Algorithm 2 Alternating Direction Genetic Algorithm

Input: $\xi , \eta , P \kappa$, Crossover probability $P_{cross}$, Mutation probability $P_{mutate}$  Output: Channel allocation $\mathit{u}$; Power allocation $\mathit{p}$ Initialization: Initialize population size: 50, max generations: 100, Tolerance: 1 × 10−9 ${\mathit{p}}^{(0)}$, ${\mathit{u}}^{(0)}$; $\alpha$ and $\beta$ randomly, let $t=0$;   repeat    $t=t+1$;    According to fitness function (24) with ${\mathit{p}}^{(\mathrm{t})}$, update ${\mathit{u}}^{(t)}$, through crossover and mutation obtain ${\mathit{u}}^{(t+1)}$;    According to fitness function (25) with ${\mathit{u}}^{(t)}$, update ${\mathit{p}}^{(\mathrm{t})}$, through crossover and muttion obtain ${\mathit{p}}^{(\mathrm{t}+1)}$;    Update $\mathit{p}$, $\mathit{u}$; until $t\ge \max$ generations