18 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
Interference Removal for Radar/Communication Co-existence: the Random Scattering Case
In this paper we consider an un-cooperative spectrum sharing scenario,
wherein a radar system is to be overlaid to a pre-existing wireless
communication system. Given the order of magnitude of the transmitted powers in
play, we focus on the issue of interference mitigation at the communication
receiver. We explicitly account for the reverberation produced by the
(typically high-power) radar transmitter whose signal hits scattering centers
(whether targets or clutter) producing interference onto the communication
receiver, which is assumed to operate in an un-synchronized and un-coordinated
scenario. We first show that receiver design amounts to solving a non-convex
problem of joint interference removal and data demodulation: next, we introduce
two algorithms, both exploiting sparsity of a proper representation of the
interference and of the vector containing the errors of the data block. The
first algorithm is basically a relaxed constrained Atomic Norm minimization,
while the latter relies on a two-stage processing structure and is based on
alternating minimization. The merits of these algorithms are demonstrated
through extensive simulations: interestingly, the two-stage alternating
minimization algorithm turns out to achieve satisfactory performance with
moderate computational complexity