In co-channel deployment of macro cell and pico cells, cell range extension （RE）, a simple and typical cell association scheme, is introduced to achieve better load balancing and improve cell edge performance. In th...In co-channel deployment of macro cell and pico cells, cell range extension （RE）, a simple and typical cell association scheme, is introduced to achieve better load balancing and improve cell edge performance. In this article, a novel dynamic and distributed bias setting scheme is proposed for RE technique in macro-pico heterogeneous networks. In this strategy, the worst user throughput of each cell during an adjusting time interval T is obtained to change the bias values according to certain procedures, where an introduced indicator is used to freeze the possibility of increasing bias value if needed. Furthermore, silent state and coarse control process are employed to achieve low overheads and computational complexity. Simulation results show that the proposed scheme can greatly improve the cell-edge performance compared with the static bias setting strategies, while maintaining the overall cell performance at the same time.展开更多
基金supported by Funds for Creative Research Groups of China (61121001)the National Science and Technology Major Project (2012ZX03003012-004, 2012ZX03004-005-002)the Program for Changjiang Scholars and Innovative Research Team in University (IRT1049)
文摘In co-channel deployment of macro cell and pico cells, cell range extension （RE）, a simple and typical cell association scheme, is introduced to achieve better load balancing and improve cell edge performance. In this article, a novel dynamic and distributed bias setting scheme is proposed for RE technique in macro-pico heterogeneous networks. In this strategy, the worst user throughput of each cell during an adjusting time interval T is obtained to change the bias values according to certain procedures, where an introduced indicator is used to freeze the possibility of increasing bias value if needed. Furthermore, silent state and coarse control process are employed to achieve low overheads and computational complexity. Simulation results show that the proposed scheme can greatly improve the cell-edge performance compared with the static bias setting strategies, while maintaining the overall cell performance at the same time.
