904 research outputs found
Impact of Spatial Filtering on Distortion from Low-Noise Amplifiers in Massive MIMO Base Stations
In massive MIMO base stations, power consumption and cost of the low-noise
amplifiers (LNAs) can be substantial because of the many antennas. We
investigate the feasibility of inexpensive, power efficient LNAs, which
inherently are less linear. A polynomial model is used to characterize the
nonlinear LNAs and to derive the second-order statistics and spatial
correlation of the distortion. We show that, with spatial matched filtering
(maximum-ratio combining) at the receiver, some distortion terms combine
coherently, and that the SINR of the symbol estimates therefore is limited by
the linearity of the LNAs. Furthermore, it is studied how the power from a
blocker in the adjacent frequency band leaks into the main band and creates
distortion. The distortion term that scales cubically with the power received
from the blocker has a spatial correlation that can be filtered out by spatial
processing and only the coherent term that scales quadratically with the power
remains. When the blocker is in free-space line-of-sight and the LNAs are
identical, this quadratic term has the same spatial direction as the desired
signal, and hence cannot be removed by linear receiver processing
Spatial Characteristics of Distortion Radiated from Antenna Arrays with Transceiver Nonlinearities
The distortion from massive MIMO (multiple-input--multiple-output) base
stations with nonlinear amplifiers is studied and its radiation pattern is
derived. The distortion is analyzed both in-band and out-of-band. By using an
orthogonal Hermite representation of the amplified signal, the spatial
cross-correlation matrix of the nonlinear distortion is obtained. It shows
that, if the input signal to the amplifiers has a dominant beam, the distortion
is beamformed in the same way as that beam. When there are multiple beams
without any one being dominant, it is shown that the distortion is practically
isotropic. The derived theory is useful to predict how the nonlinear distortion
will behave, to analyze the out-of-band radiation, to do reciprocity
calibration, and to schedule users in the frequency plane to minimize the
effect of in-band distortion
Sub-Nyquist Sampling: Bridging Theory and Practice
Sampling theory encompasses all aspects related to the conversion of
continuous-time signals to discrete streams of numbers. The famous
Shannon-Nyquist theorem has become a landmark in the development of digital
signal processing. In modern applications, an increasingly number of functions
is being pushed forward to sophisticated software algorithms, leaving only
those delicate finely-tuned tasks for the circuit level.
In this paper, we review sampling strategies which target reduction of the
ADC rate below Nyquist. Our survey covers classic works from the early 50's of
the previous century through recent publications from the past several years.
The prime focus is bridging theory and practice, that is to pinpoint the
potential of sub-Nyquist strategies to emerge from the math to the hardware. In
that spirit, we integrate contemporary theoretical viewpoints, which study
signal modeling in a union of subspaces, together with a taste of practical
aspects, namely how the avant-garde modalities boil down to concrete signal
processing systems. Our hope is that this presentation style will attract the
interest of both researchers and engineers in the hope of promoting the
sub-Nyquist premise into practical applications, and encouraging further
research into this exciting new frontier.Comment: 48 pages, 18 figures, to appear in IEEE Signal Processing Magazin
Coding for Parallel Channels: Gallager Bounds for Binary Linear Codes with Applications to Repeat-Accumulate Codes and Variations
This paper is focused on the performance analysis of binary linear block
codes (or ensembles) whose transmission takes place over independent and
memoryless parallel channels. New upper bounds on the maximum-likelihood (ML)
decoding error probability are derived. These bounds are applied to various
ensembles of turbo-like codes, focusing especially on repeat-accumulate codes
and their recent variations which possess low encoding and decoding complexity
and exhibit remarkable performance under iterative decoding. The framework of
the second version of the Duman and Salehi (DS2) bounds is generalized to the
case of parallel channels, along with the derivation of their optimized tilting
measures. The connection between the generalized DS2 and the 1961 Gallager
bounds, addressed by Divsalar and by Sason and Shamai for a single channel, is
explored in the case of an arbitrary number of independent parallel channels.
The generalization of the DS2 bound for parallel channels enables to re-derive
specific bounds which were originally derived by Liu et al. as special cases of
the Gallager bound. In the asymptotic case where we let the block length tend
to infinity, the new bounds are used to obtain improved inner bounds on the
attainable channel regions under ML decoding. The tightness of the new bounds
for independent parallel channels is exemplified for structured ensembles of
turbo-like codes. The improved bounds with their optimized tilting measures
show, irrespectively of the block length of the codes, an improvement over the
union bound and other previously reported bounds for independent parallel
channels; this improvement is especially pronounced for moderate to large block
lengths.Comment: Submitted to IEEE Trans. on Information Theory, June 2006 (57 pages,
9 figures
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