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| Space
Time Coding : |
| Space-time
coding has received increasing attention because of its ability to
combat fading channels by making use of multiple transmitters or receivers.
The original space-time schemes, both space-time trellis doing (STTC)
and space-time block coding (STBC), assume known or perfect estimated
channel state information (CSI). However for practical implementation,
CSI changes with time and is difficult to estimate, if not impossible.
The focus of research in this field lies in developing new structures
and algorithms, especially non-coherent (without knowledge of channel
phase) and non-CSI ( without knowledge of channel phase or amplitude),
for improved system performance in severe fading channels with both
time and frequency selectivity. Different techniques are explored,
including multiple-symbol detection, iterative decoding with serial
concatenated convolutional coding, OFDM, etc. Detailed explanations
are please referred to our publications. |
| Iterative
Decoding: |
| Error
Correction Coding is a signal transformation designed to withstand
the effects of various channel impairments like noise, fading, and
interferences. Turbo coding is one of these error correction coding
schemes. Turbo code was proposed in 1993 by a group of French researchers.
The performance was so good that lots of researchers were skeptical
of the performance at the first time it was proposed, but since then,
many researchers over the world reproduce the performance and even
develop the scheme. And now it becomes the standard of error correction
codes for the third generation wireless communication systems. Turbo
encoder is a combination of two recursive convolutional encoders whose
outputs are interleaved between each other and transmitted over the
channel. Maximum A Posteriori probability (MAP) algorithms for both
signals transmitted through separate channels perform their decoding
operation iteratively between two decoders, updating the A Posteriori
probability by passing the updated A Priori probability as the algorithms
repeat iterations. Turbo code has been known to perform near the shannon
limit in AWGN (Additive White Gaussian Noise) channel environment.
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| OFDM
Systems: |
| Orthogonal
frequency division multiplexing (OFDM) modulation is a promising technique
for achieving the high bit rates required for a wireless multimedia
service. To reduce the effect of intersymbol interference (ISI) caused
by the dispersive Rayleigh-fading environment, the symbol suration
must be much larger than the channel delay spread. In OFDM, the entire
channel is divided into many narrow subchannels, which are transmitted
in parallel, thereby increasing the symol duration and reducing the
ISI. Therefore, OFDM is an effective technique for combating multipath
fading and for high-bit-rate transmission over mobile wireless channels.
Historical Perspective: Frequency division multiplexing or multitone
systems have been employed in military applications since the 1960's.
The use of Discrete Fourier Transform (DFT) to replace the banks of
sinusoidal generators and the demodulators significantly reduces the
implementation complexity of OFDM modems. This substantial implementational
complexity reduction was attributable to the simple realization that
the DFT uses a set of harmonically related sinusoidal and cosinusoidal
basis function, whose frequency is an integer multiple of the lowest
non zero frequency of the set, which is referred to as the basis frequency.
These harmonically related frequencies can hence be used as the set
of carriers required by the OFDM system. While OFDM transmissions
over mobile communciations channels can alleviate the problem of multipath
propagation, recent research efforts have focused on solving a set
of inherent difficulties regarding OFDM,namely, on reducing the associated
peak-to-mean-power ratio fluctuation, on time and frequency synchronisation
and on mitigating the effects of cochannel interference sensitivity
in mutiuser environments |
| Ultra
Wide Band: |
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| Adhoc
Networks: |
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| Multi
User Detection: |
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| Cross
Layer Optimization: |
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