Cross-layered Random Access Protocol for Distributed Estimation
| Autor: | Keng-U Lei, 李景裕 |
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| Rok vydání: | 2007 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 95 A cross-layered slotted ALOHA protocol is proposed for distributed estimation in sensor networks. Suppose that the sensors in the network record local measurements of a common event and report the data back to the fusion center through direct transmission links. We employ a channel-aware transmission control where the transmission probability of each sensor is chosen based on the quality of the local observation and the conditions of the transmission channel in each time slots. In contrast to conventional ALOHA systems, our goal is to design the transmission control functions such that the estimation performance is optimized as opposed to maximizing the system throughput. Two probability assignment schemes are proposed: the maximum mean-square-error (MSE) reduction (MMR) scheme and the suboptimal two-mode MSE-reduction (TMMR) scheme. The MMR maximizes the reduction in MSE of the estimation in each time slots, but requires knowledge of the number of active sensors and the error of the estimate obtained up to this point. Instead of obtaining a different transmission control function for each time slot, in TMMR, the sensors switch among two predetermined transmission control functions based on the average estimation. Furthermore, we notice that if new observations are made by the sensors in each time slot, those data can be fully exploited by employing diversity combining techniques when the sensors are not scheduled to transmit. Specifically, we propose the use of selective combining on the backlogged measurements within a certain time window before each transmission. The transmission control functions are then adjusted accordingly. As a result, we are able to exploit both the spatial and temporal diversity gains inherent in the multi-user system. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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