Dynamic spectrum access policy is crucial in improving the performance of over- lay cognitive radio networks. Most of the previ- ous works on spectrum sensing and dynamic spe- ctrum access consider the sensing effecti...Dynamic spectrum access policy is crucial in improving the performance of over- lay cognitive radio networks. Most of the previ- ous works on spectrum sensing and dynamic spe- ctrum access consider the sensing effective- ness and spectrum utilization as the design cri- teria, while ignoring the energy related issues and QoS constraints. In this article, we propose a QoS provisioning energy saving dynamic acc- ess policy using stochastic control theory con- sidering the time-varying characteristics of wir- eless channels because of fading and mobility. The proposed scheme determines the sensing action and selects the optimal spectrum using the corresponding power setting in each decis- ion epoch according to the channel state with the objective being to minimise both the flame error rate and energy consumption. We use the Hidden Markov Model （HMM） to model a wir- eless channel, since the channel state is not dir- ectly observable at the receiver, but is instead embedded in the received signal. The proced- ure of dynamic spectrum access is formulated as a Markov decision process which can be sol- ved using linear programming and the primal- dual index heuristic algorithm, and the obta- ined policy has an index-ability property that can be easily implemented in real systems. Sim- ulation results are presented to show the per- formance improvement caused by the propo- sed approach.展开更多
提出了基于奇异值分解(Singular Value Decomposition,SVD)特征矩阵压缩和隐Markov模型(Hidden Markov Model,HMM)的动态手势识别方法。该方法通过SVD对特征矩阵进行时间维度的压缩,然后通过HMM的方法对提取的动态手势进行识别。通过对...提出了基于奇异值分解(Singular Value Decomposition,SVD)特征矩阵压缩和隐Markov模型(Hidden Markov Model,HMM)的动态手势识别方法。该方法通过SVD对特征矩阵进行时间维度的压缩,然后通过HMM的方法对提取的动态手势进行识别。通过对特征矩阵压缩可以显著地减少训练HMM的迭代计算量,提高模型的训练效率。采用Leap Motion体感控制器追踪并提取自定义的10个阿拉伯数字的动态手势特征。实验验证结果表明,该方法对这些动态手势在当前有限样本条件下的总识别率均在96%以上。展开更多
基金supported by the National Natural Science Foundation of China under Grant No.61101107the Beijing Higher Education Young Elite Teacher Project under Grant No.YETP0439
文摘Dynamic spectrum access policy is crucial in improving the performance of over- lay cognitive radio networks. Most of the previ- ous works on spectrum sensing and dynamic spe- ctrum access consider the sensing effective- ness and spectrum utilization as the design cri- teria, while ignoring the energy related issues and QoS constraints. In this article, we propose a QoS provisioning energy saving dynamic acc- ess policy using stochastic control theory con- sidering the time-varying characteristics of wir- eless channels because of fading and mobility. The proposed scheme determines the sensing action and selects the optimal spectrum using the corresponding power setting in each decis- ion epoch according to the channel state with the objective being to minimise both the flame error rate and energy consumption. We use the Hidden Markov Model （HMM） to model a wir- eless channel, since the channel state is not dir- ectly observable at the receiver, but is instead embedded in the received signal. The proced- ure of dynamic spectrum access is formulated as a Markov decision process which can be sol- ved using linear programming and the primal- dual index heuristic algorithm, and the obta- ined policy has an index-ability property that can be easily implemented in real systems. Sim- ulation results are presented to show the per- formance improvement caused by the propo- sed approach.
