  In this paper, the security-aware robust resource allocation in energy
harvesting cognitive radio networks is considered with cooperation between two
transmitters while there are uncertainties in channel gains and battery energy
value. To be specific, the primary access point harvests energy from the green
resource and uses time switching protocol to send the energy and data towards
the secondary access point (SAP). Using power-domain non-orthogonal multiple
access technique, the SAP helps the primary network to improve the security of
data transmission by using the frequency band of the primary network. In this
regard, we introduce the problem of maximizing the proportional-fair energy
efficiency (PFEE) considering uncertainty in the channel gains and battery
energy value subject to the practical constraints. Moreover, the channel gain
of the eavesdropper is assumed to be unknown. Employing the decentralized
partially observable Markov decision process, we investigate the solution of
the corresponding resource allocation problem. We exploit multi-agent with
single reward deep deterministic policy gradient (MASRDDPG) and recurrent
deterministic policy gradient (RDPG) methods. These methods are compared with
the state-of-the-art ones like multi-agent and single-agent DDPG. Simulation
results show that both MASRDDPG and RDPG methods, outperform the
state-of-the-art methods by providing more PFEE to the network.
