TEL AVIV UNIVERSITY Gaddi Blumrosen

The JSO algorithm selects an optimal set of the transmitter antenna weights, which
optimizes, in the ML sense, the reception of an OSTBC transmitted code, as a
function of the channel state information and the reliability of the information at the
transmitter. It can be seen as a smart compromise, sometimes simply as a switch,
between OSTBC and BF. As a general ML approach to the problem of weighted
OSTBC transmission, this algorithm is definitely superior to maximization of signal
strength (maximum SNR approaches) where only first SNR moment is used and also
to BF based only on channel correlation (second channel moment) since in slow
fading scenario the nonzero channel mean value, e.g. in Rician channel, can
contribute to performance.
We have studied the JSO algorithm in Rayleigh, Rician and correlated channel fading
and examined, by simulation, its sensitivity to errors in its parameters. We found that
a 10% error is equivalent in Rician fading, according to SNR/BER graphs to 0.3dB
degradation in performance and to 0.2dB in Rayleigh channel. This motivated us for
suggesting a simple approximation function to the exact solution for Rayleigh and
Rice channels which fulfills the same asymptotical properties as the ML optimal
solution.
We have shown that this approximation performs quite close to the optimal JSO
solution for a typical range of channel parameters. With the more manageable and
simpler approximation function, we can easily maintain the behavior of the solution
as a function of CSI parameters and thus the approximation may be used for
implementation and for deriving antenna weights sensitivity to changes in CSI
parameters in a simple manner. The computational benefit of the approximation,
increases with the number of transmit antennas.
Correlated fading causes degradation in performance in both OSTC and BF.
Consequently, JSO for the case of correlated fading, which is a set of non linear
equations, also has degradation in performance. We derived a numeric way for
obtaining the antenna weights for the correlated channel fadings, examined
analytically and by simulation the performance loss of BF, OSTBC and “uncorrelated
fadings JSO” and suggested an approximation to the weights which discard the need
for numerical calculations and should be further studied.
A future work in this field can generalize the approximation for the case of MIMO
channel, add channel coding, simulate the STC techniques derived in this work in
different channel scenarios and standards, study the estimation of the various CSI
parameters as a function of real measurements such as measurement accuracy,
feedback rate and quantization ratio and TDD or FDD.