Optimal Power Allocation for Fading Channels in Cognitive Radio Networks: Ergodic Capacity and Outage Capacity
arXiv:0808.3689 · doi:10.1109/TWC.2009.071448
Abstract
A cognitive radio network (CRN) is formed by either allowing the secondary users (SUs) in a secondary communication network (SCN) to opportunistically operate in the frequency bands originally allocated to a primary communication network (PCN) or by allowing SCN to coexist with the primary users (PUs) in PCN as long as the interference caused by SCN to each PU is properly regulated. In this paper, we consider the latter case, known as spectrum sharing, and study the optimal power allocation strategies to achieve the ergodic capacity and the outage capacity of the SU fading channel under different types of power constraints and fading channel models. In particular, besides the interference power constraint at PU, the transmit power constraint of SU is also considered. Since the transmit power and the interference power can be limited either by a peak or an average constraint, various combinations of power constraints are studied. It is shown that there is a capacity gain for SU under the average over the peak transmit/interference power constraint. It is also shown that fading for the channel between SU transmitter and PU receiver is usually a beneficial factor for enhancing the SU channel capacities.
26 pages, 9 figures, to appear in IEEE Transactions on Wireless Communications
References in corpus (2)
Cited by in corpus (52)
- On Ergodic Sum Capacity of Fading Cognitive Multiple-Access and Broadcast Channels
- Multiband Spectrum Access: Great Promises for Future Cognitive Radio Networks
- Optimal Bandwidth and Power Allocation for Sum Ergodic Capacity under Fading Channels in Cognitive Radio Networks
- The Effects of Limited Channel Knowledge on Cognitive Radio System Capacity
- Mobile Data Offloading through A Third-Party WiFi Access Point: An Operator's Perspective
- Intelligent Wireless Communications Enabled by Cognitive Radio and Machine Learning
- A Unified Framework for the Ergodic Capacity of Spectrum Sharing Cognitive Radio Systems
- Random Subcarrier Allocation in OFDM-Based Cognitive Radio Networks
- Energy-Efficient Power Adaptation for Cognitive Radio Systems under Imperfect Channel Sensing
- Full-Duplex Wireless-Powered Communication Network with Energy Causality
- Asymptotic Performance Analysis of Generalized User Selection for Interference-Limited Multiuser Secondary Networks
- Primary Traffic Characterization and Secondary Transmissions
- Symbiotic Radio: Cognitive Backscattering Communications for Future Wireless Networks
- Throughput Enhancement of Multicarrier Cognitive M2M Networks: Universal-Filtered OFDM Systems
- Joint optimal power allocation and sensing threshold selection for SUs capacity maximization in SS CRNs
- On the Performance Analysis of Underlay Cognitive Radio Systems: A Deployment Perspective
- Riding on the Primary: A New Spectrum Sharing Paradigm for Wireless-Powered IoT Devices
- Optimized Power Control for Over-the-Air Computation in Fading Channels
- Ergodic Capacity of Cognitive Radio under Imperfect Channel State Information
- On Active Learning and Supervised Transmission of Spectrum Sharing Based Cognitive Radios by Exploiting Hidden Primary Radio Feedback
- Capacity Analysis in Multi-Radio Multi-Channel Cognitive Radio Networks: A Small World Perspective
- Cognitive Beamforming Made Practical: Effective Interference Channel and Learning-Throughput Tradeoff
- Cognitive UAV Communication via Joint Trajectory and Power Control
- Multiuser Diversity for the Cognitive Uplink with Generalized Fading and Reduced Primary's Cooperation
- On Peak versus Average Interference Power Constraints for Protecting Primary Users in Cognitive Radio Networks
- Cognitive Multiple Access Network with Outage Margin in the Primary System
- Energy-Efficient Power Allocation in Cognitive Radio Systems with Imperfect Spectrum Sensing
- Optimal Transmit Power Allocation for MIMO Two-Way Cognitive Relay Networks with Multiple Relays
- Power Allocation for Outage Minimization in Cognitive Radio Networks with Limited Feedback
- Transmit Antenna Selection in Underlay Cognitive Radio Environment
- Spectrum Refarming: A New Paradigm of Spectrum Sharing for Cellular Networks
- Joint Uplink-and-Downlink Optimization of 3D UAV Swarm Deployment for Wireless-Powered NB-IoT Networks
- Sequential Joint Detection and Estimation: Optimum Tests and Applications
- Optimal Link Adaptation for Multicarrier Communication Systems
- Investigation on Multiuser Diversity in Spectrum Sharing Based Cognitive Radio Networks
- Asymptotic Analysis of Multi-Antenna Cognitive Radio Systems Using Extreme Value Theory
- Sequential Joint Spectrum Sensing and Channel Estimation for Dynamic Spectrum Access
- Error Rate Analysis of Cognitive Radio Transmissions with Imperfect Channel Sensing
- On the Performance of Adaptive Modulation in Cognitive Radio Networks
- Multi-user Diversity in Spectrum Sharing Systems over Fading Channels with Average Power Constraints
- Performance Analysis of Mean Value-Based Power Allocation with Primary User Interference in Spectrum Sharing Systems
- Multi-User Diversity with Optimal Power Allocation in Spectrum Sharing under Average Interference Power Constraint
- Performance Analysis of Cognitive Radio Systems with Imperfect Channel Sensing and Estimation
- Adaptive Modulation in OSA-based Cognitive Radio Networks
- Underlay Cognitive Radios with Capacity Guarantees for Primary Users
- Capacity Optimization through Sensing Threshold Adaptation for Cognitive Radio Networks
- Throughput of Cognitive Radio Systems with Finite Blocklength Codes
- On the Ergodic Rate of OFDMA Cognitive Radios under Imperfect Cross-Link Information
- Optimizing DF Cognitive Radio Networks with Full-Duplex-Enabled Energy Access Points
- Resource Allocation Based on Deep Neural Networks for Cognitive Radio Networks
- Ergodic Sum-Rate Maximization for Fading Cognitive Multiple Access Channels without Successive Interference Cancellation
- Cost minimization for fading channels with energy harvesting and conventional energy