Improved Resource Allocation Algorithm Based on Partial Solution Estimation for SC-FDMA Systems

Single carrier frequency division multiple access (SC-FDMA) has been adopted as the standard multiple access scheme for 3GPP LTE uplink. In comparison to orthogonal frequency division multiple access (OFDMA), the subcarriers assigned to each user are required to be consecutive in SC-FDMA localized s...

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Bibliographic Details
Published in:2013 IEEE 78th Vehicular Technology Conference (VTC Fall) pp. 1 - 5
Main Authors: Lei Lei, Fowler, Scott, Di Yuan
Format: Conference Proceeding
Language:English
Published: IEEE 01.09.2013
Series:Vehicular Technology Conference
Subjects:
Algorithm design and analysis
Complexity theory
Estimation
Heuristic algorithms
Resource management
TECHNOLOGY
TEKNIKVETENSKAP
Uplink
Wireless communication
Partial Solution
Binary Integer Programming
SC-FDMA
Resource Allocation
Algorithm
Estimation
ISBN:1467361852, 1467361879, 9781467361873, 9781467361859
ISSN:1090-3038
Online Access:Get full text
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Summary:Single carrier frequency division multiple access (SC-FDMA) has been adopted as the standard multiple access scheme for 3GPP LTE uplink. In comparison to orthogonal frequency division multiple access (OFDMA), the subcarriers assigned to each user are required to be consecutive in SC-FDMA localized scheme, which imposes more difficulties on resource allocation problem. Subject to this constraint, various optimization objectives, such as utility maximization and power minimization, have been studied for SC-FDMA resource allocation. In this paper, we focus on developing a general algorithm framework with near-optimal performance and polynomial-time complexity to maximize the total utility for SC-FDMA systems. The proposed algorithm is based on low-complexity estimation for the partial solution space. Compared with existing algorithms, simulation results show that our algorithm improves the system utility significantly and has less deviation to global optimum. In addition, the proposed algorithm framework allows a flexible trade-off between computational effort and solution performance by varying the complexity of estimation approaches.
ISBN:1467361852
1467361879
9781467361873
9781467361859
ISSN:1090-3038
DOI:10.1109/VTCFall.2013.6692229