Accelerating Content Delivery via Efficient Resource Allocation for Network Coding Aided D2D Communications

Abstract

Device-to-device (D2D) communication is one of the emerging paradigms in 5G networks to facilitate ever-increasing demands for local area services. For content delivery, direct transmission via D2D communications among proximity nodes and cooperative content downloading from base stations can enhance system capacity, which on the other hand cause interference to regular cellular networks due to spectrum sharing. Random linear network coding is capable of improving robustness to the varying channel state with severe interference. It also increases collaborative efficiency between users for content sharing. This paper investigates cooperative relaying scheme (RNCC) for cooperative D2D communications, which is aided by the random linear network coding. This is achieved by allocating the downlink resource among multiple cellular users, cooperative relays, and D2D pairs. First a binary integer linear programming-based resource allocation problem is modeled by introducing D2D pairs' clustering concept, which is an NP-hard problem. For the optimal solution, we leverage the branch-and-cut algorithm. While for large scale networks, we contributed a distributed QoS-aware greedy algorithm, which yields close to optimal solution. Our proposed schemes are evaluated via the extensive simulations considering practical scenarios, and the system sum rate results demonstrate an enhancement of ~20% performance in comparison with several other practical strategies in literature, which validates our schemes' effectiveness.

Keywords

• Cooperative device-to-device communication
• network coding
• resource allocation
• content delivery