计算机技术与发展
計算機技術與髮展
계산궤기술여발전
COMPUTER TECHNOLOGY AND DEVELOPMENT
2014年
9期
37-40,44
,共5页
卫星移动信道%正交频分复用%信道估计%最小均方误差%SVD-MMSE
衛星移動信道%正交頻分複用%信道估計%最小均方誤差%SVD-MMSE
위성이동신도%정교빈분복용%신도고계%최소균방오차%SVD-MMSE
mobile satellite channel%OFDM%channel estimation%MMSE%SVD-MMSE
针对卫星移动信道的特点,结合正交频分复用( Orthogonal Frequency Division Multiplexing,OFDM)技术,在卫星移动信道模型基础上分析并讨论了三种典型的信道估计算法,即最小二乘( Least-Square,LS)估计算法、最小均方误差( Mini-mum Mean Square Error,MMSE)估计算法和奇异值分解( Singular Value Decomposition,SVD)算法。采用经典的抽头延迟线模型,对各算法进行仿真试验,得出不同算法下信道估计误比特曲线。理论分析和仿真实验表明,三种算法均能够有效地抑制卫星移动信道衰落产生的误码率,其中SVD-MMSE算法能够在降低MMSE算法复杂度的基础上,抑制噪声,提高信道估计精度。
針對衛星移動信道的特點,結閤正交頻分複用( Orthogonal Frequency Division Multiplexing,OFDM)技術,在衛星移動信道模型基礎上分析併討論瞭三種典型的信道估計算法,即最小二乘( Least-Square,LS)估計算法、最小均方誤差( Mini-mum Mean Square Error,MMSE)估計算法和奇異值分解( Singular Value Decomposition,SVD)算法。採用經典的抽頭延遲線模型,對各算法進行倣真試驗,得齣不同算法下信道估計誤比特麯線。理論分析和倣真實驗錶明,三種算法均能夠有效地抑製衛星移動信道衰落產生的誤碼率,其中SVD-MMSE算法能夠在降低MMSE算法複雜度的基礎上,抑製譟聲,提高信道估計精度。
침대위성이동신도적특점,결합정교빈분복용( Orthogonal Frequency Division Multiplexing,OFDM)기술,재위성이동신도모형기출상분석병토론료삼충전형적신도고계산법,즉최소이승( Least-Square,LS)고계산법、최소균방오차( Mini-mum Mean Square Error,MMSE)고계산법화기이치분해( Singular Value Decomposition,SVD)산법。채용경전적추두연지선모형,대각산법진행방진시험,득출불동산법하신도고계오비특곡선。이론분석화방진실험표명,삼충산법균능구유효지억제위성이동신도쇠락산생적오마솔,기중SVD-MMSE산법능구재강저MMSE산법복잡도적기출상,억제조성,제고신도고계정도。
Aiming at the characteristics of the mobile satellite channel,combined with OFDM technology,analyze and discuss three typical channel estimation algorithm based on the mobile satellite channel model,namely Least Squares (LS),Minimum Mean Square Error ( MMSE) channel estimation algorithm and simplified Singular Value Decomposition ( SVD) channel estimation algorithm. Use the clas-sical tapped delay line model for simulation of all algorithms,obtaining the bit error curve under different channel estimation algorithms. As theoretical and simulation results proved that,the three algorithms are able to effectively suppress the BER of the mobile satellite chan-nel fading,among which SVD-MMSE algorithm has more advantage,it can reduce the complexity of MMSE algorithm and at the same time improve the channel estimation accuracy.
