Energy-efficiency performance of wireless cognitive radio sensor network with hard-decision fusion over generalized α-μ fading channels.

In order to address the issue of spectrum scarcity, cognitive radio (CR) offers an effective usage of radio spectrum resources by offering dynamic spectrum access. One kind of wireless sensor networks having CR capabilities are wireless cognitive radio sensor networks (WCRSNs). The present work investigates throughput and energy-efficiency of WCRSN. More precisely, scenarios involving both noise and α - μ fading that affect the sensing (S) channels are taken into consideration. Each cognitive radio sensor (CRS) receives an unknown licensed signal information from the primary user (PU). The CRS uses an energy detection sensing technique and makes a local decision in one-bit binary form. The decisions from all the CRSs are forwarded to control center via reporting (R) channels and are combined based on the hard-decision fusion technique for making the final decision about active and inactive status of the PU. Throughput and energy-efficiency performances of WCRSN are assessed while taking into account the effects of pertinent network factors. To that end, first a brand-new mathematical probability of detection that is subject to noise plus generalized α - μ fading is established. Additionally, a computer based simulation and experimental setup are performed to verify the resulting expression. The analytical frameworks for assessing throughput and energy-efficiency performances under a variety of network and channel situations are then developed. Further, the effect of inaccurate S and R channels with channel error probability (q) on the general effectiveness of WCRSN is also examined. Finally, the effects of the α - μ fading parameters, the signal-to-noise ratio, the number of CRSs, and the detection threshold on the WCRSN are examined. For a number of network characteristics, throughput is maximized and energy-efficiency is up to 75% has been achieved. [ABSTRACT FROM AUTHOR]