針對有限去程網路的節能雲端無線接取網路所設計之混合式使用者連線和資源分配機制

Abstract

為了減少溫室效應，高網路能源效益(Energy Efficiency, EE)在通訊系統上逐漸被視為一項研究指標。因此，本論文探討藉由頻譜資源與基地台傳輸功率的資源分配，來抑制小型基地台網路的同頻帶干擾。除此之外，在雲端無線接取網路(Cloud Radio Access Network, C-RAN)架構下，一群小型基地台可以由一個中央小型基地台(Central Small Cell, CSC)和數個遠端小型基地台(Remote Small Cells, RSCs)。考量所有遠端小型基地台可以被一個中央小型基地台集中式控制可以達到協作的功能，分離媒體存取控制(Split Medium Access Control, Split MAC)的功能切割使得中央小型基地台擁有排程器以及遠端小型基地台擁有混合式自動重傳請求的功能。然而，去程網路的頻寬限制對於遠短小型基地台要滿足使用者的服務品質需求有很嚴重的影響。因此，本論文設計控制網路負擔的機制提升網路能源效益。本論文對於區域的小型基地台網路提出了一個基於控制網路負擔之使用者連線和資源分配的演算法(Traffic Control-Based User Association and Resource Allocation, TURA)。並且考量在實際的大規模小型基地台網路系統上，只由一個中央小型基地台來控制多個遠端小型基地台是不可行的。因此本論文提出了混合式之使用者連線和資源分配的演算法(Hybrid Controlled User Association and Resource Management, HARM)，在小型基地台群內，使用基於控制網路負擔之使用者連線和資源分配演算法來降低群集內的干擾並且使用合作式資源競爭(Cooperative Resource Competition, CRC)的方式來消除群集之間的干擾。雖然中央小型基地台各自的執行基於控制網路負擔之使用者連線和資源分配的演算法，中央小型基地台們會藉由學習的演算法，做資源分配的決策機率交換，並且達到相關均衡。模擬結果驗證基於控制網路負擔之使用者連線和資源分配的演算法中負擔控制的機制之效能，以及合作式資源競爭的收斂性。除此之外，基於控制網路負擔之使用者連線和資源分配演算法、混合式使用者連線和資源分配演算法以及合作式資源競爭演算法的效能比較也在本論文中一併分析。雖然基於控制網路負擔之使用者連線和資源分配演算法擁有較高的效能，但其在實際情況下的實現是不可行的。而混合式使用者連線和資源分配演算法在可被實現的情況下，提供了一個可行的效能。

To alleviate green house effect, high network energy efficiency (EE) has increasingly become an important research target in wireless communication systems. Therefore, the investigation for subchannel and transmit power allocation to mitigate the co-tier interference in the small cell network (SCN) is provided. Moreover, triggered by the merits of cloud radio access network (C-RAN), a groups of small cell base stations (SBSs) can be decomposed of a central small cell (CSC) and remote small cells (RSCs). Given that all the RSCs can be centrally controlled by the CSC to achieve the coordination, the split medium access control (MAC)-based functional splitting is adopted for the C-RAN network with scheduler in the CSCs and hybrid automatic repeat request (HARQ) functions left in the RSCs. However, the difficulty of limited fronthaul capacity puts severe impact for the RSCs to satisfy the quality-of-service (QoS) requirements of users. As a result, the traffic control mechanism is designed in this paper to overcome above-mentioned difficulty and obtain better EE performance. The traffic control-based user association and resource allocation (TURA) algorithm is proposed for a centralized resource management of a localized SCN. Consider there is hardware limitation for a CSC, it is infeasible for a single CSC to control all the RSCs in a large scale SCN. Accordingly, this paper proposes a hybrid controlled user and resource management (HARM) scheme, where a CSC centrally performs TURA for the RSCs to mitigate intra-group interference within localized C-RANs and the CSCs among different localized C-RANs conduct a cooperative resource competition (CRC) for inter-group interference alleviation. Although the CSCs in respective groups conduct TURA distributively, the CSCs will reach the correlated equilibrium (CE) by means of their own observations and the probability of taken decision for resource assignments in proposed CRC scheme, which is adopted from the regret-based learning algorithm. Simulation results verify the effect on traffic control mechanism in TURA scheme and the convergence in CRC scheme. Moreover, the comparison of system performance between proposed TURA, HARM, and CRC schemes are also analyzed. It can be shown that the TURA scheme outperforms the other schemes without the consideration of infeasible control ability for numerous RSCs, while the proposed HARM scheme falls a little performance on EE with consideration of feasible implementation.