載波聚合於LTE-A系統之室內位置推薦演算法
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2014
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本論文中,我們解決了一個在長期演進無線網路系統(Long-Term Evolution, LTE-A)毫微微基地台網路(Femtocell network)的下行鏈路(Downlink)中所遭遇的載波聚合(Carrier Aggregation, CA)問題。我們提出了一個從不同角度切入的新概念─位置推薦(Location Recommendation, LR),藉此改善在室內LTE-A系統的載波聚合表現。室內位置推薦(Indoor Location Recommendation, ILR)演算法會建構一個介於微型基地台間無線干擾的先備知識並由此建立一個相對應的服務品質(Quality-of-Service, QoS)地圖,使得用戶能顯而易見地預測在室內中各處所獲取的QoS情形以及分量載波(Component Carrier, CC)的選擇。藉由利用室內定位及QoS地圖,我們所提出的方法可以建議用戶到室內特定的位置以獲取滿足使用額外分量載波的能力和各種服務需求。透過模擬,驗證了所提出的演算法能夠藉由位置的推薦改善在LTE-A系統的載波聚合表現。
In this paper, we tackled the problem of Carrier Aggregation (CA) in downlink of Long Term Evolution Advanced (LTE-A) femtocell networks. We proposed a novel approach from a totally different perspective, location recommendation, for improving the CA performance in LTE-A indoor environments. The proposed Indoor Location Recommendation (ILR) algorithm structures the prior knowledge of radio interference between femtocells to build a Quality-of-Service (QoS) map, enabling users to visualize the predicted QoS levels spatially for Component Carriers (CC) selections. By exploiting indoor positioning and QoS map, the proposed method is cable of suggesting users where to go in order to achieve sufficient wireless link qualities for selecting additional CCs (i.e., secondary CCs) and satisfy various service requirements. We conducted simulations to compare the performance of our proposed scheme with that of other approaches. The simulations demonstrate the ability of the proposed algorithm to recommend use locations for improving the CA performance in LTE-A system.
In this paper, we tackled the problem of Carrier Aggregation (CA) in downlink of Long Term Evolution Advanced (LTE-A) femtocell networks. We proposed a novel approach from a totally different perspective, location recommendation, for improving the CA performance in LTE-A indoor environments. The proposed Indoor Location Recommendation (ILR) algorithm structures the prior knowledge of radio interference between femtocells to build a Quality-of-Service (QoS) map, enabling users to visualize the predicted QoS levels spatially for Component Carriers (CC) selections. By exploiting indoor positioning and QoS map, the proposed method is cable of suggesting users where to go in order to achieve sufficient wireless link qualities for selecting additional CCs (i.e., secondary CCs) and satisfy various service requirements. We conducted simulations to compare the performance of our proposed scheme with that of other approaches. The simulations demonstrate the ability of the proposed algorithm to recommend use locations for improving the CA performance in LTE-A system.
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長期演進計畫, 載波聚合, 毫微微型基地台, 位置推薦, 服務品質, Long Term Evolution Advanced (LTE-A), Carrier Aggregation (CA), Femtocell networks, indoor Location Recommendation (ILR) algorithm, Quality of Services (QoS)