Convex Optimization
A heuristic optimal discrete bit allocation algorithm for margin maximization in DMT systems
EURASIP Journal on Applied Signal Processing
Bit and power allocation in constrained multicarrier systems: the single-user case
EURASIP Journal on Advances in Signal Processing
Practical approaches to adaptive resource allocation in OFDM systems
EURASIP Journal on Wireless Communications and Networking - Multicarrier Systems
Practical algorithms for a family of waterfilling solutions
IEEE Transactions on Signal Processing
Optimum linear joint transmit-receive processing for MIMO channels with QoS constraints
IEEE Transactions on Signal Processing
Orthogonal transmultiplexers in communication: a review
IEEE Transactions on Signal Processing
Novel efficient bit-loading algorithms for peak-energy-limitedADSL-type multicarrier systems
IEEE Transactions on Signal Processing
Bit loading with BER-constraint for multicarrier systems
IEEE Transactions on Wireless Communications
Adaptive OFDM Systems With Imperfect Channel State Information
IEEE Transactions on Wireless Communications
Optimum power allocation for parallel Gaussian channels with arbitrary input distributions
IEEE Transactions on Information Theory
Combined equalization and coding using precoding
IEEE Communications Magazine
Efficient Modulation for Band-Limited Channels
IEEE Journal on Selected Areas in Communications
An introduction to convex optimization for communications and signal processing
IEEE Journal on Selected Areas in Communications
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Bit error rate (BER) minimization and SNR-gap maximization, two robustness optimization problems, are solved, under average power and bitrate 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, using 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 bitrates 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 the 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 Rayleigh fading channel for multicarrier systems. Simulation results confirm the asymptotic convergence of both resource allocation policies. In nonasymptotic regime the resource allocation policies can be interchanged depending on the robustness measure and on the operating point of the communication system. The low computational effort leads to a good trade-off between performance and complexity.