To achieve the higher resource efficiency, Coverage and Capacity Optimization(CCO) as an important role of the network self-healing and self-optimization, has become a focus topic in wireless Self-Organized Network(SO...To achieve the higher resource efficiency, Coverage and Capacity Optimization(CCO) as an important role of the network self-healing and self-optimization, has become a focus topic in wireless Self-Organized Network(SON). In this paper, a novel CCO scheme is proposed to maximize utility function of the integrated coverage and capacity. It starts with the analysis on the throughput proportional fairness(PF) algorithm and then proposes the novel Coverage and Capacity Proportional Fairness(CCPF) allocation algorithm along with a proof of the algorithms convergence. This proposed algorithm is applied in a coverage capacity optimization scheme which can guarantee the reasonable network capacity by the coverage range accommodation. Next, we simulate the proposed CCO scheme based on telecom operators' real network data and compare with three typical resource allocation algorithms: round robin(RR), proportional fairness(PF) and max C/I. In comparison of the PF algorithm, the numerical results show that our algorithm increases the average throughput by 1.54 and 1.96 times with constructed theoretical data and derived real network data respectively.展开更多
The intelligent vehicle network uses advanced information technology to establish an efficient integrated vehicle transport system, which has received great attention in industry and academia, lnternet of Vehicles （...The intelligent vehicle network uses advanced information technology to establish an efficient integrated vehicle transport system, which has received great attention in industry and academia, lnternet of Vehicles （loV） in an urban environment is operated in a wireless environment with high bit error rate and interference. In addition, the wireless link between vehicles is likely to be lost. All of this makes it an important challenge to provide reliable mobile routing in an urban traffic environment. In this paper, a reliable routing algorithm with network coding （RR_ NC） is proposed to solve the above problems. A routing node sequence is discovered in IoV from source to destination by multi-metric ant colony optimization algorithm （MACO）, and then clusters are formed around every node in the sequence. By adding linear encoding into the transmission of data between vehicle＇s clusters, the RR_NC provides much more reliable transmission and can recover the original message in the event of disorder and loss of message. Simulations are taken under different scenarios, and the results prove that this novel algorithm can deliver the information more reliably between vehicles in real-time with lower data loss and communication overhead.展开更多
基金supported by the 863 Program (2015AA01A705)NSFC (61271187)
文摘To achieve the higher resource efficiency, Coverage and Capacity Optimization(CCO) as an important role of the network self-healing and self-optimization, has become a focus topic in wireless Self-Organized Network(SON). In this paper, a novel CCO scheme is proposed to maximize utility function of the integrated coverage and capacity. It starts with the analysis on the throughput proportional fairness(PF) algorithm and then proposes the novel Coverage and Capacity Proportional Fairness(CCPF) allocation algorithm along with a proof of the algorithms convergence. This proposed algorithm is applied in a coverage capacity optimization scheme which can guarantee the reasonable network capacity by the coverage range accommodation. Next, we simulate the proposed CCO scheme based on telecom operators' real network data and compare with three typical resource allocation algorithms: round robin(RR), proportional fairness(PF) and max C/I. In comparison of the PF algorithm, the numerical results show that our algorithm increases the average throughput by 1.54 and 1.96 times with constructed theoretical data and derived real network data respectively.
基金supported by the Science and Technology Development Fund(No.037/2015/A1),Macao SAR,China
文摘The intelligent vehicle network uses advanced information technology to establish an efficient integrated vehicle transport system, which has received great attention in industry and academia, lnternet of Vehicles （loV） in an urban environment is operated in a wireless environment with high bit error rate and interference. In addition, the wireless link between vehicles is likely to be lost. All of this makes it an important challenge to provide reliable mobile routing in an urban traffic environment. In this paper, a reliable routing algorithm with network coding （RR_ NC） is proposed to solve the above problems. A routing node sequence is discovered in IoV from source to destination by multi-metric ant colony optimization algorithm （MACO）, and then clusters are formed around every node in the sequence. By adding linear encoding into the transmission of data between vehicle＇s clusters, the RR_NC provides much more reliable transmission and can recover the original message in the event of disorder and loss of message. Simulations are taken under different scenarios, and the results prove that this novel algorithm can deliver the information more reliably between vehicles in real-time with lower data loss and communication overhead.
