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
In Cognitive radio ad hoc networks （CRAHNs）, the secondary users （SUs） or cognitive radio nodes （CRs） are always equipped with limited energy and have a high error probability of data transmission. To address th...In Cognitive radio ad hoc networks （CRAHNs）, the secondary users （SUs） or cognitive radio nodes （CRs） are always equipped with limited energy and have a high error probability of data transmission. To address this issue, we first describe the network utility under energy constraint as a max-min model, where the re-transmission strategy with network coding is employed. Additionally, the expression of retransmission probability is presented in terms of power and bit error rate （BER）. Moreover, since the max-min model is non-convex in both objective and constraints, we use a normal- form game to find a near-optimal solution. The simulation results show that the proposed approach could achieve a higher network utility than the compared approaches.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.
基金This work was supported in part by the Research Fund for the Doctoral Program of Higher Education of China under Grant 20122304130002,the Natural Science Foundation in China under Grant 61370212,the Fundamental Research Fund for the Central Universities under Grant HEUCFZ1213 and HEUCF100601
文摘In Cognitive radio ad hoc networks （CRAHNs）, the secondary users （SUs） or cognitive radio nodes （CRs） are always equipped with limited energy and have a high error probability of data transmission. To address this issue, we first describe the network utility under energy constraint as a max-min model, where the re-transmission strategy with network coding is employed. Additionally, the expression of retransmission probability is presented in terms of power and bit error rate （BER）. Moreover, since the max-min model is non-convex in both objective and constraints, we use a normal- form game to find a near-optimal solution. The simulation results show that the proposed approach could achieve a higher network utility than the compared approaches.
