ETH Series in Information Theory
and its Applications, Vol. 5
edited by Amos Lapidoth
Tobias Koch,
On Heating Up and Fading in
Communication Channels.
1st edition 2009. XVIII, 206 pages, € 64,00.
ISBN 3-86628-261-3, 978-3-86628-261-2
Abstract
This dissertation
studies two phenomena that affect the transmission of data: heating up and
fading. In particular, the effect of these phenomena on channel
capacity, which is the largest rate at which data transmission with arbitrarily
lower error probability is possible, is investigated.
Heating up is
relevant in on-chip communication, where multiple terminals that are located on
the same microchip wish to communicate with each other. It accounts for thermal
coupling of data and noise. Indeed, the data to be transmitted are corrupted by
thermal noise, whose variance depends on the local temperature of the chip. Furthermore,
the transmission of data is associated with dissipation of energy into heat and
raises therefore the local temperature of the chip. This gives rise to a
channel model where the variance of the additive noise is datadependent. The
capacity of this channel is studied at low and at high transmit powers. At low
transmit powers, the slope of the capacity-vspower curve at zero is computed,
and it is shown that the heating-up effect is beneficial. At high transmit
powers, it is demonstrated that the heating-up effect is detrimental. In fact,
if the heat dissipates slowly then the capacity is bounded in the transmit
power, i.e., the capacity does not tend to infinity as the allowed average
power tends to infinity. A sufficient condition and a necessary condition for
the capacity to be bounded is derived.
The results of the
above analyses suggest that at low transmit powers heat sinks are not only
unnecessary, but they even reduce the capacity by dissipating heat, which
contains information about the transmitted signal. The results further
accentuate the importance of an efficient heat sink at large transmit powers.
Fading occurs in
wireless communication channels. In such channels the transmitted signal is not
only corrupted by additive noise, but also by multiplicative noise, which
accounts for the variation of the signal’s attenuation. This multiplicative
noise is referred to as fading. In contrast to many other
information-theoretic studies, where it is assumed that the receiver has
perfect knowledge of the fading, in this dissertation it is assumed that the
transmitter and the receiver only know the statistics of the fading but not its
realization.
First, the
capacity of multiple-input multiple-output (MIMO) Gaussian flat-fading channels
with memory is considered. Nonasymptotic upper and lower bounds on the capacity
are derived, and their asymptotic behavior is analyzed in the limit as the
signal-to-noise ratio (SNR) tends to infinity. In particular, upper bounds on
the fading number (which is defined as the second-order term in the high-SNR
expansion of capacity) and on the capacity pre-log (which is defined as the
limiting ratio of capacity to log SNR as SNR tends to infinity) are computed. Furthermore,
an approach to derive lower bounds on the fading number is proposed. This lower
bound is applied to derive a lower bound on the fading number of spatially IID,
zero-mean, MIMO Gaussian fading channels with memory. The derived upper and
lower bounds on the fading number demonstrate that when the number of receive
antennas does not exceed the number of transmit antennas, the fading number of
spatially IID, zero-mean, slowly-varying, Gaussian fading channels is proportional
to the number of degrees of freedom, i.e., to the minimum of the number of
transmit and receive antennas.
Second, the
capacity pre-log of single-input single-output (SISO) flatfading channels with
memory is studied. It is shown that, among all stationary and ergodic fading
processes of a given spectral distribution function and whose law has no mass
point at zero, the Gaussian process gives rise to the smallest pre-log. It is
further demonstrated that the assumption that the fading law has no mass point
at zero is essential in the sense that there exist stationary and ergodic
fading processes of some spectral distribution function (and whose law has a
mass point at zero) that give rise to a smaller pre-log than the Gaussian
process of equal spectral distribution function. These results are then
extended to multiple-input single-output (MISO) fading channels with memory.
Finally, the
capacity of multipath (frequency-selective) fading channels is studied. It is
shown that if the delay spread is large in the sense that the variances of the
path gains decay exponentially or slower, then the capacity is bounded in the
SNR. Thus, in this case the capacity does not grow to infinity as the SNR tends
to infinity. In contrast, if the variances of the path gains decay faster than
exponentially, then the capacity is unbounded in the SNR. It is further
demonstrated that if the number of paths is finite, then the capacity
pre-loglog, which is defined as the limiting ratio of capacity to log log SNR
as SNR tends to infinity, is 1, irrespective of the number of paths.
The conclusions
that can be drawn from the above described analyses of fading channels are
manifold. First, the presence of multiple antennas at the transmitter and
receiver is very beneficial, even if the receiver does not know the realization
of the fading. Second, the Gaussian fading assumption in the analysis of fading
channels at high SNR is conservative in the sense that for a large class of
fading processes the Gaussian process
gives rise to the smallest capacity pre-log. Third, at high SNR multipath
fading channels with an infinite number of paths should not be approximated by multipath fading
channels with a finite number of paths, since these channels possess completely
different high-SNR capacity behaviors. And last but not least, the high-SNR asymptotic
behavior of the capacity of fading channels is very sensitive to the employed
channel model. Thus, in the information-theoretic analysis of fading channels
at high SNR and in the evaluation of the results thereof, one should attach
great importance to the channel model. .
Keywords: Information theory, channel capacity, capacity
per unit, cost, channels with memory, high signal-to-noise ratio, on-chip
communication, wireless communication, .at-fading channels, multipath fading
channels.
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