Radio resource allocation and system-level evaluation for full-duplex systems

Recent studies have shown the feasibility of full-duplex transceivers, which have the potential to double the system spectral efficiency by allowing transmission and reception at the same time on the same frequency. In this paper, we consider the radio resource allocation problem for full-duplex systems that jointly maximize the uplink and downlink sum-rate. The problem is coupled between uplink and downlink channels due to the self-interference. An iterative algorithm is proposed based on game theory by modelling the problem as a non-cooperative game between the uplink and downlink channels. The algorithm iteratively carries out optimal uplink and downlink resource allocation until a Nash equilibrium is achieved. Simulation results show that the algorithm can significantly improve the full-duplex performance comparing to the equal resource allocation approach. Furthermore, the full-duplex system performance is evaluated under different system settings, and it is shown that the superiority of the full-duplex technique over half-duplex is more prominent in cells with lower transmission power and smaller coverage area.