CURT: A Real-Time Scheduling Algorithm for Coexistence of LTE and Wi-Fi in Unlicensed Spectrum

Carrier-Sensing Adaptive Transmission (CSAT) is a major approach from industry to address coexistence between LTE and Wi-Fi in unlicensed bands. Under CSAT, a key problem is the design of a scheduling algorithm to allocate radio resources across multiple channels and a large number of sub-channels. This paper investigates this scheduling problem through an optimization formulation with the objective of minimizing LTE’s adverse impact on Wi-Fi users. This is achieved by optimal allocation of radio resources at channel and sub-channel levels to meet each LTE user’s uplink and downlink rate requirements. Special considerations of channel conditions are given during LTE scheduling. A major challenge here is to obtain an optimal (or near-optimal) scheduling solution on ~1 ms time scale — a stringent timing requirement for the algorithm to be useful in the field. Our main contribution is the development of CURT, a scheduling algorithm that can obtain near-optimal solution in ~1 ms. CURT exploits the unique structure of the underlying optimization problem and decomposes it into a large number of independent sub-problems. These sub-problems can be solved efficiently and in parallel by GPU multi-processors. By implementing CURT on Nvidia GPU/CUDA platform, we demonstrate that CURT can indeed deliver near-optimal scheduling solution in ~1 ms and meet all our design objectives.