The Experts below are selected from a list of 10047 Experts worldwide ranked by ideXlab platform
Nivedita Sumi Majumdar - One of the best experts on this subject based on the ideXlab platform.
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xg Dynamic Spectrum Access field test results topics in radio communications
IEEE Communications Magazine, 2007Co-Authors: Mark A Mchenry, Eugene Livsics, Thao T N Nguyen, Nivedita Sumi MajumdarAbstract:The XG Radio system uses Dynamic Spectrum Access technology to determine locally unused Spectrum, and then operates on these channels without causing interference to existing non-cooperative users. In August 2006 the XG Radio system was field tested at Fort A.P. Hill, Virginia, in the laboratory, and at field locations in Northern Virginia. There were three major test criteria: to cause no harm (avoid interference), to work (form and maintain connected networks), and to add value (efficiently use Spectrum). This article defines the test metrics for fulfillment of these criteria, and describes the test results.
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xg Dynamic Spectrum Access field test results
IEEE Communications Magazine, 2007Co-Authors: Mark A Mchenry, Eugene Livsics, Thao T N Nguyen, Nivedita Sumi MajumdarAbstract:The XG Radio system uses Dynamic Spectrum Access technology to determine locally unused Spectrum, and then operates on these channels without causing interference to existing non-cooperative users. In August 2006 the XG Radio system was field tested at Fort A.P. Hill, Virginia, in the laboratory, and at field locations in Northern Virginia. There were three major test criteria: to cause no harm (avoid interference), to work (form and maintain connected networks), and to add value (efficiently use Spectrum). This article defines the test metrics for fulfillment of these criteria, and describes the test results.
Brian M. Sadler - One of the best experts on this subject based on the ideXlab platform.
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cognitive radios for Dynamic Spectrum Access Dynamic Spectrum Access in the time domain modeling and exploiting white space
IEEE Communications Magazine, 2007Co-Authors: Stefan Geirhofer, Lang Tong, Brian M. SadlerAbstract:Dynamic Spectrum Access is a promising approach to alleviate the Spectrum scarcity that wireless communications face today. In short, it aims at reusing sparsely occupied frequency bands while causing no (or insignificant) interference to the actual licensees. This article focuses on applying this concept in the time domain by exploiting idle periods between bursty transmissions of multi-Access communication channels and addresses WLAN as an example of practical importance. A statistical model based on empirical data is presented, and it is shown how to use this model for deriving Access strategies. The coexistence of Bluetooth and WLAN is considered as a concrete example
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optimal Dynamic Spectrum Access via periodic channel sensing
Wireless Communications and Networking Conference, 2007Co-Authors: Qianchuan Zhao, Stefan Geirhofer, Lang Tong, Brian M. SadlerAbstract:The problem of Dynamically Accessing a set of parallel channels occupied by primary users is considered. The secondary user is allowed to sense and to transmit in a single channel. By exploiting idle periods between bursty transmissions of primary users, and by using a periodic sensing strategy, optimal Dynamic Access is achieved by maximizing the throughput of the secondary user while constraining collision probability with the primary user. The optimal Dynamic Spectrum Access problem can then be formulated within the framework of constrained Markov decision processes (CMDPs). The optimal control policy is identified via a linear program, and its performance is analyzed numerically and through Monte Carlo simulations. Finally, we compare the optimal scheme to an ideal benchmark case when simultaneous sensing of all channels is assumed.
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Dynamic Spectrum Access in the time domain modeling and exploiting white space
IEEE Communications Magazine, 2007Co-Authors: Stefan Geirhofer, Lang Tong, Brian M. SadlerAbstract:Dynamic Spectrum Access is a promising approach to alleviate the Spectrum scarcity that wireless communications face today. In short, it aims at reusing sparsely occupied frequency bands while causing no (or insignificant) interference to the actual licensees. This article focuses on applying this concept in the time domain by exploiting idle periods between bursty transmissions of multi-Access communication channels and addresses WLAN as an example of practical importance. A statistical model based on empirical data is presented, and it is shown how to use this model for deriving Access strategies. The coexistence of Bluetooth and WLAN is considered as a concrete example.
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Dynamic Spectrum Access: Signal Processing, Networking, and Regulatory Policy
arXiv: Networking and Internet Architecture, 2006Co-Authors: Qing Zhao, Brian M. SadlerAbstract:In this article, we first provide a taxonomy of Dynamic Spectrum Access. We then focus on opportunistic Spectrum Access, the overlay approach under the hierarchical Access model of Dynamic Spectrum Access. we aim to provide an overview of challenges and recent developments in both technological and regulatory aspects of opportunistic Spectrum Access.
Kobi Cohen - One of the best experts on this subject based on the ideXlab platform.
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Deep Multi-User Reinforcement Learning for Distributed Dynamic Spectrum Access
IEEE Transactions on Wireless Communications, 2019Co-Authors: Oshri Naparstek, Kobi CohenAbstract:We consider the problem of Dynamic Spectrum Access for network utility maximization in multichannel wireless networks. The shared bandwidth is divided into K orthogonal channels. In the beginning of each time slot, each user selects a channel and transmits a packet with a certain transmission probability. After each time slot, each user that has transmitted a packet receives a local observation indicating whether its packet was successfully delivered or not (i.e., ACK signal). The objective is a multi-user strategy for Accessing the Spectrum that maximizes a certain network utility in a distributed manner without online coordination or message exchanges between users. Obtaining an optimal solution for the Spectrum Access problem is computationally expensive, in general, due to the large-state space and partial observability of the states. To tackle this problem, we develop a novel distributed Dynamic Spectrum Access algorithm based on deep multi-user reinforcement leaning. Specifically, at each time slot, each user maps its current state to the Spectrum Access actions based on a trained deep-Q network used to maximize the objective function. Game theoretic analysis of the system Dynamics is developed for establishing design principles for the implementation of the algorithm. The experimental results demonstrate the strong performance of the algorithm.
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deep multi user reinforcement learning for distributed Dynamic Spectrum Access
arXiv: Networking and Internet Architecture, 2017Co-Authors: Oshri Naparstek, Kobi CohenAbstract:We consider the problem of Dynamic Spectrum Access for network utility maximization in multichannel wireless networks. The shared bandwidth is divided into K orthogonal channels. In the beginning of each time slot, each user selects a channel and transmits a packet with a certain transmission probability. After each time slot, each user that has transmitted a packet receives a local observation indicating whether its packet was successfully delivered or not (i.e., ACK signal). The objective is a multi-user strategy for Accessing the Spectrum that maximizes a certain network utility in a distributed manner without online coordination or message exchanges between users. Obtaining an optimal solution for the Spectrum Access problem is computationally expensive in general due to the large state space and partial observability of the states. To tackle this problem, we develop a novel distributed Dynamic Spectrum Access algorithm based on deep multi-user reinforcement leaning. Specifically, at each time slot, each user maps its current state to Spectrum Access actions based on a trained deep-Q network used to maximize the objective function. Game theoretic analysis of the system Dynamics is developed for establishing design principles for the implementation of the algorithm. Experimental results demonstrate strong performance of the algorithm.
Mark A Mchenry - One of the best experts on this subject based on the ideXlab platform.
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xg Dynamic Spectrum Access field test results topics in radio communications
IEEE Communications Magazine, 2007Co-Authors: Mark A Mchenry, Eugene Livsics, Thao T N Nguyen, Nivedita Sumi MajumdarAbstract:The XG Radio system uses Dynamic Spectrum Access technology to determine locally unused Spectrum, and then operates on these channels without causing interference to existing non-cooperative users. In August 2006 the XG Radio system was field tested at Fort A.P. Hill, Virginia, in the laboratory, and at field locations in Northern Virginia. There were three major test criteria: to cause no harm (avoid interference), to work (form and maintain connected networks), and to add value (efficiently use Spectrum). This article defines the test metrics for fulfillment of these criteria, and describes the test results.
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xg Dynamic Spectrum Access field test results
IEEE Communications Magazine, 2007Co-Authors: Mark A Mchenry, Eugene Livsics, Thao T N Nguyen, Nivedita Sumi MajumdarAbstract:The XG Radio system uses Dynamic Spectrum Access technology to determine locally unused Spectrum, and then operates on these channels without causing interference to existing non-cooperative users. In August 2006 the XG Radio system was field tested at Fort A.P. Hill, Virginia, in the laboratory, and at field locations in Northern Virginia. There were three major test criteria: to cause no harm (avoid interference), to work (form and maintain connected networks), and to add value (efficiently use Spectrum). This article defines the test metrics for fulfillment of these criteria, and describes the test results.
Alagan Anpalagan - One of the best experts on this subject based on the ideXlab platform.
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Dynamic Spectrum Access in time varying environment distributed learning beyond expectation optimization
IEEE Transactions on Communications, 2017Co-Authors: Jinlong Wang, Jianchao Zheng, Liang Shen, Alagan AnpalaganAbstract:This paper investigates the problem of Dynamic Spectrum Access for canonical wireless networks, in which the channel states are time-varying. In the most existing work, the commonly used optimization objective is to maximize the expectation of a certain metric (e.g., throughput or achievable rate). However, it is realized that expectation alone is not enough since some applications are sensitive to fluctuations. Effective capacity is a promising metric for time-varying service process since it characterizes the packet delay violating probability (regarded as an important statistical quality-of-service index), by taking into account not only the expectation but also other high-order statistic. Therefore, we formulate the interactions among the users in the time-varying environment as a non-cooperative game, in which the utility function is defined as the achieved effective capacity. We prove that it is an ordinal potential game which has at least one pure strategy Nash equilibrium. Based on an approximated utility function, we propose a multi-agent learning algorithm which is proved to achieve stable solutions with Dynamic and incomplete information constraints. The convergence of the proposed learning algorithm is verified by simulation results. Also, it is shown that the proposed multi-agent learning algorithm achieves satisfactory performance.
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Dynamic Spectrum Access in time varying environment distributed learning beyond expectation optimization
arXiv: Information Theory, 2015Co-Authors: Jinlong Wang, Jianchao Zheng, Liang Shen, Alagan AnpalaganAbstract:This article investigates the problem of Dynamic Spectrum Access for canonical wireless networks, in which the channel states are time-varying. In the most existing work, the commonly used optimization objective is to maximize the expectation of a certain metric (e.g., throughput or achievable rate). However, it is realized that expectation alone is not enough since some applications are sensitive to fluctuations. Effective capacity is a promising metric for time-varying service process since it characterizes the packet delay violating probability (regarded as an important statistical QoS index), by taking into account not only the expectation but also other high-order statistic. Therefore, we formulate the interactions among the users in the time-varying environment as a non-cooperative game, in which the utility function is defined as the achieved effective capacity. We prove that it is an ordinal potential game which has at least one pure strategy Nash equilibrium. Based on an approximated utility function, we propose a multi-agent learning algorithm which is proved to achieve stable solutions with Dynamic and incomplete information constraints. The convergence of the proposed learning algorithm is verified by simulation results. Also, it is shown that the proposed multi-agent learning algorithm achieves satisfactory performance.
