提出了一种基于MUSIC算法的子空间扩频码估计算法。该方法通过对接收信号进行特征值分解,并将特征序列映射为子空间的形式,然后采用MUSIC算法寻找一切可能的扩频码序列,最后运用线性解相关检测器对得到的所有扩频码序列进行排错。这样就可以找到所有活动用户,并检测出活动用户的扩频码和信息码,及其用户功率,完成多用户检测。仿真表明,该算法能精确地估计出活动用户的扩频码和用户功率,有优异的误码率性能,在实际应用中有很大的价值。
Presented an algorithm based on subspace spread spectrum code estimation.Performed EVD(eigenvalue decomposition) on the received signal,and projected all the signature sequences onto the subspace,and then applied MUSIC algorithm to seek all possible spread spectrum codes.Then,applied decorrelator reiceiver to do false exclusion on the spread spectrum codes which had been gotten by MUSIC algorithm.Thus,it could find all the active users,and detect the active users' information codes,spread spectrum codes and users' power.Simulation results show that the spread spectrum codes and users' power can be estimated correctly,the estimated information codes have good bit error rate performance.So it has a great value in practical application.