# CS-FL: Cross-Zone Secure Federated Learning with Blockchain and a Credibility Mechanism
## 5 Experiments and Analysis
### Simulation Setup
According to the 5G NR specifications, CQI values (ranging from 0 to 15) reflect the quality of the channel [31]. Higher CQI values mean better reliability, more bandwidth, and lower latency. In this setup, the normal ENs typically have CQI values between 13 and 15, corresponding to higher SINR, sufficient bandwidth, and lower delays. The malicious ENs, however, have CQI values between 1 and 12, leading to lower SINR, reduced bandwidth, and significantly increased delays. The relationship between CQI and SINR varies in real systems, depending on factors like modulation, coding schemes, and system configurations. According to 3 GPP TS 38.214, CQI values are calculated by measuring the SINR and matching it with modulation and coding schemes (MCS). However, for simplicity in this experiment, a fixed mapping between CQI and SINR is assumed. The mapping is shown in Table 2 below. Channel noise is modeled using the Additive White Gaussian Noise (AWGN) model, and the noise power \(P_{noise,n}\) is calculated using the following formula:  
\[P_{noise}=k\cdot T\cdot B\cdot F \tag{19}\]  
where \(k=1.38\times 10^{-23}\) J/K is the Boltzmann constant, \(T=290\) K is the environmental temperature, \(B\) is the channel bandwidth (determined by CQI), and \(F\) is the noise figure. Normal ENs have \(P_{normal}=10\), while malicious nodes have \(F_{malicious}=20\). The experiment takes place in a single-cell environment with ENs uniformly distributed within a radius \(d=100\) m. The path loss is modeled as:  
\[PL(d)=PL_{0}+10\cdot\tau\cdot\log_{10}(d)+X_{shadow} \tag{20}\]  
where \(PL_{0}=30\) dB is the reference path loss, \(\tau=3\) is the path loss exponent, and \(X_{shadow}\sim N(0,6^{2})\) represents shadow fading. Multipath fading follows a Rayleigh distribution, and the interference power \(P_{interference}\) is caused by co-channel interference from neighboring nodes. Based on this channel model, two common communication scenarios in FL systems are set up:  
* Poor communication attack (PCA): To simulate unstable network conditions, malicious ENs are assigned highly variable CQI values, ranging randomly between 1 and 12. This leads to increased communication delays and higher channel noise. In contrast, normal ENs have CQI values randomly selected from the range of 13 to 15. * Channel cheated attack (CCA): Attackers may periodically manipulate the channel state to bypass certain pre-detection methods of channel quality. In this scenario, CCA nodes intentionally improve the channel quality at the start of a round, and then, during the training phase, the CQI values change from the range of 13-15 at the beginning of the round to a randomly selected range between 1 and 12 during the training phase. \begin{table}
\begin{tabular}{c c c} \hline \hline
**CQI Values** & **SINR Range (dB)** & **Available Bandwidth (MHz)** \\ \hline
0 & \((-\infty,-6.7]\) & 5 \\
1–4 & \([-6.7,-4.7]\) & 10 \\
5–7 & \([-4.7,0]\) & 20 \\
8–12 & \([0,6]\) & 50 \\
13–15 & \([6,+\infty)\) & 100 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Defined mapping relationship between CQI values, SINR range, and available bandwidth. For malicious behavior models, identity forgery, a common issue in blockchain networks, serves as an example:  
* Identity forgery attack (IFA): To simulate the malicious behaviors towards blockchain, attackers forge their ID\({}_{n}\) in specific rounds to undermine the FL system. In this context, these malicious ENs launch DPA attacks after successfully entering the formal training phase of FL. **Parameters Settings. ** A Zone-Chain architecture is set up to simulate a standard EC scenario, including 50 ENs and 5 ZSs. The number of local iterations is 5, and the number of global epochs is 40. The threshold for subjective SCI value is \(\rho\) = 0.3. The number of ENs selected in each round is \(K\) = 25. The factor of GNSS is \(\varepsilon\) = 0.75. The penalty value of SIM is \(P_{t}\) = \(P_{b}\) = 0.3. The maximum waiting time for each round is \(T_{m}\) = 2 (s). For MNIST, \(|D_{test}|\) = 50.