优化认知SWIPT网络的时间分配和功率控制

无线网络中出现的频谱稀缺、能源受限和干扰等各种问题,已成为国内外研究学者的研究热点。为此,提出一种基于能量收集衬底式的认知无线携能通信(Simultaneous Wireless Information and Power Transfer, SWIPT)网络,称为认知SWIPT或二级SWIPT网络,采用认知无线电技术,允许无线能量传输和无线信息传输与现有的主系统共享相同的频谱,能将主用户对二级用户的干扰转化为有效能量。在温度干扰约束条件下,通过联合优化时间分配和功率控制,最大限度地提高认知SWIPT网络的加权吞吐量,同时保证主系统的通信质量。利用软件Matlab进行仿真,分析和比较所提联合优化方案与等时间分配方案,仿真结果表明,前者显著提高了频谱效率和能量利用率,明显优于后者。     

认知无线电中频谱效率与能量效率的折中分析

在接收端较高的比特信噪比能够提高数据包检测率,但同时也消耗更多的能量,导致能量效率降低。为此,在认知无线电技术可灵活配置的基础上,研究频谱效率(SE)和能量效率(EE)的折中问题,提出综合指标频谱/能量效率(SEE)对SE和EE进行偏好分析的方案。对于不同的联合调制与编码方式,获取信号传输能量和每一帧信息比特长2个参数的闭式解,考虑不同情形的SE和EE,以更好地提高认知无线电的自适应性。仿真结果表明,该方案可实现SE和EE之间的均衡折中,比单纯优化其中任何指标达到的效果要更好。     

基于遗传算法的协作频谱租借策略研究

随着认知无线电（CR）技术的发展，协作认知无线电网络（CCRN）成为提高频谱利用效率和解决频谱稀缺问题的有效途径。而且，无线通信系统中的过度能量消耗已变得越来越重要。能量采集（EH）被认为是缓解此类问题的有效解决方案。然而，由于自然能量的随机性和间断性，从自然能源采集的能量不能保证EH网络中令人满意的服务质量（QoS）。混合能源供应已经成为解决不稳定电力供应问题的一种新模式，这意味着，这样的网络是由固定电源能量和采集能量共同提供动力。提出了一种新的混合能量供应认知无线电网络协作频谱租借方案。主用户（PU）雇佣次用户（SUs）作为协作中继，SUs通过从PU的RF信号中采集的能量来帮助PU传输数据，作为回报，PU授予SU接入信道的权利。PU的目标是通过与SUs 合作来最大化其收益并节约自身能源，而SU旨在最大化其吞吐量和能源利用率。将此模式制定为Stackelberg 博弈。最后，通过遗传算法解决了PU和SU在定价和频谱租借中的最优策略问题。     

认知无线电网络中频谱感知性能分析

分析了认知无线电网络中使用能量检测器进行频谱检测的性能。仿真结果表明,衰落会使认知无线电用户检测性能下降,采用硬合并协作方案的合作频谱检测可以提高认知无线电系统的检测概率,但认知无线电系统的虚警概率也会随着参与协作的用户数的增多而上升,特别是控制信道不理想时,协作检测会导致虚警概率下限的出现,造成频谱利用率达不到预期的目标。     

能量效率和碰撞概率联合优化的协作频谱感知算法

协作频谱感知能提高认知无线电网络的感知性能。随着认知网络频谱感知性能的提高,一方面感知网络将会消耗更多的能量;另一方面次用户拥有更多的机会接入授权频谱,次用户的吞吐量不断增加,同时在通信过程中主用户与次用户发生碰撞的概率也不断增大。本文提出了一种联合优化能量效率和碰撞概率的协作频谱感知算法,通过最优感知检测点判断节点所处信道状态,融合中心舍弃信道状态不好的节点使其不参与数据融合,既消除了信道状态不好的节点对全局判决的不良影响,又提高了能量利用率。仿真结果表明,该算法提高了网络的频谱检测性能,并延长了感知网络的生命周期。     

基于分簇协作频谱感知的认知无线网能量效率研究

针对认知无线网能量消耗引起的能量效率较低问题,在研究认知无线网分簇协作频谱感知能量效率的基础上,提出了一种最优功率分配算法来最大化次用户系统的能量效率。通过建立基于次用户能量效率最大化传输优化模型,在考虑传输功率、感知时间以及干扰限制的情况下,利用拉格朗日函数及KKT条件,得到最优次用户发射功率分配算法,以达到系统能量效率最大化的目的,同时分析了不同参数对能量效率的影响。仿真结果表明,本文所提算法能有效提高次用户系统的能量效率、减少系统开销。     

基于权值协作和能量感知的频谱检测技术

为了提高认知无线电频谱检测的可靠性,介绍了一种新的基于加权协作和能量感知的频谱检测方案;建立了多用户协作检测模型,结合本地能量检测法构建了全局检测统计量,推导出权值融合的协作检测概率解析式,同时分析了相关节点对协作的影响;数据表明,在虚警概率为0.1时,从单个用户到6个用户,权值检测增益从15%提升到80%;OR检测增益从15%提升到64%,权值协作方案优于传统OR方案,更能有效提高全局检测性能和消除阴影衰落及多径效应的影响.     

基于BP神经网络的协作频谱感知技术

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 Propagation)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。     

混合模式下认知无线电网络的能效优化算法

认知无线电网络中,协作频谱感知利用多个节点同时感知可提高频谱感知检测性能。然而随着感知的次用户(SU)个数增加,导致能耗增高、能效(EE)降低。为解决这一问题,本文结合机会频谱接入和衬垫式频谱共享2种共享模式,构造基于混合频谱共享模式的能效模型,同时考虑3种不同的融合规则、主用户(PU)的再占据概率和报告信道误差,以最大化SU系统的EE为目标,使用拉格朗日乘子法与次梯度下降算法对感知时间、参与感知个数、次用户发射功率进行迭代优化求解。仿真结果表明,在最低服务质量要求(QoS)和发射功率的约束下,该能效优化算法能够实现更高的吞吐量和更高的能量效率。     

基于能量获取下协作认知网的资源联合分配

频谱共享和能量获取是提高带宽和能量效率的前沿技术,满足了无线传输数据的不断增长的要求。在协作认知无线网络中,由混合接入点提供无线能量的次用户系统帮助主用户传输数据。作为回报,次用户以时分多址的方式获得频谱接入的机会来传输自己的数据。为了最大限度地提高次用户系统的吞吐量,提出了一个次系统吞吐量最优的资源分配方案。在满足主系统基本性能的约束下,根据次用户参与度来选择最佳次用户集合,联合对SUS进行时隙和能量的分配。     

Cooperative spectrum sensing based on stochastic resonance in cognitive radio networks

A new censoring cooperative spectrum sensing scheme based on stochastic resonance(SR)technique in cognitive radio(CR)network is proposed in this paper.The observations of the cooperative secondary users(SUs)whose statistics fall into the censoring interval are processed by SR system in the proposed scheme.The hard fusion and the soft fusion for the censoring cooperative spectrum sensing scheme are analyzed respectively.Theoretical analyses and simulation results show that the proposed censoring cooperative spectrum sensing scheme has the same detection performance as and lower computational complexity than the method that each cooperative SU performs spectrum sensing using SR-based energy detection,and its detection performance is superior to that of the conventional method that all the cooperative SUs perform spectrum sensing using energy detection in hard fusion.In soft fusion,the proposed censoring cooperative spectrum sensing based on equal gain combination can achieve the optimal sensing performance approximately.     

Partial cooperative spectrum sensing schedule in cognitive network

Cognitive radio has emerged as a promising technology for maximizing the utilization efficiency of the limited spectrum resources while accommodating the increasing amount of services and applications in wireless networks. One of the most important and critical components of the cognitive radio is spectrum sensing and accordingly, detection of primary users. Considering the hardware constraints existing in cognitive devices, based on the coarse estimation of channel occupancy, partial cooperative spectrum sensing with adaptive spectrum schedule scheme is proposed to increase the possibility to discover more spectrum opportunities promptly. Simulation results show the gain of sensing performance and the energy-saving feature of partial spectrum sensing. Special security scheme is designed to protect the reliability of sensing result from the false message attack. For the scenarios tested, the proposed scheme is shown to increase opportunities by up to 15 percent.     

On optimized decode and forward relay assisted CR system design for throughput maximization

This paper proposes a joint spectral sensing and secondary data transmission scheme in a decode-and-forward (DF) relay assisted cognitive radio network (CRN). Periodic spectral sensing is done in each frame that primarily consists of two slots: sensing slot and data transmission slot. Sensing information of cognitive source (CS) and cognitive relay (CR) are cooperatively combined at CS to determine reliably the presence or absence of the primary user (PU). An optimization framework is developed to determine the sensing time, data transmission time for CS and CR along with their associated transmission power with an aim to maximize the average throughput of secondary transmission under the constraints of target detection probability, sum transmission power and interference to PU. Simulation results show that significant improvement in average throughput is achieved when the transmission power of CS and CR are jointly optimized with the sensing duration and transmission time of CS and CR. Performance improvement over amplify-and-forward (AF) relay is also reported.     

认知Ad hoc网络的频谱接入跨层设计方案*

为提高分布式认知Ad hoc网络的频谱感知精准性和能量有效性,提出了一种基于能量效率的频谱接入跨层设计方案。首先通过基于感知因子的完全二分图分解法对网络进行分簇,进而在簇内联合优化次用户的发射功率和接入概率,最终得到最优信道接入和功率分配方案。仿真结果表明,与传统算法相比该方案可通过合理分簇提高分布式认知网络的感知精度,在保证感知性能的条件下使系统能量效率得到有效提升。     

Optimal MAC based cooperative spectrum sensing in cognitive radio networks

This paper considers a cognitive radio (CR) system in non-ideal fading wireless channels and pro-poses cooperative spectrum sensing schemes based on coherent multiple access channels (MAC),serving as an alternative way to improve the cooperative spectrum sensing performance and provide space diversity for spec-trum sensing.Sufficient statistics are transmitted using a common channel from the secondary users (SUs) to a fusion center (FC) where the global decision is obtained.The optimal scaling factors of the proposed schemes are obtained by maximizing the detection probability under a target false alarm probability and a transmit power constraint.Because the proposed optimal MAC scheme has high computational complexity,a sub-optimal solu-tion based on maximization of the deflection coefficient (DC) is also proposed.Simulation results show that the proposed algorithms can significantly improve the spectrum sensing performance and approach the detection baseline.     

Adaptive sensing scheduling for cognitive radio systems

In cognitive radio (CR) systems, the efficiency of primary user (PU) detection scheme directly affects the system performance. In this paper, we propose an adaptive sensing scheduling scheme for CR networks with a central controller, which is based on the partially observable Markov decision process (POMDP) framework. With the proposed scheme, the CR system detects the PU activation by using one or more energy detections followed by zero or one feature detection, and protects the PU by using the channel switching. In the proposed scheme, the energy/feature detections and the channel switching are adaptively scheduled according to the number of active CR nodes, the received signal power from a PU, and the degree of noise uncertainty. Simulation results show that the proposed scheme provides very high maximum channel utilization to CR nodes while protecting the PU effectively, under time-varying network environment.     

Distributed cooperative spectrum sensing in cognitive radio for ad hoc networks

Cognitive radio refers to an intelligent radio with the capability of sensing the radio environment and dynamically reconfiguring the operating parameters. Recent research has focused on using cognitive radios in ad hoc environments. Spectrum sensing is the most important aspect of successful cognitive radio ad hoc network deployment to overcome spectrum scarcity. Multiple cognitive radio users can cooperate to sense the primary user and improve sensing performance. Cognitive radio ad hoc networks are dynamic in nature and have no central point for data fusion. In this paper, gradient-based fully distributed cooperative spectrum sensing in cognitive radio is proposed for ad hoc networks. The licensed band used for TV transmission is considered the primary user. The gradient field changes with the energy sensed by cognitive radios, and the gradient is calculated based on the components, which include energy sensed by secondary users and received from neighbors. The proposed scheme was evaluated from the perspective of reliable sensing, convergence time, and energy consumption. Simulation results demonstrated the effectiveness of the proposed scheme.     

Spectrum sensing algorithms for primary detection based on reliability in cognitive radio systems

One of the main requirements of cognitive radio systems is the ability to detect the presence of the primary user with fast speed and high accuracy. To achieve that, in this paper, we propose a spectrum sensing scheme by considering the reliability of spectrum sensing. Only the user with no reliable information will perform spectrum sensing again using one-order feature detection. Otherwise, the user directly transmits its binary decision (0 or 1) to the MAC layer. The performance of the one-order feature detection is studied and numerical results are presented to show that the one-order feature detector can perform better than the energy detector due to its robustness to the noise uncertainty. Since the feature detection is performed in time domain, the real-time operation and low-power consumption can be achieved. Furthermore, the performance of proposed spectrum sensing scheme based on reliability is also deduced and the analysis of the performance results indicate that the sensing performance is greatly improved as opposed to energy detector. However, due to the effects of channel fading/shadowing, individual cognitive radios may be not able to reliably detect the existence of a primary user. To solve this problem, cooperative sensing among secondary users are studied using the methodology proposed in this paper. The performance of cooperative spectrum sensing is investigated when various decision fusion rules are applied. We find that, regardless of the decision fusion rule used, the sensing performance can be significantly improved compared to conventional cooperative methods.