多用戶波束成型和機會式排程於透明階層式蜂巢式系統;Multiuser Beamforming and Opportunistic Scheduling for Transparent Hierarchical Cellular Systems

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题名:	多用戶波束成型和機會式排程於透明階層式蜂巢式系統;Multiuser Beamforming and Opportunistic Scheduling for Transparent Hierarchical Cellular Systems
作者:	何家卉;Ho,Chia-hui
贡献者:	通訊工程學系
关键词:	干擾對齊;用戶排程;感知無線電;迭代注水演算法;Interference alignment;user scheduling;cognitive radio;iterative water-filling
日期:	2014-08-28
上传时间:	2014-10-15 17:03:39 (UTC+8)
出版者:	國立中央大學
摘要:	在感知無線電系統中，用戶都希望傳輸資料到所對應的接收器，但由於主系統的用戶使用頻帶的優先權較大，次系統需要處理對主系統的干擾訊號。近幾年干擾對齊的概念被提出來克服干擾的問題並且達到最大的總傳輸速率，此種方法是利用多天線所提供的空間上的維度來將所有干擾訊號對齊在同一個干擾子空間中，這在多天線系統下是可以被達成。本篇提出一種結合干擾對齊與多用戶迭代注水演算法來設計次系統的預編碼矩陣，由於原始問題為一非凸化問題，本論文利用將預編碼矩陣做變數變換使得干擾條件可以移除，並且可以使用低複雜度的多用戶迭代注水演算法使系統總和速率達到局部最佳解，並透過多用戶排程使系統和速率增加並能同時考慮用戶之間的正交性來抑止次系統本身細胞內的用戶之間的干擾以及防止特定用戶獨佔頻帶而造成某些用戶長時間無法傳輸訊號的公平性問題。最後根據模擬結果得知本篇提出的干擾對齊確實可以增加整個系統的加總和速率，而兩階段的用戶排程方法與其他用戶排程，確實可以使系統的和速率較佳。;The idea of cognitive radio (CR) has embodied concretely in hierarchical cellular systems by deploying an underlying microcellular system to reuse the underutilized spectrum licensed by a macrocellular system. The fundamental challenges for successfully realizing such hierarchical systems are to manage the intercell interference between the macrocell and microcell and to pursue the goal of maximizing the spectrum recycling efficiency. Recently, the idea of interference alignment has been emerged to utilize the spatial dimension offered by multiple antennas to overcome the interference problem and achieve the maximum sum rate performance. In this thesis, we jointly consider antenna beamforming, power allocation, and multiuser scheduling for the secondary system to utilize the uplink spectrum of the primary cell and to concurrently serve multiple secondary users in the uplink. IA is applied to manage the interference from the secondary users to the primary cellular system in a transparent hierarchical cognitive radio (HCR) system. By change of variables, we can remove the IA constraint by absorbing it into the sum rate formula, and the original beamforming problem becomes solvable and the optimal solution can be gotten by using an iterative water-filling approach. The iterative water-filling algorithm transform the multiuser sum rate maximization into a series of single-user sum rate maximizations for each user by regarding all other users’ signals as additional noise at each step. The algorithm finds the single-user water-filling covariance matrix for each step. The sum rate objective is increasing with each water-filling step and the sum rate will converge to a limit. Furthermore, the two-stage user scheduling that makes use of multiuser diversity is investigated to further improve the sum rate performance and the fairness among users via PF rule and orthogonality.
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