Opportunistic spectrum analytics and enhanced channel selection algorithm in multi channel cognitive radio networks

Abstract

The rapid rise of mobile devices in the Internet of Things (IoT) epoch, accompanies the proliferation of the use of wireless services to a greater extent. Spectrum allocation for such mobile devices mainly in the ISM band makes it difficult to deploy real-time applications. Currently, Cognitive Radio Network (CRN) is the guaranteeing technology that renders data transmission over the licensed spectrum bands and within the ISM frequency range. The dynamic spectrum access mechanism enables the unlicensed secondary users (SUs) to access wireless channel bands that were initially licensed to primary users (PUs) ensuring the policy of hindrance. Despite the heterogeneous nature of the network, co-existence between PUs and SUs remain unconventional since it may change the quality requirements of the channel. Discovering the availability of spectrum with the help of spectrum sensing techniques assists the SUs to acquire a channel for transmission. The SUs performance is evaluated and analyzed while considering reasonable issues such as Signal to Noise Ratio (SNR), PUs detection and its protection against SUs interference. Sensing of PUs presence and acquiring of the channel could be accomplished opportunistically on enhancing the traditional single radio channel access to a dual channel or multi-channel access. A Cooperative Spectrum sensing algorithm which incorporates two radio channel access scheme, namely Channel Acquiring and Detection protocol (CADP) has been proposed in this research. newline