认知网络下TCP协议性能分析

首先在无线环境下的基础上搭建认知平台,当主用户想要占次用户信道时,通过基站的频谱监测,频谱分配,分配次用户到其他空闲信道继续通信.其次,在此平台下分析TCP Reno,TCP Newreno,TCP Sackl和TCP vegas协议的性能,包括拥塞窗口、吞吐量.最后定量分析主用户活跃程度、切换后信道带宽和信道误比特率...     

Prediction based channel allocation performance for cognitive radio

The interdependency, in a cognitive radio (CR) network, of spectrum sensing, occupancy modelling, channel switching and secondary user (SU) performance, is investigated. Achievable SU data throughput and primary user (PU) disruption rate have been examined for both theoretical test data as well as data obtained from real-world spectrum measurements done in Pretoria, South Africa. A channel switching simulator was developed to investigate SU performance, where a hidden Markov model (HMM) was employed to model and predict PU behaviour, from which proactive channel allocations could be made. Results show that CR performance may be improved if PU behaviour is accurately modelled, since accurate prediction allows the SU to make proactive channel switching decisions. It is further shown that a trade-off may exist between achievable SU throughput and average PU disruption rate. When using the prediction model, significant performance improvements, particularly under heavy traffic density conditions, of up to double the SU throughput and half the PU disruption rate were observed. Results obtained from a measurement campaign were comparable with those obtained from theoretical occupancy data, with an average similarity score of 95% for prediction accuracy, 90% for SU throughput and 70% for PU disruption rate.     

Joint optimisation of transmission and waiting times in cognitive radio

Transmission time optimisation is one of the key considerations of cognitive network design. There are many studies in cognitive radio networks (CRNs) focusing on finding the best transmission time for secondary users (SUs) to maximise transmission or energy efficiency. While longer sensing duration leads to a higher sensing accuracy and causes less interference, the SU spends less time for transmission and more energy on sensing spectrum. On the other hand, when the transmission duration becomes longer, although the SU has more opportunities to access the channel, it may encounter higher interference due to primary user (PU) returns and the probability of collision becomes higher. In this article, in a decentralised slotted protocol for CRN, the SU spectrum access is proved as a renewal process, then the interference due to PU return during SU transmission, the missed opportunities due to waiting for the channel to become idle and the energy consumed by the SU in the whole spectrum access process including idling energy, transmission energy and sensing energy consumption are formulated and integrated into newly defined efficiency to obtain the optimum transmission time and waiting time.     

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.     

感知频谱共享下的多天线功率优化分配算法研究

本文构建了一种在感知结果下具有多天线次用户的频谱共享模型,该模型由单入单出主用户对和多入单出认知用户对构成。当认知用户感知到主用户占用信道时,主用户向认知用户发送Message信息,使得认知用户发射端能够得知主用户对干扰总功率的限制要求,通过自适应地调整认知用户发射机的发射功率,以保证其对主用户不造成有害干扰;如果主用户未占用信道,认知用户立刻以最大发射功率占用信道。并分别在主用户存在和不存在两种情况下,优化认知用户发射机各天线的发射功率来最大化系统总的数据传输率。最后,通过数值仿真来验证推导出的功率分配策略,并对其进行分析和讨论。仿真结果表明:相比于机会频谱接入（Opportunistic Spectrum Access, OSA）和基于感知的频谱共享（Sensing-based spectrum sensing）模式,推导的功率分配策略在提出的模型中可以获得更高的信息传输率。      

Adaptive code symbol assignment in a rateless coded multichannel cognitive radio network

Because of its robustness to packet loss and adaptivity to channel conditions, rateless codes have been used in cognitive radio networks to improve the secondary system performance. In this paper, we investigate an adaptive code symbol assignment scheme for the secondary user (SU) in a multichannel cognitive radio network based on rateless coding. In particular, the SU transmitter first encodes its information data through rateless coding and then assigns the unceasingly generated code symbols adaptively to each available channel obtained by spectrum sensing. Thanks to the forward incremental redundancy provided by rateless codes, it is unnecessary for the SU receiver to request the retransmission of lost symbols and the code symbols collected from any channel at any time contribute to the final data recovery. With an alternating channel occupancy model of the primary user (PU), we conduct a weight enumerator analysis to derive the optimal number of code symbols to be assigned to each available channel, thus to maximize the system throughput while protecting PU from interference. Both theoretical analysis and numerical results demonstrate the good performance of our proposed scheme. Copyright © 2012 John Wiley & Sons, Ltd.     

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.     

Improving CSMA/CA network performance under hidden collision

Dynamic spectrum access policy allows a secondary user (SU) to access a primary user (PU) channel when it is idle. However, the idle state may result from the PU's silent activities, which can be wrongly perceived as an opportunity for the SU to access the channel and lead to “hidden collision” when it effectively tries to access the channel under this condition. At best of our knowledge, this issue has yet to be addressed in the literature. In this paper, we will first define a three‐state model that describes hidden collision conditions, then propose a probabilistic model in which a transient state is added to force the SU to wait a certain period of time before accessing the channel, thereby translating into better protection for the PU. Based on this model and using Carrier Sense Multiple Access/Collision Avoidance protocol, we will evaluate the PU's and SU's throughput and delay with and without transient state as well as the gain in using our approach. Our computation results show a substantial improvement of the PU's throughput from 19.6 to 61.1%.     

认知无线电中认知用户的重新建模与性能分析

针对认知网络频谱接入问题,讨论了以往建模和理论分析中存在的不足.为了真实地模拟授权用户和认知用户的行为,对频谱接入策略重新进行建模,并利用矩阵几何法和离散事件系统仿真的事件调度法重新评估和比较了不同接入策略下的认知系统性能,针对不同业务类型选取最佳接入策略.理论分析和仿真实验结果一致,验证了所提模型的可靠性.频谱切换和信道预留接入策略增大了阻塞率并有效地降低了掉话率,后者通过调整预留信道数目使认知系统吞吐量最大.     

认知网络中的能量回收技术：性能分析及优化设计

通信网络中有限的能源和频带资源限制了网络容量的进一步提升.对能量回收技术在认知网络中的应用进行研究,量化评估用户可回收的能量以及可达吞吐率,并进行优化设计很有必要.在所分析的系统中,当授权用户进行通信时,非授权用户可回收无线信号中所带有的能量,并利用回收的能量进行频谱检测;当检测到授权用户空闲时,非授权用户将接入频谱,利用回收到的能量进行数据传输.采用马尔科夫链模型对通信场景进行描述分析,发现授权用户的活跃程度对非授权用户可回收的能量、获得的传输机会带来影响,进而决定了非授权用户的可达吞吐量.在此基础上,提出一种通过控制授权用户业务量,以最大化网络能量效用和频谱效用的优化方案,并通过仿真证实了理论分析的正确性.     

Adaptive dual‐radio spectrum‐sensing scheme in cognitive radio networks

In this paper, a novel spectrum‐sensing scheme, called adaptive dual‐radio spectrum‐sensing scheme (ADRSS), is proposed for cognitive radio networks. In ADRSS, each secondary user (SU) is equipped with a dual radio. During the data transmission, with the received signal‐to‐noise ratio of primary user (PU) signal, the SU transmitter (SUT) and the SU receiver (SUR) are selected adaptively to sense one channel by one radio while communicating with each other by the other one. The sensing results of the SUR are sent to the SUT through feedback channels (e.g., ACK). After that, with the sensing results from the SUT or the SUR, the SUT can decide whether the channel switching should be carried out. The theoretical analysis and simulation results indicate that the normalized channel efficiency, defined as the expected ratio of time duration without interference to PUs in data transmission to the whole frame length, can be improved while satisfying the interference constraint to PUs. After that, an enhanced ADRSS is designed by integrating ADRSS with cooperative spectrum sensing, and the performance of ADRSS under imperfect feedback channel is also discussed. Copyright © 2011 John Wiley & Sons, Ltd.     

数据驱动的开放动态频谱接入系统构建方法

在认知无线电(CR)背景下,动态频谱接入已成为提高无线网络频谱利用率的重要途径。基于全球移动通信系统-铁路(GSM-R)系统中采集的细粒度频谱监测数据,提出一种数据驱动的深度学习方法,建模频谱模式,并建立一套动态频谱接入访问框架。采用一种深度频谱生成模型指导频谱分配;设计一种综合递归序列表征与场景特征嵌入的深度网络,建模和预测短时频谱占用情况,并由此提出一种动态信道接入策略。进一步,利用软件无线电(SDR)平台实现一套跳频系统,并将其与动态频谱接入策略进行集成。使用真实的历史频谱数据评估该系统的数据吞吐能力,测试结果表明,所提方法及构建的跳频系统能有效提高机会通信能力,高效利用频谱资源。该频谱接入框架及SDR系统实现具有较强的通用性,易于集成到不同场景和频段的系统中。     

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。      

Optimizing the Use of Random Access Channels in GSM-GPRS

The random access channels and traffic channels are utilized, respectively, for call establishment and information transmission in the uplink direction (from mobile to base station) of the Global System for Mobile communications (GSM) networks. A call is either rejected or blocked depending on its inability to succeed either in the random access channels or in the traffic channels. The optimum number of random access slots is directly proportional to the average call arrival rate, being independent of the average channel holding time and the number of traffic channels. The number of slots occupied by a given call can be changed dynamically in the newly developed General Packet Radio Service (GPRS) systems. A complete analysis is executed for the traffic channel utilization and call blocking probability with the exact number of random access slots that provide almost zero call rejection probability. The overall call success probability is derived considering call rejection and call blocking probabilities.     

Ergodic capacity and outage probability optimization for secondary user in cognitive radio networks under interference outage constraint

This paper considers a cognitive radio network where a secondary user (SU) coexists with a primary user (PU). The interference outage constraint is applied to protect the primary transmission. The power allocation problem to jointly maximize the ergodic capacity and minimize the outage probability of the SU, subject to the average transmit power constraint and the interference outage constraint, is studied. Suppose that the perfect knowledge of the instantaneous channel state information (CSI) of the interference link between the SU transmitter and the PU receiver is available at the SU, the optimal power allocation strategy is then proposed. Additionally, to manage more practical situations, we further assume only the interference link channel distribution is known and derive the corresponding optimal power allocation strategy. Extensive simulation results are given to verify the effectiveness of the proposed strategies. It is shown that the proposed strategies achieve high ergodic capacity and low outage probability simultaneously, whereas optimizing the ergodic capacity (or outage probability) only leads to much higher outage probability (or lower ergodic capacity). It is also shown that the SU performance is not degraded due to partial knowledge of the interference link CSI if tight transmit power constraint is applied.     

Efficient Spectrum Handoff Using Hybrid Priority Queuing Model in Cognitive Radio Networks

Wireless Personal Communications - Cognitive radio networks can achieve high spectrum efficiency through dynamic spectrum allocation to the secondary users (SU) by way of using primary user (PU)...     

Optimal Transmission Strategies for Dynamic Spectrum Access in Cognitive Radio Networks

Cognitive radio offers a promising technology to mitigate spectrum shortage in wireless communications. It enables secondary users (SUs) to opportunistically access low-occupancy primary spectral bands as long as their negative effect on the primary user (PU) access is constrained. This PU protection requirement is particularly challenging for multiple SUs over a wide geographical area. In this paper, we study the fundamental performance limit on the throughput of cognitive radio networks under the PU packet collision constraint. With perfect sensing, we develop an optimum spectrum access strategy under generic PU traffic patterns. Without perfect sensing, we quantify the impact of missed detection and false alarm, and propose a modified threshold-based spectrum access strategy that achieves close-to-optimal performance. Moreover, we develop and evaluate a distributed access scheme that enables multiple SUs to collectively protect the PU while adapting to behavioral changes in PU usage patterns. Our results provide useful insight on the trade-off between the protection of the primary user and the throughput performance of cognitive radios.     

Capacity maximization in spectrum sensing for Cognitive Radio Networks thru Outage Probability

With today's increase in the usage of wireless devices and the consequent spectrum allocation, radio spectrum is becoming scarce. In practice most of the allotted spectrum is not used for large periods of time. Cognitive radio has been proposed to exploit the presence of these unused spectrum band (called as spectrum hole). Cognitive radios perform radio environment analysis, identify the spectrum holes and operate in those holes. Several factors like fading and shadowing affects the ability of the cognitive radio to detect the primary user. The current research shows that cooperation among the cognitive users can increase the detection probability for a given probability of false alarm. We proposed the system that to have maximized the capacity in spectrum sensing for Cognitive Radio Networks thru Outage Probability for Rayleigh fading channel.     

OS-MAC: An Efficient MAC Protocol for Spectrum-Agile Wireless Networks

Wireless networks and devices have been rapidly gaining popularity over their wired counterparts. This popularity, in turn, has been generating an explosive and ever-increasing demand for, and hence creating a shortage of, the radio spectrum. Existing studies indicate that this foreseen spectrum shortage is not so much due to the scarcity of the radio spectrum, but due to the inefficiency of current spectrum access methods, thus leaving spectrum opportunities along both the time and the frequency dimensions that wireless devices can exploit. Fortunately, recent technological advances have made it possible to build software-defined radios (SDRs) which, unlike traditional radios, can switch from one frequency band to another at little or no cost. We propose a MAC protocol, called Opportunistic Spectrum MAC (OS-MAC), for wireless networks equipped with cognitive radios like SDRs. OS-MAC (1) adaptively and dynamically seeks and exploits opportunities in both licensed and unlicensed spectra and along both the time and the frequency dimensions; (2) accesses and shares spectrum among different unlicensed and licensed users; and (3) coordinates with other unlicensed users for better spectrum utilization. Using extensive simulation, OS-MAC is shown to be far more effective than current access protocols from both the network's and the user's perspectives. By comparing its performance with an Ideal-MAC protocol, OS-MAC is also shown to not only outperform current access protocols, but also achieve performance very close to that obtainable under the Ideal-MAC protocol.     

COGNITIVE RADIOS FOR DYNAMIC SPECTRUM ACCESS - An Agile Radio for Wireless Innovation

We present the details of a portable, powerful, and flexible software-defined radio development platform called the Kansas University Agile Radio (KUAR). The primary purpose of the KUAR is to enable advanced research in the areas of wireless radio networks, dynamic spectrum access, and cognitive radios. We describe the KUAR hardware implementation and software architecture and present example application of the KUAR to modulation, spectrum measurement, channel estimation, and rapid configuration and adaptation. We outline research directions enabled by the KUAR