Capacity and Energy Efficiency of Multi-User Spectrum Sharing Systems with Opportunistic Scheduling

• Published in: IEEE transactions on wireless communications Vol. 8; no. 6; pp. 2836 - 2841
• Main Authors: Ban, Tae Won, Choi, Wan, Sung, Dan Keun
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.06.2009; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Analytical models; Applied sciences; Channels; cognitive radio; Computational complexity; Computational modeling; Computer simulation; Detection; Energy consumption; Energy efficiency; Energy loss; Exact sciences and technology; Interference; Interference constraints; multiuser diversity; Networks; Optimization; Performance loss; Power system reliability; Radiocommunication specific techniques; Radiocommunications; sensing power; Spectrum sharing; Studies; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Throughput; Transmission and modulation (techniques and equipments); Wireless communication; Performance evaluation; Energy spectrum; Multiple access; multiuser diversity; Data transmission; Scheduling; Computational complexity; Optimal strategy; cognitive radio; sensing power; Simulation; Energetic efficiency; Analytical method; Minimum energy; Metric; Spectrum sharing; Transmission loss; Software radio; Power spectrum
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2009.080944

This paper investigates the capacity and energy efficiency of spectrum sharing systems with opportunistic user selection where a secondary network utilizes spectrum bands licensed to a primary network under interference regulation. In spectrum sharing systems, secondary users consume a fraction of their resources in sensing the channels to the primary users to comply with the interference constraints. Although more resources for sensing improve reliability and performance, the throughput loss due to time overhead and energy loss due to power overhead should be properly incorporated in performance evaluation. In this context, we define and derive a new metric-average capacity normalized by the total energy consumption-reflecting time and power overhead for spectrum sensing. Based on the developed framework, the optimal normalizedcapacity is investigated. We also propose a simple and practical suboptimal best-n scheme motivated by the infeasibility and high computational complexity of the optimal strategy, where n denotes the number of sensing secondary users. Our analytical and simulation results show that the proposed best-1 scheme is an energy-efficient technique with near optimality in terms of the capacity normalized by the energy consumption.