In cognitive radio (CR) networks, cooperation can greatly improve the spectrum sensing performance. However, more energies are required in the local spectrum sensing and sensing results reporting process. When the energies of the secondary users (SUs) are constrained, using their energies efficiently is a crucial problem, which must be considered. In this paper, the energy efficiency is defined as the ratio of the average channel throughput and the average energy consumption. We focus on the optimization of the final decision threshold to maximize the energy efficiency for additive white Gaussian noise (AWGN) channels, Nakagami fading channels and Rayleigh fading channels. An energy efficient optimization strategy (EEOS) is proposed to calculate the optimal solutions. Computer simulations show that fundamental improvement of the energy efficiency can be obtained by using our proposed EEOS, and there is an optimal number of cooperating SUs that can maximize the energy efficiency.

In cognitive radio (CR) networks, cooperation can greatly improve the performance of spectrum sensing. In this paper, we propose a novel cooperative spectrum sensing (CSS) frame structure in which CR users conduct spectrum sensing and data transmission concurrently over two different parts of the primary user (PU) spectrum band. Energy detection sensing scheme is used to prove that there exists an optimal sensing bandwidth which yields the highest throughput for the CR network. Thus, we focus on the optimal sensing settings of the proposed sensing scheme in order to maximize the throughput of the CR network under the conditions of sufficient protection to PUs and required bandwidth for potential CR user data transmission. Some algorithms are also derived to jointly optimize the sensing bandwidth and the final decision threshold. Our simulation results show that optimizing the sensing bandwidth and the final decision threshold together will further increase the throughput of the CR network as compared to that which only optimizes the sensing bandwidth or the final decision threshold.

认知无线电技术可以利用主用户未使用的频谱资源来有效地提高频谱利用率.单用户感知技术虽然简单但可靠性较低,协作频谱感知技术可以显著地提高频谱感知的性能.现有的大部分协作感知都是在假设各认知用户的信噪比相同的前提下进行研究.然而在实际环境中,由于每个认知用户所处的环境不同,其信噪比不同,对融合中心判决的影响也不同.如何在提升检测性能的同时提升系统的能量效率是关键问题.提出一种基于BP (Back Propa-gation)神经网络的协作频谱感知技术,它利用频谱环境的历史信息,通过BP神经网络提高频谱感知性能.仿真结果表明,该算法可以在保证协作感知性能的同时减少参与协作的认知用户数,从而减少能量消耗.

Spectrum sensing is regarded as an important part of the CR network. Its detection accuracy is the key aspect which affects the performance of CR network. In this paper, a novel cooperative spectrum sensing based on radio environment map (REM) is proposed. This new algorithm utilizes the REM information of the primary users (PUs) and the secondary users (SUs) to raise the detective performance of the spectrum sensing. Simulations show that the detection accuracy is improved and this algorithm is more suitable for practice wireless channel because it needs no priori information of SNR.

Cognitive radio (CR) is a promising paradigm proposed to cope with the spectrum scarcity problem by reusing the authorized idle spectrum resource. Accurate spectrum sensing of CR is important for raising the utilization efficient of spectrum resource meanwhile avoiding interference to authorized users. In this paper, a new efficient cooperative spectrum sensing algorithm based on the BP neural network is proposed. This algorithm adjusts iteratively the parameters of BP neural network to raise the sensing accuracy. Simulation results show that the detection accuracy is improved and the consumption of energy is reduced by the new cooperative spectrum sensing algorithm.

Cooperative spectrum sensing (CSS) is a promising technology in spectrum sensing with an admirable performance. In this paper, we define a utility function which jointly considers the spectrum-efficiency and the energy-efficiency. In a single-user sensing scenario, by maximizing the utility function, a rigorous analytical expression for the optimal threshold of the energy detector is derived. In CSS, the general frame structure is inefficient since the time consumed by reporting contributes little to the sensing performance. In this paper, we propose a novel CSS frame structure, in which one secondary user's (SU's) reporting time is also used for other SUs’ sensing. For time varying channels, collecting the sensing results at different time points is expected to achieve a time diversity gain for a SU, then the novel multi-minislot CSS scheme is proposed. In CSS, the optimal randomized rule and the optimal final decision threshold are derived. Simulation results show a significant improvement of the utility by using the proposed multi-minislot CSS scheme. It is also shown that there exists an optimal number of cooperating SUs that maximizes the utility, and the optimal number decreases as the price of the sensing energy increases.