長期演進（Long Term Evolution；LTE）技術為第3代合作夥伴計畫所制定的無線行動網路標準；長期演進技術升級版（Long Term Evolution-Advanced；LTE-A），為LTE的演進版本。在LTE-A新增的技術中，異質網路（Heterogeneous networks；HetNets）是於大型網路內傳輸功率最高的大型基地站（Macro eNB）下，在訊號範圍死角或人口稠密的地方，架設傳輸功率較小的超微型基地站（Pico eNB）、毫微微型基地站（Femto eNB）或中繼站（Relay），提升用戶端的通訊品質。
在異質網路中，當兩種不同的eNB在同時間使用相同頻率傳送訊號給所屬用戶端，且用戶端正好在彼此的傳輸訊號範圍內時，就會產生同頻道干擾（Co-channel Interference）問題，造成用戶端無法準確接收所屬eNB傳送的訊號。本論文針對Macro eNB和Pico eNB之間的同頻道干擾問題進行研究，提出了一個頻寬資源分配方法，稱為運用受害者列表之資源分配（Resource Allocation via Victim list Application；RAVA），來減少同頻道干擾問題。在所提出的方法中，運用參考訊號接收功率（Reference Signal Received Power；RSRP），用戶端以RSRP測量Macro eNB和Pico eNB的訊號強度，並將測量結果回報給所屬eNB，定義出可能遭受同頻道干擾的區域。在資源分配方法裡，將可能受干擾的用戶端所分配到的頻寬資源，記錄在受害者列表（Victim list），利用基地站間的溝通機制，協調受害者列表裡用戶端的頻寬資源配置，避免分配到同時間和同頻率的頻寬資源，減少同頻道干擾發生。經模擬結果顯示，在各效能評估項目上，本論文提出的頻寬資源分配方法能有效減少同頻道干擾發生，提升網路效能。

Long Term Evolution (LTE) is a standard for wireless mobile network from The 3rd Generation Partnership Project Agreement (3GPP). Long Term Evolution–Advanced (LTE-A) is evolutionary version from LTE. LTE-A add some new technologies, one of which is Heterogeneous networks (HetNets). HetNets can build Pico eNB (eNodeB), Femto eNB and Relay whose transmission power is less than Macro eNB in Macro network to improve the communication quality on cell edge or hot spot users. However, when different kind of eNB transmit signals to their UEs (User Equipment) using same frequency at the same time, and two of UEs are in each other's transmission signal range, that will cause Co-channel Interference to make two of UEs can’t accurately receive the transmitted signals from their service eNB.
In this paper, the Co-channel Interference problem between Macro eNB and Pico eNB are investigated, we propose a radio resource allocation method called Resource Allocation via Victim list application (RAVA). In the method, we using Reference Signal Received Power (RSRP) that UEs measures RSRP received from its serving eNB and reports to the eNB, then define an area that may cause co-channel interference. In our resource allocation, we take radio resources down in the Victim list which may cause interference to the UEs. Then we use communication mechanisms between eNBs to coordinate radio resources of UEs which is in the Victim list, to mitigate Co-channel interference. Our simulation results show that RAVA can effectively mitigate Co-channel Interference and improved the network throughput.

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