This demo shows the BER performance of linear, decision feedback (DFE), and maximum likelihood sequence estimation (MLSE) equalizers when operating in a static channel with a deep null. The MLSE equalizer is invoked first with perfect channel knowledge, then with an imperfect, although straightforward, channel estimation algorithm. The BER results are determined through Monte Carlo simulation. The demo shows how to use these equalizers seamlessly across multiple blocks of data, where equalizer state must be maintained between data blocks.
This document contains official rules of the 3D soccer simulation competition
at RoboCup 2006. While we will try to cover all cases, if unexpected
events do occur, the rule committee will seek input from the
participants and then make a decision. However, once the committee has
made a decision, that decision is final and will not be open to further
discussion
ABC_FDTD_Die(T) Implements simulation of a Gaussian Pulse
over T time steps. ABC are for free space. If boundaries are in
the Dielectric medium then the ABC fail. Dielectric medium begin and
end can be specified with the code
ABC_FDTD_Die(T) Implements simulation of a Gaussian Pulse
over T time steps. ABC are for free space. If boundaries are in
the Dielectric medium then the ABC fail. Dielectric medium begin and
end can be specified with the code
The NCTUns network simulator and emulator is developed at NCTU, Taiwan. Its predecessor is the Harvard network simulator (invented by Prof. S.Y. Wang in 1999).
By using a novel simulation methodology, it can do several tasks that traditional network simulators cannot easily do.
Single/Multipath Channel Model Verificaiton
EbNo vs. BER/SER under AWGN
BPSK vs. QPSK
Theory vs. Simulation
AWGN vs. Flat Fading Channel
Most files are written by myself, enjoy it.
Figures are attached.
We simulate uncoded BER of BPSK modulated
data as a function of SNR
-in an AWGN channel
-in a Rayleigh fading channel
-in an AWGN channel when direct sequence spreading
is used
and compare results to the theoretical ones.
We assume coherent receiver and perfect
synchronization.
A combined space鈥搕ime block coding (STBC) and eigen-space tracking
(EST) scheme in multiple-input-multiple-output systems is
proposed. It is proved that the STBC-EST is capable of shifting
hardware complexity from the receiver to the transmitter without
any bit error rate (BER) performance loss. A computation efficient
EST algorithm is also proposed, which makes the STBC-EST affordable.
Simulation results show that the STBC-EST with a modest
feedback requirement results in a negligible BER performance loss
compared with a dual system configuration.
MATSNL is a package of MATLAB M-files for computing wireless sensor node lifetime/power budget and solving optimal node architecture choice problems. It is intended as an analysis and simulation tool for researchers and educators that are easy to use and modify. MATSNL is designed to give the rough power/ lifetime predictions based on node and application specifications while giving useful insight on platform design for the large node lifetime by providing side-by-side comparison across various platforms. The MATSNL code and manual can be found at the bottom of this page. A related list of publications describing the models used in MATSNL is posted on the ENALAB part of the 2 project at http://www.eng.yale.edu/enalab/aspire.htm
