Mixed numerologies interference analysis and inter-numerology interference cancellation for windowed OFDM systems

Extremely diverse service requirements are one of the critical challenges for the upcoming fifth-generation (5G) radio access technologies. As a solution, mixed numerologies transmission is proposed as a new radio air interface by assigning different numerologies to different subbands. However, coexistence of multiple numerologies induces the inter-numerology interference (INI), which deteriorates the system performance. In this paper, a theoretical model for INI is established for windowed orthogonal frequency division multiplexing (W-OFDM) systems. The analytical expression of the INI power is derived as a function of the channel frequency response of interfering subcarrier, the spectral distance separating the aggressor and the victim subcarrier, and the overlapping windows generated by the interferer's transmitter windows and the victim's receiver window. Based on the derived INI power expression, a novel INI cancellation scheme is proposed by dividing the INI into a dominant deterministic part and an equivalent noise part. A soft-output ordered successive interference cancellation (OSIC) algorithm is proposed to cancel the dominant interference, and the residual interference power is utilized as effective noise variance for the calculation of log-likelihood ratios (LLRs) for bits. Numerical analysis shows that the INI theoretical model matches the simulated results, and the proposed interference cancellation algorithm effectively mitigates the INI and outperforms the state-of-the-art W-OFDM receiver algorithms

PAPR reduction using iterative clipping/filtering and ADMM approaches for OFDM-based mixed-numerology systems

Mixed-numerology transmission is proposed to support a variety of communication scenarios with diverse requirements. However, as the orthogonal frequency division multiplexing (OFDM) remains as the basic waveform, the peak-to average power ratio (PAPR) problem is still cumbersome. In this paper, based on the iterative clipping and filtering (ICF) and optimization methods, we investigate the PAPR reduction in the mixed-numerology systems. We first illustrate that the direct extension of classical ICF brings about the accumulation of inter-numerology interference (INI) due to the repeated execution. By exploiting the clipping noise rather than the clipped signal, the noise-shaped ICF (NS-ICF) method is then proposed without increasing the INI. Next, we address the in-band distortion minimization problem subject to the PAPR constraint. By reformulation, the resulting model is separable in both the objective function and the constraints, and well suited for the alternating direction method of multipliers (ADMM) approach. The ADMM-based algorithms are then developed to split the original problem into several subproblems which can be easily solved with closed-form solutions. Furthermore, the applications of the proposed PAPR reduction methods combined with filtering and windowing techniques are also shown to be effective