Jamming of Wireless Localization Systems

Abstract

Abstract-In this paper, the optimal jamming of wireless localization systems is investigated. Two optimal power allocation schemes are proposed for jammer nodes in the presence of total and peak power constraints. In the first scheme, power is allocated to jammer nodes in order to maximize the average Cramér-Rao lower bound (CRLB) of target nodes, whereas in the second scheme, the power allocation is performed for the aim of maximizing the minimum CRLB of target nodes. Both the schemes are formulated as linear programs, and a closed-form solution is obtained for the first scheme. For the second scheme, under certain conditions, the property of full total power utilization is specified, and a closed-form solution is obtained when the total power is lower than a specific threshold. In addition, it is shown that non-zero power is allocated to at most N T jammer nodes according to the second scheme in the absence of peak power constraints, where N T is the number of target nodes. In the presence of parameter uncertainty, robust versions of the power allocation schemes are proposed. Simulation results are presented to investigate the performance of the proposed schemes and to illustrate the theoretical results.

Power Control Games Between Anchor and Jammer Nodes in Wireless Localization Networks

“…Contrary to the anchor nodes, the aim of the jammer nodes is to reduce the localization performance of the target nodes. In accordance with the common approach in the literature [11], [23]- [25], it is assumed that the jammer nodes transmit zero-mean white Gaussian noise in order to distort the signals observed by the target nodes. The reasons behind the use of a Gaussian noise model can be explained as follows: In wireless localization systems, when the knowledge of the ranging signals sent from the anchor nodes to the target nodes is unavailable to the jammer nodes, the jammer nodes can continuously transmit noise to degrade the localization performance of the target nodes [11].…”

“…In accordance with the common approach in the literature [11], [23]- [25], it is assumed that the jammer nodes transmit zero-mean white Gaussian noise in order to distort the signals observed by the target nodes. The reasons behind the use of a Gaussian noise model can be explained as follows: In wireless localization systems, when the knowledge of the ranging signals sent from the anchor nodes to the target nodes is unavailable to the jammer nodes, the jammer nodes can continuously transmit noise to degrade the localization performance of the target nodes [11]. In the literature, it is shown that the Gaussian noise is the worst-case noise for generic wireless networks modeled with additive noise that is independent of the transmit signals [26]- [28].…”

“…(In particular, the Gaussian distribution corresponds to the worst-case scenario among all possible noise distributions in terms of some metrics such as the mutual information and the mean squared error since it minimizes the mutual information between the input and the output when the input is Gaussian, and maximizes the mean squared error of estimating the input given the output for an additive noise channel with a Gaussian input [29].) Therefore, the jammer nodes are expected to transmit Gaussian noise for efficient jamming [11]. Also, a non-cooperative localization scenario is considered; that is, the target nodes do not receive any signals from each other for localization purposes.…”

“…Since a signal traveling from an anchor node to a target node experiences multipath fading, shadowing, and path-loss, position estimates of target nodes are subject to errors and uncertainty. As the Cramér-Rao lower bound (CRLB) expresses a lower bound on the variance of any unbiased estimator for a deterministic parameter, it is also considered as a common performance metric for wireless localization networks [11]- [13].…”

“…Similarly, in [15], an adaptive GPS anti-jamming algorithm is proposed. In addition, the optimal power allocation problem is investigated for jammer nodes in a given wireless localization network based on the CRLB metric, and the optimal jamming strategies are obtained in the presence of peak power and total power constraints in [11].…”