The energy efficiency optimization based on dynamic spectrum sensing and nodes scheduling in cognitive radio sensor networks

Abstract

Cognitive ratio (CR) makes nodes in cognitive ratio network are enable to adjust work parameter according to operating environment and access idle licensed spectrum dynamically without causing significant interference to primary users transmission [1]. Spectrum sensing as an important function of cognitive ratio technology is used for detecting the status of unused authorized spectrum owed by primary users (PU) [2]. However, when channels suffer multipath fading or shadowing, the performance of detection will decrease [3][4]. Besides sensing results from a single node may not be sufficient reliable to decide the state of a PU [5]. Cooperative spectrum sensing techniques can improve the cognitive radio network performance by enhancing spectrum efficiency and spectrum reliability by effectively combating the destructive effects present in the cognitive ratio sensor network (CRSN) environment at the cost of comprises in overhead traffic, power consumption, and complexity and control channels [6] .Because of the static spectrum allocation policy reduce cooperative spectrum sensing overheads is important to enhance spectral efficiency (SE). In [7], a distributed wide band sensing scheme for CRSN is presented, it assumes sparse use of spectrum, which is contrary to the current status of wireless spectrum. Wireless sensor devices are irreplaceable battery powered, reducing energy consumption and enhancing energy efficiency (EE) is also important to prolong network lifetime. In [8], a spectrum sensing scheme which aims to minimize energy consumption due to spectrum sensing is proposed. the proposed scheme is not practical Abstract: Nowadays, cognitive radio sensor networks are facing the inherent energy constraint and spectrum resource scarce problems. Hence in this paper, novel spectrum sensing and nodes selection methods are investigated to jointly optimize the energy and spectrum efficiency. Firstly, to shorten sensing time and save unnecessary spectrum sensing energy, a dynamic censored spectrum sensing scheme is employed to decide when to stop sensing. Then a priority-based sensor node scheduling algorithm in cooperative spectrum sensing is proposed to balance the trade-off between energy efficiency and spectral efficiency. Through mapping discrete parameters into continues real domains, we could decide which nodes are selected for spectrum sensing at an lower complexity. Simulation results demonstrate that significant energy and spectral efficiency could be achieved through the proposed methods.