Iterative Weighting Factor Estimation Method for Peak Power Reduction with Adaptive Subcarrier-Phase Control in Turbo-Coded Multi-Carrier CDM Systems

In this paper, we propose a weighting factor (WF) iterative estimation method for a turbo-coded multi-carrier code division multiplexing (MC-CDM) system using partial-transmit sequence (PTS) based peak-to-average power (PAPR) reduction, where the transmitter structure in the proposed system is an extended version of the PTS and the systematic bits of turbo-code is adaptively flipped by multiplying WFs so as to reduce PAPR of MC-CDM signal. On the receiver side, WF estimation and error correction are jointly performed with turbo decoding, where WFs are estimated by exploiting the decoding results of two data streams using different spreading code. When PTS like PAPR reduction using 9 clusters is applied to MC-CDM signal with spreading factor of 16, PAPR of the transmit signal at the CCDF of 10^-4 can be reduced by about 2.0 dB, where the number of multiplexed codes is 8. With the proposed method, WF estimation accuracy is improved as the subcarrier modulation level increases. The degradation in block error rate (BLER) performance as compared with case of the perfect WF estimation is about 0.7 dB at BLER=10^-2 for QPSK-MC-CDM signal with PAPR reduction using 5 clusters in attenuated 12-path Rayleigh fading condition. In the MC-CDM system using 64QAM, the proposed method achieves almost the same BLER performance as case of the perfect WF estimation, even when the number of clusters is L = 9.