  This letter introduces a novel framework to optimize the power allocation for
users in a Rate Splitting Multiple Access (RSMA) network. In the network,
messages intended for users are split into different parts that are a single
common part and respective private parts. This mechanism enables RSMA to
flexibly manage interference and thus enhance energy and spectral efficiency.
Although possessing outstanding advantages, optimizing power allocation in RSMA
is very challenging under the uncertainty of the communication channel and the
transmitter has limited knowledge of the channel information. To solve the
problem, we first develop a Markov Decision Process framework to model the
dynamic of the communication channel. The deep reinforcement algorithm is then
proposed to find the optimal power allocation policy for the transmitter
without requiring any prior information of the channel. The simulation results
show that the proposed scheme can outperform baseline schemes in terms of
average sum-rate under different power and QoS requirements.
