Algorithm 1 Client Selection Algorithm

1:Input: $Z_k^t=0,\forall k,Y_r^t=0$ 2:Set $X_0^t=⌀,X_a^t=⌀,{\mathcal{X}}^t=⌀$ 3:for $k\in \mathcal{K}$ do 4:    Calculate $I_k^t=P_k^t{Z}_k^t-V\mu q_k^t$ 5:    if $I_k^t\le 0$ then 6:        $X_0^t=X_0^t\cup \left\{k\right\}$ 7:    end if 8:end for 9:Rank the clients in $X_0^t$ according to their ${\tau }_k^t$. Therefore we have ${\tau }_1^t\le {\tau }_2^t\le \dots \le {\tau }_{|X_0^t|}^t$ 10:for $x\in X_0^t$ do 11:    Update $X_a^t=X_a^t\cup \left\{x\right\}$ 12:    Add $X^t$ to ${\mathcal{X}}^t$, i.e., ${\mathcal{X}}^t={\mathcal{X}}^t\cup \left\{X^t\right\}$ 13:    Calculate $J\left(X_a^t\right)={\displaystyle \sum _{k\in X_a^t}}\left(P_k^t{Z}_k^t\right)+P_r^t{Y}_r^t+V{U}^t$ 14:end for 15:Find ${\left(X_a^t\right)}^{*}=arg{min}_{X_a^t\in {\mathcal{X}}^t}\left(J\left(X_a^t\right)\right)$ 16:Return ${\left({\mathit{a}}^t\right)}^{*}$, where ${\left(a_k^t\right)}^{*}=1\{k\in {\left(X_a^t\right)}^{*}\},\forall k$