The Experts below are selected from a list of 14505 Experts worldwide ranked by ideXlab platform
Janne Lehtomaki - One of the best experts on this subject based on the ideXlab platform.
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On the Sample Size for the Estimation of Primary Activity Statistics Based on Spectrum Sensing
IEEE Transactions on Cognitive Communications and Networking, 2019Co-Authors: Ahmed Al-tahmeesschi, Miguel Lopez-benitez, Janne Lehtomaki, Dhaval K. Patel, Kenta UmebayashiAbstract:Dynamic Spectrum access (DSA)/cognitive radio (CR) systems can benefit from the knowledge of the activity statistics of primary channels, which can use this information to intelligently adapt their Spectrum use to the operating environment. Particularly relevant statistics are the minimum, mean and variance of the on/off period durations, the channel duty cycle and the governing distribution. However, most DSA/CR systems have limited resources (power consumption, memory capacity, computational capability) and an important question arises of how many on/off period observations are required (i.e., the number of observed on/off periods, referred to as observation sample size in this paper) to estimate the statistics of the primary channel to a certain desired level of accuracy. In this paper, closed-form expressions to link such sample size with the accuracy of the observed primary activity statistics are proposed. A comprehensive theoretical analysis is performed on the required number of observed on/off periods to obtain a specific estimation accuracy. The accuracy of the obtained analytical results is validated and corroborated with both simulation and experimental results, showing a perfect agreement. The analytical results derived in this paper can be used in the design and dimensioning of DSA/CR systems in which the Spectrum Awareness function relies on Spectrum sensing.
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a study on false alarm cancellation for Spectrum usage measurements
Wireless Communications and Networking Conference, 2017Co-Authors: Riki Mizuchi, Kenta Umebayashi, Janne Lehtomaki, Miguel LopezbenitezAbstract:Two-layer smart Spectrum access (SSA) consists of Spectrum sharing based on dynamic Spectrum access (DSA: first layer) and Spectrum Awareness system (SAS: second layer). A main role of SAS is providing useful statistical information in terms of Spectrum usage by long term, wide-band and wide-area measurements. In this paper, we focus on signal area (SA) estimation which is a core signal processing in SAS to understand the Spectrum usage. Specifically, SA estimation is used as post processing for energy detector outputs. It has been shown that Simple-SA (S-SA) estimation can enhance the Spectrum usage measurement performance, but it inherently increases false alarms. For this issue, efficient false alarm cancellation technique, L-shaped false alarm cancellation (L-FC), is proposed in this paper. Numerical evaluations show that the proposed method can achieve proper detection performance while the computational cost is small compared to other methods.
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WCNC Workshops - A Study on False Alarm Cancellation for Spectrum Usage Measurements
2017 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), 2017Co-Authors: Riki Mizuchi, Kenta Umebayashi, Janne Lehtomaki, Miguel Lopez-benitezAbstract:Two-layer smart Spectrum access (SSA) consists of Spectrum sharing based on dynamic Spectrum access (DSA: first layer) and Spectrum Awareness system (SAS: second layer). A main role of SAS is providing useful statistical information in terms of Spectrum usage by long term, wide-band and wide-area measurements. In this paper, we focus on signal area (SA) estimation which is a core signal processing in SAS to understand the Spectrum usage. Specifically, SA estimation is used as post processing for energy detector outputs. It has been shown that Simple-SA (S-SA) estimation can enhance the Spectrum usage measurement performance, but it inherently increases false alarms. For this issue, efficient false alarm cancellation technique, L-shaped false alarm cancellation (L-FC), is proposed in this paper. Numerical evaluations show that the proposed method can achieve proper detection performance while the computational cost is small compared to other methods.
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a study on welch fft segment size selection method for Spectrum Awareness
Wireless Communications and Networking Conference, 2016Co-Authors: Hiroki Iwata, Kenta Umebayashi, Samuli Tiiro, Yasuo Suzuki, Janne LehtomakiAbstract:We investigate Welch FFT segment size selection method for Spectrum Awareness in the context of smart Spectrum access (SSA), in which Spectrum usage information of primary users (PUs), such as duty cycle (DC), will be exploited by secondary users (SUs). Energy detector (ED) based on the Welch FFT can detect the presence of PU signal in a broadband environment efficiently and DC can be estimated based on the detection results. There is a trade-off between the detection performance and the frequency resolution in terms of the Welch FFT segment size. The optimum segment size depends on signal-to-noise ratio (SNR), and therefore practical segment size setting is difficult. In this paper, we will show two practical segment size selection methods: the first one can achieve accurate Spectrum Awareness while it requires relatively high computational complexity since it employs exhaustive search, and the second one can achieve reasonable Spectrum Awareness performance with low computational complexity since limited search is used. Numerical evaluations show that the method with limited search can achieve comparable Spectrum Awareness performance to the method of exhaustive search while requiring significantly lower complexity.
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WCNC Workshops - A study on Welch FFT segment size selection method for Spectrum Awareness
2016 IEEE Wireless Communications and Networking Conference, 2016Co-Authors: Hiroki Iwata, Kenta Umebayashi, Samuli Tiiro, Yasuo Suzuki, Janne LehtomakiAbstract:We investigate Welch FFT segment size selection method for Spectrum Awareness in the context of smart Spectrum access (SSA), in which Spectrum usage information of primary users (PUs), such as duty cycle (DC), will be exploited by secondary users (SUs). Energy detector (ED) based on the Welch FFT can detect the presence of PU signal in a broadband environment efficiently and DC can be estimated based on the detection results. There is a trade-off between the detection performance and the frequency resolution in terms of the Welch FFT segment size. The optimum segment size depends on signal-to-noise ratio (SNR), and therefore practical segment size setting is difficult. In this paper, we will show two practical segment size selection methods: the first one can achieve accurate Spectrum Awareness while it requires relatively high computational complexity since it employs exhaustive search, and the second one can achieve reasonable Spectrum Awareness performance with low computational complexity since limited search is used. Numerical evaluations show that the method with limited search can achieve comparable Spectrum Awareness performance to the method of exhaustive search while requiring significantly lower complexity.
Kenta Umebayashi - One of the best experts on this subject based on the ideXlab platform.
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On the Sample Size for the Estimation of Primary Activity Statistics Based on Spectrum Sensing
IEEE Transactions on Cognitive Communications and Networking, 2019Co-Authors: Ahmed Al-tahmeesschi, Miguel Lopez-benitez, Janne Lehtomaki, Dhaval K. Patel, Kenta UmebayashiAbstract:Dynamic Spectrum access (DSA)/cognitive radio (CR) systems can benefit from the knowledge of the activity statistics of primary channels, which can use this information to intelligently adapt their Spectrum use to the operating environment. Particularly relevant statistics are the minimum, mean and variance of the on/off period durations, the channel duty cycle and the governing distribution. However, most DSA/CR systems have limited resources (power consumption, memory capacity, computational capability) and an important question arises of how many on/off period observations are required (i.e., the number of observed on/off periods, referred to as observation sample size in this paper) to estimate the statistics of the primary channel to a certain desired level of accuracy. In this paper, closed-form expressions to link such sample size with the accuracy of the observed primary activity statistics are proposed. A comprehensive theoretical analysis is performed on the required number of observed on/off periods to obtain a specific estimation accuracy. The accuracy of the obtained analytical results is validated and corroborated with both simulation and experimental results, showing a perfect agreement. The analytical results derived in this paper can be used in the design and dimensioning of DSA/CR systems in which the Spectrum Awareness function relies on Spectrum sensing.
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a study on false alarm cancellation for Spectrum usage measurements
Wireless Communications and Networking Conference, 2017Co-Authors: Riki Mizuchi, Kenta Umebayashi, Janne Lehtomaki, Miguel LopezbenitezAbstract:Two-layer smart Spectrum access (SSA) consists of Spectrum sharing based on dynamic Spectrum access (DSA: first layer) and Spectrum Awareness system (SAS: second layer). A main role of SAS is providing useful statistical information in terms of Spectrum usage by long term, wide-band and wide-area measurements. In this paper, we focus on signal area (SA) estimation which is a core signal processing in SAS to understand the Spectrum usage. Specifically, SA estimation is used as post processing for energy detector outputs. It has been shown that Simple-SA (S-SA) estimation can enhance the Spectrum usage measurement performance, but it inherently increases false alarms. For this issue, efficient false alarm cancellation technique, L-shaped false alarm cancellation (L-FC), is proposed in this paper. Numerical evaluations show that the proposed method can achieve proper detection performance while the computational cost is small compared to other methods.
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WCNC Workshops - A Study on False Alarm Cancellation for Spectrum Usage Measurements
2017 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), 2017Co-Authors: Riki Mizuchi, Kenta Umebayashi, Janne Lehtomaki, Miguel Lopez-benitezAbstract:Two-layer smart Spectrum access (SSA) consists of Spectrum sharing based on dynamic Spectrum access (DSA: first layer) and Spectrum Awareness system (SAS: second layer). A main role of SAS is providing useful statistical information in terms of Spectrum usage by long term, wide-band and wide-area measurements. In this paper, we focus on signal area (SA) estimation which is a core signal processing in SAS to understand the Spectrum usage. Specifically, SA estimation is used as post processing for energy detector outputs. It has been shown that Simple-SA (S-SA) estimation can enhance the Spectrum usage measurement performance, but it inherently increases false alarms. For this issue, efficient false alarm cancellation technique, L-shaped false alarm cancellation (L-FC), is proposed in this paper. Numerical evaluations show that the proposed method can achieve proper detection performance while the computational cost is small compared to other methods.
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a study on welch fft segment size selection method for Spectrum Awareness
Wireless Communications and Networking Conference, 2016Co-Authors: Hiroki Iwata, Kenta Umebayashi, Samuli Tiiro, Yasuo Suzuki, Janne LehtomakiAbstract:We investigate Welch FFT segment size selection method for Spectrum Awareness in the context of smart Spectrum access (SSA), in which Spectrum usage information of primary users (PUs), such as duty cycle (DC), will be exploited by secondary users (SUs). Energy detector (ED) based on the Welch FFT can detect the presence of PU signal in a broadband environment efficiently and DC can be estimated based on the detection results. There is a trade-off between the detection performance and the frequency resolution in terms of the Welch FFT segment size. The optimum segment size depends on signal-to-noise ratio (SNR), and therefore practical segment size setting is difficult. In this paper, we will show two practical segment size selection methods: the first one can achieve accurate Spectrum Awareness while it requires relatively high computational complexity since it employs exhaustive search, and the second one can achieve reasonable Spectrum Awareness performance with low computational complexity since limited search is used. Numerical evaluations show that the method with limited search can achieve comparable Spectrum Awareness performance to the method of exhaustive search while requiring significantly lower complexity.
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WCNC Workshops - A study on Welch FFT segment size selection method for Spectrum Awareness
2016 IEEE Wireless Communications and Networking Conference, 2016Co-Authors: Hiroki Iwata, Kenta Umebayashi, Samuli Tiiro, Yasuo Suzuki, Janne LehtomakiAbstract:We investigate Welch FFT segment size selection method for Spectrum Awareness in the context of smart Spectrum access (SSA), in which Spectrum usage information of primary users (PUs), such as duty cycle (DC), will be exploited by secondary users (SUs). Energy detector (ED) based on the Welch FFT can detect the presence of PU signal in a broadband environment efficiently and DC can be estimated based on the detection results. There is a trade-off between the detection performance and the frequency resolution in terms of the Welch FFT segment size. The optimum segment size depends on signal-to-noise ratio (SNR), and therefore practical segment size setting is difficult. In this paper, we will show two practical segment size selection methods: the first one can achieve accurate Spectrum Awareness while it requires relatively high computational complexity since it employs exhaustive search, and the second one can achieve reasonable Spectrum Awareness performance with low computational complexity since limited search is used. Numerical evaluations show that the method with limited search can achieve comparable Spectrum Awareness performance to the method of exhaustive search while requiring significantly lower complexity.
Samuli Tiiro - One of the best experts on this subject based on the ideXlab platform.
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a study on welch fft segment size selection method for Spectrum Awareness
Wireless Communications and Networking Conference, 2016Co-Authors: Hiroki Iwata, Kenta Umebayashi, Samuli Tiiro, Yasuo Suzuki, Janne LehtomakiAbstract:We investigate Welch FFT segment size selection method for Spectrum Awareness in the context of smart Spectrum access (SSA), in which Spectrum usage information of primary users (PUs), such as duty cycle (DC), will be exploited by secondary users (SUs). Energy detector (ED) based on the Welch FFT can detect the presence of PU signal in a broadband environment efficiently and DC can be estimated based on the detection results. There is a trade-off between the detection performance and the frequency resolution in terms of the Welch FFT segment size. The optimum segment size depends on signal-to-noise ratio (SNR), and therefore practical segment size setting is difficult. In this paper, we will show two practical segment size selection methods: the first one can achieve accurate Spectrum Awareness while it requires relatively high computational complexity since it employs exhaustive search, and the second one can achieve reasonable Spectrum Awareness performance with low computational complexity since limited search is used. Numerical evaluations show that the method with limited search can achieve comparable Spectrum Awareness performance to the method of exhaustive search while requiring significantly lower complexity.
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WCNC Workshops - A study on Welch FFT segment size selection method for Spectrum Awareness
2016 IEEE Wireless Communications and Networking Conference, 2016Co-Authors: Hiroki Iwata, Kenta Umebayashi, Samuli Tiiro, Yasuo Suzuki, Janne LehtomakiAbstract:We investigate Welch FFT segment size selection method for Spectrum Awareness in the context of smart Spectrum access (SSA), in which Spectrum usage information of primary users (PUs), such as duty cycle (DC), will be exploited by secondary users (SUs). Energy detector (ED) based on the Welch FFT can detect the presence of PU signal in a broadband environment efficiently and DC can be estimated based on the detection results. There is a trade-off between the detection performance and the frequency resolution in terms of the Welch FFT segment size. The optimum segment size depends on signal-to-noise ratio (SNR), and therefore practical segment size setting is difficult. In this paper, we will show two practical segment size selection methods: the first one can achieve accurate Spectrum Awareness while it requires relatively high computational complexity since it employs exhaustive search, and the second one can achieve reasonable Spectrum Awareness performance with low computational complexity since limited search is used. Numerical evaluations show that the method with limited search can achieve comparable Spectrum Awareness performance to the method of exhaustive search while requiring significantly lower complexity.
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optimum welch fft segment size for duty cycle estimation in Spectrum Awareness system
Wireless Communications and Networking Conference, 2015Co-Authors: Hiroki Iwata, Kenta Umebayashi, Samuli Tiiro, Yasuo Suzuki, Janne LehtomakiAbstract:In order to realize practical dynamic Spectrum access (DSA), implementing Spectrum sensing with reasonably low cost is very challenging due to the required detection accuracy and quickness. For this issue, we have introduced an extended DSA, smart Spectrum access (SSA), where any useful information in terms of Spectrum utilization, such as statistics regarding Spectrum utilization, is used not only for accomplishing the requirements of Spectrum sensing but also for enhancing the performance of the DSA. In this approach, obtaining the statistics of the Spectrum utilization is an important issue for which we have developed a Spectrum Awareness system prototype. One issue in the Spectrum Awareness is the Welch FFT segment size design which is used for Spectrum analysis. This issue involves a trade-off between the Spectrum usage detection accuracy and available frequency resolution. For this issue, we derive an optimum segment size based on analysis and show that the optimum segment size depends on signal-to-measurement bandwidth ratio and duty cycle. The optimum segment size derived by the analysis is validated with numerical simulation and experimental results.
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WCNC Workshops - Optimum welch FFT segment size for duty cycle estimation in Spectrum Awareness system
2015 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), 2015Co-Authors: Hiroki Iwata, Kenta Umebayashi, Samuli Tiiro, Yasuo Suzuki, Janne LehtomakiAbstract:In order to realize practical dynamic Spectrum access (DSA), implementing Spectrum sensing with reasonably low cost is very challenging due to the required detection accuracy and quickness. For this issue, we have introduced an extended DSA, smart Spectrum access (SSA), where any useful information in terms of Spectrum utilization, such as statistics regarding Spectrum utilization, is used not only for accomplishing the requirements of Spectrum sensing but also for enhancing the performance of the DSA. In this approach, obtaining the statistics of the Spectrum utilization is an important issue for which we have developed a Spectrum Awareness system prototype. One issue in the Spectrum Awareness is the Welch FFT segment size design which is used for Spectrum analysis. This issue involves a trade-off between the Spectrum usage detection accuracy and available frequency resolution. For this issue, we derive an optimum segment size based on analysis and show that the optimum segment size depends on signal-to-measurement bandwidth ratio and duty cycle. The optimum segment size derived by the analysis is validated with numerical simulation and experimental results.
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development of a measurement system for Spectrum Awareness
1st International Conference on 5G for Ubiquitous Connectivity, 2014Co-Authors: Kenta Umebayashi, Samuli Tiiro, Janne LehtomakiAbstract:Dynamic Spectrum access (DSA) is an attractive approach to solve the Spectrum scarcity problem. Among DSA techniques, Spectrum overlay is an approach where the Spectrum licensed to a primary user (PU) is shared by a secondary user (SU) while protecting the PU from the interference caused by SU Spectrum reuse. In the case where PU traffic is dynamic, Spectrum sharing is difficult as satisfying requirements of Spectrum sensing, the challenging accuracy, quickness and low cost requirements in practice, is difficult. For this issue, we propose a new concept of smart Spectrum access (SSA) where useful information related to PU Spectrum utilization is used to achieve not only the above requirements but also more efficient Spectrum utilization. We also show an approach to realize practical SSA and it consists of a Spectrum Awareness system (SAS) and a dynamic Spectrum access system (DSAS). The main role of the SAS is to provide useful information to the DSAS. The information can be obtained by the SAS through Spectrum utilization measurement and analysis of the measurement data. In this paper, we present a framework for smart Spectrum access and discuss the challenges of this approach. In addition, we report some of the experimental results related to SAS.
Hiroki Iwata - One of the best experts on this subject based on the ideXlab platform.
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a study on welch fft segment size selection method for Spectrum Awareness
Wireless Communications and Networking Conference, 2016Co-Authors: Hiroki Iwata, Kenta Umebayashi, Samuli Tiiro, Yasuo Suzuki, Janne LehtomakiAbstract:We investigate Welch FFT segment size selection method for Spectrum Awareness in the context of smart Spectrum access (SSA), in which Spectrum usage information of primary users (PUs), such as duty cycle (DC), will be exploited by secondary users (SUs). Energy detector (ED) based on the Welch FFT can detect the presence of PU signal in a broadband environment efficiently and DC can be estimated based on the detection results. There is a trade-off between the detection performance and the frequency resolution in terms of the Welch FFT segment size. The optimum segment size depends on signal-to-noise ratio (SNR), and therefore practical segment size setting is difficult. In this paper, we will show two practical segment size selection methods: the first one can achieve accurate Spectrum Awareness while it requires relatively high computational complexity since it employs exhaustive search, and the second one can achieve reasonable Spectrum Awareness performance with low computational complexity since limited search is used. Numerical evaluations show that the method with limited search can achieve comparable Spectrum Awareness performance to the method of exhaustive search while requiring significantly lower complexity.
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WCNC Workshops - A study on Welch FFT segment size selection method for Spectrum Awareness
2016 IEEE Wireless Communications and Networking Conference, 2016Co-Authors: Hiroki Iwata, Kenta Umebayashi, Samuli Tiiro, Yasuo Suzuki, Janne LehtomakiAbstract:We investigate Welch FFT segment size selection method for Spectrum Awareness in the context of smart Spectrum access (SSA), in which Spectrum usage information of primary users (PUs), such as duty cycle (DC), will be exploited by secondary users (SUs). Energy detector (ED) based on the Welch FFT can detect the presence of PU signal in a broadband environment efficiently and DC can be estimated based on the detection results. There is a trade-off between the detection performance and the frequency resolution in terms of the Welch FFT segment size. The optimum segment size depends on signal-to-noise ratio (SNR), and therefore practical segment size setting is difficult. In this paper, we will show two practical segment size selection methods: the first one can achieve accurate Spectrum Awareness while it requires relatively high computational complexity since it employs exhaustive search, and the second one can achieve reasonable Spectrum Awareness performance with low computational complexity since limited search is used. Numerical evaluations show that the method with limited search can achieve comparable Spectrum Awareness performance to the method of exhaustive search while requiring significantly lower complexity.
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optimum welch fft segment size for duty cycle estimation in Spectrum Awareness system
Wireless Communications and Networking Conference, 2015Co-Authors: Hiroki Iwata, Kenta Umebayashi, Samuli Tiiro, Yasuo Suzuki, Janne LehtomakiAbstract:In order to realize practical dynamic Spectrum access (DSA), implementing Spectrum sensing with reasonably low cost is very challenging due to the required detection accuracy and quickness. For this issue, we have introduced an extended DSA, smart Spectrum access (SSA), where any useful information in terms of Spectrum utilization, such as statistics regarding Spectrum utilization, is used not only for accomplishing the requirements of Spectrum sensing but also for enhancing the performance of the DSA. In this approach, obtaining the statistics of the Spectrum utilization is an important issue for which we have developed a Spectrum Awareness system prototype. One issue in the Spectrum Awareness is the Welch FFT segment size design which is used for Spectrum analysis. This issue involves a trade-off between the Spectrum usage detection accuracy and available frequency resolution. For this issue, we derive an optimum segment size based on analysis and show that the optimum segment size depends on signal-to-measurement bandwidth ratio and duty cycle. The optimum segment size derived by the analysis is validated with numerical simulation and experimental results.
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WCNC Workshops - Optimum welch FFT segment size for duty cycle estimation in Spectrum Awareness system
2015 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), 2015Co-Authors: Hiroki Iwata, Kenta Umebayashi, Samuli Tiiro, Yasuo Suzuki, Janne LehtomakiAbstract:In order to realize practical dynamic Spectrum access (DSA), implementing Spectrum sensing with reasonably low cost is very challenging due to the required detection accuracy and quickness. For this issue, we have introduced an extended DSA, smart Spectrum access (SSA), where any useful information in terms of Spectrum utilization, such as statistics regarding Spectrum utilization, is used not only for accomplishing the requirements of Spectrum sensing but also for enhancing the performance of the DSA. In this approach, obtaining the statistics of the Spectrum utilization is an important issue for which we have developed a Spectrum Awareness system prototype. One issue in the Spectrum Awareness is the Welch FFT segment size design which is used for Spectrum analysis. This issue involves a trade-off between the Spectrum usage detection accuracy and available frequency resolution. For this issue, we derive an optimum segment size based on analysis and show that the optimum segment size depends on signal-to-measurement bandwidth ratio and duty cycle. The optimum segment size derived by the analysis is validated with numerical simulation and experimental results.
Yasuo Suzuki - One of the best experts on this subject based on the ideXlab platform.
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a study on welch fft segment size selection method for Spectrum Awareness
Wireless Communications and Networking Conference, 2016Co-Authors: Hiroki Iwata, Kenta Umebayashi, Samuli Tiiro, Yasuo Suzuki, Janne LehtomakiAbstract:We investigate Welch FFT segment size selection method for Spectrum Awareness in the context of smart Spectrum access (SSA), in which Spectrum usage information of primary users (PUs), such as duty cycle (DC), will be exploited by secondary users (SUs). Energy detector (ED) based on the Welch FFT can detect the presence of PU signal in a broadband environment efficiently and DC can be estimated based on the detection results. There is a trade-off between the detection performance and the frequency resolution in terms of the Welch FFT segment size. The optimum segment size depends on signal-to-noise ratio (SNR), and therefore practical segment size setting is difficult. In this paper, we will show two practical segment size selection methods: the first one can achieve accurate Spectrum Awareness while it requires relatively high computational complexity since it employs exhaustive search, and the second one can achieve reasonable Spectrum Awareness performance with low computational complexity since limited search is used. Numerical evaluations show that the method with limited search can achieve comparable Spectrum Awareness performance to the method of exhaustive search while requiring significantly lower complexity.
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WCNC Workshops - A study on Welch FFT segment size selection method for Spectrum Awareness
2016 IEEE Wireless Communications and Networking Conference, 2016Co-Authors: Hiroki Iwata, Kenta Umebayashi, Samuli Tiiro, Yasuo Suzuki, Janne LehtomakiAbstract:We investigate Welch FFT segment size selection method for Spectrum Awareness in the context of smart Spectrum access (SSA), in which Spectrum usage information of primary users (PUs), such as duty cycle (DC), will be exploited by secondary users (SUs). Energy detector (ED) based on the Welch FFT can detect the presence of PU signal in a broadband environment efficiently and DC can be estimated based on the detection results. There is a trade-off between the detection performance and the frequency resolution in terms of the Welch FFT segment size. The optimum segment size depends on signal-to-noise ratio (SNR), and therefore practical segment size setting is difficult. In this paper, we will show two practical segment size selection methods: the first one can achieve accurate Spectrum Awareness while it requires relatively high computational complexity since it employs exhaustive search, and the second one can achieve reasonable Spectrum Awareness performance with low computational complexity since limited search is used. Numerical evaluations show that the method with limited search can achieve comparable Spectrum Awareness performance to the method of exhaustive search while requiring significantly lower complexity.
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optimum welch fft segment size for duty cycle estimation in Spectrum Awareness system
Wireless Communications and Networking Conference, 2015Co-Authors: Hiroki Iwata, Kenta Umebayashi, Samuli Tiiro, Yasuo Suzuki, Janne LehtomakiAbstract:In order to realize practical dynamic Spectrum access (DSA), implementing Spectrum sensing with reasonably low cost is very challenging due to the required detection accuracy and quickness. For this issue, we have introduced an extended DSA, smart Spectrum access (SSA), where any useful information in terms of Spectrum utilization, such as statistics regarding Spectrum utilization, is used not only for accomplishing the requirements of Spectrum sensing but also for enhancing the performance of the DSA. In this approach, obtaining the statistics of the Spectrum utilization is an important issue for which we have developed a Spectrum Awareness system prototype. One issue in the Spectrum Awareness is the Welch FFT segment size design which is used for Spectrum analysis. This issue involves a trade-off between the Spectrum usage detection accuracy and available frequency resolution. For this issue, we derive an optimum segment size based on analysis and show that the optimum segment size depends on signal-to-measurement bandwidth ratio and duty cycle. The optimum segment size derived by the analysis is validated with numerical simulation and experimental results.
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WCNC Workshops - Optimum welch FFT segment size for duty cycle estimation in Spectrum Awareness system
2015 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), 2015Co-Authors: Hiroki Iwata, Kenta Umebayashi, Samuli Tiiro, Yasuo Suzuki, Janne LehtomakiAbstract:In order to realize practical dynamic Spectrum access (DSA), implementing Spectrum sensing with reasonably low cost is very challenging due to the required detection accuracy and quickness. For this issue, we have introduced an extended DSA, smart Spectrum access (SSA), where any useful information in terms of Spectrum utilization, such as statistics regarding Spectrum utilization, is used not only for accomplishing the requirements of Spectrum sensing but also for enhancing the performance of the DSA. In this approach, obtaining the statistics of the Spectrum utilization is an important issue for which we have developed a Spectrum Awareness system prototype. One issue in the Spectrum Awareness is the Welch FFT segment size design which is used for Spectrum analysis. This issue involves a trade-off between the Spectrum usage detection accuracy and available frequency resolution. For this issue, we derive an optimum segment size based on analysis and show that the optimum segment size depends on signal-to-measurement bandwidth ratio and duty cycle. The optimum segment size derived by the analysis is validated with numerical simulation and experimental results.