944 research outputs found
MIMO Radars and Massive MIMO Communication Systems can Coexist
In this paper, we investigate the coexistence of a single cell massive MIMO
communication system with a MIMO radar. We consider the case where the massive
MIMO BS is aware of the radar's existence and treats it as a non-serviced user,
but the radar is unaware of the communication system's existence and treats the
signals transmitted by both the BS and the communication users as noise. Using
results from random matrix theory, we derive the rates achievable by the
communication system and the radar. We then use these expressions to obtain the
achievable rate regions for the proposed joint radar and communications system.
We observe that due to the availability of a large number of degrees of freedom
at the mMIMO BS, results in minimal interference even without co-design.
Finally we corroborate our findings via detailed numerical simulations and
verify the validity of the results derived previously under different settings.Comment: 15 pages, 11 figure
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
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
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
Network MIMO with Partial Cooperation between Radar and Cellular Systems
To meet the growing spectrum demands, future cellular systems are expected to
share the spectrum of other services such as radar. In this paper, we consider
a network multiple-input multiple-output (MIMO) with partial cooperation model
where radar stations cooperate with cellular base stations (BS)s to deliver
messages to intended mobile users. So the radar stations act as BSs in the
cellular system. However, due to the high power transmitted by radar stations
for detection of far targets, the cellular receivers could burnout when
receiving these high radar powers. Therefore, we propose a new projection
method called small singular values space projection (SSVSP) to mitigate these
harmful high power and enable radar stations to collaborate with cellular base
stations. In addition, we formulate the problem into a MIMO interference
channel with general constraints (MIMO-IFC-GC). Finally, we provide a solution
to minimize the weighted sum mean square error minimization problem (WSMMSE)
with enforcing power constraints on both radar and cellular stations.Comment: (c) 2015 IEEE. Personal use of this material is permitted. Permission
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