隨著無線多媒體網際網路應用的日益頻繁，地面微波通訊的應用上日趨重要，由於頻譜之擁擠，世界各國均傾向採用Ka(26~40GHz)波段。不過此一波段信號在地表大氣通道傳播時，容易受到自然環境因素影響，其中又以降雨衰減和植被遮蔽造成的信號衰減情況最為嚴重，所以本文將針對降雨和植被遮蔽的效應進行討論。 在降雨衰減估計部分，即考慮電波在大氣通道中傳播時，雨滴粒子對電波能量所造成的吸收及散射之程度，因此雨滴粒徑分佈便成為估計降雨衰減之重要指標。雨滴粒徑分佈對應於降雨量之研究在多年前即被提出，Exponential、Gamma、Weibull、Lognormal分佈都曾被用來做為雨滴粒徑分佈模型的依據;主要是建立適用的雨滴粒徑分佈模型，我們才能方便準確的使用在雨衰估計的理論中。而在林,2004[14]分析中壢地區之雨滴粒徑分類統計，發現中壢之雨滴粒徑分佈為Gamma分佈。接續著我們討論空間中雨滴顆粒數，因為空間中雨滴顆粒數的多寡會影響到我們利用邁氏(Mie Scattering)來計算雨滴的總消散係數(Total Cross Section)。接著利用雨滴譜儀量測資料擬合出N0(R)的關係式，再將此模型代入雨衰估計理論中，以達成雨衰估計之目的。 在植被遮蔽效應份，特別探討在不同風速下，針對闊葉榕樹進行量測信號穿透和反射的功率機率分布，闊葉榕樹下發現因其幾何結構的關係，所以在不同風速下，其功率機率分佈並不會不同。而信號穿透則針對有效衰減路徑去探討每公尺衰減多少的變化。 With more and more applications in the wireless internet multimedia, the importance of terrestrial microwave communication should be studied and investigated. However, most people tend to apply the frequency in Ka-band (26-40GHz) for the lack of the useful spectra. But the region of Ka-band is sensitive to be influenced by the environment, when it transferred in the atmosphere, especially for the attenuation by the rain or the vegetations. In this study, we will discuss some effects of them. The prediction of rain attenuation due to rain is considered the EM wave propagating through rain drops, the energy of the EM wave will be absorbed and scattered by rain drops, then the raindrop-size distribution (DSD) is the most effective part in the prediction of attenuation. Various raindrop-size distributions have been proposed in a number of recent studies. Exponential、Gamma 、Weibull、Lognormal distribution have been use to be the raindrop-size model. By applying the suitable raindrop-size distribution model, we can calculate the rain attenuation more accurately. Lin [ 14 ] analyzed the raindrop-size distribution in Chung-Li and find out the raindrop-size distribution in Chung-Li following the Gamma distribution. In this study, we consider number of Raindrop, because it will effect TCS(Total Cross Section). Our measurements of rainfall observed is using a distrometer in Chung-Li and fitting parameter N0(R), then use rain attenuation model to calculate attenuation. In the effects of vegetations, the situation of vegetation in different wind speed is considered. We measured signals the transmission and reflection through the broadleaf -tree, and find the relation with wind speed change by statistics calculating. The results show that the probability distributions in different winds are invariable. Finally, we can just care about the path of attenuation rate through the broadleaf –tree inside.
