## 3 Results
### Comparison of OFDM and UFMC  
The parameters for OFDM are derived from the G.9991 standard, utilizing 256 sub-carriers. To ensure a consistent basis for comparison, the parameters for UFMC were then adjusted. This adjustment includes the use of 256 effective subcarriers, organized into 24 sub-bands, each containing 12 subcarriers, with a filter length (L) of 19.  
A set of 10,000 symbols was generated to produce the results presented in Figure 12. The DC bias is set to 0.5, and the graph illustrates the trends for DC-OFDM and DC-UFMC in terms of BER as a function of SNR.  
It can be observed that in general, the UFMC performs better than the OFDM. The difference between the QPSK and 16-QAM for both modulation techniques is the same and is approximately 6 dB of penalty. The observed 6 dB enhancement in UFMC, attributed to its superior spectral efficiency compared to OFDM, may effectively offset the 4 dB loss incurred due to the introduced DC bias.This means that UFMC needs 6 dB of power less than OFDM to achieve the same performance. Furthermore, as we saw the necessity of the 4 dB additional power to make the signal real-valued, this 6 dB gain makes UFMC more energy efficient than its OFDM counterpart. Consequently, the implementation of DC-UFMC demonstrates a significantly improved performance compared to DC-OFDM.  
Figure 12: UFMC and OFDM performance for different constellation sizes with a DC bias of 0.5.  
Due to the analytical computation of the relative spectral efficiency gain between OFDM and UFMC, its result highlights a gain of 16% when the UFMC is used instead of OFDM. To compute this value, the results of the following work were used [33]. The spectral efficiency of UFMC compared to OFDM is defined in Equation (2).  
\[P_{OFDM-UFMC}=100\bigg{(}1-\frac{M_{OFDM}}{M_{UFMC}+(N_{FFT}GI)}\bigg{)} \tag{2}\]  
where \(M_{OFDM}\) is the number of effective subcarriers, \(M_{UFMC}\) is the effective number of UFMC subcarriers, \(N_{FFT}\) is the total number of subcarriers, and \(GI\) is the number of subcarriers used as GI. The effective number of subcarriers refers to those used to carry the data. In terms of complexity, the filtering stage in UFMC is more constitutionally intensive than OFDM. Further studies should be carried on to quantify it, but the most important fact is laid down. Nevertheless, some studies have been carried out to make UFMC's level of complexity the same as OFDM. For example, lightweight IFFT can be introduced in the UFMC transmitter, combining both finite impulse response (FIR) or CIR in our work, and the poly-phase filter structure could be the way to reduce the computational complexity of the transmitter [34]. This is an interesting perspective to further prove that UFMC can improve the performance significantly.  
These promising results increase the relevance of UFMC-VLC for 6G application. The efficient spectrum usage of UFMC allows more devices to connect simultaneously without interference. It also enables faster and more reliable data transmission to the end-user or IoT application. This translates to quicker response times for smart city services such as traffic management, emergency response systems, V2V communications, etc. On the end-user point of view, this means seamless connectivity, whether they are accessing smart city services through smartphones, IoT devices, or other gadgets. Furthermore, the utilization of the existing infrastructure such as LED streetlights for data transmission makes VLC a sustainable and energy-efficient solution for smart cities. By utilizing VLC for communication purposes, cities can reduce energy consumption while simultaneously providing connectivity to residents and visitors.