Resource Allocation Techniques In Green Cognitive Radio

The emerging wireless techniques, the unprecedented increase of mobile devices, the ever-increasing higher data rate requirements, the ubiquitous wireless services and the fixed spec-trum allocation have resulted in severe spectrum scarcity problem and energy scarcity prob-lem. Green cognitive radio (GCR) is a promising technique that can simultaneously alleviate the spectrum scarcity problem and the energy scarcity problem, and it has attracted much at-tention. There are two different lines of research on designing GCR, namely, energy-efficient GCR and energy-harvesting GCR. Energy-efficient GCR aims to maximize its energy effi-ciency on the condition that the interference caused by the secondary user is tolerable to the primary user, whereas energy-harvesting GCR exploits energy harvesting techniques to simultaneously transmit information and harvest energy.In GCR, an optimal resource allocation scheme not only provides the secondary user a rea-sonably high transmission rate with limited power, but well protects the primary user from harmful interference. Moreover, in energy-efficient GCR, an optimal resource allocation scheme cuts deployment costs to enable economical GCR and reduces environmental im-pact; in energy-harvesting GCR, an optimal resource allocation scheme not only can provide users a more satisfactory experience, but also can satisfy the energy harvesting requiremen-t of energy harvesting receivers. Thus, in GCR, it is of crucial importance to design an optimal resource allocation scheme. On the other hand, due to the inherent characteristics of GCR, malicious users may exist and illegitimately access the primary users’ bands or change the radio environment. As a result, the legitimate secondary user is unable to use frequency bands of the primary user or has his confidential transmitted information inter-cepted. Thus, in GCR where malicious users exist, it is exceedingly important to design an optimal resource allocation to provide users a more satisfactory experience on the condition that confidential information can be securely transmitted.However, investigation into the design of an optimal resource allocation for GCR has been limited up to now. Even worse, the optimal resource allocation for traditional CR is unadapt-able to GCR. Specifically, although the optimal resource allocation scheme for traditional CR can maximize its spectrum efficiency, it can not guarantee that the maximum energy efficiency can be obtained. Thus, it is inappropriate to energy-efficient GCR since the ob-jective of energy-efficient GCR is to maximize its energy efficiency. Moreover, since the design of an optimal resource allocation scheme in traditional CR is not required to take the energy harvesting requirement into account, the optimal resource allocation scheme for tra-ditional CR is also unadaptable to energy-harvesting GCR. To address the above-mentioned problems, optimal resource allocation schemes are proposed in energy-efficient GCR and energy-harvesting GCR, respectively. The spectrum efficiency, energy efficiency and the se-crecy of GCR can be improved by using the proposed optimal resource allocation schemes. The main contributions of this work are summarized as follows.1. Energy-efficient optimal power allocation for GCREnergy efficiency maximization problems are formulated in delay-insensitive GCR, delay-sensitive GCR, and simultaneously delay-insensitive and delay-sensitive GCR, where the channels are fading. Using fractional programming and convex optimization techniques, energy-efficient optimal power allocation strategies are proposed subject to constraints on the average interference power, along with the peak/average transmit power. A power iter-ative algorithm based on the proposed energy-efficient optimal power allocation strategy is designed to maximize the energy efficiency of the secondary user. It is shown that the sec-ondary user can achieve energy efficiency gains under the average transmit power constraint, in contrast to the peak transmit power constraint. Simulation results show that the fading of the channel between the primary user transmitter and the secondary user receiver and the fading of the channel between the secondary user transmitter and the primary user receiver are favorable to the secondary user with respect to the energy efficiency maximization of the secondary user, whereas the fading of the channel between the secondary user transmitter and the secondary user receiver is unfavorable to the secondary user.2. Secure energy-efficient optimal power allocation for secure GCRErgodic secure energy efficiency maximization problems are formulated for secure GCR, where the channels are fading. The definition of ergodic secure energy efficiency of the secondary user is first given in secure GCR based on physical-layer security. Using fraction-al programming and dual decomposition techniques, secure energy-efficient optimal power allocation strategies are proposed to maximize the ergodic secure energy efficiency of the secondary user under an average interference power constraint, along with an average/peak transmit power constraint. An iterative power allocation algorithm is presented to solve ergodic secure energy efficiency maximization problems. Moreover, under the peak in-terference power constraint, secure energy-efficient optimal power allocation strategies are proposed on the condition that a minimum secrecy capacity of a secondary user is guaran-teed. It is shown that the conclusion that the secondary user can achieve better performance under the average transmit power constraint in contrast to the peak transmit power constraint can be obtained only when the optimal strategy matches the optimized object. The tradeoff between the ergodic secure energy efficiency and the ergodic secure capacity is found.3. Robust fairness resource allocation for GCR with SWIPTRobust max-min fairness resource allocation in sensing-based green wideband CR with SWIPT is studied under the imperfect spectrum sensing and channel state information. Robust max-min fairness resource allocation problems are formulated in green wideband CR under opportunistic spectrum access and under sensing-based spectrum sharing, respec-tively. Using time sharing and convex optimization techniques, robust optimal power and subchannel allocation schemes are proposed. An efficient one-dimensional search algo-rithm based on the proposed transmit power and subchannel allocation scheme is designed to solve the formulated problems. Simulation results show that the spectrum efficiency of green wideband CR with SWIPT under sensing-based spectrum sharing is higher than that of green wideband CR with SWIPT under opportunistic spectrum access. Several tradeoff-s are found, such as the tradeoff between the sensing performance and the throughput of secondary users achieved under a max-min fairness criterion.4. Robust beamforming desing for secure green MISO CR with SWIPTA green MISO cognitive radio downlink network with SWEPT is studied. In order to guar-antee secure communication and energy harvesting, the problem of robususecure artificial noise-aided beamforming and power splitting design is investigated under imperfect CSI. The transmit power minimization problem and the max-min fairness energy harvesting prob-lem are formulated for both the bounded CSI error model and the probabilistic CSI error model. A one-dimensional search algorithm is proposed to solve these problems based on S-Procedure under the bounded CSI error model and based on Bernstein-type inequalities under the probabilistic CSI error model. It is shown that the optimal robust secure beam-forming and AN covariance matrix can be achieved under the bounded CSI error model, whereas a suboptimal beamforming solution can be obtained under the probabilistic CSI error model. A tradeoff is elucidated between the secrecy rate of the secondary user receiv-er and the energy harvested by the energy harvesting receivers under a max-min fairness criterion.5. An efficient spectrum sensing scheme based on Cholesky factorisationIn order to reduce the energy consumed by spectrum sensing, an efficient cooperative spec-trum sensing scheme is proposed based on Cholesky decomposition of the covariance matrix for GCR. The maximum eigenvalue of the matrix obtained by Cholesky decomposition is used as a test statistic. Analytical expressions for the false alarm probability and the decision threshold are derived. The effects of noise uncertainty on the maximum eigenvalue spectrum sensing algorithm and on the Cholesky maximum eigenvalue cooperative spectrum sensing scheme are assessed. It is proved that the proposed spectrum sensing scheme is more robust than the conventional maximum eigenvalue scheme in terms of noise uncertainty. Simu-lation results show that the performance of the proposed scheme is better than that of the existing maximum eigenvalue scheme.