85,888 research outputs found
On the Impact of Optimal Modulation and FEC Overhead on Future Optical Networks
The potential of optimum selection of modulation and forward error correction
(FEC) overhead (OH) in future transparent nonlinear optical mesh networks is
studied from an information theory perspective. Different network topologies
are studied as well as both ideal soft-decision (SD) and hard-decision (HD) FEC
based on demap-and-decode (bit-wise) receivers. When compared to the de-facto
QPSK with 7% OH, our results show large gains in network throughput. When
compared to SD-FEC, HD-FEC is shown to cause network throughput losses of 12%,
15%, and 20% for a country, continental, and global network topology,
respectively. Furthermore, it is shown that most of the theoretically possible
gains can be achieved by using one modulation format and only two OHs. This is
in contrast to the infinite number of OHs required in the ideal case. The
obtained optimal OHs are between 5% and 80%, which highlights the potential
advantage of using FEC with high OHs.Comment: Some minor typos were correcte
Linear-Combined-Code-Based Unambiguous Code Discriminator Design for Multipath Mitigation in GNSS Receivers
Unambiguous tracking and multipath mitigation for Binary Offset Carrier (BOC) signals are two important requirements of modern Global Navigation Satellite Systems (GNSS) receivers. A GNSS discriminator design method based on optimization technique is proposed in this paper to meet these requirements. Firstly, the discriminator structure based on a linear-combined code is given. Then the requirements of ideal discriminator function are converted into the mathematical constraints and the objective function to form a non-linear optimization problem. Finally, the problem is solved and the local code is generated according to the results. The theoretical analysis and simulation results indicate that the proposed method can completely remove the false lock points for BOC signals and provide superior multipath mitigation performance compared with traditional discriminator and high revolution correlator (HRC) technique. Moreover, the proposed discriminator is easy to implement for not increasing the number of correlators
Optical Time-Frequency Packing: Principles, Design, Implementation, and Experimental Demonstration
Time-frequency packing (TFP) transmission provides the highest achievable
spectral efficiency with a constrained symbol alphabet and detector complexity.
In this work, the application of the TFP technique to fiber-optic systems is
investigated and experimentally demonstrated. The main theoretical aspects,
design guidelines, and implementation issues are discussed, focusing on those
aspects which are peculiar to TFP systems. In particular, adaptive compensation
of propagation impairments, matched filtering, and maximum a posteriori
probability detection are obtained by a combination of a butterfly equalizer
and four 8-state parallel Bahl-Cocke-Jelinek-Raviv (BCJR) detectors. A novel
algorithm that ensures adaptive equalization, channel estimation, and a proper
distribution of tasks between the equalizer and BCJR detectors is proposed. A
set of irregular low-density parity-check codes with different rates is
designed to operate at low error rates and approach the spectral efficiency
limit achievable by TFP at different signal-to-noise ratios. An experimental
demonstration of the designed system is finally provided with five
dual-polarization QPSK-modulated optical carriers, densely packed in a 100 GHz
bandwidth, employing a recirculating loop to test the performance of the system
at different transmission distances.Comment: This paper has been accepted for publication in the IEEE/OSA Journal
of Lightwave Technolog
A Method for the Combination of Stochastic Time Varying Load Effects
The problem of evaluating the probability that a structure becomes unsafe under a
combination of loads, over a given time period, is addressed. The loads and load effects
are modeled as either pulse (static problem) processes with random occurrence time, intensity and a specified shape or intermittent continuous (dynamic problem) processes which
are zero mean Gaussian processes superimposed 'on a pulse process. The load coincidence
method is extended to problems with both nonlinear limit states and dynamic responses,
including the case of correlated dynamic responses. The technique of linearization of a
nonlinear limit state commonly used in a time-invariant problem is investigated for timevarying
combination problems, with emphasis on selecting the linearization point. Results
are compared with other methods, namely the method based on upcrossing rate, simpler
combination rules such as Square Root of Sum of Squares and Turkstra's rule. Correlated
effects among dynamic loads are examined to see how results differ from correlated static
loads and to demonstrate which types of load dependencies are most important, i.e., affect'
the exceedance probabilities the most.
Application of the load coincidence method to code development is briefly discussed.National Science Foundation Grants CME 79-18053 and CEE 82-0759
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Selection of earthquake ground motions for multiple objectives using genetic algorithms
Existing earthquake ground motion (GM) selection methods for the seismic assessment of structural systems focus on spectral compatibility in terms of either only central values or both central values and variability. In this way, important selection criteria related to the seismology of the region, local soil conditions, strong GM intensity and duration as well as the magnitude of scale factors are considered only indirectly by setting them as constraints in the pre-processing phase in the form of permissible ranges. In this study, a novel framework for the optimum selection of earthquake GMs is presented, where the aforementioned criteria are treated explicitly as selection objectives. The framework is based on the principles of multi-objective optimization that is addressed with the aid of the Weighted Sum Method, which supports decision making both in the pre-processing and post-processing phase of the GM selection procedure. The solution of the derived equivalent single-objective optimization problem is performed by the application of a mixed-integer Genetic Algorithm and the effects of its parameters on the efficiency of the selection procedure are investigated. Application of the proposed framework shows that it is able to track GM sets that not only provide excellent spectral matching but they are also able to simultaneously consider more explicitly a set of additional criteria
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