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This cooperative sensing algorithm is referred to as decision fusion.
Generally speaking, if each user sends its observed data or processed data to a specific user, which jointly processes the collected data and makes a final decision, this cooperative sensing scheme is called data fusion.
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In DCR-MAC [21], the cooperative sensing is used for solving the hidden PU problem.
They also investigated the impact of reporting channel errors on the cooperative sensing performance.
We will present the cooperative sensing model and throughput analysis considering reporting errors in the following.
In this model, two cooperative sensing schemes have been proposed.
In this way, the proposed cooperative sensing will be performed with an extremely low cooperation resource while a certain high level of sensing performance is ensured.
To improve the spectrum-sensing performance, cooperative sensing and geo-location technology were proposed.
In addition, cooperative sensing also shortens the sensing time of the spectrum while improving the overall sensitivity [18].
This paper proposes a new cooperative sensing scheme that introduces silence periods in the sensing reporting to lower the reporting bandwidth by 50%.
To tackle the issue of reducing the sensing report overhead, this paper introduces a new cooperative sensing scheme that introduces silence periods in the reporting and, relying on information theory principles, explores the information present in these periods to reduce by 50% the sensing reporting overhead while maintaining the same performance of standard reporting schemes.
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