pure Nash equilibrium exists for the two classes of games: (1) any Spatial Spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the Spatial Spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We also quantify the price of anarchy of the Spatial Spectrum access game. We then propose a distributed learning algorithm, which only utilizes users' local observations to adaptively adjust the Spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any Spatial Spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to superior performance improvement over a random access algorithm.
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Spatial Spectrum access game nash equilibria and distributed learning
Mobile Ad Hoc Networking and Computing, 2012Co-Authors: Xu Chen, Jianwei HuangAbstract:A key feature of wireless communications is the Spatial reuse. However, the Spatial aspect is not yet well understood for the purpose of designing efficient Spectrum sharing mechanisms. In this paper, we propose a framework of Spatial Spectrum access games on directed interference graphs, which can model quite general interference relationship with Spatial reuse in wireless networks. We show that a pure strategy equilibrium exists for the two classes of games: (1) any Spatial Spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the Spatial Spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We then propose a distributed learning algorithm, which only utilizes users' local observations to adaptively adjust the Spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any Spatial Spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to 100% performance improvement over a random access algorithm.
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MobiHoc - Spatial Spectrum access game: nash equilibria and distributed learning
Proceedings of the thirteenth ACM international symposium on Mobile Ad Hoc Networking and Computing - MobiHoc '12, 2012Co-Authors: Xu Chen, Jianwei HuangAbstract:A key feature of wireless communications is the Spatial reuse. However, the Spatial aspect is not yet well understood for the purpose of designing efficient Spectrum sharing mechanisms. In this paper, we propose a framework of Spatial Spectrum access games on directed interference graphs, which can model quite general interference relationship with Spatial reuse in wireless networks. We show that a pure strategy equilibrium exists for the two classes of games: (1) any Spatial Spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the Spatial Spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We then propose a distributed learning algorithm, which only utilizes users' local observations to adaptively adjust the Spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any Spatial Spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to 100% performance improvement over a random access algorithm.
Xu Chen - One of the best experts on this subject based on the ideXlab platform.
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Spatial Spectrum Access Game
IEEE Transactions on Mobile Computing, 2015Co-Authors: Xu Chen, Jianwei HuangAbstract:A key feature of wireless communications is the Spatial reuse. However, the Spatial aspect is not yet well understood for the purpose of designing efficient Spectrum sharing mechanisms. In this paper, we propose a framework of Spatial Spectrum access games on directed interference graphs, which can model quite general interference relationship with Spatial reuse in wireless networks. We show that a pure Nash equilibrium exists for the two classes of games: (1) any Spatial Spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the Spatial Spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We also quantify the price of anarchy of the Spatial Spectrum access game. We then propose a distributed learning algorithm, which only utilizes users’ local observations to adaptively adjust the Spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any Spatial Spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to $100$ percent performance improvement over a random access algorithm.
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Spatial Spectrum Access Game
arXiv: Networking and Internet Architecture, 2014Co-Authors: Xu Chen, Jianwei HuangAbstract:A key feature of wireless communications is the Spatial reuse. However, the Spatial aspect is not yet well understood for the purpose of designing efficient Spectrum sharing mechanisms. In this paper, we propose a framework of Spatial Spectrum access games on directed interference graphs, which can model quite general interference relationship with Spatial reuse in wireless networks. We show that a pure Nash equilibrium exists for the two classes of games: (1) any Spatial Spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the Spatial Spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We also quantify the price of anarchy of the Spatial Spectrum access game. We then propose a distributed learning algorithm, which only utilizes users' local observations to adaptively adjust the Spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any Spatial Spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to superior performance improvement over a random access algorithm.
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Spatial Spectrum access game nash equilibria and distributed learning
Mobile Ad Hoc Networking and Computing, 2012Co-Authors: Xu Chen, Jianwei HuangAbstract:A key feature of wireless communications is the Spatial reuse. However, the Spatial aspect is not yet well understood for the purpose of designing efficient Spectrum sharing mechanisms. In this paper, we propose a framework of Spatial Spectrum access games on directed interference graphs, which can model quite general interference relationship with Spatial reuse in wireless networks. We show that a pure strategy equilibrium exists for the two classes of games: (1) any Spatial Spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the Spatial Spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We then propose a distributed learning algorithm, which only utilizes users' local observations to adaptively adjust the Spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any Spatial Spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to 100% performance improvement over a random access algorithm.
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MobiHoc - Spatial Spectrum access game: nash equilibria and distributed learning
Proceedings of the thirteenth ACM international symposium on Mobile Ad Hoc Networking and Computing - MobiHoc '12, 2012Co-Authors: Xu Chen, Jianwei HuangAbstract:A key feature of wireless communications is the Spatial reuse. However, the Spatial aspect is not yet well understood for the purpose of designing efficient Spectrum sharing mechanisms. In this paper, we propose a framework of Spatial Spectrum access games on directed interference graphs, which can model quite general interference relationship with Spatial reuse in wireless networks. We show that a pure strategy equilibrium exists for the two classes of games: (1) any Spatial Spectrum access games on directed acyclic graphs, and (2) any games satisfying the congestion property on directed trees and directed forests. Under mild technical conditions, the Spatial Spectrum access games with random backoff and Aloha channel contention mechanisms on undirected graphs also have a pure Nash equilibrium. We then propose a distributed learning algorithm, which only utilizes users' local observations to adaptively adjust the Spectrum access strategies. We show that the distributed learning algorithm can converge to an approximate mixed-strategy Nash equilibrium for any Spatial Spectrum access games. Numerical results demonstrate that the distributed learning algorithm achieves up to 100% performance improvement over a random access algorithm.
Tang Bin - One of the best experts on this subject based on the ideXlab platform.
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A Spatial Spectrum Estimation Method Based on the Spatial Filtering Approach
Signal Processing, 2010Co-Authors: Tang BinAbstract:The paper has proposed a Spatial Spectrum estimation method based on the Spatial filtering approach.After the overlap subarrays are set in the array,the Spatial jamming signals have been filtered and restrained using the adaptive beam formed by the subarray and the SINR is increased for the desired signal.Based on the secondary combination of the subarrays,the direction-of-arrivals are estimated with the outputs of the subarrays and the locations of the subarrays using the Spatial Spectrum estimation method in the desired Spatial regions.Simulation results show the Spatial Spectrum estimation method based on the Spatial filtering approach has improved the electromagnetic environment for the desired signal and the estimate accuracy and the anti-jamming ability achieved are better than regular Spatial Spectrum estimation method.
Jeffrey L. Krolik - One of the best experts on this subject based on the ideXlab platform.
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Time-varying Spatial Spectrum estimation using a maneuverable sonar array
The Journal of the Acoustical Society of America, 2011Co-Authors: Jonathan L. Odom, Jeffrey L. KrolikAbstract:This paper addresses the problem of Spatial Spectrum estimation in dynamic environments with a maneuverable sensor array. Estimation of the time-varying acoustic field directionality is of fundamental importance in passive sonar. In this paper, mobility of the array is treated as a feature allowing for left-right disambiguation as well as improved resolution toward endfire. Two new methods for on-line Spatial Spectrum estimation are presented: (1) recursive maximum likelihood estimation using the EM algorithm and (2) time-varying Spatial Spectrum estimation via derivative-based updating. A multi-source simulation is used to compare the proposed algorithms in terms of their ability to suppress ambiguous array backlobes. A broadband method is presented utilizing knowledge of the source temporal Spectrum. Detection performance of weak high-bearing rate sources in interference-dominated environments is evaluated for a flat Spectrum. [This work was supported by ONR under grant N000140810947.]
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An online method for time-varying Spatial Spectrum estimation using a towed acoustic array
2010 Conference Record of the Forty Fourth Asilomar Conference on Signals Systems and Computers, 2010Co-Authors: Jeffrey S. Rogers, Jeffrey L. KrolikAbstract:This paper addresses the problem of time-varying field directionality mapping (FDM) or Spatial Spectrum estimation in dynamic environments with a maneuverable towed acoustic array. Array processing algorithms for towed arrays are typically designed assuming the array is straight, and are thus degraded during tow ship maneuvers. In this paper, maneuvering the array is treated as a feature allowing for left and right disambiguation as well as improved resolution towards endfire. A new method for online Spatial Spectrum estimation is presented. The maximum likelihood of the time-varying field is solved for using a single expectation maximization step after each received data snapshot. A multi-source simulation is used to illustrate the proposed algorithm's ability to suppress ambiguous towed-array backlobes and resolve closely spaced interferers near endfire which pose challenges for conventional beamforming approaches, especially during array maneuvers.
Minglu Jin - One of the best experts on this subject based on the ideXlab platform.
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Blind Central-Symmetry-Based Feature Detection for Spatial Spectrum Sensing
IEEE Transactions on Vehicular Technology, 2016Co-Authors: Chang Liu, Minglu JinAbstract:State-of-the-art sensing methods mostly detect the Spectrum holes by exploring the feature in frequency, time, and geography dimensions. In this paper, we analyze the sensing problem from angle/space domain by using the angle of arrival (AoA) estimation technology. We show a property that the Spatial Spectrum of noise has the feature of central symmetry, which the arriving signal does not have in general. Hence, the existence of the central symmetry feature depends on the presence or absence of the primary user signal. Motivated by this, we introduce a novel Spatial Spectrum sensing framework and propose a blind central-symmetry-based feature detection (CSFD) method correspondingly. Different from conventional Spectrum sensing, the designed sensing framework reduces the complexity of Spatial Spectrum sensing and is available for Spectrum access. Taking advantage of the inherent central symmetry feature of noise Spatial Spectrum, the proposed CSFD can achieve higher probability of detection even at low signal-to-noise ratios (SNRs) and offer AoA information. Theoretical performance analysis of the proposed CSFD method is also provided. Simulation results are presented to verify the efficiency of the proposed algorithm.
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Blind Energy-based Detection for Spatial Spectrum Sensing
IEEE Wireless Communications Letters, 2015Co-Authors: Chang Liu, Minglu JinAbstract:Conventional energy detection (ED) Spectrum sensing method requires the knowledge of noise power and consequently suffers from noise uncertainty. In this letter we propose a novel blind Spatial Spectrum sensing method to conquer this problem. We utilize an Electronically Steerable Parasitic Antenna Receptor (ESPAR) which can divide the space into several sectors and switch receive beampattern to each sector in a time-division fashion. The difference of received signal energies among sectors heavily depends on the presence/absence of the primary user (PU) signal. Motivated by this fact, we introduce a blind energy-based Spatial Spectrum sensing algorithm using the ratio of maximum-minimum energy (MMEN). The MMEN Spectrum sensing method can overcome the noise uncertainty problem and achieve higher accuracy performance with lower computational complexity. Theoretical performance analysis of the proposed MMEN method is also provided. Simulation results are presented to verify the efficiency of the proposed algorithm.
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ICCC - Maximum-minimum Spatial Spectrum detection for cognitive radio using parasitic antenna arrays
2014 IEEE CIC International Conference on Communications in China (ICCC), 2014Co-Authors: Chang Liu, Minglu JinAbstract:The Spatial Spectrum indicates the energy distribution in all directions. If we can get the Spatial Spectrum, then the Spectrum holes in space are known. In Spatial Spectrum sensing of cognitive radio, an electronically steerable parasitic antenna receptor (ESPAR) divides the space into sectors which are accessed by directional beamforming on a time division basis. Hence, the energy at different direction can be collected respectively, that is, the Spatial Spectrum is available. In this paper, we first propose a new sensing method using the ratio of maximum-minimum Spatial Spectrum. Considering the situation of multiple primary users, we then propose an algorithm extension scheme based on the ratio of average-minimum Spatial Spectrum. The proposed methods can not only overcome the noise uncertainty problem, but also achieve high performance with low complexity. Theoretical performance analysis of the proposed methods is provided. Simulation results based on Nakagami-m fading channel are presented to verify the efficiency of proposed methods.
