隨著科技日新月異，多通道通訊已成為近代通訊中的一大熱門議題。在多通道通訊系統中，為因應每一子通道擁有不同增益與雜訊影響，我們必須針對每一子通道決定在該子通道上要採用的調變方式及使用之能量；這是一個調適性調變與能量分配的問題，此問題在文獻中已有人探討，唯隨著子通道數目之增加，此問題之計算量將成指數式急遽增加，而造成實際計算上之無法達成。本論文則是嘗試要將此調適性調變與能量分配的問題之計算量降低。

在本論文中，我們的基本想法乃是在多通道通訊中使用分群機制讓子通道群組化。我們嘗試三個階段之分群與能量回收機制，首先在第一階段初步分群機制中，以通道的頻率響應為分群依據，分群後再計算資料傳輸率之最大化；在第二階段重分群機制中，有機會增加資料傳輸率；在第三階段利用能量回收與能量預算最大之分配，再次有機會使資料傳輸率提高，以及降低位元錯誤率。

在經過模擬實驗後，我們觀察到經由第一階段初步分群，可大大降低計算複雜度，而經由第二階段重分群後，延續初步分群，有機制的重新排列群組間子通道的數目，讓總資料傳輸率提升，接著，第三階段的能量回收與能量預算最大之分配後，則總資料傳輸率將可能再次增加，並且降低位元錯誤率。

The technique of multichannel communication has been intensely investigated in recently years. It offers the feasibility to take into account the different characteristics of different subchannels and thus make the best use of them, typically achieved by adopting adaptive modulation/coding (AMC) schemes and also by power allocation (PA) for the subchannels. One difficulty with the afore-mentioned AMC-PA problem is that the computation complexity becomes prohibitively high as the number of subchannels grows.

In this thesis, we try to reduce the computation complexity in the AMC-PA problem, through a method that we call the grouping scheme, wherein the subchannels are divided into a few groups. The same modulation scheme is adopted for all the subchannels in the same group. The grouping scheme consists of three stages. In the first stage, the subchannels are divided into a few groups, wherein each group consists of all the subchannels whose fading gains are close to each other. Then, a modulation scheme is chosen, according to a data rate maximization algorithm, for each group. In the mean time, the power allocated to each group is also computed. The second stage is regrouping, wherein the modulation of the best subchannel in a group has a chance to be upgraded. The third stage is an energy recycling mechanism, through which the bit error rates are lowered.

Experimental results show that our regrouping mechanism can achieve a data rate very close to the optimum value (achieved when each subchannel is treated as a single group of its own). At the price of this slight decrease in data transmission rate, however, the computation complexity is greatly reduced.

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