Iterative interference cancellation and channel estimation for coded OFDM-CDMA

In recent years, spectral efficiency has become a key parameter in mobile radio communications. For Code Division Multiple Access systems, high spectral efficiencies can only be achieved by the application of multi-user detection schemes combatting the inherent multi-user interference. This paper analyzes the system performance of a quasi-synchronous OFDM-CDMA uplink for nonlinear successive interference cancellation (SIC). Realizing that channel estimation is crucial for the performance of interference cancellation schemes, their iterative structure is exploited for improving channel estimation as well as SIC significantly. First, it is shown that convolutional codes with low memory perform much better for extremely high system loads than codes with large memory. Furthermore, correlative, maximum likelihood (ML) channel estimation as well as iteratively improved ML estimation are compared. Simulation results demonstrate that the loss compared to the single-user bound with perfect channel knowledge amounts only 0.7 dB even for loads of β = 2, QPSK modulation and real channel estimation.