Amplitude Clipping and Iterative Reconstruction of MIMO-OFDM Signals with Optimum Equalization

Multi-input multi-output orthogonal frequency-division multiplexing (MIMO-OFDM) has become a promising candidate for next generation broadband wireless communications. However, like a single-input single-output (SISO)-OFDM, one main disadvantage of the MIMO-OFDM is the high peak-to-average power ratio (PAPR), which can be reduced by using an amplitude clipping. In this paper, we propose clipped signal reconstruction methods for the MIMO-OFDMs with spatial diversity, such as space-time and space-frequency block codes (STBC/SFBC). The proposed methods are based on the technique called iterative amplitude reconstruction (IAR) for SISO-OFDM. It is shown that the IAR can be easily employed for the STBC-OFDM, but it cannot be directly applied to the SFBC-OFDM, because the transmitted sequences over different antennas are dependent due to the use of space-frequency code. We propose a new SFBC transmitter for clipped OFDM, which has approximately half the computational complexity of conventional SFBC-OFDM. The proposed clipping preserves the orthogonality of transmitted signals, and the clipped signals are iteratively recovered at the receiver. Further, we theoretically analyze the performance of IAR with optimum equalization, and also provide highly accurate channel estimation of the OFDM with amplitude clipping. Simulation results show that the proposed receivers effectively recover contaminated OFDM signals with a moderate computational complexity.