Fuzzy C-Means Clustering-Based Jamming Detection Algorithm at Base Station

Jamming is defined as the act of intentionally directing electromagnetic energy towards a communication system to disrupt or prevent signal transmission. Jamming represents the most serious security threat in the field of wireless cellular networks (WCN), as it can easily put out of order even WCNs that utilize strong high-layer security mechanisms. In this paper, a fuzzy c-means algorithm is proposed for clustering the jammed signals at the base station in WCNs. The jamming detection process itself uses an improved LCR-based Doppler shift estimation algorithm using only inherent information which is available in common receivers without any excessive hardware requirements. The estimation of channel Doppler shift at base station in cellular networks helps base stations in channel estimation, which effectively improves jamming detection performance. The performance of the proposed algorithms in a TETRA network is modeled and compared with conventional methods, and simulation shows acceptable results in a wide range of user terminal velocities.