## 5 Discussion  
Compared to conventional receivers, the coordinated multi-input and single-output photonic millimeter-wave communication in W-band using a neural network-based waveform-to-symbol converter demonstrates significant performance improvements in terms of BER and interference resilience. However, there are several areas for future exploration, including the extension of the proposed algorithm to more complex communication scenarios and modulation schemes.  
In this section, we first discuss the application of the proposed receiving algorithm in a multiple-input multiple-output (MIMO) system. By utilizing multiple transmitters and receivers, MIMO systems can significantly enhance the capacity and reliability of communication systems. To extend the proposed algorithm to MIMO systems, we apply it to each receiver. In an MIMO system, each receiver not only receives the target sub-band signal but is also subject to interference from other sub-band signals. To quantify this interference, we introduce the multi-user interference factor (MIF). For the i-th receiver, the algorithm treats other sub-band signals as noise and adjusts the weight of the interference signals using the MIF. The interference power of the j-th sub-band signal on the i-th receiver can be expressed as follows:  
\[\begin{array}{l}\text{MIF}_{\text{ij}}\\ =\frac{\text{Interference power of the j--th sub--band signal on the i--th receiver}}{\text{Power of the target sub--band signal on the i--th receiver}}\end{array}\]  
Here, \(\text{MIF}_{\text{ij}}=0\) indicates no interference, which is equivalent to a single-input single-output (SISO) mode, while \(\text{MIF}_{\text{ij}}=1\) indicates that the interference signal power is comparable to the target signal power, which is equivalent to a multiple-input single-output (MISO) system. To validate the performance of the proposed algorithm in MIMO systems, we conducted further simulation experiments. In the simulations, the first receiver was used to receive the target signal S2, while the second receiver was used to receive the target signals S1 and S3. By setting different MIF values, we observed the BER performance of the system, as shown in Figure 11. The results demonstrate that when the MIF is low, both the NNWSC algorithm and the traditional algorithm can effectively demodulate the target sub-band signals with similar performance. As the MIF increases, the BER also increases, but the performance advantage of the NNWSC algorithm becomes more pronounced.  
While the proposed NNWSC was demonstrated in an NM-CAP system, its underlying principles are generalizable to other modulation schemes, including OFDM. The NNWSC's ability to directly convert received waveforms into symbols makes it a versatile framework that could be adapted to handle challenges such as ICI and ISI in OFDM systems. In such scenarios, the NNWSC could potentially replace or augment traditional equalization techniques, offering improved interference resilience and reduced computational complexity. Future work will explore the application of the NNWSC to OFDM systems, including its performance under different channel conditions and its compatibility with existing OFDM frameworks.