This paper proposed an iterative soft interference canceller (IC) referred to as turbo equalizer for the self-coherent detection, and extrinsic information transfer (EXIT) chart based irregular low density parity check (LDPC) code optimization for the turbo equalizer in optical fiber short-reach transmissions. The self-coherent detection system is capable of linear demodulation by a single photodiode receiver. However, the self-coherent detection suffers from the interference induced by signal-signal beat components, and the suppression of the interference is a vital goal of self-coherent detection. For improving the error-free signal detection performance of the self-coherent detection, we proposed an iterative soft IC with the aid of forward error correction (FEC) decoder. Furthermore, typical FEC code is no longer appropriate for the iterative detection of the turbo equalizer. Therefore, we designed an appropriate LDPC code by using EXIT chart aided code design. The validity of the proposed turbo equalizer with the appropriate LDPC is confirmed by computer simulations.

This paper proposes an iterative cancellation technique for adjacent channel interference (ACI), induced by amplifier nonlinearity in millimeter wave (mmW) communication systems. In mmW communications, a large spectrum leak is expected because of the amplifier nonlinearity, and such a spectrum leak disturbs multichannel utilization. In order to mitigate the ACI, iterative interference cancellation in the receiver side is designed in this paper. Typically, iterative interference cancellation is conducted by generating a soft replica of interference from the feedback of the decoder, and subtracting the replica from the received signals. In this case, the canceller must know the amplifier nonlinearity in order to regenerate a soft replica of ACI. In this paper, amplifier nonlinearity is estimated by subjecting the received pilot signals to polynomial regression. We reveal that using only pilot signals in estimating amplifier nonlinearity is insufficient for guaranteeing replica accuracy. To address this issue, the proposed scheme exploits the detected data sequence in the regression analysis. We demonstrate that the proposed ACI cancellation technique can effectively mitigate ACI in multichannel utilization.