20 research outputs found
Phase Modulation for Discrete-time Wiener Phase Noise Channels with Oversampling at High SNR
A discrete-time Wiener phase noise channel model is introduced in which
multiple samples are available at the output for every input symbol. A lower
bound on the capacity is developed. At high signal-to-noise ratio (SNR), if the
number of samples per symbol grows with the square root of the SNR, the
capacity pre-log is at least 3/4. This is strictly greater than the capacity
pre-log of the Wiener phase noise channel with only one sample per symbol,
which is 1/2. It is shown that amplitude modulation achieves a pre-log of 1/2
while phase modulation achieves a pre-log of at least 1/4.Comment: To appear in ISIT 201
Upper Bound on the Capacity of Discrete-Time Wiener Phase Noise Channels
A discrete-time Wiener phase noise channel with an integrate-and-dump
multi-sample receiver is studied. An upper bound to the capacity with an
average input power constraint is derived, and a high signal-to-noise ratio
(SNR) analysis is performed. If the oversampling factor grows as
for , then the capacity pre-log is at
most at high SNR.Comment: 5 pages, 1 figure. To be presented at IEEE Inf. Theory Workshop (ITW)
201
Capacity Outer Bound and Degrees of Freedom of Wiener Phase Noise Channels with Oversampling
The discrete-time Wiener phase noise channel with an integrate-and-dump
multi-sample receiver is studied.
A novel outer bound on the capacity with an average input power constraint is
derived as a function of the oversampling factor.
This outer bound yields the degrees of freedom for the scenario in which the
oversampling factor grows with the transmit power as .
The result shows, perhaps surprisingly, that the largest pre-log that can be
attained with phase modulation at high signal-to-noise ratio is at most .Comment: 5 pages, 1 figure, Submitted to Intern. Workshop Inf. Theory (ITW)
201
Lower Bound on the Capacity of Continuous-Time Wiener Phase Noise Channels
A continuous-time Wiener phase noise channel with an integrate-and-dump
multi-sample receiver is studied.
A lower bound to the capacity with an average input power constraint is
derived, and a high signal-to-noise ratio (SNR) analysis is performed.
The capacity pre-log depends on the oversampling factor, and amplitude and
phase modulation do not equally contribute to capacity at high SNR.Comment: Extended version of a paper submitted to ISIT 2015. 9 pages and 1
figure. arXiv admin note: text overlap with arXiv:1411.039
On continuous-time white phase noise channels
A continuous-time model for the additive white Gaussian noise (AWGN) channel in the presence of white (memoryless) phase noise is proposed and discussed. It is shown that for linear modulation the output of the baud-sampled filter matched to the shaping waveform represents a sufficient statistic. The analysis shows that the phase noise channel has the same information rate as an AWGN channel but with a penalty on the average signal-to-noise ratio, the amount of penalty depending on the phase noise statistic. © 2014 IEEE
Oversampling Increases the Pre-Log of Noncoherent Rayleigh Fading Channels
We analyze the capacity of a continuous-time, time-selective, Rayleigh
block-fading channel in the high signal-to-noise ratio (SNR) regime. The fading
process is assumed stationary within each block and to change independently
from block to block; furthermore, its realizations are not known a priori to
the transmitter and the receiver (noncoherent setting). A common approach to
analyzing the capacity of this channel is to assume that the receiver performs
matched filtering followed by sampling at symbol rate (symbol matched
filtering). This yields a discrete-time channel in which each transmitted
symbol corresponds to one output sample. Liang & Veeravalli (2004) showed that
the capacity of this discrete-time channel grows logarithmically with the SNR,
with a capacity pre-log equal to . Here, is the number of
symbols transmitted within one fading block, and is the rank of the
covariance matrix of the discrete-time channel gains within each fading block.
In this paper, we show that symbol matched filtering is not a
capacity-achieving strategy for the underlying continuous-time channel.
Specifically, we analyze the capacity pre-log of the discrete-time channel
obtained by oversampling the continuous-time channel output, i.e., by sampling
it faster than at symbol rate. We prove that by oversampling by a factor two
one gets a capacity pre-log that is at least as large as . Since the
capacity pre-log corresponding to symbol-rate sampling is , our result
implies indeed that symbol matched filtering is not capacity achieving at high
SNR.Comment: To appear in the IEEE Transactions on Information Theor
Capacity bounds for MIMO microwave backhaul links affected by phase noise
We present bounds and a closed-form high-SNR expression for the capacity of
multiple-antenna systems affected by Wiener phase noise. Our results are
developed for the scenario where a single oscillator drives all the
radio-frequency circuitries at each transceiver (common oscillator setup), the
input signal is subject to a peak-power constraint, and the channel matrix is
deterministic. This scenario is relevant for line-of-sight multiple-antenna
microwave backhaul links with sufficiently small antenna spacing at the
transceivers. For the 2 by 2 multiple-antenna case, for a Wiener phase-noise
process with standard deviation equal to 6 degrees, and at the medium/high SNR
values at which microwave backhaul links operate, the upper bound reported in
the paper exhibits a 3 dB gap from a lower bound obtained using 64-QAM.
Furthermore, in this SNR regime the closed-form high-SNR expression is shown to
be accurate.Comment: 10 pages, 2 figures, to appear in IEEE Transactions on Communication
On the Capacity of the Wiener Phase-Noise Channel: Bounds and Capacity Achieving Distributions
In this paper, the capacity of the additive white Gaussian noise (AWGN)
channel, affected by time-varying Wiener phase noise is investigated. Tight
upper and lower bounds on the capacity of this channel are developed. The upper
bound is obtained by using the duality approach, and considering a specific
distribution over the output of the channel. In order to lower-bound the
capacity, first a family of capacity-achieving input distributions is found by
solving a functional optimization of the channel mutual information. Then,
lower bounds on the capacity are obtained by drawing samples from the proposed
distributions through Monte-Carlo simulations. The proposed capacity-achieving
input distributions are circularly symmetric, non-Gaussian, and the input
amplitudes are correlated over time. The evaluated capacity bounds are tight
for a wide range of signal-to-noise-ratio (SNR) values, and thus they can be
used to quantify the capacity. Specifically, the bounds follow the well-known
AWGN capacity curve at low SNR, while at high SNR, they coincide with the
high-SNR capacity result available in the literature for the phase-noise
channel.Comment: IEEE Transactions on Communications, 201
Multi-sample Receivers Increase Information Rates for Wiener Phase Noise Channels
A waveform channel is considered where the transmitted signal is corrupted by
Wiener phase noise and additive white Gaussian noise (AWGN). A discrete-time
channel model is introduced that is based on a multi-sample receiver. Tight
lower bounds on the information rates achieved by the multi-sample receiver are
computed by means of numerical simulations. The results show that oversampling
at the receiver is beneficial for both strong and weak phase noise at high
signal-to-noise ratios. The results are compared with results obtained when
using other discrete-time models.Comment: Submitted to Globecom 201