126,261 research outputs found
Cooperative Radar and Communications Signaling: The Estimation and Information Theory Odd Couple
We investigate cooperative radar and communications signaling. While each
system typically considers the other system a source of interference, by
considering the radar and communications operations to be a single joint
system, the performance of both systems can, under certain conditions, be
improved by the existence of the other. As an initial demonstration, we focus
on the radar as relay scenario and present an approach denoted multiuser
detection radar (MUDR). A novel joint estimation and information theoretic
bound formulation is constructed for a receiver that observes communications
and radar return in the same frequency allocation. The joint performance bound
is presented in terms of the communication rate and the estimation rate of the
system.Comment: 6 pages, 2 figures, to be presented at 2014 IEEE Radar Conferenc
Towards Dual-functional Radar-Communication Systems: Optimal Waveform Design
We focus on a dual-functional multi-input-multi-output (MIMO)
radar-communication (RadCom) system, where a single transmitter communicates
with downlink cellular users and detects radar targets simultaneously. Several
design criteria are considered for minimizing the downlink multi-user
interference. First, we consider both the omnidirectional and directional
beampattern design problems, where the closed-form globally optimal solutions
are obtained. Based on these waveforms, we further consider a weighted
optimization to enable a flexible trade-off between radar and communications
performance and introduce a low-complexity algorithm. The computational costs
of the above three designs are shown to be similar to the conventional
zero-forcing (ZF) precoding. Moreover, to address the more practical constant
modulus waveform design problem, we propose a branch-and-bound algorithm that
obtains a globally optimal solution and derive its worst-case complexity as a
function of the maximum iteration number. Finally, we assess the effectiveness
of the proposed waveform design approaches by numerical results.Comment: 13 pages, 10 figures. This work has been submitted to the IEEE for
possible publication. Copyright may be transferred without notice, after
which this version may no longer be accessibl
MU-MIMO Communications with MIMO Radar: From Co-existence to Joint Transmission
Beamforming techniques are proposed for a joint multi-input-multi-output
(MIMO) radar-communication (RadCom) system, where a single device acts both as
a radar and a communication base station (BS) by simultaneously communicating
with downlink users and detecting radar targets. Two operational options are
considered, where we first split the antennas into two groups, one for radar
and the other for communication. Under this deployment, the radar signal is
designed to fall into the null-space of the downlink channel. The communication
beamformer is optimized such that the beampattern obtained matches the radar's
beampattern while satisfying the communication performance requirements. To
reduce the optimizations' constraints, we consider a second operational option,
where all the antennas transmit a joint waveform that is shared by both radar
and communications. In this case, we formulate an appropriate probing
beampattern, while guaranteeing the performance of the downlink communications.
By incorporating the SINR constraints into objective functions as penalty
terms, we further simplify the original beamforming designs to weighted
optimizations, and solve them by efficient manifold algorithms. Numerical
results show that the shared deployment outperforms the separated case
significantly, and the proposed weighted optimizations achieve a similar
performance to the original optimizations, despite their significantly lower
computational complexity.Comment: 15 pages, 15 figures. This work has been submitted to the IEEE for
possible publication. Copyright may be transferred without notice, after
which this version may no longer be accessibl
Coexistence Analysis between Radar and Cellular System in LoS Channel
Sharing spectrum with incumbents such as radar systems is an attractive
solution for cellular operators in order to meet the ever growing bandwidth
requirements and ease the spectrum crunch problem. In order to realize
efficient spectrum sharing, interference mitigation techniques are required. In
this letter we address techniques to mitigate MIMO radar interference at MIMO
cellular base stations (BSs). We specifically look at the amount of power
received at BSs when radar uses null space projection (NSP)-based interference
mitigation method. NSP reduces the amount of projected power at targets that
are in-close vicinity to BSs. We study this issue and show that this can be
avoided if radar employs a larger transmit array. In addition, we compute the
coherence time of channel between radar and BSs and show that the coherence
time of channel is much larger than the pulse repetition interval of radars.
Therefore, NSP-based interference mitigation techniques which depends on
accurate channel state information (CSI) can be effective as the problem of CSI
being outdated does not occur for most practical scenarios.Comment: Corrected some typos and reference
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
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