Using the genetic algorithm to adapt intelligent systems
Symbols versus neurons?
CDMA: principles of spread spectrum communication
CDMA: principles of spread spectrum communication
Ant algorithms for discrete optimization
Artificial Life
What is evolutionary computation?
IEEE Spectrum
Multiuser Detection
Microwave Mobile Communications
Microwave Mobile Communications
The influence of run-time limits on choosing ant system parameters
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Multiuser detection techniques using maximum likelihood sphere decoding in multicarrier CDMA systems
IEEE Transactions on Wireless Communications
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
IEEE Communications Magazine
| Hi-index | 0.00 |
This paper explores the application of the ant colony algorithm for an NP-complete problem in the area of wireless communications. The specific problem is one of detecting users (binary vectors) in a multi-user environment in synchronous MC-CDMA (multi-carrier Code Division Multiple Access) systems, such that the total interference noise in minimized. This approach is particularly attractive as ACO is well suited for physically realizable, real-time use, where fast convergence is absolutely necessary. Results suggest that the algorithm reduces the computer time requirement by as much as 98% over an exhaustive search method.