Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
We investigate the problem of sparse signal medium access control in the wireless sensor networks. The proposed sparse signal Aloha (SSA) transmits sampled compressive data to the fusion center using Aloha random access protocol. In order to maximize the overall data transmission rate in the presence of packet collision, redundant data are randomly subsampled at individual sensor nodes according to...
To extend the system life, duty-cycling technique is widely adopted in wireless sensor network. However, this technique also introduces limited throughput and extra packet delay to the system. To solve the problem, in this paper, we propose eQueue-MAC, a multi-channel traffic adaptive CSMA/TDMA hybrid MAC protocol with slotted channel hopping technique which is robust to external interference and...
Inspired by numerous sparse signal in IoT and the theory of compressed sensing (CS), CS has been applied to random channel access so that sparse signal can be transmitted efficiently when multiple wireless channel access exists.
Frame length control has been widely applied to traditional communication system to improve their performance. However, most of the existing research using the data transmission efficiency oriented approach can not adapt to situation of Internet of Thing (IoT), where quality of received information is more important In this paper, based on our former work where compressive sensing is applied to facilitate...
In this work, compressive sensing (CS) is applied to facilitate efficient wireless information transmission over lossy communication links. Inherently sparse data packets are transmitted without compression or error protection. The packet loss during transmission is modeled as a random sampling process of the transmitted data. The original signal then is reconstructed based on correctly received data...
Compressive sensing (CS) is applied to sparse signal transmission so that it can be transmitted efficiently over lossy wireless links. By exploiting the commonly sparse property of measured signal within wireless sensor networks (WSNs), we propose a CS-reconstruction based efficient information transmission framework. According to CS theory, if the sensed information has some sparsity, it can be reconstructed...
High sampling rate signal acquisition is challenging for wireless platform in terms of energy supply and transmission delay. Instead of performing compression at sensor node or having in-network processing for data been sampled at Nyquist rate, Compressive Sensing (CS) is applied to enable real time wireless sensor network with strict energy and processing constraints by significantly reducing the...
We present AWSAN, a adjustable wireless sensor array network based target monitoring system. It is universal for different scenarios and convenient for deploymen- t. A compressed sampling scheme is introduced to greatly reduce the data exchange volume, moving most processing load to fusion center. It provides similar performance to the traditional wireless or fixed array while using low-cost &...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.