认知无线电网络中基于跨层设计的能效优化算法

为提高认知无线电网络中次用户节点的能量有效性,该文基于连续时间马尔科夫理论对次用户的频谱感知和接入过程进行联合建模,对影响次用户传输能效的主要因素进行了分析,提出了一种基于跨层设计的能量有效优化算法。该算法可有效减小主用户非时隙返回信道对次用户能量有效性的影响,并通过联合优化感知时间和接入概率,使次用户在感知性能和传输能效间实现了有效折衷。仿真结果表明,本文算法相对于仅考虑频谱感知或接入策略的单层优化算法,可使次用户的能量有效性得到较大提高。      

一种基于信道质量的鲁棒机会频谱接入策略

为了提高分等级网络中次用户通过机会频谱接入获得的有效吞吐率,提出了一种基于信道质量的鲁棒机会频谱接入策略.该策略利用信道质量信息和信道占用信息做出传输决策,使得次用户在信道感知结果为空闲和占用时分别以不同的信道质量门限选择传输机会发起传输,充分利用了信道质量好的传输机会.结合该策略,建立了以对主用户的干扰为约束条件,最大化次用户有效吞吐率的优化问题,并考虑到了信道传播特性统计参数存在不准确估计的情况,对该接入策略的门限进行了鲁棒性设计.仿真结果表明:所提出的鲁棒机会频谱接入策略能够显著提高次用户的有效吞吐率.     

混合式频谱共享系统功率分配研究

该文结合机会式频谱共享(Overlay)与共存式频谱共享(Underlay)提出一种混合式频谱共享模型。基于提出的模型,考虑次用户理想感知和非理想感知两种情况,采用离散状态马尔科夫过程对信道活动进行建模,进而在平均容量最大化准则下分析了混合式频谱共享系统的功率分配问题,导出了次用户的最优功率分配策略及系统可获得的最大容量。理论和仿真结果表明,基于最优功率分配策略的混合式频谱共享系统可以获得比Overlay或Underlay系统更高的容量。     

认知无线网络动态权值调整的频谱切换策略

认知无线网络中,次用户的目标信道选择受次用户传输功率、信道衰落因子、信道带宽、信道可用率等因素影响。针对基于多属性判决的频谱切换没有充分考虑各因素的重要程度和动态变化问题,本文提出了基于动态权值调整的频谱切换策略。根据主观经验和网络环境变化动态调整权值,采用多属性简单加权法计算各信道目标函数值,根据目标函数值降序排列结果选择切换的目标信道。仿真结果表明,本文所提出的算法能够减少次用户的切换次数,提高有效数据传输速率。      

基于排队时延及博弈分析的认知无线网络信道分配算法

提出了一种适用于认知无线网络的分布式动态频谱资源分配算法。该方法以业务分组的传输成功率作为用户的效用函数,通过优先级排队模型求解传输时延,并采用分布式博弈获得各用户的信道分配策略。与已有的算法相比,所提算法对策略迭代方式进行了改进,且采用了动态策略调整步长。各从用户根据当前感知的网络状态和其余用户的策略,不断动态调整自身的信道选择策略。所提出的算法能够使各认知用户信道选择策略更加快速地收敛到策略均衡点,有效抑制策略的振荡,减小分组丢失率。基于MATLAB对所提出的算法的性能进行了仿真,仿真结果验证了该算法的有效性。     

认知车载网络中基于三态模型的频谱感知策略

本文将认知无线电技术应用于车载通信,车载用户被看作是未授权用户（次用户）,并且能够机会主义地动态感知、分析和访问频谱。在车载用户频谱感知过程中提出一种三态模型,频谱占用状态分为空闲时,被主用户占用时以及被车载用户占用时三种。仿真结果表明,认知车载网络中基于三态模型的频谱感知策略可以显著提升车载用户信道利用率和传输公平性。     

认知无线网络基于信号博弈的分布式功率控制算法

针对认知无线网络分布式环境下信道信息不对称导致资源分配冲突的问题,该文提出一种基于信号博弈的分布式功率分配算法。考虑具有竞争关系的次用户在不使用控制信道的情况下,通过信号博弈策略依次选择功率分配策略,达到信道信息共享的目的,能有效避免对主用户正常传输的干扰以及竞争次用户之间功率分配冲突。该文对均衡结果进行分析,仿真结果表明该算法可以有效估计信道增益,次用户的吞吐量相对于已有研究得到明显提升。     

一种非理想感知条件下的双门限机会频谱接入策略

为了有效提高认知网络中次用户的吞吐率性能,提出了一种应用于非理想感知条件下的双门限机会频谱接入策略。该策略能在次用户对信道占用情况感知非理想的条件下,综合考虑次用户的信道质量和非准确的信道占用信息,使次用户在信道感知为空闲和占用时分别以不同的信道质量门限选择接入信道,从而最大程度地利用信道质量较好的传输机会,提高次用户的吞吐率性能。结合本策略,建立了以次用户的有效吞吐率最大化为目标、以对主用户的干扰程度为约束条件的优化问题,并在次用户对信道感知存在误差的条件下给出了最优门限的设计方法。仿真结果表明,所提出的双门限机会频谱接入策略能够在非理想感知条件下显著提高次用户的有效吞吐率。     

基于地理位置的频谱共享系统功率分配

针对次用户地理位置分布的随机性,提出一种基于地理位置的多信道underlay频谱共享模型,并设计了一种基于凸优化的功率分配算法以提高频谱资源利用率。首先根据不同地理位置的次用户对主用户干扰的差异,设计一种基于产出投入比的公平性信道分配准则,将复杂的多信道资源分配问题转化为单信道功率分配问题;继而采用一种基于凸优化的迭代寻优方式进行功率分配,最终获得次用户的系统信道容量。仿真结果表明,相比按接入时间先后分配信道的方法,基于地理位置的多信道underlay频谱共享模型可以获得更高的信道容量。     

主用户活跃性下的多功率分配策略

考虑到认知用户在信息传输过程中主用户的状态可能随时变化,提出了一种新的功率分配模式——多功率分配策略。在基于频谱感知的系统模型中,以认知系统的吞吐量为目标函数,得出了主用户感知过程的多种状态,并分配三种不同的功率,最大化认知系统的容量。仿真结果表明,随着主用户活跃指数的逐渐提高,所提新模型的功率分配策略要优于传统方法。同时分析了新的功率分配下平均干扰功率与主用户接收端的信噪比对系统吞吐量和最优感知时间的影响,进一步验证了所提出新策略的有效性。 〖HT5H〗关键词：〖HT5K〗认知无线电;主用户活跃;频谱感知分配;多功率分配;吞吐量最大化     

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。     

Multi-channel energy detection under phase noise: analysis and mitigation

For the development of highly integrated, flexible and low-cost cognitive radio (CR) devices, simple transceiver architectures, like direct-conversion receiver, are expected to be deployed and provide viable radio frequency (RF) spectrum sensing solutions for practical implementation. Yet, this can be very challenging task especially if spectrum sensing and down-conversion are conducted over multiple RF channels simultaneously for improved efficiency in channel scans. Then, the so-called dirty RF problem that degrades link performance of traditional transmission systems starts to be influential from spectrum sensing perspective as well. The unavoidable RF impairments, e.g., oscillator phase noise in direct-conversion receiver, could generate crosstalk between multiple channels that are down-converted simultaneously, and thus considerably limit the spectrum sensing capabilities. Most of the existing spectrum sensing studies in literature assume an ideal RF receiver and have not considered such practical RF hardware problem. In this article, we study the impact of oscillator phase noise on energy detection (ED) based spectrum sensing in multi-channel direct-conversion receiver scenario. With complex Gaussian primary user (PU) signal models, we first derive the detection and false alarm probabilities in closed-form expression. The analytical results, verified through extensive simulations, show that the wideband multi-channel sensing receiver is very sensitive to the neighboring channel crosstalk induced by oscillator phase noise. More specifically, it is shown that the false alarm probability of multi-channel energy detection increases significantly, compared to the ideal RF receiver case. The exact performance degradation depends on the power of neighboring channels as well as statistical characteristics of the phase noise in the deployed receiver. In order to prevent such performance degradation in spectrum identification, an enhanced energy detection technique is proposed. The proposed technique calculates the leakage power from neighboring channels for each channel and improves the sample energy statistics by subtracting this leakage power from the raw values. An analytical expression is derived for the leakage power which is shown to be a function of power spectral levels of neighboring channels and 3-dB bandwidth of phase noise process. Practical schemes for estimating these two quantities are discussed. Extensive computer simulations show that the proposed enhanced detection yields false alarm rates that are very close to those of an ideal RF receiver and hence clearly outperforms classical energy detection.     

Elastic bandwidth allocation scheme with softened peak interference power constraint for the dynamic cognitive radio systems

The popularity of diverse wireless communication systems has led to increased strains on the unlicensed spectrum. However, investigations have shown that vast portions of the licensed spectrum remain underutilized across frequency, space and time. To improve the utilization of the existing radio spectrum, cognitive radio (CR) allows a secondary system to access the licensed spectrum as long as the primary system’s operation is not compromised. Two main CR transmission modes, spectrum overlay and underlay have been proposed. In the spectrum overlay mode, challenges in quality-of-service (QoS) provisioning arise due to the necessity for secondary users to vacate the channels when a primary user appears. In the underlay model, interference caused to the primary system has to be carefully managed resulting in a constraint of the secondary system’s transmit power, which causes difficulty in QoS provisioning. In this paper, we propose an elastic bandwidth allocation scheme to make concurrent use of both spectrum overlay and underlay transmission modes. Different from existing hybrid transmission strategy, our scheme employ a novel softened peak interference power constraint to improve the performance of the secondary system while still granting the superior protection to the primary system transmissions. This allows the proposed scheme to achieve a superior transmission capacity in the CR network while avoiding the weaknesses of the both spectrum overlay and spectrum underlay transmission modes.     

基于信道定价的无线虚拟网络资源分配策略:匹配/Stackelberg分层博弈

针对分层匹配博弈不能跟踪信道变化以及循环迭代收敛慢等问题,该文提出一种基于信道定价的无线虚拟网络资源分配策略:匹配/Stackelberg分层博弈。分别以基于流带宽的用户满意度、系统带宽及切片功率作为报酬函数建立3级联合优化模型,并采用匹配/Stackelberg分层博弈求解。在博弈下层,定义移动虚拟网络操作者(MVNOs)m—切片n对m_n及其与用户(UEs)的1对1匹配博弈以代替UEs与MVNOs的多对1匹配,对\begin{document}${m_n}$\end{document}定义基于信道平均信息的切片功率价格,加速上、下一致收敛并使UEs适应信道选择最优,证明均衡点存在并给出了低复杂度的分布式拒绝-接收算法;在博弈上层,基于UEs与已匹配关系,形成基础资源提供者(InPs)与的Stackelberg博弈,给出了基于局部信道信息的功率定价和分配策略,使系统效用及频谱效率基于信道最优。最后定义了双层循环稳定条件及过程。仿真表明,该策略在信道跟踪、频谱效率、效用方面均优于随机定价的匹配/Stackelberg分层博弈以及传统分层匹配博弈。     

Capacity and Energy Efficiency of Multi-User Spectrum Sharing Systems with Opportunistic Scheduling

This paper investigates the capacity and energy efficiency of spectrum sharing systems with opportunistic user selection where a secondary network utilizes spectrum bands licensed to a primary network under interference regulation. In spectrum sharing systems, secondary users consume a fraction of their resources in sensing the channels to the primary users to comply with the interference constraints. Although more resources for sensing improve reliability and performance, the throughput loss due to time overhead and energy loss due to power overhead should be properly incorporated in performance evaluation. In this context, we define and derive a new metric ? average capacity normalized by the total energy consumption ? reflecting time and power overhead for spectrum sensing. Based on the developed framework, the optimal normalizedcapacity is investigated. We also propose a simple and practical suboptimal best-n scheme motivated by the infeasibility and high computational complexity of the optimal strategy, where n denotes the number of sensing secondary users. Our analytical and simulation results show that the proposed best-1 scheme is an energy-efficient technique with near optimality in terms of the capacity normalized by the energy consumption.     

A joint sensing and transmission power control policy for RF energy harvesting cognitive radio networks

We consider a radio frequency energy harvesting cognitive radio network in which a secondary user (SU) can opportunistically access channel to transmit packets or harvest radio frequency energy when the channel is idle or occupied by a primary user. The channel occupancy state and the channel fading state are both modeled as finite state Markov chains. At the beginning of each time slot, the SU should determine whether to harvest energy for future use or sense the primary channel to acquire the current channel occupancy state. It then needs to select an appropriate transmission power to execute the packet transmission or harvest energy if the channel is detected to be idle or busy, respectively. This sequential decision‐making, done to maximize the SU's expected throughput, requires to design a joint spectrum sensing and transmission power control policy based on the amount of stored energy, the retransmission index, and the belief on the channel state. We formulate this as a partially observable Markov decision process and use a computationally tractable point‐based value iteration algorithm. Section 5 illustrate the significant outperformance of the proposed optimal policy compared with the optimal fixed‐power policy and the greedy fixed‐power policy.     

Cluster‐based adaptive multispectrum sensing and access in cognitive radio networks

Spectrum sensing and access have been widely investigated in cognitive radio network for the secondary users to efficiently utilize and share the spectrum licensed by the primary user. We propose a cluster‐based adaptive multispectrum sensing and access strategy, in which the secondary users seeking to access the channel can select a set of channels to sense and access with adaptive sensing time. Specifically, the spectrum sensing and access problem is formulated into an optimization problem, which maximizes the utility of the secondary users and ensures sufficient protection of the primary users and the transmitting secondary users from unacceptable interference. Moreover, we explicitly calculate the expected number of channels that are detected to be idle, or being occupied by the primary users, or being occupied by the transmitting secondary users. Spectrum sharing with the primary and transmitting secondary users is accomplished by adapting the transmission power to keep the interference to an acceptable level. Simulation results demonstrate the effectiveness of our proposed sensing and access strategy as well as its advantage over conventional sensing and access methods in terms of improving the achieved throughput and keeping the sensing overhead low. Copyright © 2012 John Wiley & Sons, Ltd.     

优化的最佳中继协作频谱感知

在基于中继的协作频谱感知中,尽管通过引入认知中继可有效提高协作频谱感知性能,然而认知中继的引入也会带来额外的系统开销及复杂度增加问题。为了节约系统开销,本文在前期取得研究成果的基础上,进一步提出了一种基于删余的最佳中继协作频谱感知方案,只有当次用户检测到主用户信号且目标次用户的报告信道衰落严重时,才申请认知中继的协作传输,同时目标次用户将其检测到的感知信息发送到认知中继;最后,分别从检测性能和次系统可获得的容量角度对所提方案下的协作频谱感知性能进行了理论分析。分析和仿真结果表明,所提方案可以有效提高检测性能,当确保主用户受到足够保护的前提下,利用所提方案可以获得更高的次系统容量。      

基于合约制的认知网络协作频谱共享模型

为了提高认知无线电网络中主用户的能效和谱效,提出了一种基于合约制的协作频谱共享新模型。在该模型中,当主用户信道质量差时,次用户为其提供中继服务;作为回报,在主用户信道质量好时,次用户可以在一定的干扰约束下以underlay的模式和主用户共享频谱。在此框架下引入经济学中的合约理论,将主次用户间的协作问题建模为合约设计问题,并建立了主次用户评价合约收益的效用函数,将提高主用户的能效和谱效问题转变为设计合约使主用户获得最大效用的优化问题,并利用差分进化算法对该问题求解。最后,在不同的环境下,将主用户协作与不协作获得的效用进行对比,结果表明,主用户在没有额外投入频谱资源的条件下,不仅节省了发送功率,而且有效地提高了数据传输速率,进而提高了能效和谱效。     

Dynamic wireless spectrum access using GNU Radio and software‐defined radios

This paper presents the design, implementation, and results from a dynamic wireless spectrum access system built using GNU Radio and software‐defined radios (SDRs) as part of an undergraduate senior design project. The project involved designing and implementing a dynamic wireless spectrum access system in which the secondary user (SU) learns the unknown transmission behavior (channel occupancy and time slots) of the primary user (PU) and then opportunistically transmits during time slots and using channels when they are not being used by the PUs. The main design objective was to maximize the throughput of the SU while minimizing the interference to the PU. A transmitted signal energy detection algorithm with an adaptive threshold was employed to set the channel states as occupied or not occupied. Channel state information was used to determine the PU behavior in a deterministic manner such that the unused time slots and channels could be exploited. A channel allocation scheme for the SU is proposed using the PU channel occupancy information to calculate the channel(s) and time slots available to the SU at any given time. Simulation and physical testing of the system validate the proposed algorithms. Students' feedback affirms GNU Radio and SDRs to be an effective platform for introducing abstract mathematical communications theory concepts, such as cognitive radios and dynamic spectrum allocation, in a hands‐on manner.