An Energy-Efficient Combination of Sleeping Schedule and Cognitive Radio in Wireless Sensor Networks Utilizing Compressed Sensing

Conventional wireless sensor networks (WSNs) have been well exploited with many applications and also numerous techniques for improvements. Recently WSNs employ muti-media services that require more resources including frequency bandwidth and transmission rate. This encourages more exploration to support the networks to approach the increasing demand in quality of service. This paper shows an investigation to combine some techniques to meet some requirements. Cognitive radio (CR) have been known to use frequency band effectively. Compressed sensing (CS) applied in WSNs reduces the data transmission in the networks. Sleeping schedules for sensor nodes in such networks are also considered to save energy while still provide enough data needed. This work is a combination that provide analysis of network models, simulation results and shows promise for future WSNs.