Resource allocation algorithm for symmetrical services in OFDMA systems
The widespread acceptance of symmetrical services has urged for performance betterment techniques in wireless communication systems. In this paper, we propose an algorithm for resource allocation in MIMO-OFDMA system for applications that demand similar quality in uplink and downlink direction. The...
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| Format: | EJournal Article |
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Institute of Advanced Engineering and Science,
2020-05-01.
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| Online Access: | Get fulltext |
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| LEADER | 02401 am a22003133u 4500 | ||
|---|---|---|---|
| 001 | ijeecs20328_13687 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a P S, Swapna |e author |
| 100 | 1 | 0 | |e contributor |
| 700 | 1 | 0 | |a S Pillai, Sakuntala |e author |
| 700 | 1 | 0 | |a K. G, Sreeni |e author |
| 245 | 0 | 0 | |a Resource allocation algorithm for symmetrical services in OFDMA systems |
| 260 | |b Institute of Advanced Engineering and Science, |c 2020-05-01. | ||
| 500 | |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/20328 | ||
| 520 | |a The widespread acceptance of symmetrical services has urged for performance betterment techniques in wireless communication systems. In this paper, we propose an algorithm for resource allocation in MIMO-OFDMA system for applications that demand similar quality in uplink and downlink direction. The problem is formulated as multiobjective optimization problem with objectives to maximize the bidirectional data rates for individual users and to minimize the difference between the uplink and downlink data rate for each user. Fairness has been considered as a constraint in the optimization problem. The power allocation for each subcarrier in the OFDMA system is carried out using Linear Programming (LP) techniques, while the subcarrier allocation problem has been undertaken using an innovative multiobjective optimization technique that employs the concept of non-dominance in evolutionary algorithms. The results are extremely encouraging as they outperform the algorithms reported in literature using linear programming techniques or evolutionary algorithms solely. | ||
| 540 | |a Copyright (c) 2020 Institute of Advanced Engineering and Science | ||
| 540 | |a http://creativecommons.org/licenses/by-nc/4.0 | ||
| 546 | |a eng | ||
| 690 | |||
| 690 | |a Adaptive resource allocation; Genetic algorithm; Linear programming; Multiobjective optimization e non dominance; OFDMA | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 18, No 2: May 2020; 867-874 | |
| 786 | 0 | |n 2502-4760 | |
| 786 | 0 | |n 2502-4752 | |
| 786 | 0 | |n 10.11591/ijeecs.v18.i2 | |
| 787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/20328/13687 | |
| 856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/20328/13687 |z Get fulltext |