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Article type: Research Article
Authors: Taki, Mehrdad*
Affiliations: University of Qom, Qom, Iran
Correspondence: [*] Corresponding author. Mehrdad Taki, University of Qom, Qom, Iran. Tel.: +98 9107784776; Fax: +98 2532854499; E-mail: m.taki@qom.ac.ir.
Abstract: This paper presented a new fuzzy based optimization framework for wireless link adaptation which maximizes throughput subject to Buffer length, Bit Error Rate (BER) and average power constraints. Buffer constrained throughput of a link is called effective capacity. At first, we present two schemes to optimize the effective capacity of a wireless link, in an analytical approach, with constant or adaptive power transmission. As shown, the scheme with constant power transmission works without any need to probability density function (PDF) of channel’s SNR. However, a considerable performance improvement is seen by using adaptive power transmission at the cost of more complicated design. In analytical approach, provisioning average power constraint requires knowledge on PDF of the link’s SNR which may not be available in practical systems especially mobile networks. We design a new fuzzy based scheme for adaptive power transmission without any need to PDF which provide instantaneous BER, buffer and average power constraints. Our numerical evaluations for adaptive LDPC or convolutional coded, QAM modulated transmission, show that after a reasonable period of time the throughput of our proposed scheme converges to its optimum value by analytical approach.
Keywords: Link adaptation, adaptive modulation and coding, buffer constraint, cross layer design
DOI: 10.3233/JIFS-16466
Journal: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 3, pp. 2499-2507, 2017
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