By Tolga M. Duman
Coding for MIMO communique platforms is a finished creation and review to a number of the rising coding concepts constructed for MIMO conversation platforms. the fundamentals of instant communications and primary problems with MIMO channel potential are brought and the space-time block and trellis coding thoughts are coated intimately. different signaling schemes for MIMO channels also are thought of, together with spatial multiplexing, concatenated coding and iterative deciphering for MIMO structures, and space-time coding for non-coherent MIMO channels. sensible concerns together with channel correlation, channel estimation and antenna choice also are explored, with difficulties on the finish of every bankruptcy to elucidate many vital topics.A entire e-book on coding for MIMO thoughts protecting major strategiesTheories and functional matters on MIMO communications are tested in detailEasy to stick with and obtainable for either newbies and skilled practitioners within the fieldReferences on the finish of every bankruptcy for additional readingCan be used comfortably as a study ebook, or a textbook on a graduate or complicated undergraduate point courseThis ebook is aimed toward complex undergraduate and postgraduate scholars, researchers and practitioners in undefined, in addition to participants operating for presidency, army, technological know-how and expertise associations who want to research extra approximately coding for MIMO verbal exchange platforms.
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Extra info for Coding for MIMO Communication Systems
Example text
Furthermore, we briefly review linear dispersion codes. Space-time trellis codes (STTCs), another class of space-time codes, are presented in detail in Chapter 5. These codes are comparable to STBCs in terms of their spatial diversity where both classes of codes can achieve the full spatial diversity for a given number of transmit and receive antennas. Unlike STBCs, the design of STTCs is based on trellises, and thus, in addition to achieving spatial diversity, they achieve coding gains. Since their encoder is represented by a trellis, STTCs are decoded using the Viterbi algorithm, which is more complex than the decoder used for STBCs.
If the channel gain has a non-zero mean, then its absolute value is Rician distributed, and the channel is said to be Rician fading. Let us denote the channel gain by a complex random variable h, where |h| is the absolute value of the channel gain, and φ = ∠h is the channel phase. 10) where Pr is the average channel power (due to path loss and shadowing), and the phase term φ is a uniform random variable on (0, 2π). f. 11) where I0 (·) is the zeroth order modified Bessel function of the first kind, and K is the Rician factor, which denotes the ratio of the power in the line of sight (LOS) (or the specular) component of the channel to the power in the diffuse component.
Some of the studies on ad-hoc and sensor networks are also inherently related to MIMO communications. Although these all are very important subjects, and represent extremely important recent research directions, they are beyond the scope of this book. On a related note, we also would like to point out that multiple access with MIMO communications is also a recent area of study. For instance, there is a large volume of literature on MIMO CDMA and MIMO orthogonal frequency division multiple access (OFDMA) that fall beyond our scope.