多无人机协作的认知通信网络中能/谱效折中优化

在无人机（Unmanned Aerial Vehicle,UAV）认知通信网络中,其能量受限和通信高吞吐量问题备受关注。然而,能量效率（Energy Efficiency,EE）的提升可能会导致频谱效率（Spectrum Efficiency,SE）的下降。针对此问题,对UAV协作认知通信网络中EE和SE的折中优化进行了研究。首先,进行了感知时间、UAV通信的发射功率和判决门限各自对SE与EE两者的优化;其次,通过二分法求解使得EE和SE最大化的感知时间值,并通过穷尽搜索法分别求解感知时间、UAV通信的发射功率和判决门限对EE和SE折中优化问题的最优参数值。在此基础上,提出一种联合参数迭代优化算法,求解EE和SE的折中优化问题。仿真实验表明,SE和EE之间存在折中的权衡,并验证了所提优化方案的有效性。     

认知无线电网络中次用户平均吞吐量的优化

协作频谱感知的认知无线电网络中,已有研究表明增加参与协作频谱感知的次用户数量能够提高感知性能,进而提高信道吞吐量。然而,由于信道容量的限制,不断增加参与协作感知的次用户数量并不会使信道吞吐量无限提高,反而会使次用户平均可获得的吞吐量不断降低。针对上述问题,该文以次用户平均吞吐量为优化目标,证明多信道条件下,对于任意给定的融合参数,次用户的平均吞吐量是感知时间的凸函数,并提出交叉迭代算法进行2维优化。仿真结果表明,当信噪比为-10 dB时,次用户使用交叉迭代算法获得的平均吞吐量较已有算法可提高20%以上。     

协作认知网络中基于融合准则与感知时间联合优化的策略

在协作频谱感知网络中,感知时间和数据融合准则均影响着感知性能.假设控制信道为二进制对称信道的前提下,基于“k秩准则”建立了协作感知网络吞吐量优化问题的数学模型,目的是在保护主用户利益的前提下联合优化感知时间和k值使认知网络吞吐量最大化.理论分析了最优感知时间和k值的存在性,并进行了相关的计算机仿真.仿真结果表明:所提议...     

认知无线电网络中合作频谱感知机制的优化

为了提高检测效率和频谱利用率,该文对认知无线电中合作频谱感知的感知机制进行了优化。针对信道监测和信道搜索两个不同的感知场景,分别给出了检测周期、检测时间和搜索时间的选取和优化方法,并提出了新的信道搜索方式。研究分析和仿真结果可以看出,合作频谱感知和主动感知方式的引入可以提高检测性能和传输速率,对感知机制和策略的选取和优化有效地提高系统吞吐量,降低感知时延和开销,这样可以提高认知无线电网络的性能和灵敏性,在保证授权用户不被干扰的同时最大化空闲频谱的接入机会。     

感知不确定下卫星认知无线网络多频谱接入优化策略

针对卫星认知无线网络频谱感知不确定性较大导致传统频谱接入机制效率降低的问题,该文提出一种基于动态多频谱感知的信道接入优化策略。认知LEO卫星根据频谱检测概率与授权用户干扰门限之间的关系,实时调整不同频谱感知结果下的信道接入概率。在此基础上以系统吞吐量最大化为目标,设计了一种基于频谱检测概率和虚警概率联合优化的判决门限选取策略,并推导了最佳感知频谱数量。仿真结果表明,认知用户能够在不大于授权用户最大干扰门限的前提下,根据授权信道空闲状态动态选择最佳频谱感知策略,且在检测信号信噪比较低时以更加积极的方式接入授权频谱,降低了频谱感知不确定性对信道接入效率的影响,提高了认知系统吞吐量。     

基于最优停止的认知无线网络下行频谱接入算法

为有效平衡认知无线网络中次用户系统中接入信道的感知时间和信道总的吞吐量之间的矛盾,提出了一种只对部分信道进行感知的频谱接入策略,联合总的感知信道数和各条信道的感知时间进行优化,并通过最优停止算法求解,在最大化节省感知时间的同时,取得较大的平均吞吐量。与HC-MAC(Hardware Constrained- Media Access Control)算法的仿真分析对比表明,该算法在相同给定条件下感知时间更短,吞吐量更大,具有明显的优势。     

分级分布式无人机协作频谱感知方法

无人机认知网络(Cognitive UAV Network,CUAVN)可以通过高精度的频谱感知提高频谱效率,但传统的集中式协作频谱感知不适用于无人机(Unmanned Aerial Vehicle,UAV)网络。UAV网络拓扑结构动态变化,使得全局信息很难快速收集至一个融合中心。针对上述问题,提出了一种基于K-means聚类算法的分级分布式协作频谱感知方法。首先,利用K-means聚类算法基于位置信息对UAV进行分簇;然后,采用两级分布式融合方案进行分层融合,在每个簇内先进行一致性信息融合得到獽个融合结果,再进行第二次融合得到最终全局收敛结果;最后将最终收敛结果与检测阈值对比,得到最终决策。仿真结果表明,所提出的分级分布式融合方案具有较好的收敛性,且信息融合迭代次数比未分级融合方案更少。在不同权重因子的加权情况下,所提方案较未分级融合方案更好,且平均接收信噪比越大时检测性能越好。与未分级分布式融合方案相比,在UAV节点较多的情况下,该方案使CUAVN的频谱检测性能得到了提升。     

Equation Chapter 1 Section 1基于中继的协作频谱感知性能分析及优化

提出了一种基于目标的中继协作频谱感知方案,证明了SU到SR链路上的信道条件对系统性能有较大的影响;鉴于此,提出了一种优化的最佳中继协作频谱感知(optimized BRCSS)方案,通过联合考虑目标SU到SR链路上的信道条件和 SR 到 FC 链路上的信道条件选择最佳认知中继;最后,从更实际的应用场景考虑,为了节约系统开销,进一步提出了一种自适应的最佳中继协作频谱感知方案（A-BRCSS）,即 SU 根据其信道条件,自适应地选择是否需要认知中继的协作传输。分析和仿真结果均表明,相比传统最佳中继协作频谱感知方案, Optimized BRCSS方案可以实现更高的感知性能;所提A-BRCSS方案可以实现几乎最佳的感知性能。     

全双工中继协作下的认知MIMO系统吞吐量最大化研究

本文研究了全双工中继协作下的认知MIMO系统的平均吞吐量最大化问题。与传统的中继协作认知无线电系统不同的是,该系统模型中的双工中继节点既能协助认知用户源节点进行多天线频谱感知以提高频谱检测性能,也能解码转发认知用户源节点的发送信号以获得更大的系统吞吐量。为使系统平均吞吐量最大,首先,本文以认知用户能获得的最大平均频谱空洞被发现的概率为目标,对系统的帧结构进行优化以获得最佳的感知时间,接着对多个发送天线进行优化以选择出最佳的发送天线,并推导出了在总的发送功率和对主用户干扰受限条件下的认知用户源节点和双工中继节点的最佳功率分配方案。最后的仿真结果表明本文提出的系统模型和优化方案相比传统的双工等功率分配方案以及单工功率分配方案能够获得更大的系统平均吞吐量。      

认知车载网络中基于QoS保障的频谱共享新策略

构建了基于认知无线电的新型车载网络,并提出基于安全业务服务质量(QoS)保障的两步式频谱共享策略:多认知小区间的频谱分配和单认知小区内的频谱共享。仿真结果表明,提出的GNBS(generalized nash bargaining solution)分配方案综合考虑了系统的公平性和总效用,可获得明显大于最大化最小方案的系统和速率,以及明显优于最大化和速率方案的多认知小区间的公平性;GNBS方案可以根据多小区间频谱需求的差异性来动态调节资源分配的比例,有效地实现了需求非对称的多小区间频谱资源的最优化配置;此外,单小区内的协作频谱共享机制,使得协作双方均获得了优于非协作方案的系统效用,有效地提高了系统吞吐量以及认知OBU间的公平性。     

一种主用户随机到达情况下改进的循环平稳特征检测算法

在认知无线电(CR)网络中,针对检测频段突然被主用户(PU)占用导致次用户频谱检测性能较差的情况。该文提出一种基于反馈叠加原理的改进循环平稳特征检测算法,该算法通过将检测周期后半部分采样点的瞬时采样值累加到检测周期前半部分采样点的瞬时采样值上,在不延长检测时间的基础上,提高了整个检测周期的判决统计值,从而提高了系统检测性能。并且从理论上详细分析了该算法的检测概率,虚警概率与吞吐量。仿真结果表明,该算法的检测性能优于传统循环平稳特征检测算法和传统能量检测算法,并且保证了不错的用户数据吞吐量。     

低信噪比条件下提高认知无线电的频谱感知能力的方法

为了提高认知无线电在强噪声环境下的频谱感知能力,该文提出了一种频谱感知方法。该方法利用循环谱相关函数,采用二次模式识别,可以显著提高在低信噪比条件下的信号调制方式识别准确率。试验结果表明,在AWGN 信道,信噪比不低于-10dB条件下,对常用5种数字调制信号的识别准确率高于99.9%,能够满足认知无线电中对频谱感知的性能要求。     

Energy-Efficient Spectrum Discovery for Cognitive Radio Green Networks

Cognitive Radio (CR) is an essential technique for the future generation green communication paradigm owing to its inherent advantages of adaptability and cognition. The compulsory spectrum sensing is a critical component to facilitate systems co-existence. In this paper, we propose a new Time-Division Energy Efficient (TDEE) sensing scheme in which the sensing period is divided into an optimal number of timeslots and each Secondary User (SU) is assigned to detect a different channel in one time-slot. An important advantage of TDEE is that the SUs do not need to exchange the control messages for the acknowledgement of a successful cooperation, leading to substantial energy saving without compromising sensing accuracy. Both homogeneous and heterogeneous networks are investigated with respect to the intrinsic trade-off between spectrum efficiency and energy-efficiency. Illustrative results demonstrate that the proposed TDEE is able to achieve much lower energy consumption and higher throughput, compared to the existing mechanisms.     

Optimization of multiple-channel cooperative spectrum sensing with data fusion rule in cognitive radio networks

This paper focuses on multi-channel Cooperative Spectrum Sensing (CSS) where Secondary Users (SUs) are assigned to cooperatively sense multiple channels simultaneously. A multi-channel CSS optimization problem of joint spectrum sensing and SU assignment based on data fusion rule is formulated, which maximizes the total throughput of the Cognitive Radio Network (CRN) subject to the constraints of probabilities of detection and false alarm. To address the optimization problem, a Branch and Bound (BnB) algorithm and a greedy algorithm are proposed to obtain the optimal solutions. Simulation results are presented to demonstrate the effectiveness of our proposed algorithms and show that the throughput improvement is achieved through the joint design. It is also shown that the greedy algorithm with a low complexity achieves the comparable performance to the exhaustive algorithm.     

Transmission Power Control Aware Routing in Cognitive Radio Ad Hoc Networks

Abstract—Cognitive radio technology has drawn much attention since it is a promising candidate to efficiently utilize the scarce radio resources. However, cognitive radio introduces new challenges in the protocol stacks in wireless networks. This paper proposes a routing protocol for Cognitive Radio Ad Hoc Networks (CRAHNs), called Transmission Power Control aware AODV (TPC-AODV). TPC-AODV is based on Ad hoc On Demand Distance Vector (AODV) routing protocol. The main objectives of TPC-AODV are to avoid interruption of primary users’ communication and to support basic Quality of Service for secondary users. TPC-AODV takes inputs from both secondary users’ application requirements and the channel condition after spectrum sensing. These inputs enable secondary users’ communication with specific transmission power on the selected channel. Our simulation results show that TPC-AODV improves network performance in terms of throughput and delay compared to AODV in CRAHNs.     

多小区毫米波系统中无人机基站飞行姿态优化及性能分析

为了提高多小区毫米波系统中无人机基站覆盖区域内用户的通信质量,本文提出了一种无人机基站的飞行姿态优化方案。该方案首先在无人机基站天线数量趋于无穷大的情况下对吞吐量进行优化,得到最大吞吐量的渐近表达式,然后将吞吐量优化问题进一步细化为天线倾斜角优化问题,最后通过穷举搜索算法来获得使吞吐量最大的天线阵列倾斜角,进一步通过调整天线倾斜角以优化无人机飞行姿态。数值仿真结果表明,所提出的优化方案能够有效提高系统性能,对于多小区无人机毫米波通信系统的性能优化具有理论指导意义。      

基于表决融合的带宽受限的协作频谱感知算法

协作的频谱感知使认知无线电（CR）网络对主用户进行可靠的检测,并避免了对主用户通信的干扰。数据融合是协作的频谱感知的关键技术。但是当协作认知无线电用户较多时,它们向融合中心汇报的感知信息就会占用大量的带宽。本文提出了将表决融合准则与检查策略相结合的协作频谱感知的方法,来减少发往融合中心的平均感知比特数,从而有效节约传输带宽。推导分析了该算法在理想信道和非理想信道中的频谱感知性能,并给出了这两种情况检测概率的闭合式。仿真结果表明,此种基于表决融合准则的检查协作频谱感知算法的性能最优,即在较高的感知性能下有大量的感知比特的节约。      

Optimization algorithm of periodical cooperative spectrum sensing in cognitive radio

To decrease the interference to the primary user (PU) and improve the detected performance of cognitive radio (CR), a single‐band sensing scheme wherein the CR periodically senses the PU by cooperative spectrum sensing is proposed in this paper. In this scheme, CR first senses and then transmits during each period, and after the presence of the PU is detected, CR has to vacate to search another idle channel. The joint optimization algorithm based on the double optimization is proposed to optimize the periodical cooperative spectrum sensing scheme. The maximal throughput and minimal search time can be respectively obtained through the joint optimization of the local sensing time and the number of the cooperative CRs. We also extend this scheme to the periodical wideband cooperative spectrum sensing, and the joint optimization algorithm of the numbers of the sensing time slots and cooperative CRs is also proposed to obtain the maximal throughput of CR. The simulation shows that the proposed algorithm has lower computational quantity, and compared with the previous algorithms, when SNR = 5 dB, the throughput and search time of the proposed algorithm can respectively improve 0.3 kB and decrease 0.4 s. The simulation also indicates that the wideband cooperative spectrum sensing can achieve higher throughput than the single‐band cooperative spectrum sensing. Copyright © 2012 John Wiley & Sons, Ltd.     

认知网络下TCP协议性能分析

首先在无线环境下的基础上搭建认知平台,当主用户想要占次用户信道时,通过基站的频谱监测,频谱分配,分配次用户到其他空闲信道继续通信.其次,在此平台下分析TCP Reno,TCP Newreno,TCP Sackl和TCP vegas协议的性能,包括拥塞窗口、吞吐量.最后定量分析主用户活跃程度、切换后信道带宽和信道误比特率...     

CATECAS: a content-aware transmission efficiency based channel allocation scheme for cognitive radio users with improved QoE

Cognitive radio (CR) is a promising technology for the upcoming 5G communication which addresses opportunistic channel usage for enhanced spectrum utilization. However, Quality of Service (QoS) provisioning is a major challenge for CR Network due to the service interruption and packet error caused by random primary activities. In addition to this, periodic spectrum sensing for primary user protection reduces the effective throughput of the secondary users (SUs). However, to ensure QoS of SUs especially for video application, throughput enhancement is necessary which can be achieved by efficient spectrum sensing and channel allocation policy. As the QoS requirements are different for different secondary applications, we propose a novel content aware channel allocation scheme that enhances the Quality of Experience (QoE) of SUs. At first, the proposed scheme analyzes the QoS requirements of different SUs and prioritizes them. Consequently, the optimum sensing duration is determined to maximize the transmission efficiency and throughput of SUs. Finally, a novel content aware transmission efficiency-based channel assignment scheme (CATECAS) is proposed for SUs, considering the estimated channel quality and QoS requirements concurrently. Extensive performance analysis of CATESCAS on real-time video and file download applications confirms significant QoE improvement for SUs especially for rapid movement type of video application, which is considered as the most critical among different secondary applications.