Bit error rate (BER) minimization and SNR-gap maximization, two robustness
optimization problems, are solved, under average power and bit-rate
constraints, according to the waterfilling policy. Under peak-power constraint
the solutions differ and this paper gives bit-loading solutions of both
robustness optimization problems over independent parallel channels. The study
is based on analytical approach with generalized Lagrangian relaxation tool and
on greedy-type algorithm approach. Tight BER expressions are used for square
and rectangular quadrature amplitude modulations. Integer bit solution of
analytical continuous bit-rates is performed with a new generalized secant
method. The asymptotic convergence of both robustness optimizations is proved
for both analytical and algorithmic approaches. We also prove that, in
conventional margin maximization problem, the equivalence between SNR-gap
maximization and power minimization does not hold with peak-power limitation.
Based on a defined dissimilarity measure, bit-loading solutions are compared
over power line communication channel for multicarrier systems. Simulation
results confirm the asymptotic convergence of both allocation policies. In non
asymptotic regime the allocation policies can be interchanged depending on the
robustness measure and the operating point of the communication system. The low
computational effort of the suboptimal solution based on analytical approach
leads to a good trade-off between performance and complexity.Comment: 27 pages, 8 figures, submitted to IEEE Trans. Inform. Theor
