In the literature, most distributed detection developed so far mainly focuses on the test rule based on fixed sample size. However, in the real situations, sequential tests are more suitable to be utilized since it might achieve the same detection performance by using fewer number of samples as compared with the fixed-sample-size test. Thus, this theses will propose a new distributed sequential detection approach for the applications in wireless sensor networks(WSNs) and cognitive radios(CRs). First we refer to the sequential detection, and it has been developed by Wald in 1994, which is well known as the sequential probability ratio test (SPRT). The SPRT is proved to be able to decrease the required average sample numbers or reducing the average detection time. Indeed, the SPRT is the optimal sequential detection in terms of the minimizing the required number of samples given the constraint of false alarm and miss probabilities when the observation samples are independent and identical distributed (i.i.d.). However, if the observation samples are not dentically distributed, by simulation results show that the SPRT is not the optimal test. Based on a heuristic approach, this thesis then developed a new distributed detection scheme based on the sorted samples. Finally , the simulation results obtained by this thesis shows that the proposed scheme can further reduce the number of samples required for making the final decision as compared with SPRT.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0709111-220810 |
| Date | 09 July 2011 |
| Creators | Lin, Fang-Ya |
| Contributors | Yunghsiang Sam Han, Tsang-Yi Wang, Yu, Chao-Tang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0709111-220810 |
| Rights | withheld, Copyright information available at source archive |
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