3.5 Clear-Air Multipath Propagation Modeling Techniques by Various Authors
3.5.13 Analysis of Data
Crombie [34] made an attempt to fit a limited equation of the type shown in (3.35) to the data of Table B.1 using linear regression. Equation (3.35) can be written as [34]:
o
o
= ' + + +
log P w log A log w w B log d C log f ,
w (3.37)
where the logarithms are base 10. The multipath fading probabilities shown in Table B.1 are for fades equal to or greater than 20 dB. Thus log w wo is a constant ( = -2), and A is a constant '
Clear-Air Radioclimatological Modeling for Terrestrial Line of Sight Links in Southern Africa Odedina P.K. Aug , 2010 68
representing the effective value of K Q in (3.35) for all paths used. The terms in A and w w can o then be lumped together with:
log A = log A' + log w wo (3.38)
giving;
log P(.01) = log A + B log d + C log f (3.39) The data shown in Table B.1 was analyzed in three groups. The first group contains all the data.
Information about the physical path clearances are missing for paths 14 – 16 (see appendix B). Thus, the analysis is confined to the effects of path length, frequency and beamwidths as discussed in sections 3.5.13(a) and 3.5.13(b). All the paths in this group, except two (i.e. paths 17 and 18 see appendix B) are believed to meet criterion (ii) of section 3.5.12. As a result, a further analysis is made in section 3.5.13(c) of the remaining 16 paths. Finally, analysis is made in section 3.5.13 (d) of the group of data (paths 1–13 together with paths 17 and 18) for which the physical clearance can be estimated. In that analysis, the effects of path clearance are included.
(a) Effects of Path Length and Frequency (All Paths)
Using information in the first three numerical columns of Table B.1 (see appendix B), the linear regression fit yields the coefficient values for A, B, and C shown in Table 3.6.
Table 3.6 Crombie Regression Results – All Paths, d, f, (Model 1) [34]
Coefficient t
A1 = -4.424 F1 = 0.978
B1 = 1.045 1.31 S1 = 0.766 C1 = 1.351 1.11 R = 0.115 12
where t and F are student’s t and the variance ration statistics, respectively, and R is the multiple correlation coefficient. The fraction of the variation of log P(.01), which is due to regression, is equal to R2. Because there are two independent variables and fifteen degrees of freedom, the critical values of t and F for a 5% significance level are 2.13 and 3.68, respectively. Thus the regression is meaningless and the observed data cannot be represented by a model of the type shown in equation (3.35). A comparison between the predicted and measured fading probability is shown in Figure 3.16.
Clear-Air Radioclimatological Modeling for Terrestrial Line of Sight Links in Southern Africa Odedina P.K. Aug , 2010 69
In addition to the use of the F statistic, a convenient means of visualizing the goodness of fit of the regression surface to the data is the standard error, s, given by [34]:
2
i i i
s = P M n k 1 , (3.40)
where Mi and Pi are measured and predicted values of log P(w) for the ith path, n is the number of paths and k is the number of independent variables. With a large sample in which the residuals, Pi – Mi are normally distributed, about 95% of the residuals will lie within ± 2s of the regression surface (measured in the P direction). These values of s are given for this and subsequent calculations.
Figure 3.16 Comparison of observed and predicted probabilities of multipath fading 20 dB for all paths (a) d and f as independent variables (eq. 3.39, Table 3.6) (b) d, f, and as independent variables (Eq. (3.40), Table 3.7) [34]
(b) Effects of Antenna Beamwidth
Crombie investigated the effects of including antenna beamwidth, in view of the inadequacy of using only path length and frequency. The beamwidths of the antennas used on the various paths are listed
Clear-Air Radioclimatological Modeling for Terrestrial Line of Sight Links in Southern Africa Odedina P.K. Aug , 2010 70
in Table B.1 (see appendix B), for both antennas on each path. For analysis, the geometric mean of the two beamwidths was used for the term of the new regression equation:
o
= + +
log P w log A B log d C log f + D log
w (3.41) where = T R . The regression analysis yielded the results shown in Table 3.7 below.
Table 3.7 Crombie Regression Results – All Paths, d, f, (Model 2) [34]
Coefficient t A2 = -10.162
B2 = 2.846 3.32 F2 = 4.29 C2 = 1.939 1.97 S2 = 0.608 D2 = 2.264 3.12 R = 0.479 22
With three independent variables and eighteen data sets, there are fourteen degrees of freedom. Thus, at 5% significance level, the critical value of t is 2.145 and F is 3.34. The overall regression is therefore quite significant (because F2 > 3.34, see Table 3.7) even though the significance of the frequency coefficient is marginal.
(c) Analysis for Paths with Adequate Fresnel Zone Clearance
The data analyzed in section 3.5.13 (b) contain two paths [90] for which the Fresnel zone clearance (criterion No. V of section 3.5.12) may not always be achieved, although the physical clearance is known. Deletion of these paths yields a model for predicting the fading probability of paths with adequate Fresnel zone clearance. Analysis of the remaining data leads to the new set of coefficients shown in Table 3.8. Crombie [34] showed improvement on the fit by deleting the data for the two inconsistent paths as can be seen from comparing Tables 3.7 and 3.8 and Figures 3.16 and 3.17.
Table 3.8 Paths with Adequate Fresnel Zone Clearance – All Paths, d, f, (Model 3) [34]
Coefficient t A3 = -12.230
B3 = 3.096 4.88 F3 = 11.78 C3 = 2.454 3.42 S3 = 0.432 D3 = 3.111 5.53 R = 0.747 22
Clear-Air Radioclimatological Modeling for Terrestrial Line of Sight Links in Southern Africa Odedina P.K. Aug , 2010 71
In this case, there are three independent variables and twelve degrees of freedom. At the 5%
significance level, the critical values of t and F are 2.179 and 3.49 respectively. As clearly shown in Figure 3.17b, the correlation is very marked, being significant at less than 0.5% level. Without the beamwidth term, the regression analysis (Figure 3.17 (a)) gives results which are very similar to those obtained for the whole data set. That is, there is no statistically meaningful dependence of fading probability on the path length and frequency [34].
Figure 3.17 Comparison of observed and predicted probabilities of multipath fading 20 dB on paths with adequate Fresnel Zone clearance (a) d and f as independent variables (Eq. (3.39)) (b) d, f, and as independent variables (Eq. (3.40), Table 3.8)[34]
+ data from Table B.1 (appendix B) 11 GHz data from Lin [93]
11 GHz data from Butler [94]
(d) Effect of Physical Path Clearance
In view of the apparent importance of Fresnel Zone clearance stated above, the use of physical path clearance in some geographical areas, and other indications [30], Crombie did additional analysis using the path clearance term. In this case, the mean height, h, of the line-of-sight (assuming a 4/3 earth radius) above the terrain at the center of the path was the variable used. This data was not available for paths 14, and 15, and the available data for path 16 was uncertain. As a result, these
Clear-Air Radioclimatological Modeling for Terrestrial Line of Sight Links in Southern Africa Odedina P.K. Aug , 2010 72
three paths were omitted, leaving a total of fifteen paths and ten degrees of freedom. The new regression equation now becomes [34]:
o
= + +
log P w log A B log d C log f + D log + E log h
w . (3.42)
The results of the analysis are shown in Table 3.9 and in Figure 3.17 (c).
Table 3.9 Paths with Known Clearance d, f, , h (Model 4) [34]
Coefficient t
A4 = -2.997
B4 = 2.487 5.42 F4 = 20.18
C4 = 0.840 1.49 S4 = 0.298
D4 = 1.190 2.88 R = 0.889 24
E4 = -2.440 -5.89
With four independent variables and ten degrees of freedom, the critical value of F at the 0.5% level is 7.34. Since the value calculated in Table 3.9 above (i.e F4 = 20.18), is much greater than 7.34, the regression is even more significant. The statistical significance of each variable, except f, is also high [34]. Deletion of the fourth variable, h, gives the result shown in Tables 3.10 and Figure 3.17 (b) below.
Table 3.10 Paths with Known Clearance d, f, (Model 5) [34]
Coefficient t A5 = -9.988
B5 = 2.931 3.21 F5 = 3.78 C5 = 1.860 1.72 S5 = 0.635 D5 = 2.171 2.84 R = 0.507 52
In this case, Crombie [34] used fifteen data sets and three independent variables giving eleven degrees of freedom. The critical value of F at the 5% level of significance is then 3.59 and the overall regression is thus significant at this level. The goodness of fit is, however, materially worse than that obtained when clearance is included. Removal of the third variable, , yields similar results to those obtained previously – in the absence of any significant correlation, as shown in Figure 3.18 (a).
Clear-Air Radioclimatological Modeling for Terrestrial Line of Sight Links in Southern Africa Odedina P.K. Aug , 2010 73
Figure 3.18 also shows that inclusion of and h, in the regression equation, reduces the range of uncertainty in the predictions by a factor of about 80.
Figure 3.18 Comparison of observed and predicted probabilities of multipath fading 20 dB for paths with known physical clearance (a) d and f as independent variables (Eq. (3.39)), (b) d, f, and as independent variables (Eq. (3.41), Table 3.10), (c) d, f, , and h as independent variables (Eq. (3.42), Table 3.9) [34].