Distributed Interference and Delay Aware Design for D2D Communication in Large Wireless Networks With Adaptive Interference Estimation

Abstract

We investigate distributed flow control and power allocation strategies for delay-aware device-to-device (D2D) communication underlaying large wireless networks, where D2D pairs reuse the resource blocks of interior cellular users (CUEs). We consider a distributed D2D power allocation framework, where the D2D pairs individually attempt to maximize their own time-average throughput utility, while collectively guaranteeing the time-average coverage probability of CUEs in multiple cells. We design a novel method to compute the individual budget of interference from each D2D pair to CUEs based on stochastic geometry tools. Then, accounting for time-varying channel fading and dynamic D2D traffic arrival, we design a distributed interference-and-delay-aware (DIDA) flow control and power allocation strategy based on Lyapunov optimization and several interference estimation methods. We also analytically derive the performance bounds of D2D pairs, and prove that the coverage probability of CUEs can be guaranteed regardless of the interference estimation error at D2D receivers. Finally, simulation results suggest that adaptive interference estimation methods are preferred and demonstrate that the DIDA strategy achieves substantial performance improvement against alternative strategies.