The data files included are .MAT or *.dat (ASCII)files. The m-files and the
data may be distributed, provided that the source is acknowledged in any
publication and the data are not sold. Since this software is being distributed
free of charge, the authors are not offering any technical support. Students who
have any questions or difficulties using this software, or require the
additional functions from the Signal Processing Toolbox should contact their
professor.
We address the problem of blind carrier frequency-offset (CFO) estimation in quadrature amplitude modulation,
phase-shift keying, and pulse amplitude modulation
communications systems.We study the performance of a standard
CFO estimate, which consists of first raising the received signal to
the Mth power, where M is an integer depending on the type and
size of the symbol constellation, and then applying the nonlinear
least squares (NLLS) estimation approach. At low signal-to noise
ratio (SNR), the NLLS method fails to provide an accurate CFO
estimate because of the presence of outliers. In this letter, we derive
an approximate closed-form expression for the outlier probability.
This enables us to predict the mean-square error (MSE) on CFO
estimation for all SNR values. For a given SNR, the new results
also give insight into the minimum number of samples required in
the CFO estimation procedure, in order to ensure that the MSE
on estimation is not significantly affected by the outliers.
Carrier-phase synchronization can be approached in a
general manner by estimating the multiplicative distortion (MD) to which
a baseband received signal in an RF or coherent optical transmission
system is subjected. This paper presents a unified modeling and
estimation of the MD in finite-alphabet digital communication systems. A
simple form of MD is the camer phase exp GO) which has to be estimated
and compensated for in a coherent receiver. A more general case with
fading must, however, allow for amplitude as well as phase variations of
the MD.
We assume a state-variable model for the MD and generally obtain a
nonlinear estimation problem with additional randomly-varying system
parameters such as received signal power, frequency offset, and Doppler
spread. An extended Kalman filter is then applied as a near-optimal
solution to the adaptive MD and channel parameter estimation problem.
Examples are given to show the use and some advantages of this scheme.
This book shows how to design and implement C++ software that is more effective: more likely to behave correctly more robust in the face of exceptions more efficient more portable makes better use of language features adapts to change more gracefully works better in a mixed-language environment is easier to use correctly is harder to use incorrectly. In short, software that s just better.
A new cable fault location method based on
wavelet reconstruction is proposed. In this method the
difference between the currents of faulty phase and sound
phase under the high voltage pulse excitation is used as the
measured signal and is decomposed in multi-scale by wavelet
transform, then reconstructed in single scale. Comparing with
traditional fault location method by travelling wave, the
presented method will not be interfered by the reflected wave
from the branch joint of cables or from other positions where
the impedances are not matched and not be influenced by fault
types, otherwise, the reflected waves can be recognized even
the faulty position is near to the measuring terminal, at the
same time, the influence of the wave speed uncertainty can be
reduced. The correctness of the proposed method is proved by
simulation results.
Summary: An example of KALMAN FILTER
MATLAB Release: R13SP1
Required Products: Communications Toolbox,Signal Processing Toolbox
Description: THIS PROGRAM DEMONSTRATES AN EXAMPLE OF KALMAN FILTER.
This R2.9 revision of the CLID detector provides the TYPE 1 (on-hook, between first and second ring, or
before first ring) signal detection and returns the message raw byte data without parsing of particular fields
such as Message Type, Parameter(s) Type(s), etc. The decoding of the message meaning should be performed by the user application.主叫號碼識別CID算法for TI DSP
基于OFDM的無線寬帶系統仿真It contains mainly two parts, i.e. link-level simulator and system-level simulator.
Link-level simulator focus on a single-cell single-user scenario, where signal is transmitted from tx, and estimated at rx. Comparing the difference in tx/rx signal, the error rate can be found out. The output of the link-level simulator is the BLER/BER vs. SNR mapping table, that can be used for the system-level simulation.
System-level simulator focus on a multi-cell multi-user scenario. For the sake of simplicity, it takes the mapping table aquired in the link-level simulation, measure the actural SNR, and finds the corresponding error rate.
