NDLI: Efficient Suboptimal Resource Allocation Algorithms for Multiuser MIMO-OFDMA Systems

Content Provider	Springer Nature Link
Author	Majidzadeh, Mohammad Eslami, Mohsen
Copyright Year	2015
Abstract	Multiple-input multiple-output (MIMO) wireless communication systems in combination with orthogonal frequency division multiple access and space division multiple access are flexible, spectrally efficient and of high capacity. These systems can allocate frequency, time, and space resources adaptively among mobile stations. Optimal resource allocation (RA) for maximizing the sum rate is usually too complex for practical applications, hence suboptimal algorithms are required. The performance of RA algorithms are degraded due to imperfections in channel state information at transmitter (CSIT). Thus, techniques that make the RA algorithm, robust against CSIT errors are favorable. In this paper, two novel suboptimal grouping algorithms are introduced that are shown to achieve better sum rate-complexity and fairness-complexity performances. A novel index is proposed to measure the efficiency of RA algorithms, which takes into account sum rate and complexity simultaneously. Moreover, the effect of erroneous CSIT on sum rate is investigated and it is shown that performance of the proposed RA algorithms with erroneous CSIT are superior to the existing schemes. Finally, fairness performance of the proposed RA algorithms are evaluated, which are shown to be the same if not superior to other existing algorithms.
Starting Page	1967
Ending Page	1985
Page Count	19
File Format	PDF
ISSN	09296212
Journal	Wireless Personal Communications
Volume Number	82
Issue Number	4
e-ISSN	1572834X
Language	English
Publisher	Springer US
Publisher Date	2015-02-11
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Resource allocation (RA) Grouping algorithm Space division multiple access (SDMA) Orthogonal frequency division multiple access (OFDMA) Multiple input-multiple output (MIMO) Communications Engineering, Networks Signal, Image and Speech Processing Computer Communication Networks
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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