混合型分碼多工蜂巢網路中下行鏈路軟性遞移機制及細胞重組規劃之研究

Abstract

考慮分碼多工無線行動通訊系統，為了在負載非平均分佈的細胞中有效率的利用無線頻譜資源，利用不同大小細胞來建構混合型蜂巢網路是一可行架構。在此種混合型蜂巢網路中，系統容量與細胞服務涵蓋範圍兩者間的互相消長特性，是系統設計中配置無線頻譜所面臨的嚴峻挑戰。此外，由於多媒體訊務的非對稱特性，下行鏈路成為系統容量的限制鏈路。因此，在本論文中，我們特別針對混合型分碼多工蜂巢網路之下行鏈路，設計軟性遞移機制的功率與速率配置方法，以及重新規劃細胞結構，來達成細胞間負載平衡的目標，並抑制系統容量與細胞服務涵蓋範圍的互相消長問題。

首先，我們探討軟性遞移機制對混合型分碼多工蜂巢網路的影響。根據具有不同細胞大小的雙細胞簡化模型，我們分析計算細胞近似容量。分析結果發現，在混合型分碼多工蜂巢系統中，傳統軟性遞移機制的『等量式功率配置法』會導致微細胞功率耗盡的問題，造成系統容量降低。對此，我們提出軟性遞移機制的『連線品質等比例式功率配置法』。我們利用具有多個巨細胞與微細胞的混合型蜂巢網路模擬模型來檢驗系統容量效能。相較於其他軟性遞移機制之功率配置法，模擬結果顯示，『連線品質等比例式功率配置法』可有效達成細胞間功率負載平衡，進而提供較佳的系統容量。此外，若在選擇連線組合時發生量測錯誤，相較於單方傳輸的遞移機制，多方傳輸的軟性遞移機制配合『連線品質等比例式功率配置法』較不易因較差的連線組合而浪費功率而造成大量干擾，系統容量的增益將更加顯著。

接著，我們考慮能提供多速率傳輸的混合型寬頻分碼多工蜂巢網路。由於在細胞邊緣活動的軟性遞移使用者相較於一般使用者通常必須配置較多的功率資源，因此針對多速率軟性遞移之資源配置問題，我們提出了一功率與速率配置法的最佳化機制。設計上，我們將此配置問題定義為一有限制條件的離散整數的最佳化問題，並且提出『結合功率與速率配置機制』。此機制包含了前述所提的『連線品質等比例式功率配置法』及『演進計算之速率配置法』。此配置方式能夠有效簡化計算複雜度過高問題，因此，在真實系統中是可實現的機制。我們利用具有多個巨細胞與微細胞的混合型蜂巢網路模擬模型來檢驗系統容量效能。相較於傳統的功率與速率配置法，此『結合功率與速率配置機制』確實能夠有效降低遞移失敗率，達成較佳的細胞涵蓋率，並且改善系統容量。

此外，由於多樣化多媒體服務活動率與使用者隨機移動的特性，訊務分佈將具有高度的時變特性，下一代蜂巢系統將必須能夠適應此高度時變訊務特性所造成的不均勻細胞負載，且能依據細胞負載狀態重組細胞涵蓋範圍，來動態的建構混合型蜂巢網路，以容納多媒體服務所需的系統容量；然而，若僅藉由調整導向訊號功率來改變細胞涵蓋範圍會有造成系統效能降低的問題。因此我們設計一新型『動態細胞重組配合無線頻譜資源管理』機制來解決此問題，包括：導向訊號功率配置，最大連線功率配置，軟性遞移機制與訊務允諾機制。我們首先將導向訊號功率配置問題模型化約為一馬可夫決策鍊過程，最大化系統容量，並運用『強化學習技術』的『乏析Q-learning』演算法，提出『乏析Q-learning式動態細胞重組機制』，精確估算各個細胞的導向訊號功率準位，並配合連線功率預算分析來動態調整無線頻譜資源管理參數。模擬結果顯示，與固定細胞結構相比，此『動態細胞重組配合無線頻譜資源管理』機制可提供較高的系統容量與細胞涵蓋率。

針對本論文所提出在混合型分碼多工蜂巢網路中的軟性遞移及細胞重組規劃機制，模擬結果顯示『動態細胞重組配合無線頻譜資源管理』機制配合軟性遞移機制的『連線品質等比例式功率配置法』，將可在系統具有高度不均勻細胞負載狀態時達成最佳的功率負載平衡和系統效能。

To utilize radio resources efficiently, the cellular system may deploy mixed-size cells in cellular systems when there exists non-uniform traffic loads among cells. This mixed-size cellular architecture raises some challenging and crucial issues about the radio resource management, in which the system design faces the dilemma between system capacity and service coverage, especially in CDMA cellular networks. Because of abundance multimedia traffics in the downlink, the downlink transmission is generally the capacity-limited direction. In this dissertation, we specialize in the downlink soft handoff mechanisms and cell reconfiguration planning in terms of it power balance characteristics to tackle tradeoffs between coverage and capacity in mixed-size CDMA cellular systems.

We first investigate impacts of the soft handoff in the CDMA system with mixed-size cells because the soft handoff mechanism directly affects the system capacity and coverage via multi-site transmission. Based on a simple analytic approximation for user capacity in a simplified model of two mixed-size cells, results show that unequal power allocation and maximum link power constraint for each active connection of soft handoff in mixed-size CDMA cellular systems are necessary, otherwise the power exhausting problem may occur in congested microcells, in which the microcell has stringent power budget. To tackle this problem, a downlink power allocation mechanism for soft handoff in mixed-size CDMA cellular systems is proposed. It is based on the concept of power balance by unequal power allocation for active links in proportional to the link qualities, which is link proportional power allocation (LPPA) scheme. A simulation model of mixed-size CDMA cellular environment is adopted, and simulation results show that the LPPA scheme outperforms existing schemes because of its excellent capability of power balance. Besides, it shows that the LPPA scheme offers better resistance to occurrences of measurement errors during active set selection.

Next, a soft handoff mechanism in multirate mixed-size WCDMA cellular systems is proposed. Most of previous studies focus on joint power and rate allocation for all users in the homogeneous system with the same-size cells, whereas the possible combinatorial numbers of the solutions are too large to be tractable for optimal allocations. To make system implementation feasible, we emphasize the optimization for multirate soft handoffs by a joint power and rate assignment (JPRA) algorithm to accomplish power balance among cells. The JPRA algorithm contains a LPPA scheme and an evolutionary computing rate assignment (ECRA) method. Compared to existing power allocation schemes with best-effort rate allocation, simulation results show that the JPRA algorithm can reduce the handoff forced termination probability and improve the total throughput, resulting in better cell coverage and higher system capacity.

Finally, to balance traffic loads over cells when there are time-varying traffic load distributions among cells, it is crucial for future multimedia cellular networks to be aware of system situations and to configure mixed-size cells dynamically. The problem of dynamic cell configuration is addressed by observing that dynamically adjusting pilot power alone while not changing other radio resource management algorithms can result in performance degradation. We then propose a novel dynamic cell configuration (DCC) scheme with radio resource management for multimedia CDMA networks via reinforcement-learning technologies. The DCC scheme takes into account pilot allocation, maximum link power allocation, call admission control as well as soft handoff mechanisms. Simulation results demonstrate that the DCC scheme is effective in next-generation situation-aware CDMA networks.