Hybrid-genetic-algorithm-based resource allocation for slow adaptive OFDMA system under channel uncertainty

作者：Xu Lei^*; Li Yaping; Tang Zhen min

来源：Electronics Letters, 2014, 50(1): 30-31.

DOI：10.1049/el.2013.2697

• approximation theory
• frequency division multiple access
• genetic algorithms
• neural nets
• OFDM modulation
• probability
• resource allocation
• telecommunication computing
• wireless channels
• hybrid-genetic-algorithm-based resource allocation
• slow adaptive OFDMA system
• channel uncertainty
• slow adaptive orthogonal frequency division multiple access system
• long-term system throughput
• subcarrier assignment
• constraint condition
• short-term data rate requirements

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.

• 出版日期2014-1-2
• 单位南京航空航天大学; 南京理工大学