17,871 research outputs found
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
"Integrating Optimization and Strategic Conservation to Achieve Higher Efficiencies in Land Protection"
Strategic land conservation seeks to select the highest quality lands given limited financial resources. Traditionally conservation officials implement strategic conservation by creating prioritization maps that attempt to identify the lands of highest ecological value or public value from a resource perspective. This paper describes the history of using optimization in strategic conservation and demonstrates how the combination of these approaches can significantly strengthen conservation efforts by making these programs more efficient with public monies.Mathematical Programming, Conservation Optimization, Cost Effectiveness Analysis, Strategic Conservation
Ellipsoidal Prediction Regions for Multivariate Uncertainty Characterization
While substantial advances are observed in probabilistic forecasting for
power system operation and electricity market applications, most approaches are
still developed in a univariate framework. This prevents from informing about
the interdependence structure among locations, lead times and variables of
interest. Such dependencies are key in a large share of operational problems
involving renewable power generation, load and electricity prices for instance.
The few methods that account for dependencies translate to sampling scenarios
based on given marginals and dependence structures. However, for classes of
decision-making problems based on robust, interval chance-constrained
optimization, necessary inputs take the form of polyhedra or ellipsoids.
Consequently, we propose a systematic framework to readily generate and
evaluate ellipsoidal prediction regions, with predefined probability and
minimum volume. A skill score is proposed for quantitative assessment of the
quality of prediction ellipsoids. A set of experiments is used to illustrate
the discrimination ability of the proposed scoring rule for misspecification of
ellipsoidal prediction regions. Application results based on three datasets
with wind, PV power and electricity prices, allow us to assess the skill of the
resulting ellipsoidal prediction regions, in terms of calibration, sharpness
and overall skill.Comment: 8 pages, 7 Figures, Submitted to IEEE Transactions on Power System
Multicast Multigroup Precoding and User Scheduling for Frame-Based Satellite Communications
The present work focuses on the forward link of a broadband multibeam
satellite system that aggressively reuses the user link frequency resources.
Two fundamental practical challenges, namely the need to frame multiple users
per transmission and the per-antenna transmit power limitations, are addressed.
To this end, the so-called frame-based precoding problem is optimally solved
using the principles of physical layer multicasting to multiple co-channel
groups under per-antenna constraints. In this context, a novel optimization
problem that aims at maximizing the system sum rate under individual power
constraints is proposed. Added to that, the formulation is further extended to
include availability constraints. As a result, the high gains of the sum rate
optimal design are traded off to satisfy the stringent availability
requirements of satellite systems. Moreover, the throughput maximization with a
granular spectral efficiency versus SINR function, is formulated and solved.
Finally, a multicast-aware user scheduling policy, based on the channel state
information, is developed. Thus, substantial multiuser diversity gains are
gleaned. Numerical results over a realistic simulation environment exhibit as
much as 30% gains over conventional systems, even for 7 users per frame,
without modifying the framing structure of legacy communication standards.Comment: Accepted for publication to the IEEE Transactions on Wireless
Communications, 201
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