Pub Date : 2011-05-03DOI: 10.1109/DYSPAN.2011.5936265
P. Conder, L. Linton, M. Faulkner
Given the issues with incompatible systems and apparent shortage of Radio Frequency Spectrum, the ability of cognitive radio technologies to identify and operate on unused allocations with the correct communications and little user input has gained much interest. These demonstrations consist of components that may enable the use Dynamic Spectrum Access to emergency Communications; a Multichannel Spectrum Occupancy Monitor and a Cognitive Trunked Base Station.
{"title":"Cognitive radio developments for emergency communication systems","authors":"P. Conder, L. Linton, M. Faulkner","doi":"10.1109/DYSPAN.2011.5936265","DOIUrl":"https://doi.org/10.1109/DYSPAN.2011.5936265","url":null,"abstract":"Given the issues with incompatible systems and apparent shortage of Radio Frequency Spectrum, the ability of cognitive radio technologies to identify and operate on unused allocations with the correct communications and little user input has gained much interest. These demonstrations consist of components that may enable the use Dynamic Spectrum Access to emergency Communications; a Multichannel Spectrum Occupancy Monitor and a Cognitive Trunked Base Station.","PeriodicalId":119856,"journal":{"name":"2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121124025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-05-03DOI: 10.1109/DYSPAN.2011.5936261
J. Lundén, V. Koivunen, S. Kulkarni, H. Poor, Smarad CoE
In this paper a distributed multiagent, multiband reinforcement learning based sensing policy for cognitive radio ad hoc networks is proposed. The proposed sensing policy employs secondary user (SU) collaboration through local interactions. The goal is to maximize the amount of available spectrum found for secondary use given a desired diversity order, i.e. a desired number of SUs sensing simultaneously each frequency band. The SUs in the cognitive radio network make local decisions based on their own and their neighbors' local test statistics or decisions to identify unused spectrum locally. Thus, the network builds a locally available map of spectrum occupancy of its geographical area. Simulation results show that the proposed sensing policy provides a significant increase in the amount of available spectrum found for secondary use compared to a random sensing policy.
{"title":"Reinforcement learning based distributed multiagent sensing policy for cognitive radio networks","authors":"J. Lundén, V. Koivunen, S. Kulkarni, H. Poor, Smarad CoE","doi":"10.1109/DYSPAN.2011.5936261","DOIUrl":"https://doi.org/10.1109/DYSPAN.2011.5936261","url":null,"abstract":"In this paper a distributed multiagent, multiband reinforcement learning based sensing policy for cognitive radio ad hoc networks is proposed. The proposed sensing policy employs secondary user (SU) collaboration through local interactions. The goal is to maximize the amount of available spectrum found for secondary use given a desired diversity order, i.e. a desired number of SUs sensing simultaneously each frequency band. The SUs in the cognitive radio network make local decisions based on their own and their neighbors' local test statistics or decisions to identify unused spectrum locally. Thus, the network builds a locally available map of spectrum occupancy of its geographical area. Simulation results show that the proposed sensing policy provides a significant increase in the amount of available spectrum found for secondary use compared to a random sensing policy.","PeriodicalId":119856,"journal":{"name":"2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125381884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-05-03DOI: 10.1109/DYSPAN.2011.5936255
G. Fusco, M. Buddhikot, Himanshu Gupta, S. Venkatesan
The information and communication technology (ICT) industry accounts for at least 2% of the world energy consumption [1], [2], and a considerable part of this energy is consumed by cell phone towers. Currently, resources are statically allocated to offer the best service during peak hours. Energy could be saved if the power is allocated adaptively, depending on the current users' demand. We provide an algorithm that minimizes power consumption by selectively turning on or off cell towers and deciding which power to assign to the active ones and what frequencies to use, so as to maintain full coverage and respect users' capacity demands. This algorithm can be executed at regular time intervals to tune up the network adaptively. We ran simulations with real data, and all experiments show that the total power allocated is proportional to the number of active users.
{"title":"Finding green spots and turning the spectrum dial: Novel techniques for green mobile wireless networks","authors":"G. Fusco, M. Buddhikot, Himanshu Gupta, S. Venkatesan","doi":"10.1109/DYSPAN.2011.5936255","DOIUrl":"https://doi.org/10.1109/DYSPAN.2011.5936255","url":null,"abstract":"The information and communication technology (ICT) industry accounts for at least 2% of the world energy consumption [1], [2], and a considerable part of this energy is consumed by cell phone towers. Currently, resources are statically allocated to offer the best service during peak hours. Energy could be saved if the power is allocated adaptively, depending on the current users' demand. We provide an algorithm that minimizes power consumption by selectively turning on or off cell towers and deciding which power to assign to the active ones and what frequencies to use, so as to maintain full coverage and respect users' capacity demands. This algorithm can be executed at regular time intervals to tune up the network adaptively. We ran simulations with real data, and all experiments show that the total power allocated is proportional to the number of active users.","PeriodicalId":119856,"journal":{"name":"2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125479826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-05-03DOI: 10.1109/DYSPAN.2011.5936242
S. Shellhammer
A overview of ATSC spectrum sensing based on detection of the pilot signal is provided. Then the theoretical performance for such a spectrum sensor is given. The formula for the probability of mis-detection (one minus the probability of detection) is derived for several different channels. The channel models that are consider are: additive white Gaussian noise, a Rayleigh fading channel with long coherence time and a multiple receive antenna Rayleigh fading channel with long coherence time and finally a Rayleigh fading channel with short coherence time. The formula for the probability of false alarm is also derived. Based on the formulas for probability of mis-detection and probability of false alarm observations are made about how changes in various design parameters impact the sensing performance. Finally, and example is given using typical parameter values.
{"title":"The theoretical performance of ATSC spectrum sensing","authors":"S. Shellhammer","doi":"10.1109/DYSPAN.2011.5936242","DOIUrl":"https://doi.org/10.1109/DYSPAN.2011.5936242","url":null,"abstract":"A overview of ATSC spectrum sensing based on detection of the pilot signal is provided. Then the theoretical performance for such a spectrum sensor is given. The formula for the probability of mis-detection (one minus the probability of detection) is derived for several different channels. The channel models that are consider are: additive white Gaussian noise, a Rayleigh fading channel with long coherence time and a multiple receive antenna Rayleigh fading channel with long coherence time and finally a Rayleigh fading channel with short coherence time. The formula for the probability of false alarm is also derived. Based on the formulas for probability of mis-detection and probability of false alarm observations are made about how changes in various design parameters impact the sensing performance. Finally, and example is given using typical parameter values.","PeriodicalId":119856,"journal":{"name":"2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125819313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-02-23DOI: 10.1109/DYSPAN.2011.5936198
Xu Chen, Jianwei Huang, Husheng Li
We propose a dynamic spectrum access scheme where secondary users recommend “good” channels to each other and access accordingly. We formulate the problem as an average reward based Markov decision process. Since the action space of the Markov decision process is continuous (i.e., transmission probabilities), it is difficult to find the optimal policy by simply discretizing the action space and use the policy iteration, or value iteration. Instead, we propose a new algorithm based on the Model Reference Adaptive Search method, and prove its convergence to the optimal policy. Numerical results show that the proposed algorithm achieves up to 18% performance improvement than the static channel recommendation scheme and up to 63% performance improvement than the random access scheme, and is robust to channel dynamics.
{"title":"Adaptive channel recommendation for dynamic spectrum access","authors":"Xu Chen, Jianwei Huang, Husheng Li","doi":"10.1109/DYSPAN.2011.5936198","DOIUrl":"https://doi.org/10.1109/DYSPAN.2011.5936198","url":null,"abstract":"We propose a dynamic spectrum access scheme where secondary users recommend “good” channels to each other and access accordingly. We formulate the problem as an average reward based Markov decision process. Since the action space of the Markov decision process is continuous (i.e., transmission probabilities), it is difficult to find the optimal policy by simply discretizing the action space and use the policy iteration, or value iteration. Instead, we propose a new algorithm based on the Model Reference Adaptive Search method, and prove its convergence to the optimal policy. Numerical results show that the proposed algorithm achieves up to 18% performance improvement than the static channel recommendation scheme and up to 63% performance improvement than the random access scheme, and is robust to channel dynamics.","PeriodicalId":119856,"journal":{"name":"2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125922620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-02-21DOI: 10.1109/DYSPAN.2011.5936229
Lingjie Duan, Lin Gao, Jianwei Huang
Providing proper economic incentives is essential for the success of dynamic spectrum sharing. Cooperative spectrum sharing is one effective way to achieve this goal. In cooperative spectrum sharing, secondary users (SUs) relay traffics for primary users (PUs), in exchange for dedicated transmission time for the SUs' own communication needs. In this paper, we study the cooperative spectrum sharing under incomplete information, where SUs' types (which capture the relay channel gains and the SUs' power costs) are private information and are not known to the PU. Inspired by the contract theory, we model the network as a labor market. The PU is an employer who offers a contract to the SUs. The contract consists of a set of items representing combinations of spectrum access time (i.e., reward) and relay power (i.e., contribution). The SUs are employees, and each of them selects the best contract item to maximize its payoff. We study the optimal contract design for both weakly and strongly incomplete information scenarios. First, we provide necessary and sufficient conditions for feasible contracts in both scenarios. In the weakly incomplete information scenario, we further derive the optimal contract that achieves the same maximum PU's utility as in the complete information benchmark. In the strongly incomplete information scenario, we propose a Decompose-and-Compare algorithm that achieves a close-to-optimal contract. We further show that the PU's expected utility loss due to the suboptimal algorithm and the strongly incomplete information are both relatively small (less than 2% and 1.3%, respectively, in our numerical results with two SU types).
{"title":"Contract-based cooperative spectrum sharing","authors":"Lingjie Duan, Lin Gao, Jianwei Huang","doi":"10.1109/DYSPAN.2011.5936229","DOIUrl":"https://doi.org/10.1109/DYSPAN.2011.5936229","url":null,"abstract":"Providing proper economic incentives is essential for the success of dynamic spectrum sharing. Cooperative spectrum sharing is one effective way to achieve this goal. In cooperative spectrum sharing, secondary users (SUs) relay traffics for primary users (PUs), in exchange for dedicated transmission time for the SUs' own communication needs. In this paper, we study the cooperative spectrum sharing under incomplete information, where SUs' types (which capture the relay channel gains and the SUs' power costs) are private information and are not known to the PU. Inspired by the contract theory, we model the network as a labor market. The PU is an employer who offers a contract to the SUs. The contract consists of a set of items representing combinations of spectrum access time (i.e., reward) and relay power (i.e., contribution). The SUs are employees, and each of them selects the best contract item to maximize its payoff. We study the optimal contract design for both weakly and strongly incomplete information scenarios. First, we provide necessary and sufficient conditions for feasible contracts in both scenarios. In the weakly incomplete information scenario, we further derive the optimal contract that achieves the same maximum PU's utility as in the complete information benchmark. In the strongly incomplete information scenario, we propose a Decompose-and-Compare algorithm that achieves a close-to-optimal contract. We further show that the PU's expected utility loss due to the suboptimal algorithm and the strongly incomplete information are both relatively small (less than 2% and 1.3%, respectively, in our numerical results with two SU types).","PeriodicalId":119856,"journal":{"name":"2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116424560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-12-02DOI: 10.1109/DYSPAN.2011.5936227
Wessam Afifi, Ahmed Sultan, M. Nafie
In a cognitive radio setting, secondary users opportunistically access the spectrum allocated to primary users. Finding the optimal sensing and transmission durations for the secondary users becomes crucial in order to maximize the secondary throughput while protecting the primary users from interference and service disruption. In this paper an adaptive sensing and transmission scheme for cognitive radios is proposed. We consider a channel allocated to a primary user which operates in an unslotted manner switching activity at random times. A secondary transmitter adapts its sensing and transmission durations according to its belief regarding the primary user state of activity. The objective is to maximize a secondary utility function. This function has a penalty term for collisions with primary transmission. It accounts for the reliability-throughput tradeoff by explicitly incorporating the impact of sensing duration on secondary throughput and primary activity detection reliability. It also accounts for throughput reduction that results from data overhead. Numerical simulations of the system performance demonstrate the effectiveness of adaptive sensing and transmission scheme over non-adaptive approach in increasing the secondary user utility.
{"title":"Adaptive sensing and transmission durations for cognitive radios","authors":"Wessam Afifi, Ahmed Sultan, M. Nafie","doi":"10.1109/DYSPAN.2011.5936227","DOIUrl":"https://doi.org/10.1109/DYSPAN.2011.5936227","url":null,"abstract":"In a cognitive radio setting, secondary users opportunistically access the spectrum allocated to primary users. Finding the optimal sensing and transmission durations for the secondary users becomes crucial in order to maximize the secondary throughput while protecting the primary users from interference and service disruption. In this paper an adaptive sensing and transmission scheme for cognitive radios is proposed. We consider a channel allocated to a primary user which operates in an unslotted manner switching activity at random times. A secondary transmitter adapts its sensing and transmission durations according to its belief regarding the primary user state of activity. The objective is to maximize a secondary utility function. This function has a penalty term for collisions with primary transmission. It accounts for the reliability-throughput tradeoff by explicitly incorporating the impact of sensing duration on secondary throughput and primary activity detection reliability. It also accounts for throughput reduction that results from data overhead. Numerical simulations of the system performance demonstrate the effectiveness of adaptive sensing and transmission scheme over non-adaptive approach in increasing the secondary user utility.","PeriodicalId":119856,"journal":{"name":"2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127506331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/dyspan.2011.5936197
Rohan Murty, Ranveer Chandra, T. Moscibroda, P. Bahl
The most recent FCC ruling proposes relying on a database of incumbents as the primary means of determining white space availability at any white spaces device (WSD). While the ruling provides broad guidelines for the database, the specifics of its design, features, implementation, and use are yet to be determined. Furthermore, architecting a network where all WSDs rely on the database raises several systems and networking challenges that have remained unexplored. Also, the ruling treats the database only as a storehouse for incumbents. We believe that the mandated use of the database has an additional opportunity: a means to dynamically manage the RF spectrum. Motivated by this opportunity, in this paper we present SenseLess, a database driven white spaces network. As suggested by its very name, in SenseLess, WSDs obviate the need to sense the spectrum by relying entirely on a database service to determine white spaces availability. The service, using a combination of an up-to-date database of incumbents, sophisticated signal propagation modeling, and an efficient content dissemination mechanism ensures efficient, scalable, and safe white space network operation. We build, deploy, and evaluate SenseLess and compare our results to ground truth spectrum measurements. We present the unique system design considerations that arise due to operating over the white spaces. We also evaluate its efficiency and scalability. To the best of our knowledge, this is the first paper that identifies and examines the systems and networking challenges that arise from operating a white space network, which is solely dependent on a channel occupancy database.
{"title":"SenseLess: A database-driven white spaces network","authors":"Rohan Murty, Ranveer Chandra, T. Moscibroda, P. Bahl","doi":"10.1109/dyspan.2011.5936197","DOIUrl":"https://doi.org/10.1109/dyspan.2011.5936197","url":null,"abstract":"The most recent FCC ruling proposes relying on a database of incumbents as the primary means of determining white space availability at any white spaces device (WSD). While the ruling provides broad guidelines for the database, the specifics of its design, features, implementation, and use are yet to be determined. Furthermore, architecting a network where all WSDs rely on the database raises several systems and networking challenges that have remained unexplored. Also, the ruling treats the database only as a storehouse for incumbents. We believe that the mandated use of the database has an additional opportunity: a means to dynamically manage the RF spectrum. Motivated by this opportunity, in this paper we present SenseLess, a database driven white spaces network. As suggested by its very name, in SenseLess, WSDs obviate the need to sense the spectrum by relying entirely on a database service to determine white spaces availability. The service, using a combination of an up-to-date database of incumbents, sophisticated signal propagation modeling, and an efficient content dissemination mechanism ensures efficient, scalable, and safe white space network operation. We build, deploy, and evaluate SenseLess and compare our results to ground truth spectrum measurements. We present the unique system design considerations that arise due to operating over the white spaces. We also evaluate its efficiency and scalability. To the best of our knowledge, this is the first paper that identifies and examines the systems and networking challenges that arise from operating a white space network, which is solely dependent on a channel occupancy database.","PeriodicalId":119856,"journal":{"name":"2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128447810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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