Simulator for a GSM traffic channel transmission and reception
This Simulink model simulates the entire transmission and reception of voice data of a traffic channel for GSM (TCH/FS)over a multipath fading channel, and it calculates the BER of the received signal
The Ntrip RTCM Multiclient "NtripRTCMMC" simultaneously reads a number of
real-time RTK data streams in RTCM 2.x format (basicly message types 18
and 19) as received from an Ntrip Broadcaster. It decodes the streams and
generates raw and RINEX files.
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.
In this paper, we consider the problem of filtering in relational
hidden Markov models. We present a compact representation for
such models and an associated logical particle filtering algorithm. Each
particle contains a logical formula that describes a set of states. The
algorithm updates the formulae as new observations are received. Since
a single particle tracks many states, this filter can be more accurate
than a traditional particle filter in high dimensional state spaces, as we
demonstrate in experiments.
Scotia Airlines is a new budget airline operating between Glasgow Airport and the Western
Isles. It operates two 24-seater light passenger aircraft and requires a flight booking system.
Because Scotia offers low cost air travel, there is a need to treat each flight as single cost centre
and to be able to ascertain, at any moment, the amount of the cash taken for that flight.
Reservations and bookings cannot be made until the flight details have been finalised (flight
number, departure and arrival airports). A seat on a flight is considered booked when payment
as been received for it. When a reservation is confirmed (changed to booked), the passenger
name is checked against the original reservation.
A flight can be in any of the following states:
Available for bookings
Checking in
Boarding
Closed
This example provides a description of how to use a DMA channel to transfer a
word data buffer from memory (Flash) to memory (RAM).
The dedicated DMA channel is configured to transfer once a time a 32 word data buffer
stored as constant in the Flash memory to another buffer in the RAM memory.
The received data are stored in the DST_Buffer.
The DMA channel transfer complete interrupt is enabled to generate an interrupt at
the end of the buffer transfer. As soon as the transfer is completed an interrupt is
generated and in the DMA channel interrupt routine the transfer complete interrupt
pending bit is cleared.
The data counter is stored before and after the transfer to show that all data has been
transfered.
TransferStatus gives the data transfer status where it is PASSED if transmitted and
received data are the same otherwise it is FAILED
This folder has some scritps that you may find usefull.
All of it comes from questions that I ve received in my email.
If you have a new request/question, feel free to send it to marceloperlin@gmail.com.
But please, don t ask me to do your homework.
Passing_your_param0
This folder contains instructions (and m files) for passing you own initial parameters to the fitting function.
I also included a simple simulation script that will create random initial coefficients
(under the proper bounds) and fit the model to the data.
Description: This program demonstrates a half-duplex 9600-baud UART using
// Timer_A3 using no XTAL and an external resistor for DCO ROSC. DCO used for
// TACLK UART baud generation. The program will wait in LPM4, echoing back
// a received character using 8N1 protocol. On valid RX character, the
// character is echoed back.
// Using a 100k resistor on ROSC, with default DCO setting, set DCOCLK ~ 2MHz.
// ACLK = n/a, MCLK = SMCLK ~2MHz DCOCLK