摘要
Although small cell offloading technology can alleviate the congestion in macrocell, aggressively offloading data traffic from macrocell to small cell can also degrade the performance of small cell due to the heavy load. Because of collision and backoff, the degradation is significant especially in network with contention-based channel access, and finally decreases throughput of the whole network. To find an optimal fraction of traffic to be offloaded in heterogeneous network, we combine Markov chain with the Poisson point process model to analyze contention-based throughput in irregularly deployment networks. Then we derive the close-form solution of the throughput and find that it is a function of the transmit power and density of base stations.Based on this, we propose the load-aware offloading strategies via power control and base station density adjustment. The numerical results verify our analysis and show a great performance gain compared with non-load-aware offloading.
Although small cell offloading technol- ogy can alleviate the congestion in macrocell, ag- gressively offloading data traffic from macrocell to small cell can also degrade the performance of small cell due to the heavy load. Because of collision and backoff, the degradation is significant especially in network with contention-based channel access, and finally decreases throughput of the whole network. To find an optimal frac- tion of traffic to be offloaded in heterogeneous network, we combine Markov chain with the Poisson point process model to analyze conten- tion-based throughput in irregularly deployment networks. Then we derive the close-form solution of the throughput and find that it is a function of the transmit power and density of base stations. Based on this, we propose the load-aware offload- ing strategies via power control and base station density adjustment. The numerical results verify our analysis and show a great performance gain compared with non-load-aware offloading.
基金
supported by the National High-Tech R&D Program (863 Program) under grant No. 2015AA01A705
Beijing Municipal Science and Technology Commission research fund project under grant No. D151100000115002
China Scholarship Council under grant No. 201406470038
BUPT youth scientific research innovation program under grant No. 500401238
