[Paper Review] Cooperative Beamforming for Cognitive Radio-Based Broadcasting Systems with Asynchronous Interferences

Mai H. Hassan, Md. Jahangir Hossain|arXiv (Cornell University)|May 8, 2014

Advanced MIMO Systems Optimization30 references3 citations

TL;DR

This paper proposes a robust cooperative beamforming technique for cognitive radio broadcasting systems that mitigates asynchronous interferences at primary receivers caused by distributed cooperating cognitive radio nodes (CCRNs). By formulating a two-phase suboptimal optimization—first determining beamforming directions and then allocating power under interference constraints—it achieves up to a 64% higher sum rate for secondary users compared to zero-forcing beamforming, even under imperfect or statistical channel knowledge and with CCRN selection for further 45% gain.

ABSTRACT

In order to address the asynchronous interference issue for a generalized scenario with multiple primary and multiple secondary receivers, in this paper, we propose an innovative cooperative beamforming technique. In particular, the cooperative beamforming design is formulated as an optimization problem that maximizes the weighted sum achievable transmission rate of secondary destinations while it maintains the asynchronous interferences at the primary receivers below their target thresholds. In light of the intractability of the problem, we propose a two-phase suboptimal cooperative beamforming technique. First, it finds the beamforming directions corresponding to different secondary destinations. Second, it allocates the power among different beamforming directions. Due to the multiple interference constraints corresponding to multiple primary receivers, the power allocation scheme in the second phase is still complex. Therefore, we also propose a low complex power allocation algorithm. The proposed beamforming technique is extended for the cases, when cooperating CR nodes (CCRNs) have statistical or erroneous channel knowledge of the primary receivers. We also investigate the performance of joint CCRN selection and beamforming technique. The presented numerical results show that the proposed beamforming technique can significantly reduce the asynchronous interference signals at the primary receivers and increase the sum transmission rate of secondary destinations compared to the well known zero-forcing beamforming (ZFBF) technique.

Motivation & Objective

• To address asynchronous interferences at primary receivers caused by distributed CCRNs in cooperative cognitive radio networks.
• To maximize the weighted sum rate of secondary destinations while ensuring asynchronous interference at primary receivers remains below threshold.
• To develop a suboptimal two-phase beamforming design that is robust to imperfect or statistical channel state information (CSI).
• To investigate joint CCRN selection and beamforming to further enhance secondary system performance.
• To evaluate performance under practical conditions such as channel estimation errors and partial CSI.

Proposed method

• Formulates a two-phase cooperative beamforming design: first, beamforming directions are determined for each secondary destination using a suboptimal approach.
• In the second phase, power is allocated across beamforming directions under multiple interference constraints from multiple primary receivers.
• Employs a robust beamforming vector design that maintains interference thresholds even with channel estimation errors or statistical CSI.
• Introduces a low-complexity power allocation algorithm to reduce computational burden despite multiple interference constraints.
• Applies a joint CCRN selection and beamforming strategy that selects nodes based on their contribution to secondary sum rate and interference impact on primary receivers.
• Uses an orthogonal projection technique to null interference at primary receivers, extending the zero-forcing beamforming (ZFBF) framework to handle asynchronous signals.

Experimental results

Research questions

• RQ1 How can cooperative beamforming be designed to minimize asynchronous interference at primary receivers in a multi-CCRNs, multi-primary-receiver cognitive radio system?
• RQ2 What is the achievable performance gain in secondary sum rate when using robust beamforming compared to conventional zero-forcing beamforming under imperfect CSI?
• RQ3 How does channel estimation error affect interference threshold violations, and can a robust beamforming design mitigate this?
• RQ4 What is the impact of using statistical CSI instead of instantaneous CSI on interference constraint satisfaction and secondary sum rate?
• RQ5 Can joint CCRN selection and beamforming further improve the secondary sum rate, and by how much?

Key findings

• The proposed robust beamforming technique reduces asynchronous interference at primary receivers more effectively than zero-forcing beamforming (ZFBF), especially under channel estimation errors.
• The proposed beamforming technique achieves up to a 64% higher sum transmission rate for secondary destinations compared to ZFBF under perfect CSI.
• With channel estimation errors, the robust beamforming design maintains interference constraints more reliably than conventional LBF, avoiding frequent threshold violations.
• When only statistical CSI is available, the robust beamforming technique keeps the probability of interference threshold violation below the maximum allowable value (ε = 0.1).
• Joint CCRN selection with beamforming increases the secondary sum rate by up to 45% compared to using all CCRNs without selection.
• The low-complexity power allocation algorithm effectively manages multiple interference constraints, making the beamforming design practical for real-time implementation.