6,996 research outputs found
A Novel Rate Control Algorithm for Onboard Predictive Coding of Multispectral and Hyperspectral Images
Predictive coding is attractive for compression onboard of spacecrafts thanks
to its low computational complexity, modest memory requirements and the ability
to accurately control quality on a pixel-by-pixel basis. Traditionally,
predictive compression focused on the lossless and near-lossless modes of
operation where the maximum error can be bounded but the rate of the compressed
image is variable. Rate control is considered a challenging problem for
predictive encoders due to the dependencies between quantization and prediction
in the feedback loop, and the lack of a signal representation that packs the
signal's energy into few coefficients. In this paper, we show that it is
possible to design a rate control scheme intended for onboard implementation.
In particular, we propose a general framework to select quantizers in each
spatial and spectral region of an image so as to achieve the desired target
rate while minimizing distortion. The rate control algorithm allows to achieve
lossy, near-lossless compression, and any in-between type of compression, e.g.,
lossy compression with a near-lossless constraint. While this framework is
independent of the specific predictor used, in order to show its performance,
in this paper we tailor it to the predictor adopted by the CCSDS-123 lossless
compression standard, obtaining an extension that allows to perform lossless,
near-lossless and lossy compression in a single package. We show that the rate
controller has excellent performance in terms of accuracy in the output rate,
rate-distortion characteristics and is extremely competitive with respect to
state-of-the-art transform coding
A Comparison of Hybrid Beamforming and Digital Beamforming with Low-Resolution ADCs for Multiple Users and Imperfect CSI
For 5G it will be important to leverage the available millimeter wave
spectrum. To achieve an approximately omni- directional coverage with a similar
effective antenna aperture compared to state of the art cellular systems, an
antenna array is required at both the mobile and basestation. Due to the large
bandwidth and inefficient amplifiers available in CMOS for mmWave, the analog
front-end of the receiver with a large number of antennas becomes especially
power hungry. Two main solutions exist to reduce the power consumption: hybrid
beam forming and digital beam forming with low resolution Analog to Digital
Converters (ADCs). In this work we compare the spectral and energy efficiency
of both systems under practical system constraints. We consider the effects of
channel estimation, transmitter impairments and multiple simultaneous users.
Our power consumption model considers components reported in literature at 60
GHz. In contrast to many other works we also consider the correlation of the
quantization error, and generalize the modeling of it to non-uniform quantizers
and different quantizers at each antenna. The result shows that as the SNR gets
larger the ADC resolution achieving the optimal energy efficiency gets also
larger. The energy efficiency peaks for 5 bit resolution at high SNR, since due
to other limiting factors the achievable rate almost saturates at this
resolution. We also show that in the multi-user scenario digital beamforming is
in any case more energy efficient than hybrid beamforming. In addition we show
that if different ADC resolutions are used we can achieve any desired
trade-offs between power consumption and rate close to those achieved with only
one ADC resolution.Comment: Submitted to JSTSP. arXiv admin note: text overlap with
arXiv:1610.0290
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