摘要
研究了短码DS-SS信号的扩频序列及信息序列联合盲估计问题。首先,利用双信息符号周期、间隔一信息符号周期的时间窗对接收信号进行重组,并形成接收信号矩阵。然后,利用奇异值分解联合盲估计信号的扩频序列与信息序列。该算法在失步时间未知、低信噪比条件下利用单一矢量空间盲估计扩频序列和信息序列。不但不受扩频序列类型的限制,而且避免了传统特征值分解盲估计算法利用2个矢量空间组合扩频序列时存在的相位模糊问题,提高了盲估计性能。最后仿真验证了算法的有效性。
The problem of joint blinding estimation of the spread-spectrum sequence and information sequence of DS-SS signals was studied.First,the received signal is divided into double-symbol-period-length temporal vectors,with one-symbol-period overlapping,accumulates of these vectors one by one to form the signal matrix.Then,an operation of singular value decomposition(SVD) may be applied to the matrix to estimate the spread-spectrum and information se-quence jointly.The algorithm makes use of a single vector space to estimate the spread-spectrum sequence and informa-tion sequence blindly,without known the desynchronization time,even in low SNR.The algorithm is not only unaffected by the type of spreading spectrum sequence,but also avoids to solving the problem of the phase ambiguity when use two vectors to reconstruct spread-spectrum sequence,which based on EVD blinding estimate algorithm.So it heightens the validity of blinding estimation.At last,simulation results demonstrate the validity of the algorithm.
出处
《通信学报》
EI
CSCD
北大核心
2012年第4期169-175,共7页
Journal on Communications
关键词
扩频序列
信息序列
奇异值分解
联合盲估计
spread-spectrum sequences
information sequences
singular value decomposition
joint blinding estimation