--- a/src/lte/doc/source/lte-design.rst Thu May 03 16:24:48 2012 +0200
+++ b/src/lte/doc/source/lte-design.rst Thu May 03 16:27:39 2012 +0200
@@ -1284,9 +1284,9 @@
MIMO Model
----------
-The use of multiple antennas both at transmitter and receiver side, known as multiple-input and multiple-output (MIMO), is a problem well studied in literature during the past years. Most of the work concentrate on evaluating analytically the gain that the different MIMO schemes might have in term of capacity; however someones provide also information of the gain in terms of received power _[CatreuxMIMO].
+The use of multiple antennas both at transmitter and receiver side, known as multiple-input and multiple-output (MIMO), is a problem well studied in literature during the past years. Most of the work concentrate on evaluating analytically the gain that the different MIMO schemes might have in term of capacity; however someones provide also information of the gain in terms of received power _[CatreuxMIMO].
-According to the considerations above, a model more flexible can be obtained considering the gain that MIMO schemes bring in the system from a statistical point of view. As highlighted before, _[CatreuxMIMO] presents the statistical gain of several MIMO solutions respect to the SISO one. In the work the gain is presented as the cumulative distribution function (CDF) of the output SINR for what concern SISO, MIMO-Alamouti, MIMO-MMSE, MIMO-OSIC-MMSE and MIMO-ZF schemes. Elaborating the results, the output SINR distribution can be approximated with a log-normal one with different mean and variance as function of the scheme considered. However, the variances are not so different and they are approximatively equal to the one of the SISO mode already included in the shadowing component of the ``BuildingsPropagationLossModel``, in detail:
+According to the considerations above, a model more flexible can be obtained considering the gain that MIMO schemes bring in the system from a statistical point of view. As highlighted before, _[CatreuxMIMO] presents the statistical gain of several MIMO solutions respect to the SISO one in case of no correlation between the antennas. In the work the gain is presented as the cumulative distribution function (CDF) of the output SINR for what concern SISO, MIMO-Alamouti, MIMO-MMSE, MIMO-OSIC-MMSE and MIMO-ZF schemes. Elaborating the results, the output SINR distribution can be approximated with a log-normal one with different mean and variance as function of the scheme considered. However, the variances are not so different and they are approximatively equal to the one of the SISO mode already included in the shadowing component of the ``BuildingsPropagationLossModel``, in detail:
* SISO: :math:`\mu = 13.5` and :math:`\sigma = 20` [dB].
* MIMO-Alamouti: :math:`\mu = 17.7` and :math:`\sigma = 11.1` [dB].
@@ -1295,13 +1295,7 @@
* MIMO-ZF: :math:`\mu = 10.3` and :math:`\sigma = 12.6` [dB].
-Therefore the PHY layer implements the MIMO model as the gain perceived by the receiver when using a MIMO scheme respect to the one obtained using SISO one. This allows to reuse the SISO PHY error model and the fading tracing scheme and apply the MIMO model in a transparent way. Moreover, new MIMO schemes can be integrated by updating the gain considered according to their statistical behavior. On this matter, considering the MIMO model defined in the standard (i.e., spatial multiplexing and transmit diversity _[TS36.211]), the gains included are:
-
- * MIMO-Alamouti: :math:`+4.2` [dB].
- * MIMO-MMSE: :math:`-2.8` [dB].
-
-where MIMO-Alamouti is a transmit diversity scheme, while MIMO-MMSE is an implementation of spatial multiplexity.
-
+Therefore the PHY layer implements the MIMO model as the gain perceived by the receiver when using a MIMO scheme respect to the one obtained using SISO one. We note that, these gains referred to a case where there is no correlation between the antennas in MIMO scheme; therefore do not model degradation due to paths correlation.
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