## 2 Related Work
Depending on these constraints, up to 25 channels of 20 MHz are available in the US and up to 19 in Europe, enabling configurations such as six non-overlapping 80 MHz channels or two 160 MHz channels. The 6 GHz band, newly allocated to Wi-Fi under Wi-Fi 6E and further expanded in Wi-Fi 7, offers a significantly broader spectral window, supporting up to 59 channels of 20 MHz and up to three non-overlapping 320 MHz channels. The figure also highlights regional differences in spectrum allocation, marked with European and US flags and corresponding frequency boundaries. This expanded availability of unlicensed spectrum underpins the deployment of high-throughput, low-latency wireless links for applications in industrial automation, multimedia streaming, and mobile connectivity. From a theoretical point of view, the capacity gains associated with wider channels are governed by the Shannon-Hartley theorem, which defines the upper bound of the achievable data rate as a function of channel bandwidth \(B\) and signal-to-noise ratio (\(SNR\)). The channel capacity \(C\), in bits per second, is given by Equation (2). \[C=B\cdot\log_{2}(1+\text{SNR})\quad[\text{bps}] \tag{2}\]  
This relationship shows that, under constant SNR, increasing the bandwidth directly increases the theoretical capacity. However, it also results in a proportional rise in noise power, which can degrade SNR if the received signal power is not adjusted accordingly [23]. This highlights a key trade-off between throughput and link robustness in practical wireless systems. This relationship is reflected by Equation (3). \[\text{SNR}_{\text{dB}}=P_{\text{rx}}-N_{0}-10\log_{10}(B) \tag{3}\]  
Figure 1: Spectral allocation of 20 MHz Wi-Fi channels and their aggregation into 40, 80, 160, and 320 MHz bonded groups across the 2.4 GHz, 5 GHz, and 6 GHz frequency bands [22]. where \(P_{\text{rx}}\) is the received power in dBm, \(N_{0}\) is the noise power spectral density, and \(B\) is the bandwidth in hertz. As bandwidth increases, the term \(10\log_{10}(B)\) grows, effectively reducing the SNR unless the transmission power or antenna gain is increased accordingly. Moreover, the received power \(P_{\text{rx}}\) itself decreases with distance, which further impacts the SNR in real deployments. This effect is commonly described using the log-distance path loss model in Equation (4). \[\text{PL}(d)=\text{PL}(d_{0})+10n\log_{10}\left(\frac{d}{d_{0}}\right)+X_{ \sigma} \tag{4}\]  
In Equation (4), \(\text{PL}(d)\) represents the path loss at a given distance \(d\), \(\text{PL}(d_{0})\) is the path loss at a reference distance \(d_{0}\), \(n\) is the path loss exponent that depends on the environment (e.g., indoor, urban, and open space), and \(X_{\sigma}\) accounts for random shadowing effects. As the transmitter-receiver distance increases, the path loss increases logarithmically, leading to a lower received power and therefore to a lower SNR. These effects illustrate some key challenges in Wi-Fi systems. Although increasing bandwidth improves capacity, it also makes the link more sensitive to distance, obstacles, and interference. Maintaining reliable high-throughput connections over wider channels therefore requires the careful tuning of transmission parameters, the use of robust modulation schemes, and, in some cases, additional infrastructure support [24].