Adaptive Qos-Support Mechanisms For Dynamic Cognitive Radio Network

The dramatic increase in wireless access services and low spectrum utilization existing in licensed channels necessitate a new communication paradigm (i.e., cognitive radio network, CRN), whose key techniques are cognitive radio and dynamic spectrum access. Through opportunistic spectrum access, CRN can improve the spectrum utilization. However, CRN do not have a fixed channel and modulation type, and its transmission parameters are determined by spectrum sensing, spectrum mobility, spectrum sharing and spectrum management processes. To realize multimedia transmissions over CRN, this paper will consider the above four processes in our research.First, a cooperative spectrum sensing algorithm is proposed, which integrals compressive sensing (CS) and the spatial-temporal data mining method. The spectrum sensing which tries to aware the radio enviroment is the basic function to realize services over CRN, which is the main difference from traditional wireless communications. Since the CRN is deployed in a certain area, different clusters may have different sparseness spectrum states and is not appropriate for information sharing in data mining, which has not been addressed very well in the spectrum sensing field. Hence, in our cooperative spectrum sensing, the Dirichlet process (DP) prior is employed to make an automatically grouping among different clusters. In each group, the Bayesian inference is used for information sharing and one common sparseness hyper-parameters is discovered in each group. Hence, the DP prior is very suitable to our heterogenous CRN and collects the spatial information of the CS data. Moreover, the sequential CS data are not independent to each other. To exploit the time-domain relevance among sequential CS observations, the hidden markov model is employed to describe the relationship between hidden subcarrier state and sequential CS data, and the Viterbi algorithm is used to find out the final hyper-parameters and make a high resolution spectrum decision for each secondary user (SU). Simulation results show that our proposed algorithm successfully exploits the spatial-temporal relationship to obtain higher spectrum sensing performance in terms of normalized mean square error, probability of correct detection, and probability of false alarming compared with some recent research works.Second, the spectrum mobility is used to guarantee the quality of service of multimedia application, and the spectrum sensing is necessary to detect the radio enviroment. However, spectrum sensing will cause extra delay. Hence, the optimal spectrum sensing frequency and packet loading schemes are discussed in this paper, which integrals spectrum sensing in spectrum mobility management. Here the sensing frequency means how frequently a CR user detects the radio enviroment, and the spectrum sensing is assumed to operated periodly. This paper well considers the packet arrive rate of PU and derives the math model between the sensing frequency and the number of remaining packets that need to be sent, as well as the relationship between sensing frequency and the new channel availability time during which the CRN user is allowed to use a new channel (after the current channel is re-occupied by primary users) to continue packets transmission. Hence, a smaller number of remaining packets and a larger value of new channel availability time will help to transmit more multimedia packets within a required delay and thus a higher QoS. Then by using the above relationship models, we select appropriate sensing frequency under single channel case, and study the trade-offs among the number of selected channels, optimal sensing frequency and packet-loading scheme under multi-channel case. The optimal sensing frequency and packet-loading solutions for multi-channel case are obtained by using the combination of Hughes-Hartogs and discrete particle swarm optimization (DPSO) algorithms. Our experiments of image and video packets transmission demonstrate the validity of our sensing frequency selection and packet loading schemes.Thrid, to fairly share the available spectrum resource of the uplink in each cluster, a distributed, cooperative and overlay spectrum sensing mechanism called cognitive cross-layer scheduling scheme is proposed for non-contiguous orthogonal frequency-division multiplexing based CRN, which can generate the optimal subcarrier selection, power and modulation allocation for each multimedia packet from SU. Conventional dynamic scheduling schemes assume significant information exchange among all SUs through a common control channel (CCC), to realize cooperative spectrum sharing. To avoid such a heavy traffic information exchange, a cognitive method to learn the traffic profile is proposed in our spectrum sharing mechanism. From the viewpoint of the target SU, the other SUs in the cluster can be grouped as a virtual SU, and the target SU uses the Dirichlet-prior based fully Bayesian model to update the statistical distribution of subcarrier selection strategy profile of the virtual SU. Moreover, such a statistical distribution is used to estimate the probability of queue waiting time less than a threshold. To learn the throughput performance of SU, the time window is introduced to accurately define the throughput of SUs. The time window can clearly demonstrate how many packets can be transmitted simultaneously over multiple subcarriers, compared with the required packets transmission rate. Finally, maximizing the delay and throughput-based utility function, the cognitive cross-layer scheduling scheme generates the optimal subcarrier selection, power and modulation allocation for each multimedia packet. The data and real video transmission are simulated to validate the correctness of our cognitive cross-layer scheduling schemes. The simulation results match with theoretical analysis very well, and the reconstructed video quality using our proposed scheduling scheme is superior to the other two recently proposed schemes.Last, the cross-layer design of spectrum management and routing design is considered, and a stability-capability oriented routing protocol is proposed. In high-mobility CRNs, the fast topology changes decrease the stability of transmission link and the end-to-end QoS performance and thus the complexity of routing scheme. In this paper, the cooperative searching (i.e., unmanned aerial vehicle, UAV) scenario is considered, and (1) a realistic mobility model is proposed to describe the movement of highly mobile airborne nodes (i.e., UAVs), and estimate the link stability performance based on node movement patterns; (2) a CRN topology management scheme based on a clustering model is also proposed which considers radio link availability, and the cluster-heads (CHs) are selected based on the node degree level, average number of hops and channel switching from member nodes to the CH; (3) two new CCC selection schemes are proposed, which are based on the node contraction concept and the DPSO algorithm. The inter-cluster control channels and gateways are selected from the CHs, considering the average delay of control information transmission between two CHs as well as the total throughput of control channels; (4) a novel routing scheme is proposed that tightly integrates with channel assignment scheme based on the node capacity for the high mobility scenario. Our simulation results show that our proposed CCC selection scheme has high throughput and small transmission time. Compared to other popular CRN routing approaches, our proposed routing scheme achieves lower average end-to-end delay and higher packet delivery ratio.