Iterative Group-by-Group Bit-Loading Algorithms for OFDM Systems

In a recent paper, we proposed group-by-group bit filling (GBF) and group-by-group bit removal (GBR) to boost the efficiency of bit loading. Generally, GBF/GBR converges to a suboptimal bit-allocation profile (BAP), and thus, a supplementary greedy bit-filling/bit-removal procedure is required to co...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology Vol. 62; no. 8; pp. 4131 - 4135
Main Authors: Wang, Deqiang, Cao, Yewen, Zheng, Laibo, Du, Zhengfeng
Format: Journal Article
Language:English
Published: New York, NY IEEE 01.10.2013
Institute of Electrical and Electronics Engineers
Subjects:
Applied sciences
Bit loading
Complexity theory
Computational efficiency
Exact sciences and technology
Frequency division multiplexing
Heuristic algorithms
Information, signal and communications theory
Iterative algorithms
Loading
multicarrier communications
Multiplexing
OFDM
orthogonal frequency-division multiplexing (OFDM)
Signal and communications theory
Systems, networks and services of telecommunications
Telecommunications
Telecommunications and information theory
Teletraffic
Transmission and modulation (techniques and equipments)
Performance evaluation
Optimal algorithm
Flow rate regulation
Multicarrier
Bit loading
Information rate
Teletraffic
Iterative method
Computational complexity
Information transmission
Bit allocation
multicarrier communications
Traffic management
Orthogonal frequency division multiplexing
Traffic control
Numerical simulation
orthogonal frequency-division multiplexing (OFDM)
ISSN:0018-9545, 1939-9359
Online Access:Get full text
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Summary:In a recent paper, we proposed group-by-group bit filling (GBF) and group-by-group bit removal (GBR) to boost the efficiency of bit loading. Generally, GBF/GBR converges to a suboptimal bit-allocation profile (BAP), and thus, a supplementary greedy bit-filling/bit-removal procedure is required to converge to the optimal BAP. In this correspondence, we propose refined GBF (r-GBF) and refined GBR (r-GBR) to overcome the imperfection of GBF and GBR. The key idea is to adjust the group size dynamically such that the optimal BAP can be directly achieved for any available target data rate. Based on r-GBF and r-GBR, a couple of bit-loading algorithms, which are named iterative GBF and iterative GBR, are presented. Numerical results show that the newly presented algorithms converge to the optimal BAP properly and outperform existing optimal algorithms in computational cost.
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2013.2257908