CDMA: principles of spread spectrum communication
CDMA: principles of spread spectrum communication
Multiuser Detection
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
A new approach to solve hybrid flow shop scheduling problems by artificial immune system
Future Generation Computer Systems - Special issue: Computational science of lattice Boltzmann modelling
Solving Multiobjective Optimization Problems Using an Artificial Immune System
Genetic Programming and Evolvable Machines
An artificial immune system algorithm for CDMA multiuser detection over multi-path channels
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
An overview of evolutionary algorithms in multiobjective optimization
Evolutionary Computation
Software radio: a modern approach to radio engineering
Software radio: a modern approach to radio engineering
Multiobjective optimization using ideas from the clonal selection principle
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Clonal selection with immune dominance and anergy based multiobjective optimization
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
An evolutionary approach to designing complex spreading codes for DS-CDMA
IEEE Transactions on Wireless Communications
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Learning and optimization using the clonal selection principle
IEEE Transactions on Evolutionary Computation
Performance assessment of multiobjective optimizers: an analysis and review
IEEE Transactions on Evolutionary Computation
Self-adaptive fitness formulation for constrained optimization
IEEE Transactions on Evolutionary Computation
A Generic Framework for Constrained Optimization Using Genetic Algorithms
IEEE Transactions on Evolutionary Computation
Quasi-orthogonal sequences for code-division multiple-access systems
IEEE Transactions on Information Theory
Bounds on crosscorrelation and autocorrelation of sequences (Corresp.)
IEEE Transactions on Information Theory
Design of pseudonoise sequences with good odd and even correlation properties for DS/CDMA
IEEE Journal on Selected Areas in Communications
A hybrid approach based on MEP and CSP for contour registration
Applied Soft Computing
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This paper proposes two new algorithms based on the clonal selection principle for the design of spreading codes for DS-CDMA. The first algorithm follows a multi-objective approach, generating complex spreading codes with ''good'' auto as well as cross-correlation properties. It also enables spreading code design with no restrictions on the number of users or code length. The algorithm maintains a repertoire of codes that are subject to cloning and undergo a process of affinity maturation to obtain better codes. Results indicate that the produced code sets lie very close to the theoretical Pareto front. A second penalty function-based constrained optimization algorithm based on clonal selection is proposed. It is applied to the design of spreading codes with pre-defined power spectral density requirement. The results suggest that the algorithm is capable of lowering significantly, the power spectra at undesired frequencies. Therefore, with the proposed algorithm, a DS-CDMA transmitter can, for the first time, selectively transmit power across the transmission bandwidth and adjust to jammers and other interferers. This study illustrates that using two stages of multi-objective and constrained optimization, using the proposed clonal selection algorithms, is an effective code design strategy.