為了能在不增加更多能源消耗及排放更多溫室效應氣體的前提下，滿足使用者對於資料量要求的巨幅成長，我們考慮一個由傳統大基地台以及獵能小基地台組成的異質蜂巢式網路，其中每個小基地台都能夠自周遭環境獵集能量並存於電池中，並且每個小基地台只有在儲存電量足夠進行下行資料傳輸時才會進行服務。我們使用應用隨機幾何技術來模擬基地台的佈建，相較於許多文獻為了分析的簡易性將大、小基地台的位置假設為獨立的卜瓦松隨機點程序，我們採用的是具有相關性的小細胞佈建方式，也就是小基地台僅佈建在和大基地台有一定距離以外的地區。雖然使用這樣的部建方式會增加分析上的複雜度，但卻能夠避免由於卜瓦松隨機點程序的假設所導致部分小基地台與大基地台的位置近乎重疊的不合理情況。此外，不同於多數文獻將所有的基地台都視為滿載的簡化假設，我們以基地台為滿足連線用戶頻寬需求的頻寬使用率定義為基地台負載。我們假設獵能小基地台的電池變化為一離散時間馬可夫鏈，並進一步得到整體網路的斷線機率。我們以模擬結果來驗證理論值，並且探討各關鍵參數對於斷線機率的影響。

In order to meet the explosive growth of data traffic without contributing to excessive energy consumption and greenhouse gas emission, in this work, we consider a heterogeneous cellular network (HCN) composed of conventional macro cells and energy harvesting (EH) small cells. It is assumed that each small-cell base station (SBS) is able to store the energy harvested from the environment in the battery and provide services when there is sufficient energy to perform downlink transmissions. To capture the randomness of BS locations, instead of modeling the locations of macro cell BSs (MBSs) and SBSs as two mutually independent PPPs that may result in impractically small distances between the BSs of different tiers, we use a non-uniform small cell deployment, in which the SBSs are not deployed in the locations within a predetermined distance away from any MBS. Besides, we consider a load aware model and take the user's throughput requirement into consideration, which is more reasonable for a lightly loaded network. The network outage probability is derived by modeling the battery dynamics of an arbitrary SBS as a discrete-time Markov chain. We provide the simulation results to verify the analysis accuracy and demonstrate the impact of a few key system parameters on the outage probability.

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