292 research outputs found
Nearest Neighbour Decoding and Pilot-Aided Channel Estimation in Stationary Gaussian Flat-Fading Channels
We study the information rates of non-coherent, stationary, Gaussian,
multiple-input multiple-output (MIMO) flat-fading channels that are achievable
with nearest neighbour decoding and pilot-aided channel estimation. In
particular, we analyse the behaviour of these achievable rates in the limit as
the signal-to-noise ratio (SNR) tends to infinity. We demonstrate that nearest
neighbour decoding and pilot-aided channel estimation achieves the capacity
pre-log - which is defined as the limiting ratio of the capacity to the
logarithm of SNR as the SNR tends to infinity - of non-coherent multiple-input
single-output (MISO) flat-fading channels, and it achieves the best so far
known lower bound on the capacity pre-log of non-coherent MIMO flat-fading
channels.Comment: 5 pages, 1 figure. To be presented at the IEEE International
Symposium on Information Theory (ISIT), St. Petersburg, Russia, 2011.
Replaced with version that will appear in the proceeding
Low-Complexity Joint Channel Estimation and List Decoding of Short Codes
A pilot-assisted transmission (PAT) scheme is proposed for short
blocklengths, where the pilots are used only to derive an initial channel
estimate for the list construction step. The final decision of the message is
obtained by applying a non-coherent decoding metric to the codewords composing
the list. This allows one to use very few pilots, thus reducing the channel
estimation overhead. The method is applied to an ordered statistics decoder for
communication over a Rayleigh block-fading channel. Gains of up to dB as
compared to traditional PAT schemes are demonstrated for short codes with QPSK
signaling. The approach can be generalized to other list decoders, e.g., to
list decoding of polar codes.Comment: Accepted at the 12th International ITG Conference on Systems,
Communications and Coding (SCC 2019), Rostock, German
Orthogonal or superimposed pilots? A rate-efficient channel estimation strategy for stationary MIMO fading channels
©IEEE, 2017This paper considers channel estimation for multiple-input multiple-output (MIMO) channels and revisits two competing concepts of including training data into the transmit signal, namely orthogonal pilot (OP) that periodically transmits alternating pilot-data symbols, and superimposed pilot (SP) that overlays pilot-data symbols over time. We investigate rates achievable by both schemes when the channel undergoes time-selective bandlimited fading and analyze their behaviors with respect to the MIMO dimension and fading speed. By incorporating the multiple-antenna factors, we demonstrate that the widely-known trend, in which the OP is superior to the SP in the regimes of high signal-to-noise ratio (SNR) and slow-fading, and vice-versa, does not hold in general. As the number of transmit antennas (nt) increases, the range of operable fading speeds for the OP is significantly narrowed due to limited time resources for channel estimation and insufficient fading samples, which results in the SP being competitive in wider speed and SNR ranges. For a sufficiently small nt, we demonstrate thatas the fading variation becomes slower, the estimation quality for the SP can be superior to that for the OP. In this case, the SP outperforms the OP in the slow-fading regime due to full utilization of time for data transmission
Optimum Pilot Overhead in Wireless Communication: A Unified Treatment of Continuous and Block-Fading Channels
The optimization of the pilot overhead in single-user wireless fading
channels is investigated, and the dependence of this overhead on various system
parameters of interest (e.g., fading rate, signal-to-noise ratio) is
quantified. The achievable pilot-based spectral efficiency is expanded with
respect to the fading rate about the no-fading point, which leads to an
accurate order expansion for the pilot overhead. This expansion identifies that
the pilot overhead, as well as the spectral efficiency penalty with respect to
a reference system with genie-aided CSI (channel state information) at the
receiver, depend on the square root of the normalized Doppler frequency.
Furthermore, it is shown that the widely-used block fading model is only a
special case of more accurate continuous fading models in terms of the
achievable pilot-based spectral efficiency, and that the overhead optimization
for multiantenna systems is effectively the same as for single-antenna systems
with the normalized Doppler frequency multiplied by the number of transmit
antennas.Comment: Submitted to IEEE Trans. Wireless Communication
A Rate-Splitting Approach to Fading Channels with Imperfect Channel-State Information
As shown by M\'edard, the capacity of fading channels with imperfect
channel-state information (CSI) can be lower-bounded by assuming a Gaussian
channel input with power and by upper-bounding the conditional entropy
by the entropy of a Gaussian random variable with variance
equal to the linear minimum mean-square error in estimating from
. We demonstrate that, using a rate-splitting approach, this lower
bound can be sharpened: by expressing the Gaussian input as the sum of two
independent Gaussian variables and and by applying M\'edard's lower
bound first to bound the mutual information between and while
treating as noise, and by applying it a second time to the mutual
information between and while assuming to be known, we obtain a
capacity lower bound that is strictly larger than M\'edard's lower bound. We
then generalize this approach to an arbitrary number of layers, where
is expressed as the sum of independent Gaussian random variables of
respective variances , summing up to . Among
all such rate-splitting bounds, we determine the supremum over power
allocations and total number of layers . This supremum is achieved
for and gives rise to an analytically expressible capacity lower
bound. For Gaussian fading, this novel bound is shown to converge to the
Gaussian-input mutual information as the signal-to-noise ratio (SNR) grows,
provided that the variance of the channel estimation error tends to
zero as the SNR tends to infinity.Comment: 28 pages, 8 figures, submitted to IEEE Transactions on Information
Theory. Revised according to first round of review
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