Improvement Of Compressed Sensing Algorithm And Its Application In The Wireless Sensornetwork

Wireless sensor network combines sensing, wireless communication, embedded systems and other related technology, under a variety of scenarios, with data acquisition and processing by the sensor node terminal for a wide range of reliable and detailed information. Compressed Sensing can discard "redundant" information of sparse or compressible signal, reducing the signal sampling frequency, save storage and transport costs, provides a new wireless sensor network communication, data collection, location and other issues technology solutions. In this paper, compressed sensing is studied in adaptive communications and localization in the virtual MIMO wireless sensor networks to improve communication performance and node localization accuracy of wireless sensor network.First, this paper provides an overview of the compressed sensing, and several commonly used compressed sensing reconstruction algorithm is described in detail. Traditional compressed sensing algorithm has some shortcomings: high complexity, slow convergence, reconstruction precision. On the foundation of compressed sensing, on the use of steep hyperbolic tangent function to optimize the approximation function of Smoothed(SL0) reconstruction algorithm, and with hybrid optimization direction for optimization, so that an improved SL0 compressed sensing algorithm is posed.Second, the improved compressed sensing reconstruction algorithm is applied in channel state information feedback of adaptive virtual MIMO wireless sensor communication network, reducing the amount of channel state information feedback, channel overhead and the rate of channel feedback, at the same time increasing the maximum total speed of system and accuracy of the feedback information, thus improving network performance, thereby providing good communications support for the wireless sensor network localization.Finally, under the premise of ensuring accurate communication premise in the wireless sensor network communication system, we combines improved compressed sensing algorithm with RSS measurement and constructs compressed sensing sensor matrix by RSS, to improve the real-time, precision and noise immunity of localization meanwhile enhance the precision and rapidity in wireless sensor network multi-target localization.