489 research outputs found
Band Limited Signals Observed Over Finite Spatial and Temporal Windows: An Upper Bound to Signal Degrees of Freedom
The study of degrees of freedom of signals observed within spatially diverse
broadband multipath fields is an area of ongoing investigation and has a wide
range of applications, including characterising broadband MIMO and cooperative
networks. However, a fundamental question arises: given a size limitation on
the observation region, what is the upper bound on the degrees of freedom of
signals observed within a broadband multipath field over a finite time window?
In order to address this question, we characterize the multipath field as a sum
of a finite number of orthogonal waveforms or spatial modes. We show that (i)
the "effective observation time" is independent of spatial modes and different
from actual observation time, (ii) in wideband transmission regimes, the
"effective bandwidth" is spatial mode dependent and varies from the given
frequency bandwidth. These findings clearly indicate the strong coupling
between space and time as well as space and frequency in spatially diverse
wideband multipath fields. As a result, signal degrees of freedom does not
agree with the well-established degrees of freedom result as a product of
spatial degrees of freedom and time-frequency degrees of freedom. Instead,
analogous to Shannon's communication model where signals are encoded in only
one spatial mode, the available signal degrees of freedom in spatially diverse
wideband multipath fields is the time-bandwidth product result extended from
one spatial mode to finite modes. We also show that the degrees of freedom is
affected by the acceptable signal to noise ratio (SNR) in each spatial mode.Comment: Submitted to IEEE Transactions on Signal Processin
Intrinsic Limits of Dimensionality and Richness in Random Multipath Fields
We study the dimensions or degrees of freedom of farfield multipath that is observed in a limited, source-free region of space. The multipath fields are studied as solutions to the wave equation in an infinite-dimensional vector space. We prove two universal upper bounds on the truncation error of fixed and random multipath fields. A direct consequence of the derived bounds is that both fixed and random multipath fields have an effective finite dimension. For circular and spherical spatial regions, we show that this finite dimension is proportional to the radius and area of the region, respectively. We use the Karhunen-Loève (KL) expansion of random multipath fields to quantify the notion of multipath richness. The multipath richness is defined as the number of significant eigenvalues in the KL expansion that achieve 99% of the total multipath energy. We establish a lower bound on the largest eigenvalue. This lower bound quantifies, to some extent, the well-known reduction of multipath richness with reducing the angular power spread of multipath angular power spectrum
Dealing with Interference in Distributed Large-scale MIMO Systems: A Statistical Approach
This paper considers the problem of interference control through the use of
second-order statistics in massive MIMO multi-cell networks. We consider both
the cases of co-located massive arrays and large-scale distributed antenna
settings. We are interested in characterizing the low-rankness of users'
channel covariance matrices, as such a property can be exploited towards
improved channel estimation (so-called pilot decontamination) as well as
interference rejection via spatial filtering. In previous work, it was shown
that massive MIMO channel covariance matrices exhibit a useful finite rank
property that can be modeled via the angular spread of multipath at a MIMO
uniform linear array. This paper extends this result to more general settings
including certain non-uniform arrays, and more surprisingly, to two dimensional
distributed large scale arrays. In particular our model exhibits the dependence
of the signal subspace's richness on the scattering radius around the user
terminal, through a closed form expression. The applications of the
low-rankness covariance property to channel estimation's denoising and
low-complexity interference filtering are highlighted.Comment: 12 pages, 11 figures, to appear in IEEE Journal of Selected Topics in
Signal Processin
Applications of Continuous Spatial Models in Multiple Antenna Signal Processing
This thesis covers the investigation and application of continuous spatial models for multiple antenna signal processing. The use of antenna arrays for advanced sensing and communications systems has been facilitated by the rapid increase in the capabilities of digital signal processing systems. The wireless communications channel will vary across space as different signal paths from the same source combine and interfere. This creates a level of spatial diversity that can be exploited to improve the robustness and overall capacity of the wireless channel. Conventional approaches to using spatial diversity have centered on smart, adaptive antennas and spatial beam forming. Recently, the more general theory of multiple input, multiple output (MIMO) systems has been developed to utilise the independent spatial communication modes offered in a scattering environment. ¶ ..
3D spatial fading correlation for uniform angle of arrival distribution
We derive a closed-form expression for the spatial fading correlation (SFC) between two arbitrary points in 3D-space for the uniform limited azimuth-elevation angle of arrival probability density function (pdf). This expression simplifies the computatio
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