# A Wideband Digital Pre-Distortion Algorithm Based on Edge Signal Correction
## 3 Simulation Results and Analysis  
This section presents a comprehensive simulation analysis of the proposed band-limited digital pre-distortion (DPD) algorithm incorporating edge signal correction, with a focus on evaluating linearization performance through Error Vector Magnitude (EVM) metrics. The study systematically compares the algorithm against four established band-limited DPD implementations: an uncompensated system, the Band-Limited DPD (BLUPDD) from reference [13], Down-Sampling DPD (DSDPD) from reference [2], and the conventional Memory Polynomial DPD (MPDPD) architecture. The experimental framework employs 5G NR-compliant 256 QAM modulated signals with 100 MHz bandwidth, while the power amplifier (PA) emulation utilizes a Doherty configuration to replicate realistic non-linear characteristics and memory effects.  
Figure 2 illustrates the power spectral density (PSD) profiles of PA output signals across the five configurations. Detailed spectral analysis reveals that the proposed algorithm achieves a 15.6 dB reduction in secondary channel power within the 80-180 MHz frequency offset range compared to the non-pre-distorted system. When benchmarked against existing DPD solutions, the method demonstrates superior spectral containment with 6.3 dB, 4.1 dB, and 9.0 dB improvements over BLDPD, DSDPD, and MPDPD, respectively. This enhanced spectral leakage suppression originates from the edge correction mechanism, which dynamically adjusts signal transition regions through adaptive windowing techniques, effectively mitigating Gibbs phenomena caused by abrupt signal truncation.  
Quantitative performance evaluation under identical linearization bandwidth constraints, as detailed in Table 1, confirms significant EVM improvements. The EVM of the proposed DPD is 0.512%, which is 59.4% lower than that of the baseline BLDPD solution (0.864%), and 40.7% higher than that of the DSDPD (1.112%). When contrasted with traditional MPDPD architectures (1.262%), the EVM enhancement reaches 59.4%, while the uncompensated system (3.281%) shows an 84.4% error reduction. These advancements stem from two key innovations: (1) The integration of cross-term parameters establishes a multi-dimensional feature space that enhances memory effect modeling accuracy, particularly for wideband signals. (2) The edge correction module uses non-linear phase compensation to maintain the integrity of the signal at the time boundary and reduce the spectral splatter in the power measurement of adjacent channels.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Algorithm Used** & **EVM (\%)** & **Improvement vs. Proposed DPD** \\ \hline No DPD & 3.281 & 84.4\% \\ MPDPD Model & 1.262 & 59.4\% \\ DSDPD Model [2] & 1.112 & 54.0\% \\ BLDPD Model [13] & 0.864 & 40.7\% \\ Proposed DPD & 0.512 & - \\ \hline \hline \end{tabular}
\end{table}
Table 1: EVM comparison under the same linearization bandwidth.  
Figure 2: Power spectral density comparison.  
These findings substantiate the algorithm's dual capability in spectral efficiency enhancement and signal fidelity preservation, offering a viable solution for emerging wideband communication systems where spectral containment and power efficiency are paramount. The technical approach provides valuable insights for addressing non-linear distortion challenges in millimeter-wave massive MIMO deployments and next-generation terahertz communication prototypes.