认知无线电MIMO中基于博弈论的功率控制算法

认知无线电MIMO通信系统结合了认知无线电技术和MIMO技术的双重优势,能够极大的提高频谱利用率和传输速率。针对认知无线电MIMO系统的功率控制问题,利用博弈论,首先建立了系统的非合作功率控制博弈模型,然后基于Goodman等人所提出的收益函数,提出了分布式迭代功率控制算法,并且对系统进行分布式功率控制。数值结果表明,算法具有快速收敛的特性,6～8次即可达到收敛。此外,随着天线数的增加,各用户发射功率不断减小,系统的收益逐渐增加。     

认知无线电中信道和功率协同分配算法研究

认知无线电是一种新的智能无线电技术,它通过动态地接入频谱为用户提供高容量的服务.主要研究了在中继协助下认知无线网络中信道和功率分配的问题.区别于传统的中继信道,认知无线网络信道可归结为3类:直接信道、多跳和中继信道.讨论了不同信道模式的系统吞吐量并且提出了一种信道和功率协同分配算法.该算法通过把感知频谱归到适合模式下,然后优化各节点频谱功率的分配以提高系统的整体吞吐量.在最后数据仿真结果中,协同分配算法在提高吞吐量方面要明显好于单一的信道和功率分配.     

基于WLC算法的频谱感知性能分析

随着科技的发展,频谱资源的短缺越来越制约无线电技术的发展,为提高频谱的利用率,从而提出了认知无线电,频谱感知作为其核心技术,受到了国内外的重视。在频谱感知中,主要的问题就是判断主用户(primary user,PU)是否存在。由于单用户检测的局限性,在多用户合作检测的基础上,提出了基于迭代的WLC算法,使用MATLAB进行仿真。理论分析和仿真结果表明,此方法与传统的EGC能量检测算法相比,即使在低信噪比情况,频谱检测的性能有明显的提高。     

基于双向拍卖的多目标频谱分配算法

认知无线网络是无线网络技术研究的热点,而频谱分配技术是认知无线网络应用的关键。基于竞价拍卖理论,定义了基于竞价拍卖的认知无线网络频谱分配模型,提出了基于双向拍卖的多目标频谱分配算法,并且对该算法在频谱分配效率和收益等方面进行了实验仿真。仿真结果表明,该算法在提高频谱利用率的基础上综合考虑了网络系统的各种性能要求。     

基于长短期记忆网络的无人机认知无线电频谱预测

为解决无线电频谱利用率低的问题,提出利用长短期记忆网络(LSTM)来预测一段时间内的无线电频谱信息,使得装有认知无线电的无人机能够机会性的接入频谱空洞,以提高无线电频谱的利用率.首先分别建立整合移动平均自回归(ARI-MA),时延神经网络(TDNN)以及LSTM的预测模型,其次构建3种预测模型相应的预测算法,最后利用提...     

自适应OFDM应用研究

认知无线电技术是一种有效提高频谱利用率的新方法,自适应OFDM能够智能的适应传输信道改变的特性,非常适应认知无线电灵活多变的传输方式。通过对基于传输带宽和固定传输功率的信道分配模型研究,提出一种应用于分布式认知无线电系统的信道及传输功率的自适应分配的方法。仿真结果表明,提出的方法能够有效的对分布式的信道进行功率自适应分配,性能比使用固定发射功率的分布式信道分配的方法有大幅度提升。     

认知物联网基于边缘计算的频谱感知-分配方法

针对多终端多信道复杂认知无线电-物联网(cognitive-radio Internet of Things, CR-IoT)当中的频谱感知-分配问题,提出了一种基于边缘计算思想的协作频谱感知-分配方法。为了评估边缘计算思想的引入为CR-IoT系统带来的性能提升,设计了一种能够量化对授权用户的干扰以及认知用户的服务质量的性能评估系统(performance evaluation system, PES)。在该系统中,基于排队论以离散时间马尔可夫模型对系统状态进行建模,能够对可配置参数的异构终端进行独立分析,进而对不同的频谱感知-分配方法进行性能评估。使用PES所进行的仿真结果表明,相比于中心感知-分配方法,所提出的边缘计算方案能够实现更低的对授权用户的干扰以及对于认知用户更好的服务质量。这一结果同样证明了,所提出的PES具有帮助网络监管者设计频谱感知-分配方案的能力。     

基于频谱感知的认知无线网络容量研究

动态频谱分配是认知无线电网络实现的关键所在,要实现动态频谱分配就必须快速准确的感知主用户的工作状况,感知时间的长短直接影响到认知无线网络的容量和对主用户的干扰程度,在主用户保护模式(PUP)和固定认知用户频谱利用率模式(CUS)下对认知无线网络容量与感知时间的关系进行了研究,仿真结果显示设计感知时间是非常重要的,同时,当感知时间超过单位时帧长度的5%后协同更多的认知用户与不协同对认知网络容量影响区别不大。     

基于车载通信网络的认知无线电信道分配技术的研究

车载通信网络的移动性对无线网络的信道分配提出了高要求,认知无线电技术能适应这一要求。将认知无线电的信道分配技术运用到车载通信网络中,根据实际交通状况对车载通信网络进行建模,主用户和认知用户分别实体化为无线网络用户及车载通信用户;运用协作最大化带宽和（CMSB）算法对认知用户进行信道分配。仿真分析结果表明在给定的车载通信网络模型下,CMSB能极大地优化网络吞吐量,并能保证一定的分配公平性。     

基于随机共振和支持向量机的频谱感知

认知无线电是一门新技术,它的目标实现用户的动态频谱接入,提高频谱的使用效率。频谱感知是认知无线电的基础,它的作用是感知频谱空洞,实现对主用户无干扰接入。频谱感知需要在极低信噪比下有较好的感知性能,才能保证感知用户在不影响主用户通信的情况下进行通信。即使在较低的信噪比条件下,它也需要较高的检测性能。提出一种对信号进行双稳态随机共振和特征识别的方法,首先信号先通过随机共振系统以提高信噪比,然后使用FAM算法将信号的循环谱特征提取出来。最后使用支持向量机(SVM)对特征进行模式识别。实验结果表明,在低信噪比下本方法相比传统的能量检测和SVM方法具有更高的检测可靠性。     

Delay optimal cognitive multiple access: a superposition coding approach

Cognitive radio (CR) is a powerful solution that can significantly improve the radio spectrum resources efficiency by allowing secondary users (SUs) to borrow unused spectrum from primary licensed networks. Conventional CR protocols allow an SU to transmit only when the primary users (PUs) are not active. However, waiting for idle timeslots may induce large packet delay and loss, so as to result in poor quality of service (QoS) for the SU. To overcome this, a joint coding and scheduling (JCS) method for cognitive multiple access is proposed. In particular, a successive interference decoder is utilized in the physical layer to thoroughly mitigate the SU’s interference to PU. A joint channel and queue aware scheduling is then proposed for the MAC layer of SU to minimize its average packet delay given a power constraint. We shall adopt Markov models to derive the analytical results on delay, packet-loss rate, and power consumption of the proposed scheme. Then by formulating and solving cross-layer optimization problem, we obtain the optimal scheduling parameter and the performance limit of the JCS in terms of delay-power tradeoff.     

基于队列博弈的认知无线电网络信道定价与选择优化

针对基于排队论的授权用户和认知用户频谱租赁问题,引入了异构认知用户概念,建立了一个双寡头垄断市场模型,提出了在M/M/1排队模式下的两种异构用户共享式的接人机制,并构建了非合作博弈和合作博弈的两种价格博弈模型,理论分析了多类型用户的频谱选择问题,联合定价机制和信道选择优化两方面,实现了频谱出售方的收益最大化和认知用户的代价最小化.认知用户选择模型最终达到了Wardrop均衡,利用凸优化和拉格朗日对偶理论对合作博弈下的优化模型进行了求解,并通过仿真对比了两种博弈模型下优化定价及获得收益的情况.     

An efficient cooperative sensing scheme with bandwidth-limited control channel

The conflict between scarcity of spectrum resources and low spectrum utilization motivates the concept of cognitive radio, which allows secondary unlicensed users to borrow temporally unused spectrum bands from primary licensed users. Spectrum sensing is one of the key functionalities that enable spectrum hole discovery and interference avoidance. As single user spectrum sensing may experience performance degradation in harsh wireless environment due to fading and shadowing, user cooperation is introduced to exploit spatial diversity for better sensing performance. However, local sensing results must be transmitted via a control channel. The advantage of cooperative sensing can be compromised by bandwidth limitation of the control channel. To overcome this, a benching cooperative sensing scheme is proposed in this paper. This scheme can reduce time overhead of sensing information exchange under a communication constraint. Analytical results of periodic sensing efficiency are then deduced while sensing parameters are optimized. Based on these, a recursive sensing algorithm exploiting prior channel state information is developed. Numerical results are presented to demonstrate the potential of our scheme.     

基于价值认同的需求侧电能共享分布式交易策略

分布式电源、储能和柔性负荷的集成赋予了需求侧灵活调控能力,使其能够以产消者身份进行电能共享,从而促进电力资源的优化配置。为此,针对电能共享市场的交易机制进行研究,文章提出了基于价值认同的需求侧电能共享分布式交易策略,旨在降低电力市场的交易成本并提高市场效率。首先,基于剩余理论设计了边际价格驱动下的电能共享模式,同时基于最优反应函数建立了市场博弈模型,揭示了市场无序竞争导致的无谓损失。对此,提出了价值认同机制以提高电能共享市场的运营效率,并设计了基于一致性算法的分布式交易策略以实现产消者间的去中心化交易,从而保护用户的隐私安全。最后,通过数值仿真验证了所提交易策略能够实现电能共享市场的帕累托改进并促进电力资源的优化配置。     

基于价值认同的需求侧电能共享分布式交易策略

分布式电源、储能和柔性负荷的集成赋予了需求侧灵活调控能力,使其能够以产消者身份进行电能共享,从而促进电力资源的优化配置。为此,针对电能共享市场的交易机制进行研究,文章提出了基于价值认同的需求侧电能共享分布式交易策略,旨在降低电力市场的交易成本并提高市场效率。首先,基于剩余理论设计了边际价格驱动下的电能共享模式,同时基于最优反应函数建立了市场博弈模型,揭示了市场无序竞争导致的无谓损失。对此,提出了价值认同机制以提高电能共享市场的运营效率,并设计了基于一致性算法的分布式交易策略以实现产消者间的去中心化交易,从而保护用户的隐私安全。最后,通过数值仿真验证了所提交易策略能够实现电能共享市场的帕累托改进并促进电力资源的优化配置。     

Flexible Spectrum and Power Allocation for OFDM Unlicensed Wireless Systems

Future generations of communication systems will benefit from cognitive radio technology, which significantly improves the efficient usage of the finite radio spectrum resource. In this paper we present a wireless unlicensed system that successfully coexists with the licensed systems in the same spectrum range. The proposed unlicensed system determines the level of signals and noise in each frequency band and properly adjusts the spectrum and power allocations subject to rate constraints. It employs orthogonal frequency-division multiplexing (OFDM) modulation and distributes each transmitted bit energy over all the bands using a novel concept of bit spectrum patterns. A distributed optimization problem is formulated as a dynamic selection of spectrum patterns and power allocations that are better suited to the available spectrum range without degrading the licensed system performance. Bit spectrum patterns are designed based on a normalized gradient approach and the transmission powers are minimized for a predefined quality of service (QoS). At the optimal equilibrium point, the receiver that employs a conventional correlation operation with the replica of the transmitted signal will have the same efficiency as the minimum mean-squared error (MMSE) receiver in the presence of noise and licensed systems. Additionally, the proposed approach maximizes the unlicensed system capacity for the optimal spectrum and power allocations. The performance of the proposed algorithm is verified through simulations.      

Robust hard decision combination scheme based on Kullback–Leibler divergence for cooperative spectrum sensing in cognitive radio

Cognitive radio (CR) network is a new, emerging research area because it has the ability to improve spectrum utilization by detecting and using vacant channels that are unused by licensed users. Reliable detection of the licensed user signal is a prerequisite for CR network to avoid interference to the licensed user. Cooperative spectrum sensing (CSS) is able to offer better sensing performance in comparison with individual sensing. However, CSS is vulnerable to attack from malicious users who falsify sensing data. In this paper, we propose a robust hard decision combination rule based on the Kullback–Leibler divergence (KL divergence) for CSS. The proposed scheme can achieve sensing performance similar to that of the optimal hard decision combination rule, the Chair–Varshney rule, while not requiring information on the signal‐to‐noise ratio. Furthermore, the proposed scheme can provide secure CSS against some common types of malicious users without any user identification step. Our simulation results prove the effectiveness of the proposed scheme. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

干扰因素下无线电能传输频率控制算法研究

为了提高无线电能传输WPT(wireless power transmission)负载端接收功率以及效率,增强传输的稳定性,研究无线电能传输系统过耦合干扰因素下无线电能传输频率控制算法,解决在该种干扰因素下频率分裂引起的传输功率下降问题。采用自适应频率跟踪WPT系统,依据DSP控制DDS(direct digital synthesis)自动调节输出频率,完成无线电能传输频率的自适应跟踪控制。采用改进粒子群优化算法,以进化因子和时间变动为依据进行自适应调整粒子的惯性权重和学习因子,提高粒子寻求最优解的速度和粒子算法的搜索力,获取无线电能传输系统功率和效率的最优值,增强频率跟踪的速度和精度。结合Zigbee,向DSP中植入改进粒子群优化算法,控制无线电能传输系统射频源频率,完成无线电能传输系统功率和效率同步频率跟踪,增强过耦合运行状态下无线电能传输负载端接收功率及效率。实验表明,该控制算法可在临界耦合点前提高无线电能传输系统整体功率,且能提高无线电能传输系统效率,系统发射端频率得到平稳控制,性能得到改善。     

A cluster‐based sequential cooperative spectrum sensing scheme utilizing reporting framework for cognitive radios

The cognitive radio (CR) technology is being considered as a novel approach for improving the spectrum utilization by detecting and using the vacant spectrum bands of licensed users. Cooperative spectrum sensing (CSS) is the most promising method for offering more reliable sensing performance compared to individual sensing. However, in a large CR network, CSS requires a huge number of sensing result transmissions from cognitive radio users (CUs) to the fusion center (FC), which can result in overhead traffic of the control channel and lack of power consumption of the CUs. In this paper, we propose a cluster‐based sequential cooperative spectrum sensing (SCSS) scheme utilizing a reporting framework to reduce the number of direct reports from CUs to FC while keeping similar sensing performance as the conventional CSS. By using the proposed scheme, the power consumption in the sensing process and the overhead of the control channel can be significantly reduced. Simulation proves the efficiency of the proposed scheme. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.