Cooperative Feedback Bits Allocation and Transmit Power Control in Underlay Cognitive Radio Networks

Abstract

In this paper, we consider an underlay cognitive radio network where the spectrum is shared with the primary network. Due to the coexistence of primary and secondary networks, primary users (PUs) are interfered with by the inter-network interference, at the same time secondary users (SUs) counteract the intra-network (inter-user) interference. Based on the cooperative feedback between the primary network and the secondary network, the secondary transmitter (ST) applies the cognitive beamforming to suppress the interference to PUs while improving the sum rate of SUs. We herein propose an adaptive feedback bits allocation among multiple PUs and SUs where the quantized channel direction information (CDI) for the interference channel is forwarded to the ST in order to utilize the beamforming. Moreover, based on the cognitive beamforming, we adjust the transmit power of the ST under the constraint of the average interference at PUs. To jointly solve the feedback bits allocation and the transmit power control problems, we formulate an optimization problem which requires a little iterations compared with the separated feedback bits allocation and the transmit power control problems. Numerical results show that the proposed scheme significantly improves the sum rate of SUs while satisfying the average interference constraint at PUs.

Feedback Bits Allocation for Guaranteed Bit Rate Services in Cooperative Cognitive Radio Networks

“…Third, we consider inter-cell interference (ICI) as well as inter-user interference (IUI) in multiple secondary cells of the secondary network while keeping the inter-network interference from STs to PUs below a certain value. Hence, although the results of this paper seem to be an incremental extension of the results of [17], this paper has significant differences and enhancements as follows: First, the considered system model is different. This paper considers multiple secondary cells in the secondary network while the previous work of [17] considered a single secondary cell in the secondary network.…”

“…Hence, although the results of this paper seem to be an incremental extension of the results of [17], this paper has significant differences and enhancements as follows: First, the considered system model is different. This paper considers multiple secondary cells in the secondary network while the previous work of [17] considered a single secondary cell in the secondary network. Hence, the previous work of [17] did not consider the ICI.…”

“…However, the previous studies of [8,[13][14][15][16] did not consider the beamforming technique with limited feedback which is an outstanding technique to mitigate the interference while increasing the sum rate. The work of [17] adaptively allocated the feedback bits and controlled the transmit power at the same time when the total number of feedback bits is fixed in the cooperative CR network, where they applied the cognitive beamforming. However, they failed to guarantee the minimum data rate for SUs.…”

“…This paper considers multiple secondary cells in the secondary network while the previous work of [17] considered a single secondary cell in the secondary network. Hence, the previous work of [17] did not consider the ICI. Second, the objectives are different.…”

“…Second, the objectives are different. This paper aims to ensure the minimum data rate for SUs while satisfying the inter-network interference constraint while the previous work of [17] aimed to maximize the sum rate of SUs without considering the minimum data rate requirement of SUs. Third, the derived results are different because of different objectives.…”