Cooperative beamforming in cognitive radio network with hybrid relay

Tao, Yi; Guo, Li; Niu, Kai; Cai, Hongyan; Lin, Jiaru; Ai, Wenbao

doi:10.1109/ictel.2012.6221214

Cited by 12 publications

(9 citation statements)

References 14 publications

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“…From (10) we can see that the interference component at the SRx is due to the transmission of the primary user in the same spectrum. Using (9) and (10), we can rewrite (7) as…”

Section: Signal Modelmentioning

confidence: 98%

“…Two of the three cases have closed-form solutions and the optimization problem in the third case is shown to be a quasi-convex problem, which can be efficiently solved using second-order-cone-programming (SOCP) and bi-section search method. Compared to the method using the technique of SDR [10] and [12], the proposed method has much lower computation complexity. Simulation results show that the proposed method improves the system performance considerably.…”

Section: Introductionmentioning

confidence: 96%

“…Relation to prior work: Both this paper and the works in [10], [12], [13] consider the distributed beamforming method for cognitive relay networks. Different from [10] and [12], this paper proposes a distributed beamforming approach that has a closed-form solution or the resultant quasi-convex problem can be solved efficiently with bi-section search method and SOCP.…”

Section: Introductionmentioning

confidence: 97%

“…Different from [10] and [12], this paper proposes a distributed beamforming approach that has a closed-form solution or the resultant quasi-convex problem can be solved efficiently with bi-section search method and SOCP. While the problems in [10] and [12] find sub-optimal solutions by using SDP, which has much higher computation complexity than SOCP. Different from [13] that considers no constraint on the total relay transmit power, this paper considers both the constraints on the total relay transmit power and the interference power.…”

Section: Introductionmentioning

confidence: 99%

“…The resultant beamforming problem is solved using Genetic algorithm in [9]. In [10] and [12], the distributed beamforming problem is relaxed to a semi-definite programming (SDP) problem using the technique of semi-definite relaxation (S-DR). The authors in [13] considers minimizing the interference power while satisfying the QoS of the secondary user.…”

Section: Introductionmentioning

confidence: 99%

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Distributed beamforming for cognitive relay networks

Chen

Zhang

Sun

2014

2014 IEEE China Summit &Amp; International Conference on Signal and Information Processing (ChinaSIP)

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A distributed beamforming technique for half-duplex underlay cognitive relay networks is developed in this paper. The considered cognitive relay network consists of one pair of primary users, one pair of secondary users and multiple relays. With the help of multiple relays, the secondary transmitter sends data to the secondary receiver. In our approach, the receive quality-of-service at the secondary user is maximized while keeping the total relay transmit power and the interference power below a predefined threshold. The resultant problem is shown to have closed-form solutions with certain conditions or can be formulated as a quasi-convex problem, which can be solved efficiently using bi-section search method and secondorder-cone programming. Simulation results demonstrate that the proposed beamforming method improves the system performance.Index Terms-Distributed beamforming, worst-case, cognitive relay networks INTRODUCTIONCognitive radio has recently attracts much interest as it can improve the utilization of wireless spectrum resources, which enables unlicensed users or secondary users to communicate with each other over licensed bands through three main ways. In the interweave approach, the secondary transmitter exploits the spectrum holes of the licensed users or primary users to transmit data [1], [2]. In the overlay method, the secondary user is allowed to operate simultaneously with the primary user over the same spectrum. The transmission of the primary user is improved by employing sophisticated signal processing and coding techniques [3]. In the underlay way, the secondary user and the primary user share the same spectrum simultaneously while the interference power at the primary user is lower than a predefined threshold or interference temperature [2], [4]. Due to the simplicity of the implementation, we consider the underlay approach in this paper.Cooperative relay networks have also attracted much interest in the literature as they can exploit cooperative spatial diversity of different users in the network [5]- [6]. These advantages are introduced by the scheme that different users in relay networks share their communication resources to help each other in data transmission.Since the transmit power of the secondary user is limited to guarantee the quality-of-service (QoS) of the primary user in the underlay approach, it is an attractive choice to employ cooperative relaying techniques in cognitive networks [7]- [15]. The secondary user can operate as a relaying node for the primary user to improve the QoS of the primary user and thus helps to improve the threshold of the interference temperature [7]. The secondary user can also work as a relaying node for other secondary users to improve the receive QoS

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“…From (10) we can see that the interference component at the SRx is due to the transmission of the primary user in the same spectrum. Using (9) and (10), we can rewrite (7) as…”

Section: Signal Modelmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Distributed beamforming for cognitive relay networks

Chen

Zhang

Sun

2014

2014 IEEE China Summit &Amp; International Conference on Signal and Information Processing (ChinaSIP)

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Optimal received SINR balancing based on cooperative beamforming in cognitive radio networks

Moghaddam

Farrokhi

Granelli

2016

Int J Communication

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In this paper, we investigate a two-step cooperative cognitive radio network, which consists of two secondary links, a number of relays, and one primary link. During the first step, the primary link is assumed to be idle; both secondary sources simultaneously broadcast their data to the relay network. During the second step, the relay network employs a proposed cooperative beamforming (CBF) scheme and transmits the received data toward both of the secondary destinations (no matter whether the primary link is idle or not). The proposed CBF scheme enables the investigated network to simultaneously maximize received signal to interference plus noise ratio at both of the secondary destinations while keeping interference plus noise power at the primary destination under a predefined threshold. Indeed, the proposed scheme represents an optimal received signal to interference plus noise ratio balancing approach based on CBF, which guarantees the required quality of service for the primary link and also both secondary links. We optimize the CBF vector by relaxing the optimization problem to a convex semidefinite programming and solving with the bisection search algorithm. Numerical results show the efficiency and robustness of our approach. A comparison of our approach with the zero-forcing beamforming method is also presented. Figure 1. Traditional two-hop cognitive radio network.The concept of cooperative communications is a new paradigm shift for wireless communications. In cooperative communications, independent paths between the source and destination are generated via a group of relays (i.e., relay network). So the relay network can represent an auxiliary path to the direct path between the source and destination [8].Cooperation among different users can improve the performance of CR networks. In a CR, because of high path loss and shadowing, the secondary source could not communicate directly with the secondary destination. Hence, a relay network could help by receiving the messages from the secondary source and forwarding them to the secondary destination [8][9][10].In CR networks, the beamforming (BF) strategy can be used to improve the performance [8,11,12]. BF is a spatial processing technique that can form the radiation pattern to meet the requirements dictated by the wireless system [13][14][15]. The BF strategy in CR networks enables both PU and SU sources to have simultaneous communications to their destinations in the same channel [9,16]. In order to exploit the BF strategy, the sources have to use multiple antennas, but they are equipped with a single antenna because of some implementation constraints [17,18].The cooperative beamforming (CBF) method would bring substantial enhancements to traditional two-hop CR networks, as shown in Figure 1. In such a network where all nodes are equipped with a single antenna, a set of SUs, which act as cooperating relays (i.e., relay network), receives the messages from the secondary source, at the first hop. At the second hop, the relays create a virtual antenna array...

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Bandwidth and Power Allocation for Wireless Cognitive Network with Eavesdropper

Zhou

et al. 2017

Machine Learning and Intelligent Communications

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Cooperative beamforming in cognitive radio network with hybrid relay

Cited by 12 publications

References 14 publications

Distributed beamforming for cognitive relay networks

Distributed beamforming for cognitive relay networks

Optimal received SINR balancing based on cooperative beamforming in cognitive radio networks

Bandwidth and Power Allocation for Wireless Cognitive Network with Eavesdropper

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