Maximizing D2D-Based Offloading Efficiency With Throughput Guarantee and Buffer Constraint

• Published in: IEEE transactions on vehicular technology Vol. 68; no. 1; pp. 832 - 842
• Main Authors: Qu, Yuben, Dong, Chao, Dai, Haipeng, Wei, Zhenhua, Wu, Qihui
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Buffers; Cellular communication; Cellular networks; Computer simulation; Device-to-device (D2D); Device-to-device communication; Downloading; Efficiency; Interference; linear-fractional programming; Mathematical model; Maximization; offloading efficiency; Optimization; Quality of service; Receivers; Throughput
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2018.2880327

Device-to-device (D2D) based offloading stands out as a promising approach to mitigate the pressure over cellular networks. From the perspectives of both operators and users, an ideal solution is expected to maximize the offloading efficiency (ratio) while guaranteeing the quality-of-service (QoS) of users. However, existing approaches seldom jointly take into consideration offloading efficiency optimization and QoS guarantee. In this paper, we study how to maximize the percentage of total offloaded traffic of mobile content downloading via D2D, while guaranteeing the user minimum throughput under limited buffer size. The major challenge is how to incorporate all potential D2D opportunities to maximize the offloading performance. We propose a spatial-temporal dynamic graph (STDG) to capture all possible D2D opportunities in D2D-based traffic offloading. Based on STDG, we mathematically formulate an optimization problem of maximizing the offloading efficiency, subject to throughput requirement and buffer size constraint. The formulated problem is a linear-fractional problem and can be transformed into an equivalent linear program, whose solution reveals the maximum offloading ability that D2D achieves under QoS satisfaction. Trace-based simulations validate the superiority of our approach over three benchmark approaches.