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In single- and multiemitter structures, the con guration of the emitter, base, and collector can in uence the ESD robustness of the homo- or heterojunction bipolar transistor [43,44]. For a single emitter transistor, with a single-side base and single-side collector (e.g., EBC, ECB, and BEC), the current- ow from the emitter-to-base or the emitter-to-collector is asymmetric. The current- ow through the emitter to either element does not distribute symmetrically; this leads to a higher series resistance, base or collector internal voltage drops, current crowding, and nonuniform current ow; this can lead to higher peak current density. Figure 5.1 shows an example of a silicon bipolar transistor. In this gure, a deep trench structure borders the subcollector and collector region. An electrical connection is established between the subcollector and surface implants using a reach-through implant in the extrinsic part of the transistor. In the intrinsic transistor region, the base and collector are under the emitter window forming a one-dimensional vertical pro le. Outside this region, the extrinsic transistor region extends from the intrinsic region to the base and collector
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Select the newly paired BlueSMiRF from the device list and click Edit Serial Ports. You should see a window similar to Figure 4-15. If you do not see the same info, change it so it matches. In Mac OS X, all serial port devices have unique names. For virtual serial ports, the name is constructed from the device type. So in the example BlueRadios-COM0-1, the device type is BlueRadios-COM0 and it s the first one of that type. (COM0 is the first serial channel for BlueRadios; apparently there can be others.) Click OK and the virtual serial port is ready to use.
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10/01-13:14:02.486194 10.10.200.200:2335 -> 10.10.1.1:23 TCP TTL:128 TOS:0x0 ID:15717 IpLen:20 DgmLen:41 DF ***AP*** Seq: 0x52B66966 Ack: 0xA82D73C8 Win: 0x3FEB TcpLen: 20 0x0000: 00 90 92 F8 80 00 00 03 47 8C 73 0A 08 00 45 00 ........G.s...E. 0x0010: 00 29 3D 65 40 00 80 06 00 00 80 96 21 4E CD E8 .)=e@.......!N.. 0x0020: 6F 66 09 1F 00 17 52 B6 69 66 A8 2D 73 C8 50 18 of....R.if.-s.P. 0x0030: 3F EB DF 4E 00 00 64 ..N..d =+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=
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sphere. Incorrect decoding happens when the number of errors produced during transmission is such that the received vector is outside the sphere of radius d and lies in the sphere of another codeword different from c. Incorrect decoding also occurs even if the received vector lies in the sphere of radius d, but another codeword is also inside that sphere. Then, the total error probability is equal to [5] Pe = Ple + Pce (81)
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so the norm of the vector is proportional to its power. By allowing the components of the vector X vary through all their possible values, a hypersphere will appear in the corresponding vector space. This hypersphere is of radius ||X||, and all the possible vectors will be enclosed by this sphere. The volume of this hypersphere is equal to Vol,n = K n ||X||n . As noise is also a signal, it can adopt a vector representation. This signal is usually passed through a lter of bandwidth B and then sampled, and so this set of samples constitutes a vector that represents the ltered noise. This vector will be denoted as N (N1 , N2 , . . . , Nn ), = and if PN is the noise power, then this vector has a norm equal to ||N|| = n PN . Thus, signals and noise have vector representation as shown in Figure 1.13. Noise in this model is additive and independent of (uncorrelated with) the transmitted signals. During transmission, channel distortion transforms input vector X into an output vector Y the whose norm will be equal to ||Y|| = ||X + N|| = n(P + PN ) [2] (see Figure 1.14). (Signal and noise powers are added as they are uncorrelated.)
We express the conditional entropy explicitly in the following theorem. Theorem 4.2.4 Let {Xi } be a stationary Markov chain with stationary distribution and transition matrix P . Let X1 . Then the entropy rate is H (X) =
4 An alternative measure of outage is the outage probability, that is, the probability that the BER exceeds some nominal value BER0 in an OFDM block. The outage probability can also obtained given the per-realization BER in Eq. (11.21).
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