Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Journal of Global Optimization
On Limits of Wireless Communications in a Fading Environment when UsingMultiple Antennas
Wireless Personal Communications: An International Journal
Wireless Networks: Multiuser Detection in Cross-Layer Design (Information Technology: Transmission, Processing and Storage)
Journal of Global Optimization
Artificial Bee Colony (ABC) Optimization Algorithm for Training Feed-Forward Neural Networks
MDAI '07 Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence
Introduction to Space-Time Wireless Communications
Introduction to Space-Time Wireless Communications
Protein Tertiary Structure Prediction Using Artificial Bee Colony Algorithm
AMS '09 Proceedings of the 2009 Third Asia International Conference on Modelling & Simulation
Artificial Bee Colony (ABC) for multi-objective design optimization of composite structures
Applied Soft Computing
Artificial Bee Colony algorithm for optimization of truss structures
Applied Soft Computing
Discrete bee algorithms and their application in multivariable function optimization
Artificial Intelligence Review
Semantically-based crossover in genetic programming: application to real-valued symbolic regression
Genetic Programming and Evolvable Machines
SAR image segmentation based on Artificial Bee Colony algorithm
Applied Soft Computing
On the complexity of sphere decoding in digital communications
IEEE Transactions on Signal Processing
On the sphere-decoding algorithm I. Expected complexity
IEEE Transactions on Signal Processing - Part I
Biogeography-Based Optimization
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Information Theory
High-rate codes that are linear in space and time
IEEE Transactions on Information Theory
Artificial bee colony programming for symbolic regression
Information Sciences: an International Journal
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A Discrete Artificial Bee Colony (DABC) is presented for joint symbol detection at the receiver in a multidevice Space-Time Block Code (STBC) Mutli-Input Multi-Output (MIMO) communication system. Exhaustive search (maximum likelihood detection) for finding an optimal detection has a computational complexity that increases exponentially with the number of mobile devices, transmit antennas per mobile device, and the number of bits per symbol. ABC is a new population-based, swarm-based Evolutionary Algorithms (EA) presented for multivariable numerical functions and has shown good performance compared to other mainstream EAs for problems in continuous domain. This algorithm simulates the intelligent foraging behavior of honeybee swarms. An enhanced discrete version of the ABC algorithmis presented and applied to the joint symbol detection problem to find a nearly optimal solution in real time. The results of multiple independent simulation runs indicate the effectiveness of DABC with other well-known algorithms previously proposed for joint symbol detection such as the near-optimal sphere decoding, minimum mean square error, zero forcing, and semidefinite relaxation, along with other EAs such as genetic algorithm, estimation of distributions algorithm, and the more novel biogeography-based optimization algorithm.