Cooperative Feedback for Multi-Antenna Cognitive Radio Networks
Kaibin Huang, Rui Zhang

TL;DR
This paper introduces a practical cooperative feedback framework for multi-antenna cognitive radio networks, improving spectrum sharing by optimizing beamforming with finite-rate feedback from primary users.
Contribution
It proposes new cooperative feedback algorithms for cognitive beamforming that enhance interference management and spectrum efficiency in MISO cognitive radio systems.
Findings
Outage probability analysis for different feedback algorithms.
Optimal bit allocation between CDI and IPC feedback.
Enhanced spectrum sharing performance with cooperative feedback.
Abstract
Cognitive beamforming (CB) is a multi-antenna technique for efficient spectrum sharing between primary users (PUs) and secondary users (SUs) in a cognitive radio network. Specifically, a multi-antenna SU transmitter applies CB to suppress the interference to the PU receivers as well as enhance the corresponding SU-link performance. In this paper, for a multiple-input-single-output (MISO) SU channel coexisting with a single-input-single-output (SISO) PU channel, we propose a new and practical paradigm for designing CB based on the finite-rate cooperative feedback from the PU receiver to the SU transmitter. Specifically, the PU receiver communicates to the SU transmitter the quantized SU-to-PU channel direction information (CDI) for computing the SU transmit beamformer, and the interference power control (IPC) signal that regulates the SU transmission power according to the tolerable…
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Taxonomy
TopicsAdvanced MIMO Systems Optimization · Cognitive Radio Networks and Spectrum Sensing · Cooperative Communication and Network Coding
