Scheduling Exploiting Frequency and Multi-User Diversity in LTE Downlink Systems

• Published in: IEEE transactions on wireless communications Vol. 12; no. 4; pp. 1843 - 1849
• Main Authors: Jinping Niu, Daewon Lee, Xiaofeng Ren, Li, Geoffrey Y., Tao Su
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.04.2013; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Applied sciences; Channels; Classification; Computer simulation; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; Frequency diversity; Frequency selective surfaces; Gain; Information, signal and communications theory; LTE downlink; Measurement; mobility; multi-user diversity; Organization, operation and development plans; Radiocommunications; Resource allocation; Resource management; Scheduling; Scheduling algorithms; Signal and communications theory; Signal, noise; Studies; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Throughput; Transmission and modulation (techniques and equipments); Transmitters. Receivers; Wireless communication; Performance evaluation; Multiple access; Parameter estimation; mobility; Computer simulation; LTE downlink; Resource allocation; Frequency allocation; Information rate; Transmitter; Equity; Downlink; multi-user diversity; Scheduling; Algorithm; Computational complexity; Frequency selector; Information transmission; Frequency selection; Channel estimation; Frequency diversity; Resource management; Multiple frequency
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2013.022013.121020

Scheduling can obtain multi-user diversity if channel state information (CSI) is known, such as for low-mobility users and can exploit frequency diversity if CSI is not available at the transmitter, such as for high-mobility users. In this paper, we investigate resource allocation exploiting frequency and multiuser diversity for LTE downlink systems with users of different mobilities. To facilitate resource allocation, we first develop a user classification algorithm to identify high- and low-mobility users. Based on user mobility classification, we then propose a scheduling algorithm to simultaneously obtain multi-user diversity for those low-mobility users and frequency diversity for those high-mobility users. It is demonstrated by computer simulation that the performance of the proposed scheduling algorithm provides 6% and 23% gain of overall cell throughput, and 5.6% and 18% gain of 10th percentile throughput over proportional fairness based frequency-selective and frequency-diversity scheduling algorithms, respectively. Furthermore, the proposed scheduling algorithm has the same order of computational complexity as the frequency-selective scheduling algorithm.