2010Unpublished venueRequires access

Superposition-based cooperative spectrum sensing in cognitive radio networks

Jing Jin, Hongbo Xu, Hua Li, Chunjian Ren

Open publisher page 9 citations

Abstract

In cognitive radio networks, cooperation is presented to improve the performance of spectrum sensing. Conventional cooperative scheme assumes that all cooperative secondary users spend the same duration on sensing, sensing results are then reported to the fusion center sequentially. With the number of cooperative users growing, the more data needs to be reported to a fusion center, thus the more reporting time overhead would be consumed. However, reporting of sensing results just consumes reporting time overhead and has no contribution to the performance of cooperative spectrum sensing. In this paper, we propose a superposition-based cooperative spectrum sensing framework. It combines spectrum sensing duration and results reporting duration to sense. Each cooperative user adopts a different sensing duration because they are superposed on different reporting durations. The proposed framework makes cooperative spectrum sensing in a more accurate way without adding extra expected time overhead. Compared with the conventional cooperative scheme, simulation results indicate that significant detection performance enhancements may be achieved through our proposed scheme.

About this research paper

What this paper is about

In cognitive radio networks, cooperation is presented to improve the performance of spectrum sensing. Conventional cooperative scheme assumes that all cooperative secondary users spend the same duration on sensing, sensing results are then reported to the fusion center sequentially. With the number of cooperative users growing, the more data needs to be reported to a fusion center, thus the more reporting time overhead would be consumed. However, reporting of sensing results just consumes reporting time overhead and has no contribution to the performance of cooperative spectrum sensing. In this paper, we propose a superposition-based cooperative spectrum sensing framework. It combines spectrum sensing duration and results reporting duration to sense. Each cooperative user adopts a different sensing duration because they are superposed on different reporting durations. The proposed framework makes cooperative spectrum sensing in a more accurate way without adding extra expected time overhead. Compared with the conventional cooperative scheme, simulation results indicate that significant detection performance enhancements may be achieved through our proposed scheme.

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OpenAlex reports 9 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In cognitive radio networks, cooperation is presented to improve the performance of spectrum sensing. Conventional cooperative scheme assumes that all cooperative secondary users spend the same duration on sensing, sensing results are then reported to the fusion center sequentially. With the number of cooperative users growing, the more data needs to be reported to a fusion center, thus the more reporting time overhead would be consumed. However, reporting of sensing results just consumes reporting time overhead and has no contribution to the performance of cooperative spectrum sensing. In this paper, we propose a superposition-based cooperative spectrum sensing framework. It combines spectrum sensing duration and results reporting duration to sense. Each cooperative user adopts a different sensing duration because they are superposed on different reporting durations. The proposed framework makes cooperative spectrum sensing in a more accurate way without adding extra expected time overhead. Compared with the conventional cooperative scheme, simulation results indicate that significant detection performance enhancements may be achieved through our proposed scheme.

Key concepts: Fusion center, Cognitive radio, Duration (music), Overhead (engineering), Computer science, Scheme (mathematics), Superposition principle, Spectrum (functional analysis)

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