Malicious relay node detection with unsupervised learning in amplify-forward cooperative networks

This paper presents malicious relay node detection in a cooperative network using unsupervised learning based on the received signal samples over the source to destination (S-D) link at the destination node. We consider the situations in which possible maliciousness of the relay is the regenerative, injection or garbling type attacks over the source signal according to attack modeling in the communication. The proposed approach here for such an attack detection problem is to apply unsupervised machine learning using one-class classifier (OCC) algorithms. Among the algorithms compared, One-Class Support Vector Machines (OSVM) with kernel radial basis function (RBF) has the largest accuracy performance in detecting malicious node attacks with certain types and also detect trustable relay by using specific features of the symbol constellation of the received signal. Results show that we can achieve detection accuracy about 99% with SVM-RBF and k-NN learning algorithms for garbling type relay attacks. The results also encourage that OCC algorithms considered in this study with different feature selections could be effective in detecting other types of relay attacks

A New Handover Management Model for Two-Tier 5G Mobile Networks

There has been an exponential rise in mobile data traffic in recent times due to the increasing popularity of portable devices like tablets, smartphones, and laptops. The rapid rise in the use of these portable devices has put extreme stress on the network service providers while forcing telecommunication engineers to look for innovative solutions to meet the increased demand. One solution to the problem is the emergence of fifth-generation (5G) wireless communication, which can address the challenges by offering very broad wireless area capacity and potential cut-power consumption. The application of small cells is the fundamental mechanism for the 5G technology. The use of small cells can enhance the facility for higher capacity and reuse. However, it must be noted that small cells deployment will lead to frequent handovers of mobile nodes. Considering the importance of small cells in 5G, this paper aims to examine a new resource management scheme that can work to minimize the rate of handovers for mobile phones through careful resources allocation in a two-tier network. Therefore, the resource management problem has been formulated as an optimization issue that we aim to overcome through an optimal solution. To find a solution to the existing problem of frequent handovers, a heuristic approach has been used. This solution is then evaluated and validated through simulation and testing, during which the performance was noted to improve by 12% in the context of handover costs. Therefore, this model has been observed to be more efficient as compared to the existing model

Target localization in wireless sensor networks for industrial control with selected sensors

This paper presents a novel energy-based target localization method in wireless sensor networks with selected sensors. In this method, sensors use Turbo Product Code (TPC) to transmit decisions to the fusion center. TPC can reduce bit error probability if communication channel errors exist. Moreover, in this method, thresholds for the energy-based target localization are designed using a heuristic method. This design method to find thresholds is suitable for uniformly distributed sensors and normally distributed targets. Furthermore, to save sensor energy, a sensor selection method is also presented. Simulation results showed that if sensors used TPC instead of Hamming code to transmit decisions to the fusion center, localization performance could be improved. Furthermore, the sensor selection method used can substantially reduce energy consumption for our target localization method. At the same time, this target localization method with selected sensors also provides satisfactory localization performance

Interference Mitigation Framework for Cellular Mobile Radio Networks

For today's cellular mobile communication networks, the needed capacity is hard to realize without much more of (expensive) bandwidth. Thus new standards like LTE were developed. LTE advanced is in discussion as the successor of LTE and cooperative multipoint transmission (CoMP) is one of the hot topics to increase the system's capacity. System simulations often show only weak gains of the signal-to-interference ratio due to high interference from noncooperating cells in the downlink. This paper presents an interference mitigation framework to overcome the hardest issue, that is, the low penetration rate of mobile stations that can be served from a cluster composed of their strongest cells in the network. The results obtained from simulation tools are discussed with values resulting from testbed on the TU Dresden. They show that the theoretical ideas can be transferred into gains on real systems

Physical detection of misbehavior in relay systems with unreliable channel state information

We study the detection 1 of misbehavior in a Gaussian relay system, where the source transmits information to the destination with the assistance of an amplify-and-forward relay node subject to unreliable channel state information (CSI). The relay node may be potentially malicious and corrupt the network by forwarding garbled information. In this situation, misleading feedback may take place, since reliable CSI is unavailable at the source and/or the destination. By classifying the action of the relay as detectable or undetectable, we propose a novel approach that is capable of coping with any malicious attack detected and continuing to work effectively in the presence of unreliable CSI. We demonstrate that the detectable class of attacks can be successfully detected with a high probability. Meanwhile, the undetectable class of attacks does not affect the performance improvements that are achievable by cooperative diversity, even though such an attack may fool the proposed detection approach. We also extend the method to deal with the case in which there is no direct link between the source and the destination. The effectiveness of the proposed approach has been validated by numerical results