Synopsis
Master's Thesis from the year 2012 in the subject Engineering - Communication Technology, Indian Institute of Technology, Delhi (IIT Delhi), course: M.Tech (Communications), language: English, abstract: To ensure that cognitive radios would not interfere with primary users, spectrum sensing is required to be efficient and accurate by reliably detecting primary user signals. In this work, we implemented a spectrum sensing methodology based on the Truncated Sequential Probability Ratio Test (TSPRT). The TSPRT is a combination of SPRT and Neyman-Pearson. We created and simulated the model and observed the variation of quantization error, noise variance and dynamic range of the signal to achieve the minimum average sample number (ASN) and desired error probabilities of detection and false alarm for sine wave and similar input signals. This report comprises of theoretical analysis and practical implementation of spectrum sensing circuit in Xilinx system generator. Simulations are done to observe the effect of various parameters on ASN and shown.
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Implementation of Cognitive Radio Spectrum sensing circuit using TSPRT algorithm
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Implementation of Cognitive Radio Spectrum sensing circuit using TSPRT algorithm
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Master's Thesis from the year 2012 in the subject Engineering - Communication Technology, Indian Institute of Technology, Delhi (IIT Delhi), course: M.Tech (Communications), language: English, abstract: To ensure that cognitive radios would not interfere with primary users, spectrum sensing is required to be efficient and accurate by reliably detecting primary user signals. In this work, we implemented a spectrum sensing methodology based on the Truncated Sequential Probability Ratio Test (TSPRT). The TSPRT is a combination of SPRT and Neyman-Pearson. We created and simulated the model and observed the variation of quantization error, noise variance and dynamic range of the signal to achieve the minimum average sample number (ASN) and desired error probabilities of detection and false alarm for sine wave and similar input signals. This report comprises of theoretical analysis and practical implementation of spectrum sensing circuit in Xilinx system generator. Simulations are done to observe the effect of various parameters on ASN and shown. 56 pp. Englisch. Seller Inventory # 9783668410855
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Implementation of Cognitive Radio Spectrum sensing circuit using TSPRT algorithm
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Implementation of Cognitive Radio Spectrum sensing circuit using TSPRT algorithm
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Master's Thesis from the year 2012 in the subject Engineering - Communication Technology, Indian Institute of Technology, Delhi (IIT Delhi), course: M.Tech (Communications), language: English, abstract: To ensure that cognitive radios would not interfere with primary users, spectrum sensing is required to be efficient and accurate by reliably detecting primary user signals. In this work, we implemented a spectrum sensing methodology based on the Truncated Sequential Probability Ratio Test (TSPRT). The TSPRT is a combination of SPRT and Neyman-Pearson. We created and simulated the model and observed the variation of quantization error, noise variance and dynamic range of the signal to achieve the minimum average sample number (ASN) and desired error probabilities of detection and false alarm for sine wave and similar input signals. This report comprises of theoretical analysis and practical implementation of spectrum sensing circuit in Xilinx system generator. Simulations are done to observe the effect of various parameters on ASN and shown. Seller Inventory # 9783668410855
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Implementation of Cognitive Radio Spectrum sensing circuit using TSPRT algorithm
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Taschenbuch. Condition: Neu. Implementation of Cognitive Radio Spectrum sensing circuit using TSPRT algorithm | Neha Pal | Taschenbuch | 56 S. | Englisch | 2017 | GRIN Verlag | EAN 9783668410855 | Verantwortliche Person für die EU: GRIN Publishing GmbH, Waltherstr. 23, 80337 München, info[at]grin[dot]com | Anbieter: preigu. Seller Inventory # 108576442