For the additive white Gaussian noise channel, there is a gap between the channel capacity and the highest achievable rate of equiprobable uniformly spaced one-dimensional signaling. It is commonly believed that approaching channel capacity requires the constituent one-dimensional signal points to have a Gaussian probability distribution. It is shown that the channel capacity can be achieved by equiprobable signaling with geometrical, Gaussian-like signal sets. Construction of these signal constellations is explicitly given. This result implicates that it is possible to approach channel capacity without using any kind of shaping codes
Abstract—Denote by Cm(snr) the Gaussian channel capacity with signal-to-noise ratio snr and input ca...
The achievability and converse bounds on the throughput of covert communication over AWGN channels a...
The i.i.d. rate of a channel is the mutual information rate between the channel input and the channe...
For the additive white Gaussian noise channel, there is a gap between the channel capacity and the h...
International audienceWe consider the scalar Gaussian channel with power constraint P. A gap exis...
In this paper we show that any sequence of infinite lattice constellations which is good for the unc...
AbstractCapacity is deremined for a class of communication channels containing additive noise. Gauss...
Abstract — Discrete input distributions are capacity-achieving for a variety of noise distributions ...
White Gaussian noise is used as a test signal in order to estimate transmission capacity. Based on t...
The form of capacity achieving input distribution is specified for a class of finite state channels ...
Abstract — Communication channels that are characterized by additive Gaussian noise have been well s...
tionary Gaussian fading channel is studied, where neither the transmitter nor the receiver knows the...
We evaluate the information capacity of channels for which the noise process is a Gaussian measure o...
Consider a communication channel with stochastic input message X and independent additive zero-mean ...
The capacity of a random-phase additive white Gaussian noise (AWGN) channel, referred to as noncoher...
Abstract—Denote by Cm(snr) the Gaussian channel capacity with signal-to-noise ratio snr and input ca...
The achievability and converse bounds on the throughput of covert communication over AWGN channels a...
The i.i.d. rate of a channel is the mutual information rate between the channel input and the channe...
For the additive white Gaussian noise channel, there is a gap between the channel capacity and the h...
International audienceWe consider the scalar Gaussian channel with power constraint P. A gap exis...
In this paper we show that any sequence of infinite lattice constellations which is good for the unc...
AbstractCapacity is deremined for a class of communication channels containing additive noise. Gauss...
Abstract — Discrete input distributions are capacity-achieving for a variety of noise distributions ...
White Gaussian noise is used as a test signal in order to estimate transmission capacity. Based on t...
The form of capacity achieving input distribution is specified for a class of finite state channels ...
Abstract — Communication channels that are characterized by additive Gaussian noise have been well s...
tionary Gaussian fading channel is studied, where neither the transmitter nor the receiver knows the...
We evaluate the information capacity of channels for which the noise process is a Gaussian measure o...
Consider a communication channel with stochastic input message X and independent additive zero-mean ...
The capacity of a random-phase additive white Gaussian noise (AWGN) channel, referred to as noncoher...
Abstract—Denote by Cm(snr) the Gaussian channel capacity with signal-to-noise ratio snr and input ca...
The achievability and converse bounds on the throughput of covert communication over AWGN channels a...
The i.i.d. rate of a channel is the mutual information rate between the channel input and the channe...