32 research outputs found
Exploiting Lack of Hardware Reciprocity for Sender-Node Authentication at the PHY Layer
This paper proposes to exploit the so-called reciprocity
parameters (modelling non-reciprocal communication
hardware) to use them as decision metric for binary hypothesis
testing based authentication framework at a receiver node Bob.
Specifically, Bob first learns the reciprocity parameters of the
legitimate sender Alice via initial training. Then, during the test
phase, Bob first obtains a measurement of reciprocity parameters
of channel occupier (Alice, or, the intruder Eve). Then, with
ground truth and current measurement both in hand, Bob
carries out the hypothesis testing to automatically accept (reject)
the packets sent by Alice (Eve). For the proposed scheme, we
provide its success rate (the detection probability of Eve), and
its performance comparison with other schemes
Distributed Beamforming with Wirelessly Powered Relay Nodes
This paper studies a system where a set of relay nodes harvest energy
from the signal received from a source to later utilize it when forwarding the
source's data to a destination node via distributed beamforming. To this end,
we derive (approximate) analytical expressions for the mean SNR at destination
node when relays employ: i) time-switching based energy harvesting policy, ii)
power-splitting based energy harvesting policy. The obtained results facilitate
the study of the interplay between the energy harvesting parameters and the
synchronization error, and their combined impact on mean SNR. Simulation
results indicate that i) the derived approximate expressions are very accurate
even for small (e.g., ), ii) time-switching policy by the relays
outperforms power-splitting policy by at least dB.Comment: 4 pages, 3 figures, accepted for presentation at IEEE VTC 2017 Spring
conferenc
Coordination and Antenna Domain Formation in Cloud-RAN systems
We study here the problem of Antenna Domain Formation (ADF) in cloud RAN
systems, whereby multiple remote radio-heads (RRHs) are each to be assigned to
a set of antenna domains (ADs), such that the total interference between the
ADs is minimized. We formulate the corresponding optimization problem, by
introducing the concept of \emph{interference coupling coefficients} among
pairs of radio-heads. We then propose a low-overhead algorithm that allows the
problem to be solved in a distributed fashion, among the aggregation nodes
(ANs), and establish basic convergence results. Moreover, we also propose a
simple relaxation to the problem, thus enabling us to characterize its maximum
performance. We follow a layered coordination structure: after the ADs are
formed, radio-heads are clustered to perform coordinated beamforming using the
well known Weighted-MMSE algorithm. Finally, our simulations show that using
the proposed ADF mechanism would significantly increase the sum-rate of the
system (with respect to random assignment of radio-heads).Comment: 7 pages, IEEE International Conference on Communications 2016 (ICC
2016
Modulation mode detection and classification for in-vivo nano-scale communication systems operating in terahertz band
This paper initiates the efforts to design an intelligent/cognitive nano receiver operating in terahertz band. Specifically, we investigate two essential ingredients of an intelligent nano receiverâmodulation mode detection (to differentiate between pulse-based modulation and carrier-based modulation) and modulation classification (to identify the exact modulation scheme in use). To implement modulation mode detection, we construct a binary hypothesis test in nano-receiverâs passband and provide closed-form expressions for the two error probabilities. As for modulation classification, we aim to represent the received signal of interest by a Gaussian mixture model (GMM). This necessitates the explicit estimation of the THz channel impulse response and its subsequent compensation (via deconvolution). We then learn the GMM parameters via expectationâmaximization algorithm. We then do Gaussian approximation of each mixture density to compute symmetric KullbackâLeibler divergence in order to differentiate between various modulation schemes (i.e., -ary phase shift keying and -ary quadrature amplitude modulation). The simulation results on mode detection indicate that there exists a unique Pareto-optimal point (for both SNR and the decision threshold), where both error probabilities are minimized. The main takeaway message by the simulation results on modulation classification is that for a pre-specified probability of correct classification, higher SNR is required to correctly identify a higher order modulation scheme. On a broader note, this paper should trigger the interest of the community in the design of intelligent/cognitive nano receivers (capable of performing various intelligent tasks, e.g., modulation prediction, and so on)
On the Downlink Coverage Performance of RIS-Assisted THz Networks
This letter provides a stochastic geometry (SG)-based coverage probability
(CP) analysis of an indoor terahertz (THz) downlink assisted by a single
reconfigurable intelligent surface (RIS) panel. Specifically, multiple access
points (AP) deployed on the ceiling of a hall (each equipped with multiple
antennas) need to serve multiple user equipment (UE) nodes. Due to presence of
blockages, a typical UE may either get served via a direct link, the RIS, or
both links (the composite link). The locations of the APs and blockages are
modelled as a Poisson point process (PPP) and SG framework is utilized to
compute the CP, at a reference UE for all the three scenarios. Monte-Carlo
simulation results validate our theoretical analysis.Comment: Extended Arxiv version of submitted paper to IEEE Communications
Letter
Channel Impulse Response-based Physical Layer Authentication in a Diffusion-based Molecular Communication System
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 Alice's 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
Channel impulse response-based source localization in a diffusion-based molecular communication system
Molecular source localization finds its applications in future healthcare systems, including proactive diagnostics. This work localizes a molecular source in a diffusion based molecular communication (DbMC) system via a minimal set of passive anchor nodes and a fusion center. Two methods are presented which both utilize (the peak of) the channel impulse response measurements to uniquely localize the source, under the assumption that the molecular source of interest lies within the open convexâhull of the sensor/anchor nodes. The first method is a oneâshot, triangulationâbased approach which estimates the unknown location of the molecular source using leastâsquares method. The second method is an iterative approach, which utilizes the gradientâdescent control law to minimize a nonâconvex cost function. The corresponding CramerâRao bound (CRB) is also derived. Simulation results reveal that: i) the gradientâdescent method outperforms the triangulation method (in terms of mean squared error performance) for a wide range of values of signalâtoânoise ratio; ii) the gradientâdescent method converges to the true source location uniformly (in less than hundred iterations)