Title :
Partial Transmit Sequences for Peak-to-Average Power Ratio Reduction of OFDM Signals With the Cross-Entropy Method
Author :
Chen, Jung-Chieh
Author_Institution :
Dept. of Optoelectron. & Commun. Eng., Nat. Kaohsiung Normal Univ., Kaohsiung
fDate :
6/1/2009 12:00:00 AM
Abstract :
This letter considers the use of the partial transmit sequence (PTS) technique to reduce the peak-to-average power ratio (PAPR) of an orthogonal frequency division multiplexing (OFDM) signal. The conventional PTS technique can provide good PAPR reduction performance for OFDM signals; however, it requires an exhaustive search over all combinations of allowed phase factors, resulting in high complexity. In order to reduce the complexity while still improving the PAPR statistics of an OFDM signal, a new method using the cross-entropy (CE) method is proposed to reduce both the PAPR and the computational load. In the proposed CE method, we first define a score or fitness function based on the corresponding PAPR reduction performance. The score function is then translated into a stochastic approximation problem which can be solved effectively. The simulation results show that the performance of the proposed CE method provides almost the same PAPR reduction as that of the conventional exhaustive search algorithm while maintaining low complexity.
Keywords :
OFDM modulation; approximation theory; entropy; statistical analysis; stochastic processes; OFDM signal; cross-entropy method; optimal phase factor; orthogonal frequency division multiplexing; partial transmit sequence; peak-to-average power ratio reduction; score function; statistical analysis; stochastic approximation problem; Computational modeling; Data communication; Frequency division multiplexing; OFDM; Partial transmit sequences; Peak to average power ratio; Signal processing algorithms; Statistics; Stochastic processes; Wireless communication; Cross-entropy method; orthogonal frequency division multiplexing; partial transmit sequence; peak-to-average power ratio;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2009.2017221