Traffic Load Based Adaptive Almost Blank Subframe Optimization in LTE-U and WiFi Coexisted Systems

Abstract

Considering the increasing service demand, the long-term evolution (LTE) system can be deployed in unlicensed band to improve the capacity with a low cost for the spectrum acquisition. However, the coexistence of LTE and WiFi systems in unlicensed band is a challenging problem in terms of the quality of service and the fairness of spectrum occupancy. To address this problem, this paper proposes an adaptive almost blank subframe (A-ABS) optimization scheme by considering the traffic loads of two coexisted systems in order to guarantee the overall performance and fairness between LTE and WiFi systems. To quantitatively analyze this problem, we utilize the M/G/1 queuing model to formulate the unlicensed band occupancy process between LTE and WiFi systems. Furthermore, the A-ABS algorithm is designed to dynamically tune the ratio of ABS based on the traffic loads. Simulation results show that our proposed A-ABS optimization scheme can improve the overall performance while ensuring the fairness between LTE-U and WiFi systems in unlicensed band.