1,802 research outputs found
Adaptive Interference Removal for Un-coordinated Radar/Communication Co-existence
Most existing approaches to co-existing communication/radar systems assume
that the radar and communication systems are coordinated, i.e., they share
information, such as relative position, transmitted waveforms and channel
state. In this paper, we consider an un-coordinated scenario where a
communication receiver is to operate in the presence of a number of radars, of
which only a sub-set may be active, which poses the problem of estimating the
active waveforms and the relevant parameters thereof, so as to cancel them
prior to demodulation. Two algorithms are proposed for such a joint waveform
estimation/data demodulation problem, both exploiting sparsity of a proper
representation of the interference and of the vector containing the errors of
the data block, so as to implement an iterative joint interference removal/data
demodulation process. The former algorithm is based on classical on-grid
compressed sensing (CS), while the latter forces an atomic norm (AN)
constraint: in both cases the radar parameters and the communication
demodulation errors can be estimated by solving a convex problem. We also
propose a way to improve the efficiency of the AN-based algorithm. The
performance of these algorithms are demonstrated through extensive simulations,
taking into account a variety of conditions concerning both the interferers and
the respective channel states
Joint Design of Overlaid Communication Systems and Pulsed Radars
The focus of this paper is on co-existence between a communication system and
a pulsed radar sharing the same bandwidth. Based on the fact that the
interference generated by the radar onto the communication receiver is
intermittent and depends on the density of scattering objects (such as, e.g.,
targets), we first show that the communication system is equivalent to a set of
independent parallel channels, whereby pre-coding on each channel can be
introduced as a new degree of freedom. We introduce a new figure of merit,
named the {\em compound rate}, which is a convex combination of rates with and
without interference, to be optimized under constraints concerning the
signal-to-interference-plus-noise ratio (including {\em signal-dependent}
interference due to clutter) experienced by the radar and obviously the powers
emitted by the two systems: the degrees of freedom are the radar waveform and
the afore-mentioned encoding matrix for the communication symbols. We provide
closed-form solutions for the optimum transmit policies for both systems under
two basic models for the scattering produced by the radar onto the
communication receiver, and account for possible correlation of the
signal-independent fraction of the interference impinging on the radar. We also
discuss the region of the achievable communication rates with and without
interference. A thorough performance assessment shows the potentials and the
limitations of the proposed co-existing architecture
Privacy Protection Performance of De-identified Face Images with and without Background
Li Meng, 'Privacy Protection Performance of De-identified Face Images with and without Background', paper presented at the 39th International Information and Communication Technology (ICT) Convention. Grand Hotel Adriatic Congress Centre and Admiral Hotel, Opatija, Croatia, May 30 - June 3, 2016.This paper presents an approach to blending a de-identified face region with its original background, for the purpose of completing the process of face de-identification. The re-identification risk of the de-identified FERET face images has been evaluated for the k-Diff-furthest face de-identification method, using several face recognition benchmark methods including PCA, LBP, HOG and LPQ. The experimental results show that the k-Diff-furthest face de-identification delivers high privacy protection within the face region while blending the de-identified face region with its original background may significantly increases the re-identification risk, indicating that de-identification must also be applied to image areas beyond the face region
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