The resource allocation in vehicle-to-everything (V2X) communications face a great challenge for satisfying the heterogeneous quality of service (QoS) requirements of the ultra-reliable safety-related services and the minimum throughput required entertainment services, due to the channel uncertainties caused by high mobility. In this paper, we first consider an optimistic scenario where the distribution of uncertain channel state information (CSI) can be deterministic and accurately known at the eNB. Then, a low-complexity resource allocation approach is developed, in which the probabilistic QoS constraint of V2V is transformed into a computable optimization constraint. To deal with the scenario with unknown uncertain CSI distribution, we develop a distributionally robust resource allocation approach for converting the intractable chance constraint of V2V into a deterministic semidefinite constraint based only on the first- and second-order moments of uncertain CSI. For alleviating the conservatism of above approach, a support-based distributionally robust resource allocation approach is developed to tighten the semidefinite constraint by utilizing the support information of uncertain CSI. Finally, we conduct simulations to show that the effectiveness of the proposed approaches outperforms other state-of-art approaches.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Electrical and Electronic Engineering
- Applied Mathematics