Open AccessHybrid‐genetic‐algorithm‐based resource allocation for slow adaptive OFDMA system under channel uncertainty
Author(s) -
Xu Lei,
Li Yaping,
Tang Zhenmin
Publication year - 2014
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2013.2697
Subject(s) - subcarrier , computer science , throughput , orthogonal frequency division multiple access , mathematical optimization , channel (broadcasting) , genetic algorithm , term (time) , frequency division multiple access , algorithm , resource allocation , orthogonal frequency division multiplexing , computer network , wireless , mathematics , telecommunications , physics , quantum mechanics
A resource allocation algorithm for the slow adaptive orthogonal frequency division multiple access system under channel uncertainty is considered. The optimisation objective maximises the long‐term system throughput over subcarrier assignment and the constraint condition satisfies the short‐term data rate requirements of individual users, except occasional outage. Such an objective has a natural chance‐constrained programming formulation. To solve the chance‐constrained optimisation, the neural network and the genetic algorithm (GA) are integrated to develop a hybrid GA (HGA) which could satisfy the user data rate requirement with the target outage probability. The simulation tests verify that the HGA yields a higher long‐term system throughput than the Li algorithm with the Bernstein approximation.