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Imperfect CSI-Based Joint Resource Allocation in Multirelay OFDMA Networks

Wang, Jun-Bo, Su, Qin, Wang, Jiangzhou, Feng, Min, Chen, Ming, Jiang, Bin, Wang, Jin-Yuan (2014) Imperfect CSI-Based Joint Resource Allocation in Multirelay OFDMA Networks. IEEE Transactions on Vehicular Technology, 63 (8). pp. 3806-3817. ISSN 0018-9545. (doi:10.1109/TVT.2014.2309992) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:45731)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1109/TVT.2014.2309992

Abstract

Radio resource allocation is very important in relay orthogonal frequency-division multiple-access (OFDMA) networks. Since perfect channel state information (CSI) is hardly obtained, the robust design that takes into account the CSI imperfection plays a crucial role in the development of efficient resource-allocation schemes. As to the chunk-based resource-allocation scheme, this paper focuses on the imperfect CSI-based resource-allocation problem to jointly optimize the chunk assignment, transmission link selection (direct or relay link), and power allocation in multirelay OFDMA systems. The optimization formulation minimizes the total transmit power with transmission requirement constraints and is considered a mixed-integer optimization problem, and a dual-maximization-based joint resource-allocation algorithm is proposed. The proposed dual-maximization-based algorithm is shown to be optimal. We also develop a low-complexity but near-optimal resource-allocation algorithm. The numerical results validate the performance gains offered by the proposed joint resource-allocation algorithms. The results also show that the impact of imperfect CSI is nonnegligible, which highlights the importance of robust designs in practical wireless networks.

Item Type: Article
DOI/Identification number: 10.1109/TVT.2014.2309992
Subjects: T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Tina Thompson
Date Deposited: 03 Dec 2014 12:54 UTC
Last Modified: 17 Aug 2022 10:58 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/45731 (The current URI for this page, for reference purposes)

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