The Experts below are selected from a list of 2562 Experts worldwide ranked by ideXlab platform
Takeo Fujii - One of the best experts on this subject based on the ideXlab platform.
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Packet Delivery Ratio Prediction for V2V Based on Radio Environment Map Considering Hidden Terminal Problem
International Journal of Intelligent Transportation Systems Research, 2020Co-Authors: Ayumu Ueda, Takeo FujiiAbstract:Recently, vehicle-to-vehicle communication has been envisaged to be one of the technologies for realizing highly safe connected and automated driving. One of the approaches for predicting the Radio Environment is the use of a measurement-based spectrum database, which stores various pieces of information on the Radio Environment of data received and collected by vehicles; however, prediction of an accurate packet delivery ratio (PDR) with consideration of packet collisions is difficult if the vehicle density changes after the generation of PDR Maps. This paper proposes a method for predicting the PDR with consideration of packet collisions, including the influence of hidden nodes, by using the positions and number of vehicles.
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Radio Environment Map updating procedure considering change of surrounding Environment
Wireless Communications and Networking Conference, 2020Co-Authors: Keita Katagiri, Takeo FujiiAbstract:In this paper, we propose a method to update a Radio Environment Map (REM) considering change of surrounding Environment. The REM provides statistical Radio information of primary users (PUs) to secondary users (SUs). SUs can utilize the information to design communication parameters for improving communication efficiency. However, if surrounding Environment changes, the newly observed datasets are significantly different from the initially observed datasets. The database server requires to detect change of surrounding Environment and to update the REM based on the detected results. In this paper, we propose a method to update the REM based on hypothesis testing. In the proposed method, sensor nodes observe a received signal strength indicator (RSSI) in each location and report that to the database server. Then, the database server updates the REM using tested results. The simulation results show that the proposed method can detect change of surrounding Environment and accurately predict the average RSSI in each location while significantly reducing the number of the REM updates.
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Radio Environment Map construction with joint space frequency interpolation
International Conference on Artificial Intelligence, 2020Co-Authors: Koya Sato, Kei Inage, Takeo FujiiAbstract:In this paper, we propose a Radio Environment Map (REM) construction method that interpolates the received signal power over not only the spatial domain but also the frequency domain. REM is a tool for analyzing Radio propagation, which is typically defined as a Map that stores the received signal power. Crowdsourcing with spatial interpolation (e.g., Kriging) can accurately construct the REM, and the accurate REM improves the efficiency of spectrum use. However, crowdsourcing can only be performed over frequencies in which the mobile terminals can perform the sensing. Thus, conventional REM construction may only improve the spectral efficiency in the frequency in which the sensing can be performed. Our proposed method focuses on the fact that the average received signal power, which consists of path loss and shadowing, shows a strong correlation over the frequency domain. We show that utilizing correlations over both frequency and spatial domains can construct the REM even if the datasets are not available at the estimated Environment.
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WCNC Workshops - Radio Environment Map Updating Procedure Considering Change of Surrounding Environment
2020 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), 2020Co-Authors: Keita Katagiri, Takeo FujiiAbstract:In this paper, we propose a method to update a Radio Environment Map (REM) considering change of surrounding Environment. The REM provides statistical Radio information of primary users (PUs) to secondary users (SUs). SUs can utilize the information to design communication parameters for improving communication efficiency. However, if surrounding Environment changes, the newly observed datasets are significantly different from the initially observed datasets. The database server requires to detect change of surrounding Environment and to update the REM based on the detected results. In this paper, we propose a method to update the REM based on hypothesis testing. In the proposed method, sensor nodes observe a received signal strength indicator (RSSI) in each location and report that to the database server. Then, the database server updates the REM using tested results. The simulation results show that the proposed method can detect change of surrounding Environment and accurately predict the average RSSI in each location while significantly reducing the number of the REM updates.
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Radio Environment Map updating procedure based on hypothesis testing
IEEE International Symposium on Dynamic Spectrum Access Networks, 2019Co-Authors: Keita Katagiri, Takeo FujiiAbstract:In this paper, we propose an updating method of a Radio Environment Map (REM) using Welch’s t -test. The REM provides statistical Radio information about primary users (PUs) to secondary users (SUs). By using REM, SUs can predict path loss and shadowing deviation in each location. However, the estimation accuracy of the Radio Environment is degraded if the surrounding Environment changes since the initial REM is constructed. The database server should update the REM by detecting the change of the Radio Environment. Therefore, in this paper, we consider that the database server judges the change of the Radio Environment by using Welch’s t-test, which is one of the hypothesis testings. In the proposed method, the sensor nodes observe the received power in each location and report this information to the database server. The database server tests the difference of the average received power between the initial REM and the new observed datasets and decides the requirement of update of the REM. The simulation results show that the proposed method can detect the change of the Radio Environment and accurately predict the average received power than the updating method using oblivion factor.
Youping Zhao - One of the best experts on this subject based on the ideXlab platform.
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WISATS (1) - Adaptive Compressed Wideband Spectrum Sensing Based on Radio Environment Map Dedicated for Space Information Networks
Wireless and Satellite Systems, 2019Co-Authors: Xiaoluan Zhang, Youping Zhao, Hongbin ChenAbstract:Spectrum sensing is the basis of dynamic spectrum access and sharing for space information networks consisting of various satellite and terrestrial networks. The traditional spectrum sensing method, guided by the Nyquist-Shannon sampling theorem, might not be suitable for the emerging communication systems such as the fifth-generation mobile communications (5G) and space information networks utilizing spectrum from sub-6 GHz up to 100 GHz to offer ubiquitous broadband applications. In contrast, compressed spectrum sensing can not only relax the requirements on hardware and software, but also reduce the energy consumption and processing latency. As for the compressed measurement (low-speed sampling) process of the existing compressed spectrum sensing algorithms, the compression ratio is usually set to a fixed value, which limits their adaptability to the dynamically changing Radio Environment with different sparseness. In this paper, an adaptive compressed spectrum sensing algorithm based on Radio Environment Map (REM) dedicated for space information networks is proposed to address this problem. Simulations show that the proposed algorithm has better adaptability to the varying Environment than the existing compressed spectrum sensing algorithms.
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adaptive compressed wideband spectrum sensing based on Radio Environment Map dedicated for space information networks
International Conference on Wireless and Satellite Systems, 2019Co-Authors: Xiaoluan Zhang, Youping Zhao, Hongbin ChenAbstract:Spectrum sensing is the basis of dynamic spectrum access and sharing for space information networks consisting of various satellite and terrestrial networks. The traditional spectrum sensing method, guided by the Nyquist-Shannon sampling theorem, might not be suitable for the emerging communication systems such as the fifth-generation mobile communications (5G) and space information networks utilizing spectrum from sub-6 GHz up to 100 GHz to offer ubiquitous broadband applications. In contrast, compressed spectrum sensing can not only relax the requirements on hardware and software, but also reduce the energy consumption and processing latency. As for the compressed measurement (low-speed sampling) process of the existing compressed spectrum sensing algorithms, the compression ratio is usually set to a fixed value, which limits their adaptability to the dynamically changing Radio Environment with different sparseness. In this paper, an adaptive compressed spectrum sensing algorithm based on Radio Environment Map (REM) dedicated for space information networks is proposed to address this problem. Simulations show that the proposed algorithm has better adaptability to the varying Environment than the existing compressed spectrum sensing algorithms.
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Radio Environment Map based cognitive doppler spread compensation algorithms for high speed rail broadband mobile communications
Eurasip Journal on Wireless Communications and Networking, 2012Co-Authors: Youping ZhaoAbstract:Recently, there is an increasing yet challenging demand on broadband mobile communications for high-speed trains. In this article, cognitive Doppler spread compensation algorithms are proposed for high-speed rail broadband mobile communications, which make use of the dedicated Radio Environment Map (REM) for railway to compensate the time-varying Doppler spread. The dedicated REM for high-speed rail can be viewed as a spatial-temporal database consisting of the Radio channel parameters along a given railway. The performance of the proposed Doppler spread compensation algorithms are evaluated with a typical OFDM-based broadband mobile system. Simulation results show that the link-level performance of high-speed rail broadband mobile communications can be improved significantly due to the REM-enabled Radio channel condition awareness and the cognitive Doppler spread compensation algorithms. The REM-based cognitive Radio approach presents a new paradigm for systems design of high-speed rail broadband mobile communications.
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network support the Radio Environment Map
Cognitive Radio Technology (Second Edition), 2009Co-Authors: Youping Zhao, Jeffrey H ReedAbstract:This chapter discusses the strategy of exploiting network support in cognitive Radio (CR) systems architectures introducing the Radio Environment Map (REM) as an innovative vehicle of providing network support to CRs. As a systematic top-down approach to providing network support to CRs, the Radio Environment Map is proposed as an integrated database consisting of multi domain information such as geographical features, available services, spectral regulations, locations and activities of Radios, policies of the user and/or service provider, and past experience. An Radio Environment Map (REM) can be exploited by a CE to enhance or achieve most of cognitive functionalities such as SA, reasoning, learning, planning, and decision support. Leveraging both internal and external network support through global and local REMs presents a sensible approach to implementing CRs in a reliable, flexible, and cost effective way. Network support can dramatically relax the requirements on a CR device as well as improve the performance of the whole CR network. Considering the dynamic nature of spectral regulation and operation policy, the REM-based CR is flexible and future proof in the sense that it allows regulators or service providers to modify or change their rules or policies simply by updating REMs accordingly.
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performance evaluation of Radio Environment Map enabled cognitive spectrum sharing networks
Military Communications Conference, 2007Co-Authors: Youping Zhao, Jeffrey H Reed, David Raymond, Claudio R C M Da Silva, Scott F MidkiffAbstract:In recent years, cognitive Radio (CR) has been introduced as a new paradigm for enabling much higher spectrum utilization by dynamically accessing and sharing the spectrum with incumbent Radio devices. This paper proposes an innovative and practical spectrum-sharing approach and evaluates its performance. The goal is to minimize CR's harmful interference to incumbent primary users and to maximize the utility of spectrum-sharing networks by exploiting the proposed Radio Environment Map (REM). REM-enabled CR adaptation algorithms are developed for various operational Environments, namely, the open area and the dense urban area. This paper also compares the performance gain when using the Global REM and the Local REM, respectively. The impact of imperfect REM information due to node mobility and REM dissemination delay is simulated. By exploiting the REM information, CR can make situation-aware adaptations in transmit power, transmit timing, routing protocol, and topology, thereby reducing interference to primary users. More importantly, the painful hidden node or hidden receiver problem can be mitigated with the help of the Global REM. REM-enabled CR could be a cost-efficient and reliable approach to "waterfilling" underutilized spectrum in both space and time domains.
Tuna Tugcu - One of the best experts on this subject based on the ideXlab platform.
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location estimation based Radio Environment Map construction in fading channels
Communications and Mobile Computing, 2015Co-Authors: Huseyin Birkan Yilmaz, Tuna TugcuAbstract:Latest regulations on TV white space communications and trend toward spectrum access through geolocation databases relax the regulatory constraints on cognitive Radios. Radio Environment Map REM is a kind of improved geolocation database and an emerging topic with the latest regulations on TV white space communications. It constructs a comprehensive temperature Map of the cognitive Radio network operation area by utilizing multi-domain information from geolocation databases, characteristics of spectrum use, geographical terrain models, propagation Environment, and regulations. REMs act as cognition engines by building long-term knowledge via processing spectrum measurements collected from sensors to estimate the state of locations without any measurement data. Active transmitter LocatIon Estimation based REM construction technique is proposed and compared with the well-known REM construction techniques such as Kriging and inverse distance weighted interpolation in shadow and multipath fading channels. The simulation results suggest that the LocatIon Estimation based REM construction outperforms the compared methods in terms of RMSE and correct detection zone ratio by utilizing additional information about channel parameters that can be estimated by classical least squares method easily.Copyright © 2013 John Wiley & Sons, Ltd.
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transmitter location estimation for Radio Environment Map construction using software defined Radio
Symposium on Communications and Vehicular Technology in the Benelux, 2014Co-Authors: Mustafa Tugrul Ozsahin, Tuna TugcuAbstract:This work focuses on the practical implementation of transmitter location estimation algorithms using software defined Radio devices for the purpose of Radio Environment Map (REM) construction, which is used to determine primary user location and available channels for Cognitive Radio. To this end, a testbed is also set up and technical and physical details of this testbed are explained. The location of an immobile transmitter is estimated using the collected signal strength data from multiple receivers by applying one known technique: LocatIon Estimation based (LIvE) REM Construction Method, and one proposed technique: exhaustive search on the discrete Map. The results of these estimations are explained and compared.
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sensor placement algorithm for Radio Environment Map construction in cognitive Radio networks
Wireless Communications and Networking Conference, 2014Co-Authors: Birkan H Yilmaz, Chanbyoung Chae, Tuna TugcuAbstract:In cognitive Radio, current trend is to utilize geolocation database for TV bands. Considering more dynamic bands in terms of primary user activity, however, necessitates the use of Radio Environment Map (REM), which is an advanced knowledge base that stores live multidomain information on the entities in the network and the Environment. In Cognitive Radio Networks (CRNs), mobile nodes that are capable of measuring the energy of the frequency bands are less capable compared to dedicated sensing nodes in the network. Therefore, deployment algorithm of the dedicated sensor nodes is of great importance and affects the constructed REM interference Map quality. We propose a novel deployment algorithm for CRNs that considers user distribution probabilities. Numerical results confirm that the proposed deployment algorithm significantly improves the REM performance. The proposed algorithm is compared with random deployments and it is applied on Kriging and LIvE REM construction techniques.
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SCVT - Transmitter location estimation for Radio Environment Map construction using software defined Radio
2014 IEEE 21st Symposium on Communications and Vehicular Technology in the Benelux (SCVT), 2014Co-Authors: Mustafa Tugrul Ozsahin, Tuna TugcuAbstract:This work focuses on the practical implementation of transmitter location estimation algorithms using software defined Radio devices for the purpose of Radio Environment Map (REM) construction, which is used to determine primary user location and available channels for Cognitive Radio. To this end, a testbed is also set up and technical and physical details of this testbed are explained. The location of an immobile transmitter is estimated using the collected signal strength data from multiple receivers by applying one known technique: LocatIon Estimation based (LIvE) REM Construction Method, and one proposed technique: exhaustive search on the discrete Map. The results of these estimations are explained and compared.
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WCNC - Sensor placement algorithm for Radio Environment Map construction in cognitive Radio networks
2014 IEEE Wireless Communications and Networking Conference (WCNC), 2014Co-Authors: H. Birkan Yilmaz, Chanbyoung Chae, Tuna TugcuAbstract:In cognitive Radio, current trend is to utilize geolocation database for TV bands. Considering more dynamic bands in terms of primary user activity, however, necessitates the use of Radio Environment Map (REM), which is an advanced knowledge base that stores live multidomain information on the entities in the network and the Environment. In Cognitive Radio Networks (CRNs), mobile nodes that are capable of measuring the energy of the frequency bands are less capable compared to dedicated sensing nodes in the network. Therefore, deployment algorithm of the dedicated sensor nodes is of great importance and affects the constructed REM interference Map quality. We propose a novel deployment algorithm for CRNs that considers user distribution probabilities. Numerical results confirm that the proposed deployment algorithm significantly improves the REM performance. The proposed algorithm is compared with random deployments and it is applied on Kriging and LIvE REM construction techniques.
Koya Sato - One of the best experts on this subject based on the ideXlab platform.
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Radio Environment Map construction with joint space frequency interpolation
International Conference on Artificial Intelligence, 2020Co-Authors: Koya Sato, Kei Inage, Takeo FujiiAbstract:In this paper, we propose a Radio Environment Map (REM) construction method that interpolates the received signal power over not only the spatial domain but also the frequency domain. REM is a tool for analyzing Radio propagation, which is typically defined as a Map that stores the received signal power. Crowdsourcing with spatial interpolation (e.g., Kriging) can accurately construct the REM, and the accurate REM improves the efficiency of spectrum use. However, crowdsourcing can only be performed over frequencies in which the mobile terminals can perform the sensing. Thus, conventional REM construction may only improve the spectral efficiency in the frequency in which the sensing can be performed. Our proposed method focuses on the fact that the average received signal power, which consists of path loss and shadowing, shows a strong correlation over the frequency domain. We show that utilizing correlations over both frequency and spatial domains can construct the REM even if the datasets are not available at the estimated Environment.
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Kriging-Based Interference Power Constraint: Integrated Design of the Radio Environment Map and Transmission Power
IEEE Transactions on Cognitive Communications and Networking, 2017Co-Authors: Koya Sato, Takeo FujiiAbstract:This paper proposes a probabilistic interference constraint method with a Radio Environment Map (REM) for spatial spectrum sharing. The REM stores the spatial distribution of the average received signal power. We can optimize the accuracy of the measurement-based REM using the Kriging interpolation. Although several researchers have maintained a continuous interest in improving the accuracy of the REM, sufficient study has not been done to actually explore the interference constraint considering the estimation error. The proposed method uses ordinary Kriging interpolation for the spectrum cartography. According to the predicted distribution of the estimation error, the allowable interference power to the primary user is approximately formulated. Numerical results show that the proposed method can achieve the probabilistic interference constraint asymptotically. Additionally, we compare the performance of the proposed technique with three methods: the perfect estimation, the path loss-based method, and the Kriging-based method without the error prediction. The comparison results show that the proposed method has a higher spectrum sharing opportunity than the path loss-based method, even if only a small amount of measurement data is available. It is also shown that the proposed method dramatically improves the outage probability of the interference power compared to the conventional Kriging-based method.
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GLOBECOM Workshops - Kriging-Based Interference Power Constraint for Spectrum Sharing Based on Radio Environment Map
2015 IEEE Globecom Workshops (GC Wkshps), 2015Co-Authors: Koya Sato, Takeo FujiiAbstract:This paper proposes a probabilistic interference constraint method with Radio Environment Map (REM) for spectrum sharing. Kriging interpolation is a well-known technique that can optimize the REM accuracy. However, although many researchers have maintained continuous interests in the accuracy of the REM, little study has been done to actually explore the interference constraint considering the estimation error. The proposed method uses ordinary kriging interpolation for the spectrum cartography. According to the predicted distribution of the estimation error, the allowed interference power to the primary user (PU) is approximately formulated. Numerical results show that the proposed method can achieve the probabilistic interference constraint asymptotically. Additionally, we compare the performance of the proposed technique with two methods: limit of the path loss-based method and perfect estimation. From the comparison results, it is shown that the kriging-based method has higher spectrum sharing opportunity than the path loss-based method, even if there are few measurement data.
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kriging based interference power constraint for spectrum sharing based on Radio Environment Map
Global Communications Conference, 2015Co-Authors: Koya Sato, Takeo FujiiAbstract:This paper proposes a probabilistic interference constraint method with Radio Environment Map (REM) for spectrum sharing. Kriging interpolation is a well-known technique that can optimize the REM accuracy. However, although many researchers have maintained continuous interests in the accuracy of the REM, little study has been done to actually explore the interference constraint considering the estimation error. The proposed method uses ordinary kriging interpolation for the spectrum cartography. According to the predicted distribution of the estimation error, the allowed interference power to the primary user (PU) is approximately formulated. Numerical results show that the proposed method can achieve the probabilistic interference constraint asymptotically. Additionally, we compare the performance of the proposed technique with two methods: limit of the path loss-based method and perfect estimation. From the comparison results, it is shown that the kriging-based method has higher spectrum sharing opportunity than the path loss-based method, even if there are few measurement data.
Hyoungjin Lim - One of the best experts on this subject based on the ideXlab platform.
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optimal threshold adaptation with Radio Environment Map for cognitive Radio networks
International Symposium on Information Theory, 2009Co-Authors: Daeyoung Seol, Hyoungjin LimAbstract:Spectrum sensing is a key enabling technology of cognitive Radio. Reliable detection increases access opportunity to temporarily unused bands and prevents harmful interference to the licensed users. Due to the receiver noise, signal attenuation, and multi-path fading effect, however, it is usually not possible to determine the existence of primary signal with absolute certainty. Without the information of primary user activity, Neyman-Pearson criterion has been commonly used to minimize the missed detection probability for a given false alarm rate. In this paper, we assume that the traffic statistic of primary system is logged into the Radio Environment Map (REM) and can be accessed by the secondary system. Considering sensing errors, Bayes criterion is adopted for total utility maximization of primary and secondary systems. The threshold of energy detector is adapted according to the utility values and a priori information from REM, i.e., both false alarm and detection probabilities are dynamically adjusted.
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ISIT - Optimal threshold adaptation with Radio Environment Map for cognitive Radio networks
2009 IEEE International Symposium on Information Theory, 2009Co-Authors: Daeyoung Seol, Hyoungjin LimAbstract:Spectrum sensing is a key enabling technology of cognitive Radio. Reliable detection increases access opportunity to temporarily unused bands and prevents harmful interference to the licensed users. Due to the receiver noise, signal attenuation, and multi-path fading effect, however, it is usually not possible to determine the existence of primary signal with absolute certainty. Without the information of primary user activity, Neyman-Pearson criterion has been commonly used to minimize the missed detection probability for a given false alarm rate. In this paper, we assume that the traffic statistic of primary system is logged into the Radio Environment Map (REM) and can be accessed by the secondary system. Considering sensing errors, Bayes criterion is adopted for total utility maximization of primary and secondary systems. The threshold of energy detector is adapted according to the utility values and a priori information from REM, i.e., both false alarm and detection probabilities are dynamically adjusted.
