MIMO认知无线电网络中的联合收发波束形成算法研究

利用半正定规划和最小均方误差准则,提出了一种最小化发射功率的MIMO认知波束形成算法,与已有对偶算法相比,降低了发射功率,提高了系统性能。此外,还提出了SINR均衡的波束形成算法,解决了MIMO认知网络中认知用户的均衡通信问题。数值仿真结果表明,新算法在避免对主用户造成干扰的同时,能保证每一个用户的通信质量,均衡SINR水平得到了大幅提升。     

Cooperative beamforming and relay selection in cognitive radio systems

In this paper, a new scheme is suggested for cooperative beamforming (BF) and relay selection in CR networks, where a pair of secondary users communicates with each other assisted by some multiple antenna relay nodes. The goal of the algorithm is to maximize signal to interference plus noise ratio of secondary user receiver subject to limited interference caused for primary user receiver and power constraints of relay nodes. The relay selection and BF optimization problem is solved separately by employing convex semidefinite programming through rank‐one relaxation. It is shown that our proposed algorithm outperforms conventional relay selection and BF schemes. Copyright © 2014 John Wiley & Sons, Ltd.     

Optimal cooperative beamforming design in cognitive radio networks with multiple secondary user links

In this paper, a novel beamforming method is proposed for a more realistic cognitive radio system with several secondary transmitters and receivers, a number of relays, and 1 primary transmitter and receiver. When the primary user link is idle, all secondary transmitters access temporal spectrum holes to simultaneously broadcast their information to the relays each associated with an infinite buffer. In the next stage, the relays transmit the information to the secondary receivers using a cooperative beamforming method no matter whether primary user link is silent or not. The proposed method of designing the beamforming vector enables the system to maximize the power received by the secondary users while maintaining the interference plus noise power at the primary user receiver below a predefined threshold. Results of simulations confirm validity of the method and improved performance compared to the zero‐forcing beamforming. The impact of channel quality between nodes on the performance of the system is also investigated.     

Optimal received SINR balancing based on cooperative beamforming in cognitive radio networks

In this paper, we investigate a two‐step cooperative cognitive radio network, which consists of two secondary links, a number of relays, and one primary link. During the first step, the primary link is assumed to be idle; both secondary sources simultaneously broadcast their data to the relay network. During the second step, the relay network employs a proposed cooperative beamforming (CBF) scheme and transmits the received data toward both of the secondary destinations (no matter whether the primary link is idle or not). The proposed CBF scheme enables the investigated network to simultaneously maximize received signal to interference plus noise ratio at both of the secondary destinations while keeping interference plus noise power at the primary destination under a predefined threshold. Indeed, the proposed scheme represents an optimal received signal to interference plus noise ratio balancing approach based on CBF, which guarantees the required quality of service for the primary link and also both secondary links. We optimize the CBF vector by relaxing the optimization problem to a convex semidefinite programming and solving with the bisection search algorithm. Numerical results show the efficiency and robustness of our approach. A comparison of our approach with the zero‐forcing beamforming method is also presented. Copyright © 2016 John Wiley & Sons, Ltd.     

基于谱分析的稳健自适应波束形成算法

针对在导向矢量存在误差情况下,自适应波束形成算法性能下降问题,提出一种基于谱分析的稳健自适应波束形成(SA-RAB)算法。算法利用空域与频域的对称性,根据真实导向矢量与理想导向矢量之间的误差,运用谱分析(SA)技术确定波束主瓣宽度,最后利用二阶锥规划(SOCP)技术在主瓣宽度内形成平顶响应,并在副瓣区域内进行干扰抑制。仿真结果表明:该算法可有效地抑制干扰,并输出理想的信号干扰噪声比(SINR),且提高了波束形成针对导向矢量误差的稳健性,验证了算法的有效性和优越性。     

认知无线网络中基于联合波束形成和功率分配的低复杂度SINR均衡算法

认知无线电作为提高频谱使用效率的有效手段成为当前通信领域的研究热点。本文研究了单输入多输出的多用户认知无线网络,在主用户的干扰功率约束和认知用户的发射功率约束下,针对认知用户的信干噪比均衡问题,提出了一种低复杂度的联合波束形成和功率分配算法。与已有算法相比,该算法可以在保证最优的均衡信干噪比水平的同时,大幅度降低矩阵求逆和矩阵特征值分解的次数,特别是当处于通信状态的主用户和认知用户数目很多时。本文理论证明了所提算法的收敛性和最优性,并进行了详细的复杂度分析。理论分析和仿真结果均表明在多用户的认知无线网络中,本文所提算法可以将已有算法的平均运算复杂度降低50%以上。     

窃听信道下认知多小区中的协同波束赋形算法

小区之间优化变量耦合使多小区联合优化问题为非线性非凸问题,通过约束泄露干扰提出了基于半正定松弛的中心式协同波束成形算法,在此基础上,采用部分对偶分解方法将中心式联合优化问题分解为一组单小区优化问题,提出了一种分布式迭代求解算法。结果表明,所提算法在保证系统安全速率需求和认知干扰约束的条件下实现了系统功耗的降低,此外,分布式算法不仅能降低实现复杂度,而且能达到中心式算法的性能。     

认知无线电系统的顽健资源分配算法

摘 要：针对多用户下垫式认知无线电网络中参数不确定性问题,提出了一种顽健分布式功率控制算法。在干扰温度门限和次用户信干噪比（SINR）的约束下,考虑信道不确定性,实现认知系统功率消耗最小化。基于欧几里得球形不确定性描述,利用拉格朗日对偶分解理论给出了顽健功率控制问题的解。仿真结果表明,该顽健功率分配算法能同时满足主用户和次用户的QoS需求,与非顽健算法和传统SOCP算法对比可提升系统性能。     

An efficient algorithm for backbone construction in cognitive radio networks

Numerous research articles exist for backbone formation in wireless networks; however, they cannot be applied straightforward in cognitive radio network (CRN) due to its peculiar characteristics. Since virtual backbone has many advantages such as reduced routing overhead, dynamic maintenance, and fast convergence speed, we intend to propose a backbone formation protocol in CRN. In this paper, we propose a tree‐based backbone formation protocol along with its maintenance. Our protocol is based on non‐iterative approach, thus leading towards limited message overhead and faster convergence speed. The proposed algorithm first forms the tree by maintaining the parent‐child relationship, and second, the parent nodes are connected together to form the virtual backbone. In the end, we evaluate the performance our protocol through extensive simulations.     

Securing cognitive radio networks

Cognitive radio is a promising technology aiming to improve the utilization of the radio electromagnetic spectrum. A cognitive radio device uses general purpose computer processors that run radio applications software to perform signal processing. The use of this software enables the device to sense and understand its environment and actively change its mode of operation based on its observations. Unfortunately, this solution entails new security challenges. Our objective in this paper is to analyze the security issues of the main recent developments and architectures of cognitive radio networks. We present vulnerabilities inherent to those systems, identify novel types of abuse, classify attacks, and analyze their impact on the operation of cognitive radio‐based systems. Moreover, we discuss and propose security solutions to mitigate such threats. Copyright © 2010 John Wiley & Sons, Ltd.     

认知无线电中协作压缩频谱感知算法

针对宽带频谱认知无线电环境中,传统能量检测法在信噪比较低时,容易出现误检而使系统的检测性能下降的问题,文中提出了一种新型高性能的协作频谱感知算法,它是基于压缩理论的多节点频谱感知方法,各节点之间采用基于双判决门限的协作方式。仿真结果显示,双门限协作压缩频谱感知算法在低信噪比的情况下,检测性能明显优于传统能量检测法。     

基于感知无线电非合作博弈功率控制算法的研究

本文基于Goodman提出的非合作博弈功率控制模型改进了代价函数。针对感知无线电系统（CR）中各用户的通信需求,采用多载波码分多址（MC-CDMA）感知无线电系统,解决感知用户对主用户干扰和通信中断等问题,为实现感知频谱资源的有效分配,提出了一种新的感知无线电系统功率控制博弈算法。通过仿真表明,该算法同几种经典算法相比,既满足不同种类用户SIR要求,又提高了系统吞吐量,实现了对不同用户发射功率的有效控制,且系统性能明显提高。     

基于干扰消减的认知无线电频谱分配算法

在认知无线电网络的频谱分配过程基础上,提出了一种基于干扰消减的频谱分配算法.该算法通过将可用频谱分配给能够同时无干扰地接入同一频谱的所有认知用户来提高授权频谱的使用率.同时,该算法参考各个认知用户在初始阶段的可用频谱数量来为未分配到频谱资源的认知用户进行频谱分配,对频谱分配过程的公平性进行了优化.仿真结果表明,该算法能够在认知用户数量较多、可用频谱紧张的情况下获得较高的吞吐量.     

Trusted cognitive radio networking

Networking cognitive radios and nodes from primary system (PS) results in a heterogeneous coexisting multi‐radio wireless network, so that significant network throughput gain can be achieved. However, by investigating cognitive radio network (CRN) architecture, the links in CRNs are unlikely to support complete security check due to link dynamics, opportunistic availability, and uni‐directional in available time window. We therefore introduce trusted cognitive radio networking (TCRN) concept to facilitate network functions such as association in dynamic spectrum access and routing. First of all, we explore the mathematical framework for trust in CRNs. We then show successful association of node to CRN based on the mathematical structure of trust from statistical decision theory. Furthermore, we modify the machine‐learning algorithm to update the trust measure for each node, and develop rules of thumbs to facilitate TCRN with learning capability, based on numerical simulations. Trusted CRN can greatly alleviate heterogeneous challenge for CRN operation. Copyright © 2009 John Wiley & Sons, Ltd.     

基于认知无线电的新型非合作功率控制博弈算法

从认知无线电技术特性出发,在干扰温度门限的限制条件下,提出了基于新的代价函数功率控制博弈论算法,以有效地提高认知用户的信干噪比。根据信道状况、吞吐量最大化和功率限制的需求,将功率控制问题转化为一个干扰受限的多约束非线性规划问题。结合博弈论和最优化理论,证明了其纳什均衡的存在性和唯一性,给出了该模型的分布式求解算法。仿真实验表明,该算法可以有效提高认知用户的QoS和系统性能,充分利用无线资源。     

认知MIMO MAC最优迭代注水算法

研究发送功率以及干扰温度约束下的认知多入多出多址接入信道(MIMO MAC)的速率和最大化问题。通过部分对偶分解技术松弛干扰温度约束,原始问题被分解为较易处理的子问题,并提出一种迭代算法,通过交替进行对偶变量更新与迭代注水运算求解使得速率和最大的最优发送协方差矩阵。最后通过仿真表明算法的有效性。     

一种软件无线电与认知引擎的接口实现方法

该文主要讨论在基于软件无线电的认知系统中,软件无线电平台和认知引擎的接口实现。文中提出了一种基于XML语言描述的接口实现方法,并简单举例说明了如何对软件无线电平台处理能力和认知引擎配置参数进行描述,进而又阐述了软件定义无线电平台与认知引擎间的信息传递方式。文章为在软件定义无线电台上构建认知无线电提供了一种简单,可行的实现方法,同时提高了认知无线通信系统的开放性。     

协同系统鲁棒波束成形算法研究

由于实际很难获得理想信道状态信息(CSI),传统协同波束成形算法性能严重下降。设计对信道误差具有鲁棒性的波束成形算法具有重要的实际意义。针对放大转发协同系统最大化目的节点信噪比(SNR)准则下的波束成形设计,提出对应鲁棒算法。该算法从最坏情况鲁棒设计思想出发,建立保证鲁棒性的最优化问题,应用扩展S引理和Schur补定理将该问题由初始不可解转化为可解的准凸问题,进而求解出保证鲁棒性的波束成形因子。仿真表明:同等CSI偏差下,所提鲁棒算法的中断概率性能优于传统波束成形算法。     

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.     

Beamforming and power allocation in the downlink of MIMO cognitive radio systems based on multiobjective optimization

In this paper, power allocation and beamforming are considered in a multiple input multiple output (MIMO) downlink cognitive radio (CR) communication system, which a base station (BS) serves one primary user (PU) and one secondary user (SU). In order to design the CR system, a constrained multiobjective optimization problem is presented. Two objectives are the signal to noise plus interference ratios (SINRs) of PU and SU. Since PU has a spectrum license for data communication, a constraint in the optimization problem is that the SINR of PU must be greater than a predefined threshold based on the PU demand requirement. Another constraint is a limitation on power in BS. By considering the mentioned model, three iterative algorithms are proposed. At each iteration of all algorithms, the receiver beamforming vectors are derived based on the maximization of PU and SU SINRs, by assuming that the allocated powers and BS beamforming vectors are known. Also, power is assigned to users such that the constraint of power limitation is satisfied. The difference between the algorithms is in the obtaining of transmitter beamforming parameters. We evaluate the performance of the proposed algorithms in terms of bit error rate (BER) in simulations. Also, the computational complexity of the proposed algorithms is obtained.