  By suppressing repeated content deliveries, wireless caching has the
potential to substantially improve the energy efficiency (EE) of the fifth
generation (5G) communication networks. In this paper, we propose two novel
energy-efficient caching schemes in heterogeneous networks, namely, scalable
video coding (SVC)-based fractional caching and SVC-based random caching, which
can provide on-demand video services with different perceptual qualities. We
derive the expressions for successful transmission probabilities and ergodic
service rates. Based on the derivations and the established power consumption
models, the EE maximization problems are formulated for the two proposed
caching schemes. By taking logarithmic approximations of the l0-norm, the
problems are efficiently solved by the standard gradient projection method.
Numerical results validate the theoretical analysis and demonstrate the
superiority of our proposed caching schemes, compared to three benchmark
strategies.
