When Distributed Outperforms Centralized Scheduling in D2D-Enabled Cellular Networks

Device-to-device (D2D) communications is a promising technique for improving the efficiency of 5G networks. Employing channel adaptive resource allocation can yield to a large enhancement in almost any performance metric of D2D communications (e.g. Energy Efficiency). Centralized approaches require the knowledge of D2D links' Channel State Information (CSI) at the BS level. However, CSI reporting suffers from the limited number of resources available for feedback transmission. Alternately, we propose a distributed algorithm for resource allocation that benefits from the users' knowledge of their local CSI in order to minimize the users' transmission power while maintaining predefined throughput constraint. The key idea is that users compute their local performance metrics (e.g. energy efficiency) and then use a new signaling mechanism to share these values between each other. Under some condition, the performance of this distributed algorithm achieves that of the ideal scheduling (i.e. with a global CSI knowledge of all the D2D links). We describe how this technique can be simply implemented by adapting existing CSI reporting (e.g. in Long-Term Evolution (LTE) systems). Furthermore, numerical results are presented to corroborate our claims and demonstrate the gain that the proposed distributed scheduling brings to cellular networks compared to the best centralized-limited feedback scheduling.