7,560 research outputs found
Demodulation and Detection Schemes for a Memoryless Optical WDM Channel
It is well known that matched filtering and sampling (MFS) demodulation
together with minimum Euclidean distance (MD) detection constitute the optimal
receiver for the additive white Gaussian noise channel. However, for a general
nonlinear transmission medium, MFS does not provide sufficient statistics, and
therefore is suboptimal. Nonetheless, this receiver is widely used in optical
systems, where the Kerr nonlinearity is the dominant impairment at high powers.
In this paper, we consider a suite of receivers for a two-user channel subject
to a type of nonlinear interference that occurs in
wavelength-division-multiplexed channels. The asymptotes of the symbol error
rate (SER) of the considered receivers at high powers are derived or bounded
analytically. Moreover, Monte-Carlo simulations are conducted to evaluate the
SER for all the receivers. Our results show that receivers that are based on
MFS cannot achieve arbitrary low SERs, whereas the SER goes to zero as the
power grows for the optimal receiver. Furthermore, we devise a heuristic
demodulator, which together with the MD detector yields a receiver that is
simpler than the optimal one and can achieve arbitrary low SERs. The SER
performance of the proposed receivers is also evaluated for some single-span
fiber-optical channels via split-step Fourier simulations
Optimal Watermark Embedding and Detection Strategies Under Limited Detection Resources
An information-theoretic approach is proposed to watermark embedding and
detection under limited detector resources. First, we consider the attack-free
scenario under which asymptotically optimal decision regions in the
Neyman-Pearson sense are proposed, along with the optimal embedding rule.
Later, we explore the case of zero-mean i.i.d. Gaussian covertext distribution
with unknown variance under the attack-free scenario. For this case, we propose
a lower bound on the exponential decay rate of the false-negative probability
and prove that the optimal embedding and detecting strategy is superior to the
customary linear, additive embedding strategy in the exponential sense.
Finally, these results are extended to the case of memoryless attacks and
general worst case attacks. Optimal decision regions and embedding rules are
offered, and the worst attack channel is identified.Comment: 36 pages, 5 figures. Revised version. Submitted to IEEE Transactions
on Information Theor
ML Detection in Phase Noise Impaired SIMO Channels with Uplink Training
The problem of maximum likelihood (ML) detection in training-assisted
single-input multiple-output (SIMO) systems with phase noise impairments is
studied for two different scenarios, i.e. the case when the channel is
deterministic and known (constant channel) and the case when the channel is
stochastic and unknown (fading channel). Further, two different operations with
respect to the phase noise sources are considered, namely, the case of
identical phase noise sources and the case of independent phase noise sources
over the antennas. In all scenarios the optimal detector is derived for a very
general parametrization of the phase noise distribution. Further, a high
signal-to-noise-ratio (SNR) analysis is performed to show that
symbol-error-rate (SER) floors appear in all cases. The SER floor in the case
of identical phase noise sources (for both constant and fading channels) is
independent of the number of antenna elements. In contrast, the SER floor in
the case of independent phase noise sources is reduced when increasing the
number of antenna elements (for both constant and fading channels). Finally,
the system model is extended to multiple data channel uses and it is shown that
the conclusions are valid for these setups, as well.Comment: (To appear in IEEE Transactions on Communications, 2015), Contains
additional material (Appendix B. T-slot Detectors
Measuring Planck beams with planets
Aims. Accurate measurement of the cosmic microwave background (CMB) anisotropy requires precise knowledge of the instrument beam. We explore how well the Planck beams will be determined from observations of planets, developing techniques that are also appropriate for other experiments.
Methods. We simulate planet observations with a Planck-like scanning strategy, telescope beams, noise, and detector properties. Then we employ both parametric and non-parametric techniques, reconstructing beams directly from the time-ordered data. With a faithful parameterization of the beam shape, we can constrain certain detector properties, such as the time constants of the detectors, to high precision. Alternatively, we decompose the beam using an orthogonal basis. For both techniques, we characterize the errors in the beam reconstruction with Monte Carlo realizations. For a simplified scanning strategy, we study the impact on estimation of the CMB power spectrum. Finally, we explore the consequences for measuring cosmological parameters, focusing on the spectral index of primordial scalar perturbations, n_s.
Results. The quality of the power spectrum measurement will be significantly influenced by the optical modeling of the telescope. In our most conservative case, using no information about the optics except the measurement of planets, we find that a single transit of Jupiter across the focal plane will measure the beam window functions to better than 0.3% for the channels at 100–217 GHz that are the most sensitive to the CMB. Constraining the beam with optical modeling can lead to much higher quality reconstruction.
Conclusions. Depending on the optical modeling, the beam errors may be a significant contribution to the measurement systematics for n_s
A Space Communications Study Final Report, Sep. 15, 1965 - Sep. 15, 1966
Reception of frequency modulated signals passed through deterministic and random time-varying channel
On Low-Resolution ADCs in Practical 5G Millimeter-Wave Massive MIMO Systems
Nowadays, millimeter-wave (mmWave) massive multiple-input multiple-output
(MIMO) systems is a favorable candidate for the fifth generation (5G) cellular
systems. However, a key challenge is the high power consumption imposed by its
numerous radio frequency (RF) chains, which may be mitigated by opting for
low-resolution analog-to-digital converters (ADCs), whilst tolerating a
moderate performance loss. In this article, we discuss several important issues
based on the most recent research on mmWave massive MIMO systems relying on
low-resolution ADCs. We discuss the key transceiver design challenges including
channel estimation, signal detector, channel information feedback and transmit
precoding. Furthermore, we introduce a mixed-ADC architecture as an alternative
technique of improving the overall system performance. Finally, the associated
challenges and potential implementations of the practical 5G mmWave massive
MIMO system {with ADC quantizers} are discussed.Comment: to appear in IEEE Communications Magazin
- …