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αK(f) = k1 + k2 * f k3 *lThis function is not directly interpretable, but is a phenomenological description. The following are constants determined by the results of measurements:
where
- f is the frequency in Mhz and
- l the length in metres
d=0.35 mm:: k1=7.9 dB/km, k2=15.1 dB/km, k3=0.62
d=0.40 mm: k1=5.1 dB/km, k2=14.3 dB/km,k3=0.59
d=0.50 mm: k1=4.4 dB/km,k2=10.8 dB/km,k3=0.60
d=0.60 mm: k1=3.8 dB/km,k2=9.2 dB/km,k3=0.61.
From these numerical values the following follows.
The attenuation factor αK(f) and the attenuation function αK(f) = α(f) * l depend significantly on the pipe diameter.
The cables laid since 1994 with d=0.35 mm and d=0.5 mm have a 10% greater attenuation factor than the older lines with d=0.4 mm or d=0.6 mm. This smaller diameter, which is based on the manufacturing and installation costs, significantly reduces the range lmax of the transmission systems used on these lines, so that in the worst case scenario expensive intermediate regenerators have to be used.
The current transmission methods for copper lines prove only a relatively narrow frequency band, for example 120 kHz with ISDN and ˜1100 kHz with DSL. For f=1MHz the attenuation factor of a 0.4 mm cable is around 20 dB/km, so that even with a cable length of l = 4 km the attenuation does not exceed 80 dB.
The k-parameters of the attenuation factor αI(f) can be converted into corresponding α-parameters, αI(f): .
αI(f) = k1 + k2 * f k3As a criterion of this conversion, the quadratic deviation of these two functions is assumed to be minimal within a bandwidth B:
αII(f) = α0 + α1 * f + α2 * √f
0∫B[ αI(f) - αII(f)]2df is a minimum
Clearly It is obvious that α0 = k1. The parameters α1 and α2 are dependent on the underlying bandwidth B and are:
α1 = 15 * (B f0)k3 - 1 *k3 - 0.5 (k3 + 1.5)(k3 + 2)*k2 f0
α2 = 10 * (B f0)k3 - 0.5 *1 - k3 (k3 + 1.5)(k3 + 2)*k2 √ f0
Data communication is subject to two theorems or laws, the Nyquist theorem that concerns the exact reproduction of a signal in the absence of noise and assumes.error-free channels and infinite precision in amplitude. The Shannon Law is more realistic in that it considers data rate, bandwidth, noise and error rate,
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