  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 some of the following Chapters, 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.
