Time-varying Channel Estimation and Symbol Detection Using Superimposed Training in OFDM Systems
Wireless Personal Communications: An International Journal
EURASIP Journal on Wireless Communications and Networking - Special issue on OFDMA architectures, protocols, and applications
Pilot design for OFDM with null edge subcarriers
IEEE Transactions on Wireless Communications
Non-redundant precoding and PAPR reduction in MIMO OFDM systems with ICA based blind equalization
IEEE Transactions on Wireless Communications
Linearly time-varying channel estimation for MIMO/OFDM systems using superimposed training
IEEE Transactions on Communications
Nonlinear L2-by-3 transform for PAPR reduction in OFDM systems
Computers and Electrical Engineering
Superimposed training for channel shortening equalization in OFDM
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
Optimal superimposed training sequences for channel estimation in MIMO-OFDM systems
EURASIP Journal on Advances in Signal Processing
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Orthogonal frequency division multiplexing (OFDM) transmission with superimposed training is considered in this paper. One major disadvantage of OFDM is the significant amplitude fluctuations, i.e., high peak-to-average power ratios (PARs). High PARs require large backoff of the average operating power of a radio-frequency (RF) power amplifier (PA) in order to linearly amplify the signal, thus reducing the dc to RF power conversion efficiency. The PAR of the OFDM signal is examined with superimposed training, and its complementary cumulative distribution function (CCDF) is derived. Achievable lower and upper bounds on the CCDF are also determined. In addition, the PAR change is linked to the effective signal-to-noise ratio (SNR) and thus the bit-error-rate (BER) performance under the fixed dc power constraint. Simulation results are presented to illustrate the proposed PAR and power analysis for OFDM with superimposed training.