18 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
Tight Upper and Lower Bounds to the Information Rate of the Phase Noise Channel
Numerical upper and lower bounds to the information rate transferred through
the additive white Gaussian noise channel affected by discrete-time
multiplicative autoregressive moving-average (ARMA) phase noise are proposed in
the paper. The state space of the ARMA model being multidimensional, the
problem cannot be approached by the conventional trellis-based methods that
assume a first-order model for phase noise and quantization of the phase space,
because the number of state of the trellis would be enormous. The proposed
lower and upper bounds are based on particle filtering and Kalman filtering.
Simulation results show that the upper and lower bounds are so close to each
other that we can claim of having numerically computed the actual information
rate of the multiplicative ARMA phase noise channel, at least in the cases
studied in the paper. Moreover, the lower bound, which is virtually
capacity-achieving, is obtained by demodulation of the incoming signal based on
a Kalman filter aided by past data. Thus we can claim of having found the
virtually optimal demodulator for the multiplicative phase noise channel, at
least for the cases considered in the paper.Comment: 5 pages, 2 figures. Accepted for presentation at ISIT 201
Capacity estimation of two-dimensional channels using Sequential Monte Carlo
We derive a new Sequential-Monte-Carlo-based algorithm to estimate the
capacity of two-dimensional channel models. The focus is on computing the
noiseless capacity of the 2-D one-infinity run-length limited constrained
channel, but the underlying idea is generally applicable. The proposed
algorithm is profiled against a state-of-the-art method, yielding more than an
order of magnitude improvement in estimation accuracy for a given computation
time
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
Capacity of SIMO and MISO Phase-Noise Channels with Common/Separate Oscillators
In multiple antenna systems, phase noise due to instabilities of the
radio-frequency (RF) oscillators, acts differently depending on whether the RF
circuitries connected to each antenna are driven by separate (independent)
local oscillators (SLO) or by a common local oscillator (CLO). In this paper,
we investigate the high-SNR capacity of single-input multiple-output (SIMO) and
multiple-output single-input (MISO) phase-noise channels for both the CLO and
the SLO configurations.
Our results show that the first-order term in the high-SNR capacity expansion
is the same for all scenarios (SIMO/MISO and SLO/CLO), and equal to , where stands for the SNR. On the contrary, the second-order
term, which we refer to as phase-noise number, turns out to be
scenario-dependent. For the SIMO case, the SLO configuration provides a
diversity gain, resulting in a larger phase-noise number than for the CLO
configuration. For the case of Wiener phase noise, a diversity gain of at least
can be achieved, where is the number of receive antennas. For
the MISO, the CLO configuration yields a higher phase-noise number than the SLO
configuration. This is because with the CLO configuration one can obtain a
coherent-combining gain through maximum ratio transmission (a.k.a. conjugate
beamforming). This gain is unattainable with the SLO configuration.Comment: IEEE Transactions on Communication
Computing the information rate of discrete-time Wiener phase noise channels by parametric Bayesian tracking
A new upper bound (UB) on the information rate (IR) transferred through the additive white Gaussian noise channel affected by Wiener\&\#x02019;s laser phase noise is proposed in the paper. The bound is based on Bayesian tracking of the noisy phase. Specifically, the predictive and posterior densities involved in the tracking are expressed in parametric form, therefore tracking is made on parameters. This make the method less computationally demanding than known non-parametric methods, e.g. methods based on phase quantization and trellis representation of phase memory. Simulation results show that the UB is so close to the lower bound that we can claim of having virtually computed the actual IR
Nonlinearity Mitigation in WDM Systems: Models, Strategies, and Achievable Rates
After reviewing models and mitigation strategies for interchannel nonlinear
interference (NLI), we focus on the frequency-resolved logarithmic perturbation
model to study the coherence properties of NLI. Based on this study, we devise
an NLI mitigation strategy which exploits the synergic effect of phase and
polarization noise compensation (PPN) and subcarrier multiplexing with
symbol-rate optimization. This synergy persists even for high-order modulation
alphabets and Gaussian symbols. A particle method for the computation of the
resulting achievable information rate and spectral efficiency (SE) is presented
and employed to lower-bound the channel capacity. The dependence of the SE on
the link length, amplifier spacing, and presence or absence of inline
dispersion compensation is studied. Single-polarization and dual-polarization
scenarios with either independent or joint processing of the two polarizations
are considered. Numerical results show that, in links with ideal distributed
amplification, an SE gain of about 1 bit/s/Hz/polarization can be obtained (or,
in alternative, the system reach can be doubled at a given SE) with respect to
single-carrier systems without PPN mitigation. The gain is lower with lumped
amplification, increases with the number of spans, decreases with the span
length, and is further reduced by in-line dispersion compensation. For
instance, considering a dispersion-unmanaged link with lumped amplification and
an amplifier spacing of 60 km, the SE after 80 spans can be be increased from
4.5 to 4.8 bit/s/Hz/polarization, or the reach raised up to 100 spans (+25%)
for a fixed SE.Comment: Submitted to Journal of Lightwave Technolog
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