TABLE OF CONTENTS In Chapter 1, we have outlined that MIMO systems essentially deliver four gains: diversity gain, spatial multiplexing gain, coding gain and array gain. So far, we have extensively covered the first three gains.
In Chapters 1 and 5, we have shown how space-time coding architectures could exploit spatial multiplexing and diversity gains in i.i.d. Rayleigh fading channels.
In Chapter 4, we have illustrated via the mutual information and the diversity-multiplexing trade-off that those gains are significantly affected by the channel correlations and the K-factor under a uniform input power allocation.
In Chapter 6, we have formalized the impact of channel correlations and K-factor on the error performance of codes obtained in Chapter 5 for i.i.d. Rayleigh fading channels, with the result that codes maximizing the spatial multiplexing gain are more affected than codes maximizing diversity.
In Chapter 7, design criteria have been developed to construct robust codes with respect to propagation conditions, without requiring any transmit channel knowledge.
Yet, improving the exploitation of the array gain performance is still possible if the transmitter has some channel knowledge. As already evoked in Chapter 1, channel knowledge is the key to array gain. At the receiver, where perfect channel knowledge is assumed throughout this book, Chapter 1 has detailed the calculation of the array gain for several schemes. At the transmitter, the array gain is a further function of the amount of channel knowledge available. This channel knowledge may be of various kinds. For instance, we may have no channel knowledge...
