Conference Proceeding

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

Comput. Sci. Dept., UCLA, Los Angeles, CA
Proceedings - IEEE INFOCOM 01/2009; DOI:10.1109/INFCOM.2009.5062197 In proceeding of: 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.

0 0
 · 
1 Bookmark
 · 
184 Views
  • Source
    [show abstract] [hide abstract]
    ABSTRACT: The LTE specification provides Quality of Service (QoS) of multimedia services with fast connectivity, high mobility, and security. However, 3GPP specifications have not defined scheduling algorithms to support real-time and non-realtime application services, this has led to the development of a variety of scheduling algorithms in the recent years. Performance is a key factor for assessing the scheduling algorithms. However, the performance analysis and evaluation for existing scheduling algorithms are limited to QoS parameters (e.g. in terms of throughput, packet loss and delay) and/or fairness metrics. It is not clear how these scheduling algorithms perform in terms of Quality of Experience (QoE) metrics (e.g. MOS score) which are more closely linked with end user experience or user perceived quality. In this paper, we investigate and evaluate the performance of three popular LTE downlink schedulers (proportional fairness (PF), exponential proportional fairness (EXP-PF), and modified largest weight delay first (M-LWDF)) in terms of QoE metric (i.e. MOS score) in addition to normal QoS metrics (e.g. packet loss and delay) for VoIP applications. Simulation results (based on LTE-Sim) show that the best suitable downlink scheduling algorithm is MLWDF, which has short end-to end delay (less than 50ms) and allowing maximum number of user access (more than 50 users) at acceptable MOS score (MOS over 3.5). The widely used scheduling algorithm (PF) will increase its end-to-end delay over 200ms, when number of user access is over 30. This will limit its application for VoIP when user access number increases. This work would help to assist the design and development of QoE-driven scheduling algorithms for mobile multimedia applications in the future.
    Globecom Workshops (GC Wkshps), Anaheim, CA; 12/2012
  • Source
    [show abstract] [hide abstract]
    ABSTRACT: We consider the allocation of spectral and power resources every subframe (1 ms) on the uplink of the Long Term Evolution (LTE) wideband orthogonal frequency division multiple access (OFDMA) cellular network. System bandwidth is divided into multiple sub-bands. The fractional power control to manage interference is allowed to be sub-band dependent. Moreover, the channel gains from the base-station to the mobiles (user equipment (UE) in LTE) can vary with the sub-band. The power and spectral resources are to be allocated among different UEs in a cell based on channel conditions, desired fairness/QoS, and constraints on power due to interference and power limitation at a UE. For N UEs and M sub-bands, we exploit the structure of the underlying optimization problem to obtain an interior point method for optimal resource allocation where each Newton step has complexity O(NM). To implement this in an OFDMA system, we delineate a simple control signalling structure where the UE computes in O(M) time a waterfllling solution every subframe it is assigned resources. When the allocation is restricted to contiguous allocation in frequency due to single carrier constraint in LTE, we convert the solution computed above into a feasible solution in O(NM) time. For typical network scenarios, the solution thus computed is numerically shown to be very close to the optimal solution without the contiguous constraint.
    Communications (ICC), 2011 IEEE International Conference on; 07/2011
  • Source
    [show abstract] [hide abstract]
    ABSTRACT: In this paper, we study resource allocation and adaptive modulation in SC-FDMA which is adopted as the multiple access scheme for the uplink in the 3GPP-LTE standard. A sum-utility maximization (SUmax), and a joint adaptive modulation and sum-cost minimization (JAMSCmin) problems are considered. Unlike OFDMA, in addition to the restriction of allocating a sub-channel to one user at most, the multiple sub-channels allocated to a user in SC-FDMA should be consecutive as well. This renders the resource allocation problem prohibitively difficult and the standard optimization tools (e.g., Lagrange dual approach widely used for OFDMA, etc.) can not help towards its optimal solution. We propose a novel optimization framework for the solution of these problems that is inspired from the recently developed canonical duality theory. We first formulate the optimization problems as binary-integer programming problems and then transform these binary-integer programming problems into continuous space canonical dual problems that are concave maximization problems. Based on the solution of the continuous space dual problems, we derive resource allocation (joint with adaptive modulation for JAMSCmin) algorithms for both the problems which have polynomial complexities. We provide conditions under which the proposed algorithms are optimal. We also propose an adaptive modulation scheme for SUmax problem. We compare the proposed algorithms with the existing algorithms in the literature to assess their performance.
    Wireless Personal Communications 03/2011; · 0.43 Impact Factor

Full-text

View
12 Downloads
Available from

Suk-Bok Lee