For channel estimation without data-induced interference in data-dependent superimposed training (DDST) scheme, the data sequence is shifted by subtracting a data-dependent sequence before added to training sequence at transmitter. The distorted term causes the data identification problem (DIP) at the receiver. In this thesis, we propose two precoding schemes based on previous work. To maintain low peak-to-average power ratio (PAPR), the precoding matrix is restricted to a diagonal matrix. The first scheme is proposed to enlarge the minimum distance between the closest codewords, termed as efficient diagonal scheme. Conditions to make sure the precoding matrix is efficient for M-ary phase shift keying (MPSK) and M-ary quadrature amplitude modulation (MQAM) modulation are listed in this paper. The second scheme pursues a lowest complexity at receiver which means the amount of searching set is reduced. It is a trade-off between the better bit error rate (BER) performance and a lower complexity at receiver. The simulation results show that PAPR have been improved and the DIP is solved in both schemes.