计算机应用与软件
計算機應用與軟件
계산궤응용여연건
COMPUTER APPLICATIONS AND SOFTWARE
2013年
12期
137-139,169
,共4页
LTE%空间复用MIMO%排序干扰逐次消去%混合检测顺序%最大似然
LTE%空間複用MIMO%排序榦擾逐次消去%混閤檢測順序%最大似然
LTE%공간복용MIMO%배서간우축차소거%혼합검측순서%최대사연
Long term evolution ( LTE)%MIMO spatial multiplexing%OSIC%Hybrid detection sequence%Maximum likelihood
考虑到用户对LTE(Long Term Evolution)系统大容量和高速率的需要,采用了空间复用多输入多输出(MIMO)技术。在对LTE下行MIMO技术的传统接收算法研究的基础上提出一种改进算法。该算法调整排序干扰逐次消去( OSIC)算法的传统检测顺序,采用混合顺序检测。首先逆序检测出最弱信号层,并根据遍历搜索的思想对该层信号进行遍历,然后正序检测剩余信号层,利用最小距离准则来确定发送数据矢量。以QPSK和16QAM调制方式为例,计算机仿真验证了改进算法有效抑制了迭代检测过程中的差错传播,检测性能与最大似然( ML)算法检测效果一致,同时具有较低的计算复杂度,在检测性能与复杂度之间给出了很好的折衷。
攷慮到用戶對LTE(Long Term Evolution)繫統大容量和高速率的需要,採用瞭空間複用多輸入多輸齣(MIMO)技術。在對LTE下行MIMO技術的傳統接收算法研究的基礎上提齣一種改進算法。該算法調整排序榦擾逐次消去( OSIC)算法的傳統檢測順序,採用混閤順序檢測。首先逆序檢測齣最弱信號層,併根據遍歷搜索的思想對該層信號進行遍歷,然後正序檢測剩餘信號層,利用最小距離準則來確定髮送數據矢量。以QPSK和16QAM調製方式為例,計算機倣真驗證瞭改進算法有效抑製瞭迭代檢測過程中的差錯傳播,檢測性能與最大似然( ML)算法檢測效果一緻,同時具有較低的計算複雜度,在檢測性能與複雜度之間給齣瞭很好的摺衷。
고필도용호대LTE(Long Term Evolution)계통대용량화고속솔적수요,채용료공간복용다수입다수출(MIMO)기술。재대LTE하행MIMO기술적전통접수산법연구적기출상제출일충개진산법。해산법조정배서간우축차소거( OSIC)산법적전통검측순서,채용혼합순서검측。수선역서검측출최약신호층,병근거편력수색적사상대해층신호진행편력,연후정서검측잉여신호층,이용최소거리준칙래학정발송수거시량。이QPSK화16QAM조제방식위례,계산궤방진험증료개진산법유효억제료질대검측과정중적차착전파,검측성능여최대사연( ML)산법검측효과일치,동시구유교저적계산복잡도,재검측성능여복잡도지간급출료흔호적절충。
In consideration of the needs of users on LTE system for large capacity and high speed , the multiple-input and multiple-output ( MIMO) spatial multiplexing technology is adopted .We bring forward an improved algorithm in the paper based on studying traditional recep -tion algorithms for LTE downlink MIMO technology .This algorithm makes adjustments on traditional detection sequence of ordered successive interference cancellation (OSIC) algorithm, and adopts hybrid sequence detection .First it detects the weakest signal layer in reverse order , traverses the single layer according to the concept of traversal search;then it detects the remaining signal layers in positive sequence , and uti-lises the minimum distance criterion to determine and transmit the data vectors .Taking QPSK and 16QAM modulation means as examples , the computer simulation verifies that the improved algorithm effectively restrains the error propagation in the progress of iterative detection , and the detection performance is in accord with the detection results of maximum likelihood ( ML) algorithm at low computational complexity . An appropriate trade-off between detection performance and computation complexity is obtained by this improved algorithm .