34 research outputs found
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
Constellation Design for Channels Affected by Phase Noise
In this paper we optimize constellation sets to be used for channels affected
by phase noise. The main objective is to maximize the achievable mutual
information of the constellation under a given power constraint. The mutual
information and pragmatic mutual information of a given constellation is
calculated approximately assuming that both the channel and phase noise are
white. Then a simulated annealing algorithm is used to jointly optimize the
constellation and the binary labeling. The performance of optimized
constellations is compared with conventional constellations showing
considerable gains in all system scenarios.Comment: 5 pages, 6 figures, submitted to IEEE Int. Conf. on Communications
(ICC) 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 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
The Noncoherent Rician Fading Channel -- Part I : Structure of the Capacity-Achieving Input
Transmission of information over a discrete-time memoryless Rician fading
channel is considered where neither the receiver nor the transmitter knows the
fading coefficients. First the structure of the capacity-achieving input
signals is investigated when the input is constrained to have limited
peakedness by imposing either a fourth moment or a peak constraint. When the
input is subject to second and fourth moment limitations, it is shown that the
capacity-achieving input amplitude distribution is discrete with a finite
number of mass points in the low-power regime. A similar discrete structure for
the optimal amplitude is proven over the entire SNR range when there is only a
peak power constraint. The Rician fading with phase-noise channel model, where
there is phase uncertainty in the specular component, is analyzed. For this
model it is shown that, with only an average power constraint, the
capacity-achieving input amplitude is discrete with a finite number of levels.
For the classical average power limited Rician fading channel, it is proven
that the optimal input amplitude distribution has bounded support.Comment: To appear in the IEEE Transactions on Wireless 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
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
On the capacity of the block-memoryless phase-noise channel
Bounds are presented on the capacity of the block-memoryless phase-noise channel.
The bounds capture the first two terms in the asymptotic expansion of capacity for SNR going to infinity and turn out to be tight for a large range of SNR values of practical interest.
Through these bounds, the capacity dependency on the coherence time of the phase-noise process is determined