基于纳什议价的认知无线电合作感知算法

认知无线电技术是建立在授权空闲频谱或非授权频谱基础上,主用户(Licensed user)享有优先频谱使用权,为保护主用户的正常需求,提高探测数据的可靠性,提出了一种新型两人纳什议价合作感知NBS算法,利用两个用户的合作感知信息,根据认知用户(secondary users)与主用户基站的距离和能量的差异,自适应的调节能量检测门限.并将多用户合作感知指派分组为两人纳什合作议价问题,结合"AND"规格融合每组感知数据,在保障主用户通信基础上,提高频谱利用率.仿真结果表明,NBS算法可有效的提高数据可信度,该算法与"AND"数据融合规则相比,感知数据的探测概率显著提高.     

认知无线电中基于MIMO波束成形的协同频谱接入设计

协同认知无线电技术由于其高效的频谱利用效率已经吸引越来越多的关注。在协同认知网络中,当第一用户（Primary User,PU）之间的信道状况恶劣时,特定的第二用户（Secondary User, SU）被选为中继协同PU完成信息传递,作为回报,PU分配一定的信道资源给SU,使其用于传输自己的信息。当SU系统中一个节点拥有多天线时,假设其可以很好的获悉其与PU之间的信道状态信息,通过波束成形设计可以使其在中继PU信息的同时完成自身信息的发送,而且使两者之间的信号互不干扰。这种频谱共享式的接入方式可以节约信道资源,提高频谱利用率。本文对采用放大转发（Amplify and Forward, AF）中继协议的SU发射端分别采用最小化加权均方误差和准则（Minimizing Sum of Weighted Mean Square Errors, MSWMSE）和迫零准则（Zero Forcing, ZF）对波束成形参数进行设计。仿真结果表明,两种设计方式都可以满足消除用户间干扰的要求;另外,由于基于MSWMSE准则的波束成形参数能够更好的平衡噪声和用户间干扰项对信号的损耗,因而获得更优的性能表现,而且通过调整加权系数可以满足PU用户不同的性能要求。      

认知无线电最优线性协作宽带频谱感知

本文提出了基于最优线性协作的宽带频谱感知方案。通过次级用户之间的协作,为认知网络的频谱感知提供分集,利用融合中心融合多个次级用户的宽带频谱感知数据来获取最优权重,并生成全局判决统计量,最终使用全局阈值完成最后的检测判决。由于所提出的两种协作宽带感知方案或需要精确地估计授权用户的信号强度和噪声方差,或感知性能不足,因而,还提出一种更易实现的方案。理论分析和仿真结果表明,本文所提出的协作感知方案可以有效地提高频谱感知性能,并且性能优于传统等增益合并方案。      

A Low Complexity High Resolution Cooperative Spectrum-Sensing Scheme for Cognitive Radios

Conventional distributed cognitive radio (CR) communication aims to increase the sensing accuracy and reduce the detection time by allowing the CR users to operate in the same frequency band in a cooperative fashion and by forming efficient decision making. In this paper, we propose a spectrum-sensing scheme which provides accurate detection at low complexity, by assigning different sensing tasks to the CRs. If the number of cooperative CRs is N, our method offers an effective sensing resolution of N times higher than that of the conventional method. An inherently low complex progressive decimation filter bank, which provides variable sensing resolutions by software reconfiguration, is employed at each CR. The design example shows that the hardware complexity of our sensing scheme is 41.3% less than that of the conventional spectrum sensor. It is also shown that the proposed system can support multiple communication standards.     

基于信干比的认知无线电自适应功率控制算法

该文以空时编码(STBC) MC-CDMA网络系统为认知无线电通信平台,将一种基于SIR的非合作功率控制博弈算法应用于该认知无线电系统,并根据用户的SIR需求差异,对算法改进设计出新的自适应功率控制博弈算法(CR-NCPCG)。仿真结果表明CR-NCPCG算法以不同用户SIR需求为前提,通过不同用户功率的有效控制,实现了用户公平共享频谱资源的需求。     

Edge-Fitting Based Energy Detection for Cognitive Radios

Two well-known drawbacks of energy detection sensing are its poor performance at low SNR and dependency on the accurate knowledge of noise power. To overcome these challenges in the context of wideband sensing, this paper proposes a spectrum sensing algorithm, inspired from edge detection techniques used in image processing. It is an improved, detailed and extended version of the gradient based method reported earlier (Koley et al. IEEE Communications Letters 19, 391–394, 2015). It is characterized by (i) histogram based noise power estimation for dynamic threshold computation (ii) preprocessing to obtain high detection probability with fewer numbers of samples and (iii) use of edge values as decision metric. Monte Carlo simulations as well as real-time wideband-sensed data captured through a Universal Software Radio Peripheral (USRP) is used to evaluate the performance of the algorithm. Mathematical formulations for the position of “SNR wall” and detection performance at different signal bandwidths is derived. Computational complexity of the edge-fitting scheme is shown to be lower than some of the wavelet approaches.     

Cooperative Spectrum Sensing with Adaptive Node Selection for Cognitive Radio Networks

In cooperative spectrum sensing, secondary users can cooperate based on their local sensing observations so as to detect primary signals in a more reliable manner. However, because of the low strength of received primary signals, observations from some secondary users may contribute little to global decisions at the fusion center. To reduce energy consumption and sensing overhead, cooperation is recommended only with a subset of nodes receiving high-strength primary signals. This paper proposes a selection probability based cooperative spectrum sensing scheme that exploits historical observations to exclude nodes receiving low-strength primary signals. The selection probability is maintained based on local sensing information and global decisions. Simulation results demonstrate that the proposed scheme can exploit location advantages and shows almost the same detection performance as cooperative spectrum sensing with accurate node selection.     

Adaptive Path Selection Scheme with Combining for Multiple Relaying Cooperative Communications Networks

In future communications, cooperative communications with relay networks will be one of the most effective schemes to enlarge the coverage area and to boost the data rate. In the recent research results, the path selection, power allocation, and relay protocols on relay networks are the most important factors to improve the system performance. However, the channel quality of the direct transmission path and the relaying path has an influential effect on the performance of relay networks. Therefore, in this paper, we propose a best relaying path selection (BRPS) scheme to obtain the path diversity to improve the system capacity and data rate for cooperative networks (CNs). Simulation results show that the more the relay nodes are selected, the lower the bit error rate (BER) is. The proposed BRPS scheme obtains a high concession between both BER and system capacity for CNs.     

Dynamic Channel Selection for Cognitive Radios with Heterogenous Primary Bands

Technological advances coupled with regulatory initiative for more efficient utilization of radio spectrum resulted in the introduction of dynamic spectrum access enabled radio called Cognitive Radio (CR). A CR network is allowed to access a frequency band owned by primary user, which can provide higher throughput and better serviceability in wireless networks. The availability of multiple primary bands requires a CR network to select the best operating band which can maximize the total system performance. The selection should be made according to heterogenous properties of primary bands which offer different maximum data rate for secondary use and generate diverse traffic pattern. In this paper, assuming such heterogenous primary bands for secondary use, simple and distributed dynamic channel selection strategies are proposed and evaluated. In addition, we introduce a measurement metric for interference experienced by primary users due to secondary network’s access in primary band. We investigate the impact of different channel selection strategies and parameters on the primary and secondary performance.

Low-Complexity Adaptive Transmission for Cognitive Radios in Dynamic Spectrum Access Networks

Cognitive radios that are employed in a network with dynamic frequency assignments must operate efficiently in the presence of uncertainties and variations in the propagation characteristics of the network's communication links. A low-complexity adaptive transmission protocol is described and evaluated for use in cognitive radio networks whose links have unknown and possibly time-varying propagation losses as a result of such phenomena as slow fading or variations in shadowing. The cognitive radios are required to derive only simple statistics in the receivers in order to provide the information that is needed by our protocol; no estimates or measurements of received power or channel gain are used. The protocol's primary mechanism for responding to changes in propagation loss is to adjust the modulation and coding. Because of disruptions that can be caused by higher levels of interference to other radios in the network, the transmitter power is increased only if the most powerful combination of coding and modulation is inadequate. We employ finite-state Markov models for slowly varying channels, and we demonstrate that for such channels our protocol performs nearly as well as an ideal protocol that is told the exact value of the propagation loss for each packet transmission. Thus, the additional complexity that is required to enable cognitive radios to obtain precise channel-gain estimates is not justified and would lead to only negligible improvement in throughput. The throughput of our adaptive transmission protocol is compared with an upper bound that is derived from information theory for a hypothetical ideal protocol that is given perfect channel-state information, and some preliminary results on learning the adaptation decision intervals are included.     

Adaptive Decode-and-Forward Protocol Based Cooperative Spectrum Sensing in Cognitive Radio with Interference at the Secondary Users

In this paper a novel multiple-user cooperative spectrum sensing scheme (MCSS) based on hybrid relay is proposed to achieve the spatial diversity gain in detection of the primary user (PU) in a cognitive radio (CR) network. A practically important case where co-channel interference signals are present at the network is considered for the analysis. Closed-form expressions of detection probability \((\hbox {P}_{\mathrm{d}})\) and false alarm probability \((\alpha )\) for the proposed adaptive decode-and-forward based multiple-user cooperative spectrum sensing scheme (ADF-MCSS) using energy detector over Rayleigh fading sensing channels is derived in presence of co-channel interference at the secondary user which is far away from the PU. Further we extend the concept of two user amplify-and-forward (AF) and decode-and-forward (DF) cooperative spectrum sensing schemes in multiple-user scenario (i.e. AF-MCSS and DF-MCSS) over Rayleigh fading channels when the secondary user (which is far away from PU) is affected by interference. Closed-form expressions of AF-MCSS and DF-MCSS schemes over a Rayleigh fading channels are also evaluated and compared with that of proposed ADF-MCSS in presence of interference signals at the secondary user. Further the performance analysis of AF-MCSS, DF-MCSS and ADF-MCSS schemes are compared with the existing non-cooperative spectrum sensing schemes in presence of interference at the secondary user. Our analysis is validated by numerical and simulation results for multiple-user CR network. The impact of number of cooperative relays, SNR in sensing channel, energy of interference signal, false alarm on detection probability in proposed ADF, AF and DF schemes is shown.     

对协作系统自适应角色选择策略的思考

在传统协作系统基础上提出了一种新颖的自适应协作方式——机会角色选择协作.为进一步说明该策略,构建了一种最基本的两用户机会协作框架,其中两个用户相互竞争将各自信息发送给同一目的端.根据瞬时信道条件,两用户均可以机会地充当信息源角色,而另一用户将作为放大转发中继来为信源服务.同时,在此基础上提出并简要描述了一种最优的中心化角色选择策略(C-ROSE).该策略能够最大化目的端接收信噪比(SNR),进而提高系统传输性能.研究表明,通过这种动态、灵活、高效的节点角色分配方式,协作系统的传输可靠性可得到进一步增强,从而为构建稳固、高效、互惠的协作传输体系开辟了新道路.     

A Statistical Method for Reconfiguration of Cognitive Radios

Recent developments in computer technology have enabled radio developers to accomplish in software what traditionally was performed with application-specific integrated circuits. A radio that has the core of its functionality implemented in software is called a software-defined radio. When an SDR has the capability to sense, reason, and dynamically adapt to requirements and environmental change, we call this more capable device a cognitive radio. Many private and public agencies are investing in the promise of CR to improve the utilization of radio frequency spectrum. They envision devices that can sense frequency vacancies and dynamically reconfigure to utilize idle channels. The promise of CR depends on the capability of a radio to change operating frequencies, power, and/or modulation schemes (physical layer flexibility). In addition to this physical layer flexibility, there are a large number of opportunities to capitalize on the interplay of the CR physical layer configuration and other parameters in the radio network protocol stack. At the core of CR functionality is the ability to select from thousands of potential configurations to maximize performance-be it in terms of spectrum use, throughput, or reliability. In this article, we describe a method for selecting from a number of potential configurations to fulfill the communication requirements of a CR network. By using accepted statistical methods, we show how parameters at the physical, data link, network, and application layers interact to affect performance. We build upon this parametric insight with our presentation of a technique for predicting radio performance.     

一种基于非对称纳什协商的认知无线电频谱共享新算法

该文研究基于MIMO-OFDMA的认知无线电系统频谱共享的新机制。首先构造了一个基于非对称纳什协商方案的效能函数,其次通过多用户最优匹配及两两协商新算法并证明其收敛性,最终实现了基于感知贡献加权的比例公平性频谱共享。仿真结果表明提出的方案不仅实现了频谱资源的公平有效分配,而且有利于最大化频谱感知的结果。     

Cooperative Spectrum Sensing with Censoring of Improved Energy Detector Based Cognitive Radios in Rayleigh Faded Channel

In this paper, the performance of cooperative spectrum sensing (CSS) with censoring of cognitive radio (CR) users under several schemes of fusions at fusion center (FC) has been assessed in the presence of Rayleigh fading. Improved energy detector (IED) with multiple antennas has been used at each CR user. The CR users utilize selection combining (SC) of the decision statistics obtained by IEDs with multiple antennas for making hard decisions about PU and transmit the decisions to the FC using BPSK if the CR user is selected to transmit. Censoring of CR users has been considered based on quality of the reporting channels between CRs and a fusion center (FC). A training based channel estimator is used at FC to estimate the fading coefficients characterizing the channels between the CR users and The FC. Several types of fusion rules such as OR-logic, AND-logic, majority-logic and maximal ratio combining (MRC) fusion rules are considered at the FC for estimating the performance in terms of missed detection (Q _m ), total error (Q _m  + Q _f ) and proposed weighted total error probabilities. Performance of CSS in terms of missed detection is evaluated for various values of IED parameter (p) and number of antennas (M) at each CR. The performance in terms of total error probability has also been estimated for several values of normalized detection thresholds, sensing and reporting channel SNRs under both perfect and imperfect channel estimation. Performance comparison amongst the fusion rules have also been presented under both perfect and imperfect channel estimation under different channel and network conditions.     

Spectrum Sensing Based on Deep Learning Classification for Cognitive Radios

Spectrum sensing is a key technology for cognitive radios.We present spectrum sensing as a classification problem and propose a sensing method based on deep learning classification.We normalize the received signal power to overcome the effects of noise power uncertainty.We train the model with as many types of signals as possible as well as noise data to enable the trained network model to adapt to untrained new signals.We also use transfer learning strategies to improve the performance for real-world signals.Extensive experiments are conducted to evaluate the performance of this method.The simulation results show that the proposed method performs better than two traditional spectrum sensing methods,i.e.,maximum-minimum eigenvalue ratio-based method and frequency domain entropy-based method.In addition,the experimental results of the new untrained signal types show that our method can adapt to the detection of these new signals.Furthermore,the real-world signal detection experiment results show that the detection performance can be further improved by transfer learning.Finally,experiments under colored noise show that our proposed method has superior detection performance under colored noise,while the traditional methods have a significant performance degradation,which further validate the superiority of our method.     

基于分布式中继选择的自适应协作传输方案

协作分集通过使网络用户共享彼此天线以形成虚拟多天线阵列,可以显著提高网络容量,然而针对网络拓扑的动态变化与无线传输的时变特性,仅靠协作分集并不能十分有效地解决这些问题,必须结合考虑相应的自适应传输策略.本文提出动态网络环境中协作中继的最佳选择准则,在此基础上给出最佳协作中继的分布式选择协议.根据协作中继与源节点间的无线信道质量,进一步提出一种自适应协作传输方案,以有效抵抗多用户网络环境中的无线衰落.此外,对自适应协作传输方案的误码性能,在瑞利衰落信道下进行相应的理论分析,得到了系统误比特率的解析表达式,据此给出数值仿真实验以进行性能比较.结果表明:相对于传统协作分集而言,本文提出的自适应协作传输方案获得了进一步的性能增益,误比特率显著下降.     

基于译码——转发的多中继协作节点选择方法

由于协作通信技术能够抵抗信道衰落的影响,提供分集增益,成为目前研究热点之一。针对传统多中继译码转发协作通信中,所有潜在中继均参与协作从而导致系统的低资源利用率问题,提出了一种基于信道容量增益的中继节点选择策略。仿真结果表明,该策略只需选择一半的中继节点数就能获得和最优中继选择方法非常相近的系统性能,同时降低了系统的功率损耗和实现复杂度。     

基于多维资源自适应分配的协作认知传输机制

该文针对协作认知无线电网络提出一种时域、频域和空域资源联合分配的传输机制,在改善授权用户传输性能的前提下使参与协作的认知用户获得合理的回报。所提机制利用多天线认知节点担任中继,通过自适应的时隙划分与带宽分配,对两跳传输链路中的瓶颈予以消除;并在包含多个协作认知用户的场景中,给出一种考虑公平性的中继选择算法。该方法一方面采用比例公平的思想实现认知用户间的公平性,另一方面通过调整奖励因子,使中继获得合理的回报。仿真结果表明,所提算法能够改善授权与认知系统的数据速率,同时给予认知中继公平的回报。