 power ratio (absolute power ratio, not in decibels). Equation (4.11) gives a theoretical limit for the data rate with an arbi- trarily low error rate when an arbitrarily long error correction code is used. It also assumes that the signal has a Gaussian distribution as does the noise, which is not the case in practice. The influence of bandwidth and noise in the case of binary and multiple value signaling is summarized in Figure 4.15. The signal power and, thus, the highest value of the signal are always restricted to a certain maximum value. Then, the more symbol values we use, the closer they are to each other, and the lower noise level can cause errors. Thus, a higher bit rate requires a wider bandwidth that allows a higher symbol rate. Alternatively, a better S/N is required to allow for more symbol values. The example in Figure 4.15 shows what happens to the distance between symbol values when the maximum amplitude is A and four symbol values are used instead of binary symbols that have only two values. In our examples we have used symbols with different amplitudes. This transmission scheme is called PAM, as discussed earlier. Transmission of this type of pulses without CW modulation is called baseband transmission. In radio systems or modems that use CW modulation, different phases of a carrier wave represent different symbol values. In the Figure 4.8 and 4.9 digital phase modulation methods, BPSK, QPSK, and 8-PSK all require the same bandwidth if symbol rate is the same, but the information data rate for QPSK is double and for 8-PSK triple compared with BPSK. The cost we 4-level Binary Makes bit rate signal signal double through the same bandwidth Maximum theoretical C = Information data rate, bps channel capacity: C Blog (1 + S/N) B = Channel bandwidth, Hz S/N = Signal to noise ratio, absolute power ratio (not in dB) Figure 4.15 The maximum capacity of a transmission channel. Introduction to Telecommunications Network Engineering have to pay is reduced noise tolerance because signals become closer to each