Abstract:

In the cognitive internet of things (CIoT), due to the non-cooperative characteristics between the primary user (PU) and the secondary user (SU), it is unreliable to seek the spectrum access opportunity by merely relying on traditional spectrum sensing technology.As an important type of auxiliary information, the mutual location information between PU and SU can assist in determining the possibility of secondary access to the licensed frequency band (LFB).A low-complexity neighbor-based weighted centroid localization (NB-WCL) algorithm was proposed to solve the localization problem of SUs in CIoT, so as to complete the decision of whether spectrum access can be performed at each geographical location in CIoT.The root mean square root error (RMSE) performance of two-dimensional position estimation was analyzed and the impacts of factors were verified such as communication radius, node density, shadowing influence, path loss exponent, connectivity metric, and the number of data transmitted on the algorithm performance in simulations.The theoretical derivation and experimental results show that the proposed scheme provides more robust and better localization error performance for the SU localization algorithm in CIoT than the traditional localization algorithms, which can effectively enhance the reliability of CIoT for spectrum access.The proposed scheme can serve as a practically effective candidate solution in the CIoT.

Key words: weighted centroid localization, cognitive internet of things, neighbor relationship, performance analysis, spectrum access