In recent years, mobile hotspots have been getting much attention of the researchers. They are implemented on moving platforms. Research interests in mobile hotspots are motivated by the demand of seamless mobility. The IEEE 802.16e or mobile WiMAX opens a new door of possibility of mobile broadband. It provides extended mobility support and larger cell coverage. In this thesis we propose a simple link adaptation (LA) algorithm for the mobile hotspots, which are supported by (mobile) WiMAX network.
The role of link adaptation (LA) is very important because it controls the physical layer throughput. Therefore, all the higher layers are affected by LA. The main function of an LA algorithm is to select an appropriate burst profile. We consider downlink scenarios of WiMAX supported mobile hotspot. We formulate a discrete value optimization problem for LA, whose objective is throughput maximization. We choose forward error correction block rate (FBER) as constraint. The proposed LA algorithm comes as solution of the optimization problem. The proposed algorithm adapt with MAC layer performance. We develop a downlink channel estimation technique, propose an intra subchannel power allocation strategy, and propose an adaptive automatic repeat request (ARQ) mechanism as part of LA technique. We estimate SNR using channel estimation and intra subchannel power allocation. Then the estimated SNR is adjusted based on velocity of mobile hotspot. Adjusted SNR is used to select optimum burst profile.
The performances of the proposed LA algorithm are evaluated through numerical results obtained from link level simulations. According to numerical results, the proposed LA algorithm is able to maintain a certain level quality of service (QoS).
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OWTU.10012/4527 |
| Date | January 2009 |
| Creators | Hasan, Md. Mahmud |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
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