Long Cao

Robust route and channel selection in cognitive radio networks

In this paper, the joint route and channel selection problem with reliability guarantee in cognitive radio network (CRN) is addressed. Since the interference to licensed spectrum owners needs to be strictly controlled, cognitive radio enabled users (CUs) should vacate the using channel immediately on detecting licensed users and the end to end performance may be seriously degraded. Furthermore, the route constructed for a session may impose great negative influence on other current or latish sessions in the network. To account for these challenges, the route reliability is formulated based on the link valid probability and a metric named interference impact is proposed to value the influence of a route to the adjacent links. With the objective of minimizing the interference impact while providing throughput and reliability guarantee, the joint route and channel selection problem is formulated and shown to be in the form of integer nonlinear programming (INLP). Based on the analysis of the problem-specific feature, an on-demand route discovery algorithm is proposed to find reliable candidate routes, and a heuristic cross-layer optimization algorithm is proposed to choose the near-optimal route. Simulation results demonstrate that the proposed algorithm can guarantee the current route requirement while improving whole network throughput.

Matching Theory for Channel Allocation in Cognitive Radio Networks

For a cognitive radio network (CRN) in which a set of secondary users (SU) competes for a limited number of channels (spectrum resources) belonging to primary user, the channel allocation is a challenge and dominates the throughput and congestion of the network . In this paper, the channel allocation problem is first formulated as the 0-1 integer programming optimization, with considering the overall utility both of primary system and secondary system. Inspired by matching theory, a many-to-one matching mechanism is used to remodel the channel allocation problem, and the corresponding PU proposing deferred acceptance (PPDA) algorithm is also proposed to yield a stable matching. We compare the performance and computation complexity between these two solutions. Numerical results demonstrate the efficiency and obtain the communication overhead of the proposed schemes.

Maximal throughput routing with stablility constraint in cognitive radio ad hoc networks

Cognitive radio (CR) is a promising technology that enables opportunistic using of the unused spectrum to alleviate the spectrum scarcity problem. However, as the interference to licensed spectrum owners needs to be strictly controlled, CR enabled users (CRs) should vacate the using channel immediately on detecting licensed users activity and the end to end performance may be seriously degraded. In this paper, we propose a robust routing scheme for cognitive radio ad hoc networks that can accommodate to the spectrum availability variation and keep stable to guarantee the end to end performance of CRs. The path stability is modeled considering both available channel numbers and channel characteristic along the path. The paths beyond a robust threshold are regarded to be feasible and the one with maximal throughput is chosen for transmission. Simulation results show that the proposed scheme performs much better than other existing protocols in terms of route throughput and stability maintenance.

Robust clustering for cognitive radio ad hoc networks with group mobility

Cognitive radio ad hoc networks (CRAHNs) have great potential to provide diverse services in the dynamic spectrum environment. And group mobility is one of the key features of CRAHNs in many applications. In this paper, the topology management of CRAHNs with group mobility is investigated. The channel availability and group mobility of nodes in CRAHNs are modeled. A robust clustering algorithm based on affinity propagation model (RCAP) is proposed. Following the message passing model of affinity propagation, RCAP relies only on the distributed interaction of nodes in the network to construct robust clusters. Simulation results demonstrate that the generated clusters of the proposed algorithm are more robust for CRAHNs with group mobility.

A spectrum map based dynamic spectrum management framework

Dynamic spectrum management (DSM) of cognitive radio networks (CRNs) has been a hotspot for spectrum management departments as well as research community to alleviate spectrum scarcity problem. With the motive of facilitating CRNs with spectrum-related information with low cost in different scenarios including infrastructure less environment, this paper proposes a spectrum map based DSM (SMDSM) framework. Spectrum map is defined to provide external support for CRs with information including spectrum policy, spectrum availability, radio propagation characteristics, etc. The distribution scheme of spectrum map is designed for CRNs with and without infrastructure. Through the construction and distribution of spectrum map, SMDSM implements efficient spectrum management and provides spectrum information service for CRNs. The hardware in loop simulation system based on USRP and GNU radio is developed. Simulation results demonstrate that the DSM framework can make better use of spectrum and improve the system performance on throughput and delay.

Distributed resource allocation for D2D-enabled two-tier cellular networks with channel uncertainties

Device-to-device (D2D) communications were proposed to offload traffic and enhance network performance with the existing cellular infrastructure. In this paper, the uplink resource allocation problem for an underlay two-tier cellular network is studied. The full-duplex relay nodes are deployed to serve the D2D users due to the poor link condition. Considering the channel uncertainty, this problem is modeled by worst-case optimization approach and student-project allocation matching game respectively. In addition, a distributed resource allocation algorithm is proposed to achieve lower computation complexity. Numerical results evaluate the performance of the proposed scheme.

Spectrum opportunity exploration based on joint spectrum sensing and the spectrum prediction enabled spectrum database

Fast and precise spectrum opportunity (SOP) exploration is a fundamental and vital procedure for dynamic spectrum management. In this paper, the temporal rather than geographical feature of spectrum database is investigated. The spectrum prediction is formulated and taken as a function of spectrum database. Furthermore, spectrum sensing is also a choice for SOP exploration to cope with the inefficiency of the solely spectrum database approach on freshness of the information and the precise of the prediction. On that consideration, a joint SOP exploration (JSE) scheme is proposed which determines SOP based on joint spectrum sensing and the spectrum prediction enabled spectrum database. The advantages of spectrum database, spectrum prediction and spectrum sensing can be taken jointly to ascertain SOP. Extensive simulation results demonstrate that the proposed scheme can accommodate to diverse scenarios with different sensing ability of SUs and prediction ability of spectrum database, while the advantages of existing SOP exploration approaches can be jointly taken.

Secure cooperative spectrum sensing based on energy efficiency under SSDF attack

Spectrum sensing is a premise for the realization of Cognitive Radio Networks (CRN). This paper considers Spectrum Sensing Data Falsification (SSDF) attack to CRN, where malicious users send false local spectrum sensing results in cooperative spectrum sensing, and it will result in wrong final decisions by the fusion center. A low overhead symmetric cryptographic mechanism utilizing message authentication code to authenticate the sensing data of Secondary User (SU) is proposed to resolve this problem. Moreover, in this article, the concept of energy efficiency in cooperative spectrum sensing is first introduced, and the optimal length of message authentication code is provided to maximize the energy efficiency. Simulation results verify the efficiency of this scheme, and the solution of optimal problem is also evaluated.

Robust Routing in Cognitive Radio Ad Hoc Networks

Cognitive radio (CR) is a promising technology that enables opportunistic using of the vacant licensed frequency to alleviate the spectrum scarcity problem. However, as the interference to licensed spectrum owners needs to be strictly controlled, CR enabled users (CRs) should vacate the using channel immediately on detecting licensed users activity and the end to end performance may be seriously degraded. In this paper, we propose a robust routing scheme for cognitive radio ad hoc networks that can accommodate to the spectrum availability variation and keep stable to guarantee the end to end performance of CRs. The path stability is modeled considering both available channel numbers and channel characteristic along the path. The paths beyond a robust threshold are regarded to be feasible and the one with maximal throughput is chosen for transmission. Simulation results demonstrate that the proposed scheme performs much better than other existing protocols in terms of end to end throughput and stability maintenance.