information from all the users. NOMA allows multiple users to share the uplink channel simultaneously. The channel coefficient between user k and the PS is hk = Lkho To simplify the analysis, we assume Lk follows the free-space path loss model Lk = Your Let the encoded gradient update st be the transformation from OK in the local update stage. Additionally, we normalize the transmitted symbols 11/5/12 = According to NOMA principle, all the selected K users share the same bandwidth simultaneously. In particular, 9.3 FL Model Update with Adaptive NOMA Transmission all the transmitted signals from multiple NOMA users are superposed [44]. The received signal at the PS at t thus can be expressed as: (9.3) where st is symbolized representation of st at time slot t, n°~CN (0, o2), o2 is noise vari- ance of the received signal. SIC is carried out at the PS side. Specifically, PS decodes the strongest signal first by treat- ing others as interference. After successful decoding, PS subtracts the decoded signal from the superposed signal. The process stops until the PS decodes all the participants' messages. Without loss of generality, we assume p1h2 > p2h2 > Pkh2. Therefore, the achievable data rate for user k is: (9.4) where T > 1 accounts for performance degradation from finite length symbol, imperfect channel estimation, and decoding error, etc. User K is the last decoded user hence its rate At the beginning of each round t, the PS notifies participating users to start the simultane- ous transmission. The maximum number of allowable bits for user k is Mk = BRktk, where B is the system bandwidth, tk is the NOMA transmission duration. The proposed uplink NOMA transmission is shown in Figure 9.1b. 9.3.2 NOMA Scheduling To select K users from a total of N to participate the model update, we should consider both the learning process and the communication process. The selection criterion is decided based on two rules: (1) NOMA fairness; (2) time budget. 1. NOMA fairness: During the PS update, the weighted average is applied, 