Near-Optimal Practical Power Control Schemes for D2D Communications in Cellular Networks

Device-to-device (D2D) communication has the potential of increasing the system capacity, energy efficiency and achievable peak rates while reducing the end-to-end latency. To realize these gains, recent works have proposed resource allocation (RA) and power control (PC) approaches that show near optimal performance in terms of spectral or energy efficiency. However, the proposed schemes either consider a single cell environment or assume instantaneous channel state information (CSI) and/or rely on iterative algorithms that require excessive inter-node message exchange and suffer from slow convergence time. For D2D user equipment (UE), we propose a distributed utility optimization based PC scheme that relies on locally available measurement data and is made practical by constraining the number of iterations and the interference caused to the cellular receiver, while legacy UEs employ the standard Long Term Evolution (LTE) PC. We investigate the performance of the proposed PC scheme when combined with two RA schemes that differ in terms of the required channel state information. We find that when properly tuned, this practical PC scheme combined with a RA algorithm that requires limited channel knowledge, not only shows near optimal performance, but it also constraints the impact of D2D communications on the cellular layer.