Download e-book for iPad: Multiple-Input Multiple-Output Channel Models: Theory and by Nelson Costa, Simon Haykin

By Nelson Costa, Simon Haykin

A whole dialogue of MIMO communications, from thought to real-world applicationsThe rising instant know-how Wideband Multiple-Input, Multiple-Output (MIMO) holds the promise of higher bandwidth potency and instant hyperlink reliability. This know-how is simply now being carried out into and dealing its means into instant criteria comparable to the ever-present 802.11g, in addition to 3rd- and fourth-generation mobile criteria. Multiple-Input Multiple-Output Channel versions uniquely brings jointly the theoretical and useful facets of MIMO communications, revealing how those platforms use their multipath variety to extend channel capability. It offers the reader a transparent knowing of the underlying propagation mechanisms within the wideband MIMO channel, that's basic to the improvement of verbal exchange algorithms, signaling ideas, and transceiver layout for MIMO systems.MIMO channel types are very important instruments in realizing the aptitude profits of a MIMO method. This e-book discusses varieties of wideband MIMO types intimately: correlative channel models—specifically the Kronecker, Weichselberger, and based models—and cluster versions, together with Saleh-Valenzuela, eu Cooperation within the box of clinical and Technical examine (COST) 273, and Random Cluster versions. From basic to complicated, the reader will comprehend the types' mechanisms and the explanations at the back of the parameters. subsequent, channel sounding is defined intimately, providing the speculation in the back of a number of channel sounding options used to sound narrowband and wideband channels. The means of electronic matched filtering is then tested and, utilizing real-life information, is proven to supply very actual estimates of channel profits. The booklet concludes with a functionality research of the dependent and Kronecker models.Multiple-Input Multiple-Output Channel versions is the 1st publication to use tensor calculus to the matter of wideband MIMO channel modeling. every one bankruptcy incorporates a checklist of vital references, together with center literary references, Matlab implementations of key versions, and the positioning of databases that may be used to assist within the improvement of latest versions or communique algorithms. Engineers who're operating within the improvement of telecommunications structures will locate this source helpful, as will researchers and scholars on the graduate or post-graduate point.

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Extra resources for Multiple-Input Multiple-Output Channel Models: Theory and Practice (Adaptive and Learning Systems for Signal Processing, Communications and Control Series)

Example text

In the literature, the wideband MIMO channel is most often assumed to be time-invariant and is expressed using discrete rather than continuous variables (see, for example, Ref. 63). Thus, the wideband SISO channel between each transmit-receive pair can be characterized using the complex channel gain hmn[d ]. 25) to the wideband case, 0 h11 [d] B .. H[d] ¼ @ . hMRx 1 [d] 1 . . h1MTx [d] C .. A: . . . 2 CHANNEL CLASSIFICATIONS 33 The elements of the wideband H-matrix H[d ] are the complex channel gains hmn[d ].

HMRx MTx [d] “Indexed matrix,” a discrete sampling of each of MRx ÂMTx ÂD timedispersive channels represented in matrix form. Unweildy. H-tensor, discrete representation of the time-dispersive MIMO channel. Makes it easier to do linear operations. H-matrix, consisting of MRx ÂMTx constant complex coefficients. Impulse response depends on t, and h(t) changes over time; the delay t is needed to describe this change. Continuous variable. Vector channel with MTx, MRx constant complex coefficients, respectively.

In this case, we say the channel is static. 2 CHANNEL CLASSIFICATIONS 27 yet other instances where the impulse response varies slowly over time. In this case, if the observation period To is short enough such that the impulse response does not change significantly over To, we can also consider it to be constant within the observation period. This is an example of a slow-fading channel. In the literature, we often see the terms static and slow-fading used interchangeably to describe a channel whose impulse response does not vary over time.

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