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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...
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 &...
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