基于非理想感知的认知无线电系统感知时间与频谱分配联合优化算法

针对非理想感知情况下感知时间与频谱分配联合优化问题,同时考虑漏检与主用户重新占用频谱两种场景所造成的主次用户碰撞,并通过量化主用户对认知用户的干扰,给出有无主用户存在时认知系统可获得的吞吐量。在总传输功率约束以及对主用户的最大干扰功率约束两个限制条件下,以最大化系统平均吞吐量为优化目标,给出感知时间与频谱分配联合优化算法。算法首先通过折半法搜索最优感知时间,在既定的感知时间下,将子信道分配给能获得最大平均吞吐量的认知用户,在此基础上,利用凸优化相关理论求得最优功率分配。仿真结果表明,本文所提算法相比于传统频谱分配算法系统平均吞吐量性能提升了10%左右。     

一种多用户协同频谱感知功率控制方案

分析和研究了多用户协同频谱感知原理,通过时分方式,实现了多用户之间的频谱共享。同时为避免对主用户产生有害的干扰,从用户通过一种算法控制它的发射功率,保证主用户的通信服务质量。最后对多用户协同频谱感知和单用户频谱感知的性能进行了仿真研究,结果表明多用户协同频谱感知可以明显提高频谱感知的性能,克服阴影/衰落作用的不利影响,提高频谱利用率。     

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...     

基于次用户功率控制辅助的合作频谱感知

传统的合作频谱感知一般将感知环境建模为单级信道,且次用户一般都以相同的发射功率向数据融合中心报告感知数据,难以体现并利用不同次用户感知数据之间的空间分集差异。为解决此问题并有效地设置次用户在感知数据上报阶段的发射功率,该文提出了3种最优功率控制方案,以获得相应设计准则下参与合作感知的次用户最优发射功率。在融合中心理想具备感知信道和报告信道的统计特性时,通过理论推导获得了基于信道统计特性的功率控制闭式解方案;当信道统计特性难以现实具备时,分别获得了基于联合信道统计特性估计的最大特征功率矢量及盲加权多特征功率矢量方案。理论分析和仿真实验表明,在不同的先验信息条件下,3种方案的性能皆远优于缺少功率控制的合作感知方案。     

认知无线电多时隙联合频谱感知方法及优化

为了降低认知无线电中次用户对主用户的干扰,提出了次用户通过多个时隙的能量感知联合检测主用户的频谱感知方法。每个传输帧被分成若干个时隙,次用户在每个时隙的开始进行能量感知,通过合并多个时隙的感知结果,提高次用户对主用户的检测性能。为了最大化次用户的频谱效率,将主用户状态建模为二维马尔科夫随机过程,并根据该过程优化单时隙频谱感知时间。仿真结果表明：相比Liang的“先听后传”频谱感知方法,提出方法仅牺牲14％的频谱效率,却使干扰概率降低了28％;随着信噪比增加,提出方法的最大频谱效率逐渐接近“先听后传”频谱感知方法。     

认知网络中协作感知吞吐量的优化

为了提高集中式认知网络的吞吐量,提出了基于信任度的吞吐量优化算法.该算法在主用户充分保护的前提下,以认知用户的吞吐量为目标函数,融合中心采用双门限值对本地感知结果进行融合.从理论上证明了吞吐量是全局漏检概率的增函数,当全局漏检概率等于门限值时,吞吐量达到最大值.并利用牛顿迭代法求出单节点概率,然后采用遍历法可得到认知用户吞吐量最大值.仿真结果表明,当信噪比为-14 dB时认知用户融合优化算法相对"AND准则"OR准则"以及"HALF准则"归一化吞吐量分别提高了0.62、0.3和0.09.     

认知无线网络中基于节点功耗和频带利用率的感知时隙优化算法

本文主要研究感知时隙对次用户节点功耗和频带利用率的影响,在保证检测性能的前提下,分析它们之间的折中关系,通过构造新的指标函数来衡量不同系统对次用户节点功耗和频带利用率的要求,并引入调节因子以便根据系统的不同需求选择不同的感知时隙。仿真结果表明,次用户节点功耗和频带利用率均是感知时隙的递减函数,在给定调节因子的情况下,总存在一个最优的感知时隙能够使得指标函数达到最小。      

认知无线电中频谱感知技术

固定频谱分配政策导致频谱使用率低下,为克服这一缺点,人们提出使用认知无线电技术实现动态频谱接入,从而有效利用频谱空穴。频谱感知是认知无线电的关键技术。文中介绍了目前已提出的频谱感知技术:发射机检测(包括匹配滤波器检测、能量检测和周期平稳特征检测)、合作检测、接收机检测及基于干扰温度的检测,仿真分析了各种方法的优缺点及有待解决的问题。为满足多用户环境和实时性要求,仍需探讨新的频谱感知方法,提高检测性能。     

OFDMA中频谱感知的功率控制算法研究

结合认知无线电的特点,将基于频谱感知的功率控制算法应用到OFDMA系统中,建立了PA-OFDMA(Power Adaptation-OFDMA)仿真模型,实现了认知环境下的多址接入技术。该模型基于频谱感知信息,通过一种功率阈值分配算法自适应地为每个子信道分配一个独立的功率阈值,限定使用该信道认知用户的最大发射功率,实现非授权用户与授权用户的频谱共享。与干扰温度模型进行了比较,仿真结果表明,该模型解决了干扰温度模型中的局部干扰问题,提高了系统容量,具有较高的频谱利用率和较低的误比特率。     

认知无线电频谱感知技术研究

认知无线电(CR)作为一种智能通信系统,能够充分了解周围的通信环境,实现频谱的动态利用。频谱感知被用作动态无线电访问的关键技术,并在近些年得到了广泛的研究及应用。文章介绍了三种不同的频谱感知技术:基于发射机的频谱检测、基于接收机的频谱检测和合作检测,并对三种检测技术的性能及优缺点进行了分析。     

Adaptive power control and beam-forming joint optimization in cognitive radio networks

A novel adaptive power control and beam-forming joint optimization algorithm is proposed in cognitive radio(CR) underlay networks,where cognitive network share spectrum with primary network which spectrum is licensed.In this paper,both primary base station(PBS) and cognitive base station(CBS) are all equipped with multi antennas,while each primary user(PU) and cognitive user(CU) has only one antenna.Different from traditional algorithms,an adaptive weight factor generating solution is supplied to different access users(both PUs and CUs) in this paper,and the different priority of users is also considered,because PUs have higher priority,the weight factor of PUs is fixed as constant and signal-to-interference and noise ratio(SINR) threshold is unchanged,while for CUs,it is set adaptively and SINR threshold is also changed accordingly.Using this algorithm,the transmit power is decreased,which relax the strict requirements for power amplifier in communication systems.And moreover,owing to PUS has fixed SINR threshold,the calculated SINR at receiver is nearly unchanged,but for CUs,the SINR is changing with the adaptive weight factor.Under the assurance of quality of service(QoS) of PUs,the solution in this paper can enable CRs access to the CR network according to adaptive SINR threshold,therefore which supplies higher spectrum utilization efficiency.     

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.     

Optimisation of sensing time and transmission time in cognitive radio-based smart grid networks

Cognitive radio (CR)-based smart grid (SG) networks have been widely recognised as emerging communication paradigms in power grids. However, a sufficient spectrum resource and reliability are two major challenges for real-time applications in CR-based SG networks. In this article, we study the traffic data collection problem. Based on the two-stage power pricing model, the power price is associated with the efficient received traffic data in a metre data management system (MDMS). In order to minimise the system power price, a wideband hybrid access strategy is proposed and analysed, to share the spectrum between the SG nodes and CR networks. The sensing time and transmission time are jointly optimised, while both the interference to primary users and the spectrum opportunity loss of secondary users are considered. Two algorithms are proposed to solve the joint optimisation problem. Simulation results show that the proposed joint optimisation algorithms outperform the fixed parameters (sensing time and transmission time) algorithms, and the power cost is reduced efficiently.     

Joint power control and spectrum sensing for capacity maximisation in spectrum sharing systems

We study the problem of joint power control and spectrum sensing for maximising the capacity at the secondary user while protecting the primary user's transmissions in spectrum sharing cognitive radio systems. Power control regulates the transmission power of the secondary user and spectrum sensing regulates the sensing time and the sensing threshold that care for the primary user's protection. This problem is a capacity maximisation problem that we formulate and solve using an iterative greedy algorithm due to its complex form. The solution of the proposed algorithm leads to the global optimal solution that represents the optimal triplet values of transmission power, sensing time and threshold. The obtained results show the potential capacity maximisation that is achieved by the proposed joint design as long as the primary user's protection is provided. Finally the convergence behaviour of the proposed algorithm is assessed in terms of the needed iterations for enhancing the capacity of spectrum sharing systems.     

考虑恶意节点的CRN合作频谱感知方法

基于带有恶意节点的更为实际的频谱感知环境,研究了基于合作感知的频谱共享网络模型,次级用户将会根据合作感知结果动态地调整其发射功率。为了防止恶意节点对感知系统的感知性能造成严重影响,研究了如何进行合作感知以提高感知性能。在一定的检测概率和相关功率约束下,建立了一个以最大化次级网络的吞吐量为目标函数的优化问题。仿真实验首先突出说明了恶意节点数目对频谱感知影响重大,同时还表明无论是否存在恶意节点,提出的算法均可有效地计算出最优的感知时间和发射功率,且在降低最大干扰功率限制和最大发射功率限制时,网络的吞吐量是增大的。     

Spectrum sensing and power/rate control in CDMA cognitive radio networks

In this paper, a two‐phase algorithm for the spectrum sensing and power/rate control of a secondary user (S‐user) or cognitive radio is proposed. In the first phase, the primary base station (P‐BS), which is conscious of both the number and the data rate of primary active users (P‐user), broadcasts theitusage capacity percentage (UCP) of its cell. Since knowing only the UCP is not enough to guarantee that the total load (of P‐users and S‐users) is less than a maximum permissible load, the S‐user must measure the total interference received from both the P‐users and other S‐users. In this direction, using both the UCP and measurement of the interference received from the P‐users and the S‐users by the S‐user or secondary base station (S‐BS), we mathematically derive an equation for issuing data transmission permission, which if it is held then the second phase of the algorithm: the transmit power/rate control starts. In this phase, the S‐user and the S‐BS look for feasible values for the transmit power level and transmission rate. If there are feasible values, it starts its transmission at these feasible transmit power and rate. Since both the location of the S‐user and the channel condition vary in time, the whole algorithm is iterated periodically with a period faster than the coherence time of the channel. Furthermore, we consider the down link of the above system with cooperation among neighboring S‐users to overcome fading channels and we investigate the amount of improvement in the reliability of the issuing data transmission permission. As well, we consider the uplink of the system with multiple antennas in the S‐BS to investigate the improvement in the same parameter over spatially correlated and independent fading channels. Theoretical analysis is validated using computer simulations. Both theoretical analysis and computer simulations show that the proposed cooperative spectrum sensing algorithm performs properly at SNR = ?5dB in flat Nakagami‐m fading channels with m = 1 even in correlated fading channels. We also address the improvement of the reliability of the issuing data transmission permission in the uplink in case of using multiple antennas only in the S‐BS. Copyright © 2011 John Wiley & Sons, Ltd.     

Dynamic control approaches of spectrum sensing in multi-band cognitive radio networks

In this paper,the dynamic control approaches for spectrum sensing are proposed,based on the theory that prediction is synonymous with data compression in computational learning. Firstly,a spectrum sensing sequence prediction scheme is proposed to reduce the spectrum sensing time and improve the throughput of secondary users. We use Ziv-Lempel data compression algorithm to design the prediction scheme,where spectrum band usage history is utilized. In addition,an iterative algorithm to find out the optimal number of spectrum bands allowed to sense is proposed,with the aim of maximizing the expected net reward of each secondary user in each time slot. Finally,extensive simulation results are shown to demonstrate the effectiveness of the proposed dynamic control approaches of spectrum sensing.     

认知中继网络中基于频谱感知的自适应功率控制策略

针对采用联合overlay和underlay频谱共享模式的认知中继网络,基于频谱感知结果和干扰信道条件,提出了自适应功率控制策略,从理论上分析了次用户的中断概率。通过Monte-Carlo仿真,与单一overlay或underlay频谱共享模式和固定功率控制方案下次用户的中断性能进行了比较。仿真结果表明,采用自适应功率控制方案,在相同中断概率条件下,次用户对主用户的干扰概率降低了70%~80%;在相同干扰概率条件下,次用户的中断概率降低了1~2个数量级,频谱共享性能得到了有效提高。