针对水下传感器网络通信过程中能量效率低、误码率高等问题,提出一种基于优先级服务质量(Quality of Service,QoS)选择策略的水下网络中继算法(PQSS)。算法首先采用有限状态马尔科夫链来建立源节点和中继节点之间的无线信道模型,并得到...针对水下传感器网络通信过程中能量效率低、误码率高等问题,提出一种基于优先级服务质量(Quality of Service,QoS)选择策略的水下网络中继算法(PQSS)。算法首先采用有限状态马尔科夫链来建立源节点和中继节点之间的无线信道模型,并得到中继节点信噪比的状态转移概率矩阵。接着提出链路QoS函数,该函数考虑了传输能耗、误码率和数据速率作为链路QoS的评价度量,通过各度量并结合状态转移概率的计算来求出中继节点的链路QoS值范围,从而选择链路QoS值更大的中继节点来作为最佳的下一跳节点。最后仿真结果表明,上述算法相比基于分簇的水下传感器网络覆盖保持路由算法和基于洪泛的逐层能量高效路由协议,能量效率分别提高了21.4%和13.1%,网络平均生命周期分别提高了13.4%和7.6%。展开更多
This paper investigates the relay selection and resource allocation problem in multiuser orthogonal frequency division multiplexing （OFDM） based cooperative cellular networks, in which user nodes could relay informa...This paper investigates the relay selection and resource allocation problem in multiuser orthogonal frequency division multiplexing （OFDM） based cooperative cellular networks, in which user nodes could relay information for each other using the decode-and-forward （DF） protocol to achieve spatial diversity gain. Specifically, the paper proposes an optimal joint relay selection and resource allocation （0RSRA） algorithm whose objective is to maximize system total achievable data rate with the constraints of each user＇ s individual quality of service （QoS） requirement and transmission power. Due to being a mixed binary integer programming （MBIP） problem, a novel two-level Lagrangian dual-primal decomposition and subgradient projection approach is proposed to not only select the appropriate cooperative relay nodes, but also allocate subcarries and power optimally. Simulation re- suits demonstrate that our proposed scheme can efficiently enhance overall system data rate and guarantee each user＇ s QoS requirement. Meanwhile, the fairness among users can be improved dramatically.展开更多
Multiple-input multiple-output(MIMO) and cooperative communications have been attracted great attention for the improvements of communication capacity, power consumption, and transmission coverage. The conventional fi...Multiple-input multiple-output(MIMO) and cooperative communications have been attracted great attention for the improvements of communication capacity, power consumption, and transmission coverage. The conventional fixed relaying protocols, amplify-and-forward(AF) and decode-and-forward(DF), have their own advantages and disadvantages, i.e. AF performs better than DF for low signal-to-noise ratio(SNR) region, while the reverse is true for high SNR region. Therefore, this paper proposes an SNR-adaptive forward(SAF) relaying scheme obtaining the advantages of both AF and DF. Furthermore, the proposed SAF does not need to switch between AF and DF when SNR changes. The main idea is to adaptively derive the soft information at the cooperative relay nodes based on the information of the received signal and the SNR. Besides, based on the theoretical analysis and the simulation results, it is affirmed that the proposed SAF achieves superior performance than both AF and DF for all SNRs. Moreover, the performance gain would be improved with the increasing number of parallel cooperative relay nodes.展开更多
文摘针对水下传感器网络通信过程中能量效率低、误码率高等问题,提出一种基于优先级服务质量(Quality of Service,QoS)选择策略的水下网络中继算法(PQSS)。算法首先采用有限状态马尔科夫链来建立源节点和中继节点之间的无线信道模型,并得到中继节点信噪比的状态转移概率矩阵。接着提出链路QoS函数,该函数考虑了传输能耗、误码率和数据速率作为链路QoS的评价度量,通过各度量并结合状态转移概率的计算来求出中继节点的链路QoS值范围,从而选择链路QoS值更大的中继节点来作为最佳的下一跳节点。最后仿真结果表明,上述算法相比基于分簇的水下传感器网络覆盖保持路由算法和基于洪泛的逐层能量高效路由协议,能量效率分别提高了21.4%和13.1%,网络平均生命周期分别提高了13.4%和7.6%。
基金Supported by the National Natural Science Foundation for Distinguished Young Scholar （ No. 61001115 ） and the Beijing Municipal Natural Science Foundation （ No. 4102044）.
文摘This paper investigates the relay selection and resource allocation problem in multiuser orthogonal frequency division multiplexing （OFDM） based cooperative cellular networks, in which user nodes could relay information for each other using the decode-and-forward （DF） protocol to achieve spatial diversity gain. Specifically, the paper proposes an optimal joint relay selection and resource allocation （0RSRA） algorithm whose objective is to maximize system total achievable data rate with the constraints of each user＇ s individual quality of service （QoS） requirement and transmission power. Due to being a mixed binary integer programming （MBIP） problem, a novel two-level Lagrangian dual-primal decomposition and subgradient projection approach is proposed to not only select the appropriate cooperative relay nodes, but also allocate subcarries and power optimally. Simulation re- suits demonstrate that our proposed scheme can efficiently enhance overall system data rate and guarantee each user＇ s QoS requirement. Meanwhile, the fairness among users can be improved dramatically.
基金supported in part by the National Natural Science Foundation of China 61501461, 61471269, 71232006, and 61533019the Early Career Development Award of SKLMCCS (Y3S9021F34)
文摘Multiple-input multiple-output(MIMO) and cooperative communications have been attracted great attention for the improvements of communication capacity, power consumption, and transmission coverage. The conventional fixed relaying protocols, amplify-and-forward(AF) and decode-and-forward(DF), have their own advantages and disadvantages, i.e. AF performs better than DF for low signal-to-noise ratio(SNR) region, while the reverse is true for high SNR region. Therefore, this paper proposes an SNR-adaptive forward(SAF) relaying scheme obtaining the advantages of both AF and DF. Furthermore, the proposed SAF does not need to switch between AF and DF when SNR changes. The main idea is to adaptively derive the soft information at the cooperative relay nodes based on the information of the received signal and the SNR. Besides, based on the theoretical analysis and the simulation results, it is affirmed that the proposed SAF achieves superior performance than both AF and DF for all SNRs. Moreover, the performance gain would be improved with the increasing number of parallel cooperative relay nodes.
