Jamming attack is a serious security threat in wireless sensor networks. Therefore, it is important to frame a mechanism to protect wireless sensor networks from various jamming attacks. Jammer intrusion detection and jamming detection are two separate issues. In this paper, a novel jammer detection framework to detect the intrusion of jammer and the presence of jamming in a cluster-based wireless sensor network is proposed. The proposed framework is novel in three aspects: whenever the cluster head receives a packet, it first verifies whether the source node is a legitimate, new node, or a jammer node. Second, when the source node is declared as a new one in the first step, then the framework validates whether the new node is legitimate node in the previous cluster or a jammer node by using cluster head code. Third, the framework observes the behavior of the newly joined node and the existing nodes to identify whether the nodes in the cluster is jammed or not. Additionally, it also classifies the types of jamming, if the presence of jamming is detected. Simulation result shows that the proposed framework performs extremely well and achieves jamming detection rate as high as 99.88 %.

Summary In this paper, a fuzzy logic–based jamming detection algorithm (FLJDA) is proposed to detect the presence of jamming in downstream data communication for cluster‐based wireless sensor networks. The proposed FLJDA keeps an eye on the existing nodes and new node to determine their behavior by applying fuzzy logic on measured jamming detection metrics. To monitor the behavior of the nodes, the FLJDA computes the jamming detection metrics, namely, packet delivery ratio and received signal strength indicator. The major features of this paper are the following: (1) The jamming detection algorithm is specifically implemented for downstream data communication, (2) cluster head estimates jamming detection metrics for detecting the jamming unlike the existing algorithms where individual nodes explicitly collect the jamming detection metrics, and (3) the proposed algorithm optimizes the jamming detection metrics on the basis of fuzzy logic unlike the existing approaches, which uses merely jamming detection threshold alone for jamming detection. The simulation results of the proposed system provide the true detection ratio as high as 99.89%.

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SUMMARYSingle-carrier frequency division multiple access is greatly sensitive to carrier frequency offset (CFO) between transceivers. This leads to the destruction of orthogonality among subcarriers, which in turn leads to intercarrier interference and multiple access interference between different users. Minimum mean square error (MMSE) equalizer that uses an inverse operation on an interference matrix with a dimension equal to the number of subcarriers is normally used to invalidate CFO effects. Hence, the terminal processing complexity is very high. The proposed conjugate gradient method attempts to mitigate the higher computational complexity by iteratively evaluating the MMSE solution without direct matrix inverse operation. To further mitigate the multiple access interference, MMSE combined with parallel interference cancellation is also implemented. The analysis of the proposed method shows better performance and fast convergence in single-carrier frequency division multiple access systems. The maximum iteration number to formulate an accurate solution is almost equal to the number of active users in the uplink access. Simulation results bring out the effectiveness of the present method compared with the existing CFO compensation schemes in terms of computational complication and system performance with large frequency offsets.

Single-carrier frequency division multiple access (SC-FDMA) systems with space frequency block coding (SFBC) transmissions achieve both spatial and frequency diversity gains in wireless communications. However, SFBC SC-FDMA schemes using linear detectors suffer from severe performance deterioration because of noise enhancement propagation and additive noise presence in the detected output. Both issues are similar to inter-symbol-interference (ISI). Traditionally, SC-FDMA system decision feedback equalizer (DFE) is often used to eliminate ISI caused by multipath propagation. This article proposes frequency domain turbo equalization based on nonlinear multiuser detection for uplink SFBC SC-FDMA transmission systems. The presented iterative receiver performs equalization with soft decisions feedback for ISI mitigation. Its coefficients are derived using minimum mean squared error criteria. The receiver configuration study is Alamouti's SFBC with two transmit and two receive antennas. New receiver approach is compared with the recently proposed suboptimal linear detector for SFBC SC-FDMA systems. Simulation results confirm that the performance of the proposed iterative detection outperforms conventional detection techniques. After a few iterations, bit-error-rate performance of the proposed receiver design is closely to the matched filter bound.