In this paper, we apply the cross entropy optimization (CEO) to the problem of joint multiple relay assignment and source/relay power allocation (JMRAPA) in green cooperative cognitive radio (GCCR) networks. We use shared-band amplify and forward relaying for cooperative communication in the JMRAPA problem. The proposed JMRAPA maximizes the total rate and minimizes the greenhouse gas emissions in GCCR networks. It is a non-convex combinatorial optimization problem and is NP-hard. We propose to use concave upper bound that makes it a convex problem. The effectiveness of the proposed CEO-based method is shown through simulation results.
I. INTRODUCTIONInformation and communication technology (ICT) is responsible for ever increasing electricity demand and greenhouse gas (GHG) emissions [1], [2]. To deal with this issue, research efforts in green communications are focussed on minimizing the environmental impact [3] by reducing overall energy consumption.Cognitive radio (CR) can improve the inefficient use of radio spectrum by allowing spectrum band sharing between primary users (PUs) and secondary users (SUs). On the other hand, cooperative communications enable single-antenna mobile devices in a multi-user environment to share their antennas [4] that can significantly reduce the required transmission power. Cooperative communication, when used for CR, can help in reducing the total transmission power and consequently, GHG emissions. Cooperative relaying and coordinated multipoint transmission are two emerging technologies that can be utilized for energy saving, since they can also extend coverage and improve throughput [5]. This underlines the importance of the work in the field of green cooperative cognitive radio (GCCR) network [6].One possible means of cooperative communication is the amplify-and-forward relaying [7]. It has been shown in [8] that relaying techniques enable solving the problem of energy efficiency via multi-hop transmission. In [9], the authors indicate that two-hop communication consumes less energy than direct communication. However, more cooperators may not necessarily be more energy efficient [10]. Therefore, it is necessary to design energy efficient cooperative relay assignment strategies. Energy efficient relay selection for wireless networks has been presented in [11]-[13].In this paper, we apply the cross-entropy optimization (CEO) [14] to relay assignment problem. The simplicity of the model, ease of implementation, and resistance to being trapped in local minima/maxima make CEO a suitable candidate for solving computationally challenging optimization problems