1,339 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
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
Beyond Geometry : Towards Fully Realistic Wireless Models
Signal-strength models of wireless communications capture the gradual fading
of signals and the additivity of interference. As such, they are closer to
reality than other models. However, nearly all theoretic work in the SINR model
depends on the assumption of smooth geometric decay, one that is true in free
space but is far off in actual environments. The challenge is to model
realistic environments, including walls, obstacles, reflections and anisotropic
antennas, without making the models algorithmically impractical or analytically
intractable.
We present a simple solution that allows the modeling of arbitrary static
situations by moving from geometry to arbitrary decay spaces. The complexity of
a setting is captured by a metricity parameter Z that indicates how far the
decay space is from satisfying the triangular inequality. All results that hold
in the SINR model in general metrics carry over to decay spaces, with the
resulting time complexity and approximation depending on Z in the same way that
the original results depends on the path loss term alpha. For distributed
algorithms, that to date have appeared to necessarily depend on the planarity,
we indicate how they can be adapted to arbitrary decay spaces.
Finally, we explore the dependence on Z in the approximability of core
problems. In particular, we observe that the capacity maximization problem has
exponential upper and lower bounds in terms of Z in general decay spaces. In
Euclidean metrics and related growth-bounded decay spaces, the performance
depends on the exact metricity definition, with a polynomial upper bound in
terms of Z, but an exponential lower bound in terms of a variant parameter phi.
On the plane, the upper bound result actually yields the first approximation of
a capacity-type SINR problem that is subexponential in alpha
Constructive Multiuser Interference in Symbol Level Precoding for the MISO Downlink Channel
This paper investigates the problem of interference among the simultaneous
multiuser transmissions in the downlink of multiple antennas systems. Using
symbol level precoding, a new approach towards the multiuser interference is
discussed along this paper. The concept of exploiting the interference between
the spatial multiuser transmissions by jointly utilizing the data information
(DI) and channel state information (CSI), in order to design symbol-level
precoders, is proposed. In this direction, the interference among the data
streams is transformed under certain conditions to useful signal that can
improve the signal to interference noise ratio (SINR) of the downlink
transmissions. We propose a maximum ratio transmission (MRT) based algorithm
that jointly exploits DI and CSI to glean the benefits from constructive
multiuser interference. Subsequently, a relation between the constructive
interference downlink transmission and physical layer multicasting is
established. In this context, novel constructive interference precoding
techniques that tackle the transmit power minimization (min power) with
individual SINR constraints at each user's receivers is proposed. Furthermore,
fairness through maximizing the weighted minimum SINR (max min SINR) of the
users is addressed by finding the link between the min power and max min SINR
problems. Moreover, heuristic precoding techniques are proposed to tackle the
weighted sum rate problem. Finally, extensive numerical results show that the
proposed schemes outperform other state of the art techniques.Comment: Submitted to IEEE Transactions on Signal Processin
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