A Unified QoS and Security Provisioning Framework for Wiretap Cognitive Radio Networks: A Statistical Queueing Analysis Approach

• Published in: IEEE transactions on wireless communications Vol. 18; no. 3; pp. 1548 - 1565
• Main Authors: Wang, Yichen, Tang, Xiao, Wang, Tao
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Bandwidths; Cognitive radio; Communication channels; Convexity; Cybersecurity; Delays; effective bandwidth; effective capacity; Equivalence; Hulls; Information security; information security protection; Interference; Optimization; power allocation; Power management; Provisioning; QoS provisioning; Quality of service; Quality of service architectures; Queues; Queuing theory; Radio broadcasting; Radio networks; Resource management; Statistical analysis; statistical queueing analysis; Wireless communication; Wireless networks; Wiretapping
• DOI: 10.1109/TWC.2019.2893381
• ISSN: 1536-1276

Due to the spectrum-sharing feature of cognitive radio networks (CRNs) and the broadcasting nature of wireless channels, providing quality-of-service (QoS) provisioning for primary users (PUs) and protecting information security for secondary users (SUs) are two crucial and fundamental issues for CRNs. Consequently, in this paper, we establish a unified QoS and security provisioning framework for wiretap CRNs. Specifically, different from the widely used deterministic QoS provisioning method and information-theoretical security protection approach, our established framework, which is built on the theory of statistical queueing analysis, can quantitatively characterize the PU's QoS and the SU's security requirements. By adopting the theories of effective capacity and effective bandwidth , we further convert the QoS and security requirements to the equivalent PU's effective capacity and SU's effective bandwidth constraints. Following our developed framework, we formulate the nonconvex optimization problem, which aims at maximizing the average throughput of SU subject to PU's QoS requirement, SU's security constraint, as well as SU's average and peak transmit power limitations. Then, we adopt the techniques of convex hull and probabilistic transmission to convert the original nonconvex problem to the equivalent convex problem and obtain the optimal power allocation scheme through the Lagrangian method. Moreover, we also develop a fixed power allocation scheme which is suboptimal but has low complexity. The simulation results are also provided, which demonstrate the impact of the PU's QoS and the SU's security requirements on SU's throughput as well as the advantage of our proposed optimal power allocation scheme over the fixed power allocation scheme and the conventional security-based water-filling policy.