No Arabic abstract
In this preliminary work, we study the problem of {it distributed} authentication in wireless networks. Specifically, we consider a system where multiple Bob (sensor) nodes listen to a channel and report their {it correlated} measurements to a Fusion Center (FC) which makes the ultimate authentication decision. For the feature-based authentication at the FC, channel impulse response has been utilized as the device fingerprint. Additionally, the {it correlated} measurements by the Bob nodes allow us to invoke Compressed sensing to significantly reduce the reporting overhead to the FC. Numerical results show that: i) the detection performance of the FC is superior to that of a single Bob-node, ii) compressed sensing leads to at least $20%$ overhead reduction on the reporting channel at the expense of a small ($<1$ dB) SNR margin to achieve the same detection performance.
Consider impersonation attack by an active malicious nano node (Eve) on a diffusion based molecular communication (DbMC) system---Eve transmits during the idle slots to deceive the nano receiver (Bob) that she is indeed the legitimate nano transmitter (Alice). To this end, this work exploits the 3-dimensional (3D) channel impulse response (CIR) with $L$ taps as device fingerprint for authentication of the nano transmitter during each slot. Specifically, Bob utilizes the Alices CIR as ground truth to construct a binary hypothesis test to systematically accept/reject the data received in each slot. Simulation results highlight the great challenge posed by impersonation attack--i.e., it is not possible to simultaneously minimize the two error probabilities. In other words, one needs to tolerate on one error type in order to minimize the other error type.
A typical handover problem requires sequence of complex signaling between a UE, the serving, and target base station. In many handover problems the down link based measurements are transferred from a user equipment to a serving base station and the decision on handover is made on these measurements. These measurements together with the signaling between the user equipment and the serving base station is computationally expensive and can potentially drain user equipment battery. Coupled with this, the future networks are densely deployed with multiple frequency layers, rendering current handover mechanisms sub-optimal, necessitating newer methods that can improve energy efficiency. In this study, we will investigate a ML based approach towards secondary carrier prediction for inter-frequency handover using the up-link reference signals.
Using commodity WiFi data for applications such as indoor localization, object identification and tracking and channel sounding has recently gained considerable attention. We study the problem of channel impulse response (CIR) estimation from commodity WiFi channel state information (CSI). The accuracy of a CIR estimation method in this setup is limited by both the available channel bandwidth as well as various CSI distortions induced by the underlying hardware. We propose a multi-band splicing method that increases channel bandwidth by combining CSI data across multiple frequency bands. In order to compensate for the CSI distortions, we develop a per-band processing algorithm that is able to estimate the distortion parameters and remove them to yield the clean CSI. This algorithm incorporates the atomic norm denoising sparse recovery method to exploit channel sparsity. Splicing clean CSI over M frequency bands, we use orthogonal matching pursuit (OMP) as an estimation method to recover the sparse CIR with high (M-fold) resolution. Unlike previous works in the literature, our method does not appeal to any limiting assumption on the CIR (other than the widely accepted sparsity assumption) or any ad hoc processing for distortion removal. We show, empirically, that the proposed method outperforms the state of the art in terms of localization accuracy.
We present experimental data on message transmission in a free-space optical (FSO) link at an eye-safe wavelength, using a testbed consisting of one sender and two receiver terminals, where the latter two are a legitimate receiver and an eavesdropper. The testbed allows us to emulate a typical scenario of physical-layer (PHY) security such as satellite-to-ground laser communications. We estimate information-theoretic metrics including secrecy rate, secrecy outage probability, and expected code lengths for given secrecy criteria based on observed channel statistics. We then discuss operation principles of secure message transmission under realistic fading conditions, and provide a guideline on a multi-layer security architecture by combining PHY security and upper-layer (algorithmic) security.
This paper considers a scenario in which a source-destination pair needs to establish a confidential connection against an external eavesdropper, aided by the interference generated by another source-destination pair that exchanges public messages. The goal is to compute the maximum achievable secrecy degrees of freedom (S.D.o.F) region of a MIMO two-user wiretap network. First, a cooperative secrecy transmission scheme is proposed, whose feasible set is shown to achieve all S.D.o.F. pairs on the S.D.o.F. region boundary. In this way, the determination of the S.D.o.F. region is reduced to a problem of maximizing the S.D.o.F. pair over the proposed transmission scheme. The maximum achievable S.D.o.F. region boundary points are obtained in closed form, and the construction of the precoding matrices achieving the maximum S.D.o.F. region boundary is provided. The obtained analytical expressions clearly show the relation between the maximum achievable S.D.o.F. region and the number of antennas at each terminal.