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The first column indicates the index of the operator The second column indicates which operator is the target of the current operator The third column indicates the name and options of the chosen operator

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these results are in agreement with the simulation results for the desired signal power algorithm in Fig. 10.8, and as D /Sth increases, the outage probability performance improves in the high-CIR range while few changes are observed in the lower-CIR range because the minimum CIR constraint dominates in that range. Similar behavior can also be observed for the outage probability of SSC as given in (10.57) and illustrated in Fig. 10.10. Figure 10.11 compares the outage performance of SC and SSC diversity techniques. As shown in the gure, both schemes provide considerable performance improvement over the no diversity case, especially in the high-CIR range. Finally, note that, as expected, even when using the optimal switching threshold for SSC, SC still clearly outperforms SSC especially in the low-CIR range. 10.4 OUTAGE RATE AND AVERAGE OUTAGE DURATION OF MULTIUSER COMMUNICATION SYSTEMS Outage rate and AOD [43 47] as well as the distribution of the outage duration [48] are also important performance measures of multiuser wireless communication systems. These performance criteria take into account the time correlation properties (i.e., the second-order statistics) of the fading channels and provide as such a dynamic representation of the system outage performance. Assuming that an outage is declared whenever either the output CIR falls below a pre-determined threshold th or the received signal power of the desired user SD falls below another predetermined threshold Sth , the average outage duration T ( th , Sth ) is given by [46, Eq. 8] T ( th , Sth ) = Pout N ( th , Sth ) (10.64)

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Figure 4.4 (a) One of British Telecom's early videophones and (b) a recent mobile "visualphone" developed in Japan.

The process of optimizing SQL queries involves analyzing these plans, determining where the bottlenecks are, and implementing solutions For example, if both of these tables are extremely large, we can create an index on one of them to speed up the JOIN operation In fact, this can even change the type of join used by the optimizer For example, in Oracle, if we create an index on the DEPARTMENT ID column:

reception on antenna i, Es is the M-FSK symbol energy, and Nim , m = 2, 3, , M, i = 1, 2 are complex, zero-mean Gaussian samples with variance 2N0 representing the AWGN on the M frequencies Standard ML detection chooses the transmitted frequency corresponding to the largest of the Wim (n)s [ie, Wmaxi (n) = maxm Wim (n)] Switching Operation The switching between antennas is made from comparison of the maximum output of the square-law detectors to a xed threshold wTi (i = 1, 2) at the end of the symbol time In other words, similar to the binary case, the metric used now for data detection is identical to that used for switching and as such is equivalent to the metric used for antenna selection in post-SC in Ref [200] model 1, and in Refs [198] and [199] The details are as follows.

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At each of the abovementioned uniform sampling instants, a decision is made whereby the channel switch in Fig 997 either remains connected as it was (ie, to the receiver output fed by the same antenna), or switches to the other position (ie, to the receiver output fed by the other antenna) The decision as to whether a channel switch occurs depends on a comparison of the receiver output currently passing through the channel switch with a threshold For example, if at time t = nTs we are connected to antenna 1, that is, if the receiver output passing through the channel switch is Wmax1 (n) = maxm W1m (n), then if Wmax1 > wT1 , the channel switch remains connected to this antenna (until at least the following sample time at t = (n + 1)Ts ) and the data decision is based on Wmax1 .

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