# Channel Access in Wireless Smart Grid Networks Operating under ETSI Frame-Based Equipment Rules
## 6 Conclusions  
In this paper, we have analyzed the performance of FBE channel access mechanisms and provided the following contributions. First, we have implemented, validated, and released a fully functional open-source discrete-event simulator which can be used to study the performance of FBE and its variants. Second, with this simulator, we performed a detailed investigation of FBE homogeneous networks with optimized and non-optimized node parameters as well as an analysis of the coexistence of FBE variants. Third, based on our research results, the following general conclusions can be drawn:  
* Variants which follow a strict periodicity of fixed frame periods (standard FBE, fixed-muting FBE, random-muting FBE) cannot operate with synchronized COTs, because this leads to low channel access probabilities, and in the extreme case (saturated network) to a lack of successful transmissions. In such a situation, synchronized nodes attempt to transmit at the same time, and the problem of constant collisions occurs. Of all the variants studied, only our adaptation of deterministic-backoff in FBE requires such synchronization. Otherwise, DB FBE is not able to fully perform and force contending nodes to follow the expected round-robin scheme. * Deployment of FBE networks with standard FBE, fixed-muting FBE, random-muting FBE, and floating FBE variants requires a detailed analysis of proper parameter selection to eliminate potential issues with a node or group of nodes that completely dominate access to channel resources. * Observing the design of floating FBE, it seems to be a variant that comes with an out-of-the-box solution for single-node domination. However, we observe that there are some edge cases in which a single floating FBE node can dominate the channel. Moreover, the random offset inside floating FBE's FFP hinders proper synchronization with an NR-U slot boundary. * Comparing results for homogeneous networks with optimized and non-optimized parameters, we conclude that FBE networks require some kind of external controller responsible for selecting and updating parameters for each node newly attached to the wireless network. It was shown that, in the optimized parameter case, all presented FBE variants perform well and achieve consistently high fairness. In the non-optimized scenario, each new node increases the possibility of network desynchronization, which leads to a complete waste of channel resources. The BITR FBE and greedy-enhanced FBE variants seem to be the most resistant to uncontrolled environments. \begin{table}
\begin{tabular}{l l l l} \hline \hline
**Variant** & **Mean Channel Efficiency** & **Mean Fairness** & **Mean Variant Airtime** \\ \hline Standard FBE & 0.98 & 0.5 & 0.98 \\ Fixed-Muting FBE & 0.77 & 0.85 & 0.41 \\ Random-Muting FBE & 0.76 & 0.88 & 0.42 \\ Floating FBE & 0.77 & 0.72 & 0.20 \\ Enhanced FBE & 0.72 & 0.61 & 0.06 \\ Greedy-Enhanced FBE & 0.92 & 0.67 & 0.62 \\ BITR FBE & 0.87 & 0.76 & 0.38 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary of coexistence performance in the studied heterogeneous networks. The channel efficiency refers to the overall airtime observed in scenarios which had the competing variant, while the variant airtime refers only to the airtime used by the given variant. * In coexistence scenarios, standard FBE with perfect node coordination and under optimal parameters can completely dominate other variants. The feature of muted periods added in fixed-muting and random-muting FBE increases the transmission opportunities of other variants. In general, the following pairs of variants exhibit good coexistence: fixed-muting with random-muting FBE and BITR with floating FBE. * In the case of variants that introduce backoff, the lack of handicap after unsuccessful CCA in enhanced FBE results in the lowest performance, while idle time reduction in BITR FBE improves its fairness and coexistence abilities. In direct comparisons between these variants, GE FBE takes the most channel resources due to its aggressive channel sampling.