# A Survey of Wi-Fi 6: Technologies, Advances, and Challenges
## 4 OFDMA in Wi-Fi 6
### Related Work
#### 4.3.2 Centralized Approaches  
Access points may execute a centralized scheduling scheme to assign RUs to different users. Some works aimed to maximize efficiency. [PERSON] et al. [51] investigated the impact of the PPDU duration. Indeed, a fixed PPDU means less flexibility. If different stations do not have the same amount of traffic to forward, padding is required. They determine the scheduling duration according to the padding overhead, the airtime fairness, and the energy consumption. The authors demonstrated that their algorithm is close to the optimal strategy through a Lyapunov optimization. The authors of [52] applied a deep reinforcement learning technique to optimize the MAC layer resource allocation. The contending station measures the channel collision probability considering all the observed timeslots between two consecutive backoff stages. Using this probability, it calculates the optimal contention window size. Then, they applied a Q-learning technique to optimize the performance of the mechanism. [PERSON] et al. [53] considered the RU allocation as an optimization problem. The target was to find the best pair of RUs and MCSs for each station. However, Wi-Fi 6 presents specific properties that must be considered during the scheduling process. In particular, Wi-Fi 6 restricts the usage of RUs. For instance, a 106-tone RU cannot be randomly located in a 40 MHz channel. They applied the Hungarian algorithm [54] to compute the most efficient scheduling matrix. Considering this optimization task, they also adapted three LTE schedulers to the Wi-Fi 6 constraints. [PERSON] et al. [55] introduced a utility function for the quality of the RUs considering the number of stations, available RUs, and MCSs. The utility function value is the transmission rate that depends on the RU and the MCS. They used a greedy heuristic to solve the optimization problem. The stations are sorted in descending order according to the utility function. The widest RU is assigned to the first station in the list and this assignment continues until all stations are scheduled. The same round is repeated for the MCS assignment. The following articles focused on maximizing the sum of the rates achieved individually by each of the emitters in the network. The authors of [56] aimed to maximize the utility of the long-term average rates of stations. To do this, they solved the optimal uplink resource allocation problem by employing Lyapunov optimization, respecting the average rate and power constraints. [PERSON] et al. [57] solved a relaxed resource allocation problem via a divide-and-conquer algorithm where a user can be assigned to multiple RUs. However, a station should receive at most one RU for its transmissions, increasing the complexity as the optimal assignment requires an exhaustive search. Thus, two heuristics, greedy or recursive, can help to solve the original assignment problem, allocating one RU per station. An extended version [58] also considered fairness among users. Some papers utilized scheduled and random accesses together. The authors of [59] proposed a hybrid mechanism for channel utilization. They introduced three control packets to collect and send information with limited flexibility in network size. This mechanism was an alternative for TF-R and is now deprecated. In the beginning, the access point acquires the demands and assigns the RUs to the requesting stations. Stations that did not ask for a dedicated resource and have data to send can contend to access the remaining non-allocated RUs. [PERSON] et al. [60; 61] also leveraged a utility metric to maximize utility and user satisfaction. They managed the RU transfer between scheduled and random access users. Moreover, they suggested a scheduling scheme to distribute the RUs by accounting for the probability distribution of multi-cell interference. The authors of [62] proposed hybrid channel access in the channel contention phase to assign the RUs efficiently. In the contention phase, the stations with expired backoff randomly select RUs to send the BSR.