$\phi_\text{ext}=55^o$ shows less random fluctuations in the phase than that at $\phi_\text{ext}=40^o$. The estimation of output power and linewidth based on Fig. 3 are in agreement with the analytical results given in and Fig. 4(a) of [@Tingsu_2014TEDI] respectively. As it can also be seen in Fig. 3, the phase noise at large in-plane external field angles degrades significantly, which is in accord with the theoretical linewidth in Fig. 4(a) of [@Tingsu_2014TEDI]. In such cases, where the phase noise is considerable, the simulation does not suffer from any signal discontinuity or convergence issues, thanks to the proposed method used to generate the phase noise. Additionally, noticed from Fig. 3, the DC voltage across the MTJ STO increases as a function of $\phi_\text{ext}$, which is in agreement with Eq.(5) in [@Tingsu_2014TEDI].

To quantify the characteristics of the MTJ STO Verilog-A model as a function of $\phi_\text{ext}$, the time domain signals obtained from the transient simulations (1 $\mu$s) are converted (in Cadence) to the frequency domain using FFT so as to obtain power spectral densities (PSDs) of the signals, which are depicted in . To perform the FFT, a Hamming window of the full waveform length 1 $\mu$s (16384 samples) is employed. This 