857 research outputs found
MIMO Radar Waveform Optimization With Prior Information of the Extended Target and Clutter
The concept of multiple-input multiple-output (MIMO) radar allows each transmitting antenna element to transmit an arbitrary waveform. This provides extra degrees of freedom compared to the traditional transmit beamforming approach. It has been shown in the recent literature that MIMO radar systems have many advantages. In this paper, we consider the joint optimization of waveforms and receiving filters in the MIMO radar for the case of extended target in clutter. A novel iterative algorithm is proposed to optimize the waveforms and receiving filters such that the detection performance can be maximized. The corresponding iterative algorithms are also developed for the case where only the statistics or the uncertainty set of the target impulse response is available. These algorithms guarantee that the SINR performance improves in each iteration step. Numerical results show that the proposed methods have better SINR performance than existing design methods
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
Overlapped-MIMO Radar Waveform Design for Coexistence With Communication Systems
This paper explores an overlapped-multiple-input multiple-output (MIMO)
antenna architecture and a spectrum sharing algorithm via null space projection
(NSP) for radar-communications coexistence. In the overlapped-MIMO
architecture, the transmit array of a collocated MIMO radar is partitioned into
a number of subarrays that are allowed to overlap. Each of the antenna elements
in these subarrays have signals orthogonal to each other and to the elements of
the other subarrays. The proposed architecture not only improves sidelobe
suppression to reduce interference to communications system, but also enjoys
the advantages of MIMO radar without sacrificing the main desirable
characteristics. The radar-centric spectrum sharing algorithm then projects the
radar signal onto the null space of the communications system's interference
channel, which helps to avoid interference from the radar. Numerical results
are presented which show the performance of the proposed waveform design
algorithm in terms of overall beampattern and sidelobe levels of the radar
waveform and finally shows a comparison of the proposed system with existing
collocated MIMO radar architectures.Comment: accepted at IEEE WCN
Joint transmit and receive beamforming design in full-duplex integrated sensing and communications
Integrated sensing and communication (ISAC) has been envisioned as a solution to realize the sensing capability required for emerging applications in wireless networks. For a mono-static ISAC transceiver, as signal transmission durations are typically much longer than the radar echo round-trip times, the radar returns are drowned by the strong residual self interference (SI) from the transmitter, despite adopting sufficient SI cancellation techniques before digital domain - a phenomenon termed the echo-miss problem. A promising approach to tackle this problem involves the ISAC transceiver to be full-duplex (FD), and in this paper we jointly design the transmit and receive beamformers at the transceiver, transmit precoder at the uplink user, and receive combiner at the downlink user to simultaneously (a) maximize the uplink and downlink communication rate, (b) maximize the transmit and receive radar beampattern power at the target, and (c) suppress the residual SI. To solve this optimization problem, we proposed a penalty-based iterative algorithm. Numerical results illustrate that the proposed design can effectively achieve up to 60 dB digital-domain SI cancellation, a higher average sum-rate, and more accurate radar parameter estimation compared with previous ISAC FD studies
Design and Implementation of a FPGA and DSP Based MIMO Radar Imaging System
The work presented in this paper is aimed at the implementation of a real-time multiple-input multiple-output (MIMO) imaging radar used for area surveillance. In this radar, the equivalent virtual array method and time-division technique are applied to make 16 virtual elements synthesized from the MIMO antenna array. The chirp signal generater is based on a combination of direct digital synthesizer (DDS) and phase locked loop (PLL). A signal conditioning circuit is used to deal with the coupling effect within the array. The signal processing platform is based on an efficient field programmable gates array (FPGA) and digital signal processor (DSP) pipeline where a robust beamforming imaging algorithm is running on. The radar system was evaluated through a real field experiment. Imaging capability and real-time performance shown in the results demonstrate the practical feasibility of the implementation
Robust Transceiver Design for Covert Integrated Sensing and Communications With Imperfect CSI
We propose a robust transceiver design for a covert integrated sensing and
communications (ISAC) system with imperfect channel state information (CSI).
Considering both bounded and probabilistic CSI error models, we formulate
worst-case and outage-constrained robust optimization problems of joint
trasceiver beamforming and radar waveform design to balance the radar
performance of multiple targets while ensuring communications performance and
covertness of the system. The optimization problems are challenging due to the
non-convexity arising from the semi-infinite constraints (SICs) and the coupled
transceiver variables. In an effort to tackle the former difficulty,
S-procedure and Bernstein-type inequality are introduced for converting the
SICs into finite convex linear matrix inequalities (LMIs) and second-order cone
constraints. A robust alternating optimization framework referred to
alternating double-checking is developed for decoupling the transceiver design
problem into feasibility-checking transmitter- and receiver-side subproblems,
transforming the rank-one constraints into a set of LMIs, and verifying the
feasibility of beamforming by invoking the matrix-lifting scheme. Numerical
results are provided to demonstrate the effectiveness and robustness of the
proposed algorithm in improving the performance of covert ISAC systems
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