Optimal link adaptation for multicarrier communication systems

Bedeer-Mohamed, Ebrahim E. (2014) Optimal link adaptation for multicarrier communication systems. Doctoral (PhD) thesis, Memorial University of Newfoundland.

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Abstract

Link adaptation is the terminology used to describe techniques that improve multicarrier communication systems performance by dynamically adapting the transmission parameters, i.e., transmit power and number of bits per subcarrier, to the changing quality of the wireless link. The research literature has focused on single objective optimization techniques to optimize the multicarrier communication systems performance, e.g., maximizing the throughput/capacity or minimizing the transmit power subject to a set of constraints. In this dissertation, we adopt a novel optimization concept, namely multiobjective optimization, where our objective is to simultaneously optimize the conflicting and incommensurable throughput and power objectives. More specifically, in Chapters 2 and 3, we propose novel algorithms that jointly maximize the multicarrier system throughput and minimize its total transmit power subject to quality-of-service, total transmit power, and maximum allocated bits per subcarrier constraints. The proposed algorithms require prior knowledge about the importance of the competing objective functions in terms of pre-determined weighting coefficients, or they can adapt the weighting coefficients during the solution process while meeting the constraints, in order to reduce the computational complexity. Simulation results show significant performance gains in terms of the achieved throughput and transmit power when compared to single optimization approaches, at the cost of no additional complexity. Motivated by the obtained results, in Chapter 4 the problem is extended to the cognitive radio environment where the multicarrier unlicensed/secondary user, with limited sensing capabilities, needs to satisfy additional constraints for the leaked interference to existing licensed/primary users. In Chapter 5, a multiobjective optimization problem is formulated to balance between the SU capacity and the leaked interference to existing primary users, where the effect of the imperfect channel-state-information on the links from the secondary user transmitter to the primary users receivers is considered. Simulation results show improvements of the energy efficiency of the secondary user when compared to its counterparts of the works in the literature, with reduced computational complexity. In Chapter 6 we investigate the optimal link adaptation problem to optimize the energy efficiency of secondary users while considering the effect of imperfect channelstate- information on the links between the secondary user transmitter and receiver pairs and the limited sensing capabilities of the secondary user. The proposed link adaptation algorithm guarantees minimum required rate for the secondary user and statistical interference constraints to the existing primary users. Finally, conclusions and possible extensions to the optimal link adaptation problem is discussed in Chapter 7.

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