Cognitive MIMO Radio: A Competitive Optimality Design Based on Subspace Projections
arXiv:0808.0978 · doi:10.1109/MSP.2008.929297
Abstract
Cognitive MIMO Radio: A Competitive Optimality Design Based on Subspace Projections
References in corpus (5)
- Joint Design and Separation Principle for Opportunistic Spectrum Access in the Presence of Sensing Errors
- Optimal Linear Precoding Strategies for Wideband Non-Cooperative Systems based on Game Theory-Part I: Nash Equilibria
- Competitive Design of Multiuser MIMO Systems based on Game Theory: A Unified View
- Optimal Linear Precoding Strategies for Wideband Non-Cooperative Systems based on Game Theory-Part II: Algorithms
- Cognitive MIMO Radio: A Competitive Optimality Design Based on Subspace Projections
Cited by in corpus (16)
- Fifty Years of MIMO Detection: The Road to Large-Scale MIMOs
- Dynamic Resource Allocation in Cognitive Radio Networks: A Convex Optimization Perspective
- Real and Complex Monotone Communication Games
- Cognitive MIMO Radio: A Competitive Optimality Design Based on Subspace Projections
- Robust Monotonic Optimization Framework for Multicell MISO Systems
- Energy Efficiency in MIMO Underlay and Overlay Device-to-Device Communications and Cognitive Radio Systems
- The One-Bit Null Space Learning Algorithm and its Convergence
- Time Delay Estimation in Cognitive Radio Systems
- Interference Mitigation for Cognitive Radio MIMO Systems Based on Practical Precoding
- Sense-and-Predict: Harnessing Spatial Interference Correlation for Cognitive Radio Networks
- Blind Null-Space Learning for MIMO Underlay Cognitive Radio Networks
- Distributed Energy Efficient Cross-layer Optimization for Multihop MIMO Cognitive Radio Networks with Primary User Rate Protection
- Spatial MAC in MIMO Communications and its Application to Underlay Cognitive Radio
- Transmit Antenna Selection in Underlay Cognitive Radio Environment
- Opportunistic Spectrum Sharing in Dynamic Access Networks: Deployment Challenges, Optimizations, Solutions, and Open Issues
- On the Throughput and Energy Efficiency of Cognitive MIMO Transmissions