An Efficient Genetic Algorithm for the Two-Level Burst Allocation Problem with Different Modulation and Coding Schemes in IEEE 802.16e Networks

• Main Authors: Wun-Huei Huang, 黃穩輝
• Other Authors: Pi-Rong Sheu
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/33952991408352960857

碩士 === 國立雲林科技大學 === 電機工程系 === 102 === In IEEE 802.16e networks, the problem of allocating a burst in a rectangular shape in an OFDMA (orthogonal frequency division multiple access) frame is called the burst allocation problem. If a burst can be divided into two parts: the MUST part and the WISH part, then such a problem may be called the two-level burst allocation problem. Furthermore, if different subchannels in the burst allocation problem may adopt different modulation and coding schemes (MCSs), then such a burst allocation problem may be called the burst allocation problem with different MCSs. In this problem, the MCS that a burst adopts must be the lowest MCS of all subchannels that the burst allocates. In this thesis, we will study the two-level burst allocation problem under the situation where different subchannels may adopt different MCSs. We call such a burst allocation problem the two-level burst allocation problem of different MCSs. In recent years, genetic algorithms have used to solve some problems in networks. Therefore, in this thesis, we propose an efficient genetic algorithm for the two-level burst allocation problem of different MCSs. In fact, computer simulation results show that compared with other algorithms for the two-level burst allocation problem of different MCSs, our genetic algorithm may generate a higher frame throughput.