Conference Paper

Proportional Fair Frequency-Domain Packet Scheduling for 3GPP LTE Uplink

Comput. Sci. Dept., UCLA, Los Angeles, CA
DOI: 10.1109/INFCOM.2009.5062197 Conference: INFOCOM 2009. 28th IEEE International Conference on Computer Communications, Joint Conference of the IEEE Computer and Communications Societies, 19-25 April 2009, Rio de Janeiro, Brazil
Source: DBLP

ABSTRACT With the power consumption issue of mobile handset taken into account, Single-carrier FDMA (SC-FDMA) has been selected for 3GPP Long-Term Evolution (LTE) uplink multiple access scheme. Like in OFDMA downlink, it enables multiple users to be served simultaneously in uplink as well. However, its single carrier property requires that all the subcarriers allocated to a single user must be contiguous in frequency within each time slot. This contiguous allocation constraint limits the sch eduling flexibility, and frequency-domain packet scheduling algor ithms in such system need to incorporate this constraint while trying to maximize their own scheduling objectives. In this paper we explore this fundamental problem of LTE SC-FDMA uplink scheduling by adopting the conventional time- domain Proportional Fair algorithm to maximize its objective (i.e. proportional fair criteria) in the frequency-domain setting. We show the NP-hardness of the frequency-domain scheduling problem under this contiguous allocation constraint and present a set of practical algorithms fine tuned to this problem. We demonstrate that competitive performance can be achieved in terms of system throughput as well as fairness perspective, which is evaluated using 3GPP LTE system model simulations.

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    ABSTRACT: he Long Term Evolution (LTE) standard plays an important role in the development of Machine-to-Machine (M2M) communication. However, the M2M communication has several different characteristics regarding to Human-to-Human (H2H) communication. Therefore, the shortage of radio resources, satisfaction of the Quality of Service (QoS) requirements and the reduction of the H2H traffic performance are important issues to be addressed when introducing the M2M communication in the network. In this article, we present a scheduler that may dynamically adjust to the level of congestion of the network based on the current traffic information of each device. The main goals of our approach are (i) satisfy the QoS requirements (ii) ensure fair allocation of resources and (iii) control the impact of H2H traffic performance. The simulation results demonstrated that the proposed scheduling has good performance according to the three objectives aforementioned.
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    ABSTRACT: This paper investigates the performance of three well-known algorithms namely Proportional Fairness, Exponential Proportional Fairness and Modified-Largest Weighted Delay First in LTE network. This study is based on their performance in three smart grid applications (Sub-Station Automation, Advance Metering Infrastructure and Wide Area Situational Awareness). In addition, a new mathematical model has been developed and proposed to target certain weakness of the above mentioned algorithms.
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    ABSTRACT: LTE uplink frequency scheduling algorithms have neglected the user equipment's (UE) QoS requirements, relying only on the time domain to provide such requirements when creating the allocation matrix for the next transmission time interval. Two time domain paradigms exist for creating the resource allocation matrix: channel-dependent and proportional fairness. The channel dependent paradigm considers mainly the channel quality of UEs, allowing for users with high channel quality to get assigned most resources. The proportional fairness paradigm allocates resources to users based on the ratio of their channel condition over their lifelong service rate, allowing for users with low channel conditions to get some resources, but fewer than those with better channel conditions. Even though the proportional fairness paradigm's main focus is to achieve high system throughput without starving any user, it does not account for QoS requirements in many scenarios especially when UEs with high priority data pending for transmission have worst channel conditions than those with lower priority data. In this paper we propose a QoS-aware resource allocation paradigm for LTE uplink scheduling that gives more advantage to UEs having high priority data, while not starving other users. The proposed approach is scalable and mobility aware where the dynamic nature of the network is taken into account while devising the algorithm. When simulated using NS3, the proposed algorithm produced very promising results and outperformed the state-of-the-art approaches presented in literature.
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