Cooperative Spectrum Sensing for Cognitive Radio-Wireless Sensors Network Based on OR Rule Decision to Enhance Energy Consumption in Greenhouses

Wireless sensors networks (WSNs) combined with cognitive radio have developed and solved the limited space of the frequency spectrum. In this paper, we propose different types of spectrums sensing and their own decisions depend on the probabilities that applied into fusion center, and how these probabilities’ techniques help to enhance the energy consumption of WSNs. In the same way, the importance of designing balanced distribution between the wireless sensors networks and their own sinks. This research also provides an overview of security issues in CR-WSN, especially in Spectrum Sensing Data Falsification (SSDF) attacks that enforces harmful effects on spectrum sensing and spectrum sharing. We adopt OR rule as four types of CRSN sensing protocolin greenhouses application by using Matlab and Netsim simulators. Our results show that the designing balanced wireless sensors and their sinks in greenhouses are very significant to decrease the energy, which is due to the traffic congestion in the sink range area. Furthermore, by applying OR rule has enhanced the energy consumption, and improved the sensors network lifetime compared to cognitive radio network.

Energy Efficiency-Based Decision Making in Cognitive Radio Networks

As a constraint for smart devices,energy consumption has attract people's attention for a long time period. How to get higher resource utilization with less energy consumption is a challenge for cognitive radio networks. Secondary users have to participate in spectrum sensing at the cost of energy and access idle spectrum without interfering primary users. However,not all participating secondary users can access idle spectrum. How to ensure the participation users access spectrum efficiently with a larger probability is an urgent problem to be solved. We propose an Energy Efficiency-based Decision Making(EEDM) for cognitive radio networks,which fully considers residual energy and probability of obtaining spectrum resources. Simulation and analysis show that the proposed scheme can maximize proportion of allocated users under the premise of ensuring the accuracy of spectrum sensing,then balance users' energy consumption and access efficiency,so as to effectively improve the utilization of spectrum resources.

Energy efficient and delay aware ternary-state transceivers for aerial base stations

In recent times, Aerial Base Stations(AeBSs) are being investigated to provide wireless coverage to terrestrial radio terminals. There are many advantages of using aerial platforms to provide wireless coverage, including larger coverage in remote areas and better line-of-sight conditions, etc. Energy is a scarce resource for the AeBSs, hence the wise management of energy is quite beneficial for the aerial network. In this context, we study the means of reducing the total energy consumption by designing and implementing an energy efficient AeBSs as presented in this paper. Implementing the sleep mode in the Base Stations (BSs) has been proven to be a very good approach for improving the energy efficiency and we propose a novel strategy for further improving energy efficiency by considering ternary state transceivers for AeBSs. Using the three state model, we propose a Markov Decision Process (MDP) based algorithm, which intelligently switches among three states of the transceivers based on the offered traffic meanwhile maintaining a prescribed minimum channel rate per user. We define a reward function for the MDP, which helps us to get an optimal policy for selecting a particular mode for the transceivers of the AeBS. Considering an AeBS with transceivers whose states are changeable, we perform simulations to analyse the performance of the algorithm. Our results show that, compared with the always active model, around 40% gain in the energy efficiency is achieved by using our proposed MDP algorithm together with the three-state transceivers model. We also show the energy-delay tradeoff in order to design an efficient AeBS.

认知Ad Hoc网络能量有效频谱接入策略

针对认知无线Ad Hoc网络中次用户能量受限问题,提出一种基于能量有效性的机会频谱接入策略。联合考虑信道状态的时变性和次用户的频谱感知准确性,基于部分可观测马尔科夫决策过程(POMDP)建立了一种最大化能量有效性的分析架构,指导次用户选择能效最佳信道,并根据信念状态、信道增益和检测概率,自适应控制传输功率。仿真结果表明,该策略能够有效提高次用户传输的能量有效性,通过对传输功率的有效控制,实现了传输性能和能量开销的有效折中。

认知无线电网络的检查协作频谱感知技术

在认知无线电中,协作频谱感知通常被用来提高感知性能。但当用户个数较多时,控制信道带宽的限制和感知时延会影响协作感知的性能。作者提出采用检查协作频谱感知可以有效避免这些问题。检查协作频谱感知通过减少认知用户上报基站的感知信息,降低通信负荷和感知时延,从而提高系统的敏感性。通过最大化频谱利用率可以得到最优的不发送概率,从而在感知时延和接入频谱机会的错失上得到折衷。通过分析及仿真结果可以看出,检查协作感知与传统协作感知相比,有效提高了系统的敏感性。通过最优的不发送概率可以确定最佳的感知门限进行感知。

一种基于能效优先的LT码协作频谱感知结果传输方案（英文）

针对认知无线电系统中,因次级用户(SUs)数量较大而造成传输能量急剧增加的问题,提出一种基于能效优先的协作频谱感知结果传输方案.首先,将分簇结构引入感知结果传输系统以降低发射功率,然后,在中心化的感知信息传输模型中采用无固定码率的LT码,因为它能动态地适应信道条件,避免传输过程中不必要的冗余度.此外,LT码采用改进的最优度分布(ODD)设计.仿真结果表明,在度分布中选取合适的参数有助于LT码获得理想的性能.与其他典型的LT码度分布相比,ODD在选取了优化参数后,当比特误码率为10-3时,可以获得超过2 d B的性能增益.所提出方案的能耗不仅比非编码系统节约至少71. 4%,而且低于不同码率的卷积码编码系统.同时,当选择合适的分簇方法时,可以进一步降低能耗.

认知无线电中时频分离的联合频谱检测方法

认知无线电是解决频谱由于利用率不高而导致资源紧张的问题。文章以现有的能量检测方法和循环平稳检测方法为基础,提出了一种以频谱集合为基础的新型联合检测方法。该方法首先对能量检测进行了噪声修正,其次对频谱以所处时间和判决结果进行分级处理,对不同集合中的频谱资源依据其环境和上一时间段的判决结果采用不同的判决方法进行判决。文章给出了联合检测的方法模型,并与能量检测和循环平稳检测在检测正确率和运算时间上进行了比较,给出了比较函数。通过仿真验证了理论结果,表明联合检测能有效提高认知用户在频谱检测的正确概率并减少运算时间,在频谱数量较多和检测时间较长时,效果更加显著。

认知无线传感网络中吞吐量能耗均衡研究

认知无线传感网可利用空闲的授权频段来解决传统无线传感器网络的频谱资源短缺的问题,在授权频段内,其利用频谱空穴进行通信,从而改善了无线传感器网的性能。由于认知无线传感网主要基于无线传感器网,因此存在着节点能力弱、需考虑网络节能及其与节点协作等问题,不能直接套用传统认知无线电网络的技术。由于次用户能耗限制和上传信道信息可能存在错误,提高能耗效率在次用户频谱感知和协作发送过程中显得非常重要。为此,提出了一种用于集中式协作频谱感知的硬判决融合算法。该算法在能耗阶段,由总的检测概率和虚警概率的限制求最小的次用户数目;在能耗效率优化阶段,在固定感知时隙等参数限制下,设计优化目标函数,迭代算法求得最优用户数,从而实现能耗的最大效率。基于信道信息误码率对能耗影响的分析,进行了硬判决融合算法与传统算法的对比仿真实验。仿真结果表明,该算法需要的感知节点最少,且能耗效率可达到最优。