1,308 research outputs found
Target Estimation in Colocated MIMO Radar via Matrix Completion
We consider a colocated MIMO radar scenario, in which the receive antennas
forward their measurements to a fusion center. Based on the received data, the
fusion center formulates a matrix which is then used for target parameter
estimation. When the receive antennas sample the target returns at Nyquist
rate, and assuming that there are more receive antennas than targets, the data
matrix at the fusion center is low-rank. When each receive antenna sends to the
fusion center only a small number of samples, along with the sample index, the
receive data matrix has missing elements, corresponding to the samples that
were not forwarded. Under certain conditions, matrix completion techniques can
be applied to recover the full receive data matrix, which can then be used in
conjunction with array processing techniques, e.g., MUSIC, to obtain target
information. Numerical results indicate that good target recovery can be
achieved with occupancy of the receive data matrix as low as 50%.Comment: 5 pages, ICASSP 201
Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays
Massive MIMO (multiple-input multiple-output) is no longer a "wild" or
"promising" concept for future cellular networks - in 2018 it became a reality.
Base stations (BSs) with 64 fully digital transceiver chains were commercially
deployed in several countries, the key ingredients of Massive MIMO have made it
into the 5G standard, the signal processing methods required to achieve
unprecedented spectral efficiency have been developed, and the limitation due
to pilot contamination has been resolved. Even the development of fully digital
Massive MIMO arrays for mmWave frequencies - once viewed prohibitively
complicated and costly - is well underway. In a few years, Massive MIMO with
fully digital transceivers will be a mainstream feature at both sub-6 GHz and
mmWave frequencies. In this paper, we explain how the first chapter of the
Massive MIMO research saga has come to an end, while the story has just begun.
The coming wide-scale deployment of BSs with massive antenna arrays opens the
door to a brand new world where spatial processing capabilities are
omnipresent. In addition to mobile broadband services, the antennas can be used
for other communication applications, such as low-power machine-type or
ultra-reliable communications, as well as non-communication applications such
as radar, sensing and positioning. We outline five new Massive MIMO related
research directions: Extremely large aperture arrays, Holographic Massive MIMO,
Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive
MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin
Target Localization Accuracy Gain in MIMO Radar Based Systems
This paper presents an analysis of target localization accuracy, attainable
by the use of MIMO (Multiple-Input Multiple-Output) radar systems, configured
with multiple transmit and receive sensors, widely distributed over a given
area. The Cramer-Rao lower bound (CRLB) for target localization accuracy is
developed for both coherent and non-coherent processing. Coherent processing
requires a common phase reference for all transmit and receive sensors. The
CRLB is shown to be inversely proportional to the signal effective bandwidth in
the non-coherent case, but is approximately inversely proportional to the
carrier frequency in the coherent case. We further prove that optimization over
the sensors' positions lowers the CRLB by a factor equal to the product of the
number of transmitting and receiving sensors. The best linear unbiased
estimator (BLUE) is derived for the MIMO target localization problem. The
BLUE's utility is in providing a closed form localization estimate that
facilitates the analysis of the relations between sensors locations, target
location, and localization accuracy. Geometric dilution of precision (GDOP)
contours are used to map the relative performance accuracy for a given layout
of radars over a given geographic area.Comment: 36 pages, 5 figures, submitted to IEEE Transaction on Information
Theor
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
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