一种改进的认知无线电频谱接入策略

认知无线电（Cognitive Radio）网络中,次用户在不干扰主用户的情况下即时接入检测到的空闲频谱以提高频谱资源的利用率。基于部分可观测马尔科夫决策过程的最优频谱接入算法计算复杂度较高,而基于贪婪算法的次优接入策略具有自私性,都不能有效的提高频谱利用率。本文提出一种新的频谱接入算法,该算法对贪婪算法的自私性进行了改进。由于贪婪算法只关注信道当前时隙的瞬时奖励值,导致最大奖励值相同的信道可能会有多个,因此给瞬时奖励值加上这些信道下一时隙的奖励值后重新选择,直至次用户选择出奖励值最大的一个信道。仿真结果表明,相比于传统的贪婪算法,改进算法虽然增加了一些计算复杂度,但有效提高了系统的吞吐量。     

认知引擎中决策方法的研究

认知无线电(Cognitive Radio,CR)技术通过智能的频谱管理来解决频谱资源"短缺"问题,它能够感知到授权用户的空闲频谱,并有效地加以利用,从而减少与授权用户的冲突。现有无线电参数调整策略无法根据环境变化和用户需求进行智能调整,认知引擎中的决策方法能够解决该问题。遗传算法(Genetic Algorithm,GA)和二进制粒子群算法是实现认知引擎决策的典型算法,在对2种算法进行了介绍之后,仿真比较了2种算法在性能方面的差异。     

基于自适应决策融合的合作频谱感知方法

频谱感知是认知无线电(CR)的关键技术之一。在该机制中,对主用户(PU)信号的可靠检测是实现CR的前提。提出一种基于自适应决策融合的合作频谱感知算法用于频谱感知,该算法通过估计PU的先验概率与各个CR用户(SU)的漏检及虚警概率,然后运用Chair-Varshney准则对局部判决进行决策融合以得到全局判决。仿真结果表明,采用该方案的全局虚警和漏检概率明显低于单个SU,可有效提高CR系统频谱感知的可靠性。     

认知无线电中基于频谱聚合的频谱分配算法

为了使认知用户可成功接入分配的频谱,进一步提高频谱利用率,提出了一种基于频谱聚合的分布式频谱分配算法(SADSA),该算法以图论着色为模型,算法过程考虑了认知用户的带宽需求和认知设备的最大聚合范围,仿真结果表明了该算法在认知用户接入率方面的优越性.     

基于DRL的IRS辅助认知电视频谱资源优化

传统静态电视频谱分配方法导致大量频谱资源存在浪费,认知无线电（Cognitive Radio,CR）因通过频谱共享技术提高电视频谱利用率得到广泛关注。当前,智能反射面（Intelligent Reflecting Surface,IRS）作为一种日益流行的、高效的解决方案,可以满足更高的数据速率、更好的通信覆盖范围。基于此,研究IRS辅助认知通信系统资源优化策略问题,考虑认知用户（Secondary User,SU）通过射频（Radio Frequency,RF）能量采集技术采集绿色能源,最大化SU的平均吞吐量。将IRS辅助认知通信建模为马尔可夫决策过程（Markov Decision Process,MDP）,提出一种基于残差网络的（Double Deep Q-network,DDQN）算法联合优化IRS相移矩阵与认知发射机（Secondary Transmitter,ST）发射功率。仿真结果表明,该算法能够有效提高SU长期累积吞吐量。     

CVANET中基于POMDP模型的频谱接入算法

针对认知车载Ad Hoc网络(CVANET)信道的动态特性,以部分可观测马尔科夫决策过程(POMDP)为模型对认知车辆用户的频谱感知和频谱接入过程进行研究,提出基于POMDP模型的分布式机会频谱接入算法,并通过贪心算法降低POMDP算法计算量,最后通过仿真研究影响认知车辆用户吞吐量的主要因素,并验证算法的可行性。仿真分析结果表明,认知车辆用户通过本算法接入吞吐量得到有效提高,降低了交通中广播风暴的可能,并且降低了计算量。     

能量收集认知无线电网络下的多接入用户信息年龄研究

针对信道资源有限的多接入信道无线传感器网络场景,实时信息的传送需要考虑信道环境和信息新鲜度问题。该文基于认知无线电物联网（Cognitive Radio-Internet of Things, CR-IoT）系统,构建了一个具有频谱访问权限的主用户（Primary User, PU）和两个可共享PU频谱次用户（Secondary User, SU）的网络模型。在考虑PU工作状态和SU数据队列稳定的条件下,提出了一个以最小化节点平均AoI为目标的优化问题。其次使用两种策略进行优化,包括概率随机接入策略（Probabilistic Random Access Policy, PRA）,该策略下两个SU节点根据相应的概率分布做出独立的传输决策;以及基于李雅普诺夫优化框架优化时隙内调度决策的漂移加罚策略（Drift Plus Penalty Policy, DPP）。仿真结果可知,DPP策略下得到的平均AoI的值要明显低于PRA策略,表明使用DPP策略对平均AoI的优化更加显著,可以有效提升数据包的时效性和新鲜度。      

基于加权平均一致算法的宽带压缩频谱感知

在认知无线电(CR)网络中进行频谱共享接入,首要的任务是进行频谱感知,并发现频谱空洞。基于认知无线网络中信号频域的固有稀疏性,本文结合了压缩感知(CS)技术与加权平均一致(weighted average consensus)算法,建立了分布式宽带压缩频谱感知模型。频谱感知分为两个阶段,在感知阶段,各个CR节点对接收到的主用户信号进行压缩采样以减少对宽带信号采样的开销和复杂度,并做出本地频谱估计;在信息融合阶段,各CR节点的本地频谱估计结果以分布式的方式进行信息融合,并得到最终的频谱估计结果,获得分集增益。仿真结果表明,结合压缩感知与加权平均一致算法增强了频谱感知的性能,比在相同的CR网络中使用平均一致算法时有了性能上的提升。      

认知无线电中的频谱共享技术

认知无线电（cognitive radio,CR）具有动态重用空闲频谱资源的能力,可以有效提高频谱利用率,是一种智能的频谱共享技术。文章给出了一种频谱共享的过程,阐述了频谱共享各个步骤包括频谱感知、频谱分配、频谱接入和频谱移动的概念、功能和研究现状,分析了频谱共享的关键技术,重点介绍了其中的频谱池策略、频谱分配算法和功率控制算法。     

基于OFDM协作中继的机会主义频谱共享协议及其最优资源分配

提出了一种基于OFDM协作中继的机会主义频谱共享协议。当主用户信道不好,不能达到其要求速率时,如果认知用户能够协作帮助主用户达到其要求速率,则该认知用户就可以以协作的方式接入主用户的频谱。在该接入方式中,认知用户利用接入频谱中的一部分子载波放大转发主用户的信息,帮助主用户达到其要求速率。然后可以利用剩余的子载波发送自己的信息。对这种接入方式中的资源分配进行了分析,利用对偶算法,提出了一种以最大化认知用户速率,保证主用户速率达到要求速率为原则的最优资源分配算法。如果认知用户不能够协作帮助主用户达到要求速率,为了有效地利用频谱资源,认知用户以非协作的方式接入主用户的频谱,利用接入的全部频谱来发送自己的信息。仿真结果验证了所提频谱共享协议的有效性,同时说明了主用户和认知用户都能够从该协议中获得好处。     

协作频谱感知在认知网络中的应用

认知无线电能够灵敏感知周围环境的变化,通过频谱感知功能发现频谱空洞,使得认知无线电能够与周围通信环境相适应。在认知无线电网络中,认知用户（次用户）必须连续地监控频谱,检测主用户是否存在。如果主用户存在,次用户必须尽快地退出该频段,从而不影响主用户。在文中采用一种协作机制,即两用户进行协作频谱感知,从而提高主用户的检测率,减少了检测时间,并且得到捷变增益。我们用Matlab给出仿真结果。     

On co-channel and adjacent channel interference mitigation in cognitive radio networks

Cognitive radio (CR) is an emerging wireless communications paradigm of sharing spectrum among licensed (or, primary) and unlicensed (or, CR) users. In CR networks, interference mitigation is crucial not only for primary user protection, but also for the quality of service of CR user themselves. In this paper, we consider the problem of interference mitigation via channel assignment and power allocation for CR users. A cross-layer optimization framework for minimizing both co-channel and adjacent channel interference is developed; the latter has been shown to have considerable impact in practical systems. Cooperative spectrum sensing, opportunistic spectrum access, channel assignment, and power allocation are considered in the problem formulation. We propose a reformulation–linearization technique (RLT) based centralized algorithm, as well as a distributed greedy algorithm that uses local information for near-optimal solutions. Both algorithms are evaluated with simulations and are shown quite effective for mitigating both types of interference and achieving high CR network capacity.     

基于稳定匹配的认知无线网络协作物理层安全机制

在Underlay认知无线网络中,次用户被允许在主用户进行数据发送时接入主用户的频谱.此时,主用户将对次用户和窃听者造成干扰.利用协作干扰技术,主用户产生的干扰可以被用来改善次用户的物理层安全.基于此,本文针对包含多个主次用户的Underlay认知无线网络,提出了一种新的协作物理层安全机制.为了在保证主用户通信质量的前提下,最大化网络中次用户的总的安全容量,该机制将对次用户进行合理的频谱接入选择和功率控制.另外,考虑到个体理性和自私性对于频谱接入稳定性的影响,该机制利用稳定匹配理论将频谱接入选择问题建模为一对一的双边匹配问题,通过构建主次用户之间的稳定匹配来保证频谱接入的稳定性.仿真结果表明,使用本文所提安全机制,可以在保证主用户通信质量的前提下,稳定而又有效地改善网络中次用户获得的总的安全容量.     

A Cluster-Based MAC Protocol for Cognitive Radio Ad Hoc Networks

The cognitive radio (CR) technology is an efficient approach to share the spectrum. But how to access the idle channels effectively is a challenging problem. To solve this problem, we propose a MAC protocol for cluster-based CR ad hoc networks, with the aim of making cluster structure more robust to the primary users’ channel re-occupancy activities, so that the CR users can use the idle spectrum more efficiently. Under this framework, a cluster formation algorithm based on available channels, geographical position and experienced statistics is proposed to maximize the network throughput and maintain the cluster topology stability. The schemes for new CR user joining a cluster and cluster maintenance are also designed. An experience database is proposed to store the experienced statistics which are obtained from spectrum occupancy history. Such a database can be used to support the acts of nodes, such as neighbor discovery and cluster forming. Simulation results reveal that our proposed framework not only outperforms conventional CR MAC protocols in terms of throughput and packet delay, but also generates a smaller number of clusters and has more stable cluster structure with less reclustering time.     

Dynamic cooperator selection in cognitive radio networks

The primary objective of cooperation in cognitive radio (CR) networks is to increase the spectrum access efficiency and improve the network performance. However, Byzantine adversaries or unintentional erroneous conduct in cooperation can lead to destructive behavior of CR users that can decrease their own and others’ performances. This work presents a dynamic solution for cooperation reliability in conditions with constraints typical for a CR network. Specifically, in CR networks, the information on the success of cooperation can be limited only to cases with interference; when malicious, cooperators can be completely non-correlated and can alter behavior; and the set of available cooperators can dynamically change in time. In order to face these challenges, each CR user autonomously decides with whom to cooperate by learning cooperators behavior with a reinforcement learning (RL) algorithm. This RL algorithm determines the suitability of the available cooperators, and selects the most appropriate ones to cooperate with the objective to increase the efficiency of spectrum access in CR networks. The simulation results demonstrate the learning capabilities of the proposed solution and especially its reliable behavior under highly unreliable conditions.     

A Multiagent Based Scheme for Unlicensed Spectrum Access in CR Networks

In recent wireless network domains static spectrum access is a major concern. Generally, this access leads to spectrum scarcity problem by creating empty holes or white spaces. However, the scarcity is temporary and can be alleviated if spectrum access is performed dynamically and efficiently. One important step towards dynamic spectrum access is the development of cognitive radio (CR) technology, which senses nearby spectrum portions (or bands) and tries to use them either opportunistically or by negotiating with the neighboring users. Nonetheless, dynamic spectrum access raises several challenges which need to be addressed in detail. These challenges include efficient allocation of spectrum for users in order to maximize spectrum utilization and to avoid user level conflicts both under licensed and unlicensed bands. In this paper, considering the relative rarity of solutions for unlicensed spectrum access and their inadequacy, we propose a scheme, where the CR devices (equipped with agents) interact with their neighbors to form several coalitions over the unlicensed bands. These types of coalitions can provide a less-conflicted access as the agents mutually agree for spectrum sharing and they allow other CR users to enter in their vicinity of acquired spectrum via bilateral message exchanges. Further, we present continuous time Markov chains to model the spectrum access process in continuous time and derive important performance metric as the blocking probability for without and with queuing systems. Amongst others, the important comparisons we made between analytical and simulation results in terms of blocking probability verify that our proposed model is correct. In essence, our proposed solution aims to increase dynamic spectrum usage by enabling cooperation between the users.     

紫外Ad hoc网络中基于历史的动态公平性避退算法

本文把UV通信与Ad hoc网络相结合,利用Ad hoc网络的多跳特性来克服UV通信距离有限的弱点。为了使UV Ad hoc网络中的各个节点能够公平有效的接入信道,本文在二进制指数退避（Binary Exponential Backoff,BEB）算法的基础上,以提高公平性为目的,提出了一种基于历史的动态公平性避退算法（Uistory-Based Dynamic Fairness Backoff,HDFB）来改善节点接入信道的公平性。仿真结果表明：新算法能有效地改善信道接入的不公平性。     

Optimization of spectrum utilization in cognitive radio system

In Cognitive Radio (CR) networks, CR user has to detect the spectrum channel periodically to make sure that the channel is idle during data transmission frame in order to avoid the collisions to the primary users. Hence recent research has been focused on the interference avoidance problem. Quality of Service (QoS) requirement of CR user will affect the time of data transmission in each frame. In this paper, in order to solve the interference avoidance and spectrum utilization problems without cooperation among CR users, a new scheme to obtain the optimal duration of data transmission frame is proposed to maximize the spectrum utilization and guarantee the protection to the primary users. The main advantages of our proposed scheme include the followings: (1) QoS requirement of CR user is concerned; (2) p-persistent Media Access Control (MAC) random access is used to avoid the collisions among CR users; (3) CR network system capacity is considered. We develop a Markov chain of the primary spectrum channel states and an exponential distribution of the CR user??s traffic model to analyze the performance of our proposed scheme. Computer simulation shows that there is an optimal data transmission time to maximize the spectrum utilization. However, the regulatory constraint of the collision rate to the primary users has to be satisfied at the expense of spectrum utilization. And also the tradeoff between the spectrum utilization and the capacity of the CR system is taken into account.     

无人机短包通信中基于NOMA传输的安全性能分析

针对物联网（IoT）通信的低延时需求,为了保证数据传输的灵活性,本文构建一种基于短包传输的无人机（UAV）通信网络。由于非正交多址接入（NOMA）技术能够增加可服务的地面用户数量,故将该技术应用到无人机短包通信（UAV-SPC）系统中可以解决多用户的安全传输问题。与正交多址（OMA）技术相比,NOMA可有效提高用户接入公平性和频谱利用率,因此被广泛用于下行链路的通信传输。为解决复杂的安全传输问题,首先证明在功率和译码错误率约束的条件下,分别存在最优的功率分配,数据传输包长和系统传输比特数使目标用户的平均安全吞吐量最大。在此基础上,通过本文所提算法得到安全传输问题的优化解。实验结果验证了该算法的稳定性和可行性。此外,与基准方案相比,本文所提方案可有效降低短包传输的通信时延,提高系统中目标用户的平均安全吞吐量。