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.     

Optimal Energy Harvesting-based Weighed Cooperative Spectrum Sensing in Cognitive Radio Network

In cognitive radio (CR) network, to improve spectrum sensing performance to primary user (PU) and decrease energy wastage of secondary user (SU) in cooperative spectrum sensing, an energy harvesting-based weighed cooperative spectrum sensing is proposed in this paper. The SU harvests the radio frequency (RF) energy of the PU signal and then converts the RF energy into the electric energy to supply the power used for energy detection and cooperation. The time switching model and power splitting model are developed to realize the notion. In the time switching model, the SU performs either spectrum sensing or energy harvesting at any time, while in the power splitting model, the received PU signal is split into two signal streams, one for spectrum sensing and the other one for energy harvesting. A joint optimization problem is formulated to maximize the spectrum access probability of the SU by jointly optimizing sensing time, number of cooperative SUs and splitting factor. The simulation results have shown that compared to the traditional cooperative spectrum sensing, the proposed energy harvesting-based weighed cooperative spectrum sensing can decrease the energy wastage obviously while guaranteeing the maximum spectrum access probability.     

Dynamic wireless spectrum access using GNU Radio and software‐defined radios

This paper presents the design, implementation, and results from a dynamic wireless spectrum access system built using GNU Radio and software‐defined radios (SDRs) as part of an undergraduate senior design project. The project involved designing and implementing a dynamic wireless spectrum access system in which the secondary user (SU) learns the unknown transmission behavior (channel occupancy and time slots) of the primary user (PU) and then opportunistically transmits during time slots and using channels when they are not being used by the PUs. The main design objective was to maximize the throughput of the SU while minimizing the interference to the PU. A transmitted signal energy detection algorithm with an adaptive threshold was employed to set the channel states as occupied or not occupied. Channel state information was used to determine the PU behavior in a deterministic manner such that the unused time slots and channels could be exploited. A channel allocation scheme for the SU is proposed using the PU channel occupancy information to calculate the channel(s) and time slots available to the SU at any given time. Simulation and physical testing of the system validate the proposed algorithms. Students' feedback affirms GNU Radio and SDRs to be an effective platform for introducing abstract mathematical communications theory concepts, such as cognitive radios and dynamic spectrum allocation, in a hands‐on manner.     

Throughput Maximization in Cognitive Radio System with Transmission Probability Scheduling and Traffic Pattern Prediction

In this paper, we propose a novel transmission probability scheduling (TPS) scheme for the opportunistic spectrum access based cognitive radio system (OSA-based CRS), in which the secondary user (SU) optimally schedules its transmission probabilities in the idle period of the primary user (PU), to maximize the throughput of the SU over a single channel when the collision probability perceived by the PU is constrained under a required threshold. Particularly, we first study the maximum achievable throughput of the SU when the proposed TPS scheme is employed under the assumption that the distribution of the PU idle period is known and the spectrum sensing is perfect. When the spectrum sensing at the SU is imperfect, we thoroughly quantify the impact of sensing errors on the SU performance with the proposed TPS scheme. Furthermore, in the situation that the traffic pattern of the PU and its parameters are unknown and the spectrum sensing is imperfect, we propose a predictor based on hidden Markov model (HMM) for the proposed TPS scheme to predict the future PU state. Extensive simulations are conducted and show that the proposed TPS scheme with the HMM-based predictor can achieve a reasonably high SU throughput under the PU collision probability constraint even when the sensing errors are severe.     

Iterative optimization of detection threshold and throughput for secondary users in multiband cognitive radio systems

In cognitive radio(CR) systems,efficient spectrum sensing ensures the secondary user(SU) to successfully access the spectrum hole.Typically,the detection problem has been considered separately from the optimization of transmission strategy.However,in practice,due to non-zero probabilities of miss detection and false alarm,the sensing phase has an impact on the throughput of SUs as well as on the transmission of primary user(PU).In this paper,using energy detection,we maximize the total throughput of SUs by ...     

采用离散小波变换的认知无线电频谱能量检测

在认知无线电系统中,频谱检测是搜索空闲信道,避免对授权用户产生有害干扰的关键环节。本文提出了一种离散小波变换与时域能量检测相结合的频谱检测方法,对SU共享的宽带信道中的窄带PU信号进行预检测。首先对接收信号进行离散小波变换,获得能够反映信道频谱变化的细节小波系数,然后以该系数作为统计量,对其进行时域能量统计计算。该方法计算量较小,容易实现,可进行多分辨率分析,能够提高检测的灵敏度;不需要被检测信号的先验知识,适用于检测各种未知信号。仿真实验对无线麦克信号和地面无线数字电视信号进行了检测,验证了该方法的正确性。      

A prediction and scheduling framework in centralized cognitive radio network for energy efficient non‐real time communication

Advent of Internet of Things led to an exponential rise in battery‐operated sensors transmitting small non‐real time (NRT) data regularly. To this end, this work proposes a framework for centralized cognitive radio network (CRN) that facilitates better spectrum utilization and low‐cost opportunistic NRT data transfer with high energy efficiency. The novelty of this framework is to incorporate Hidden Markov Model–based prediction within the traditional cognitive radio sensing‐transmission cycle. To minimize the prediction time, we design a Hardware‐based Hidden Markov Model engine (H2M2) to be used by the cognitive base station (CBS). CBS exploits the H2M2 engine over high primary user (PU) activity channels to minimize the collisions between PUs and NRT secondary users, thereby reducing the SU energy consumption. However, this is at the cost of reduced throughput. Taking this into account, we propose an Intersensing‐Prediction Time Optimization algorithm that identifies the predictable PU activity channels and maximizes the throughput within a PU interference threshold. Furthermore, to minimize the total battery consumption of all the SUs within CRN, a Battery Consumption Minimizing Scheduler is designed at the CBS that efficiently allocates the predictable PU channels to the NRT SUs. By exploiting the unutilized high PU activity channels, the proposed Centralized Scheduling, Sensing and Prediction (CSSP) framework improves the spectral efficiency of the CRN. Exhaustive performance studies show that CSSP outperforms traditional nonpredictive sensing techniques in terms of energy efficiency and interference management. Finally, through a proof of concept, we validate the ability of CSSP framework in enabling NRT communication.     

Throughput optimization using simultaneous sensing and transmission in energy harvesting cognitive radio networks

A three‐dimensional continuous‐time Markov model is proposed for an energy harvesting cognitive radio system, where each secondary user (SU) harvests energy from the ambient environment and attempts to transmit data packets on spectrum holes in an infinite queuing buffer. Unlike most previous works, the SU can perform spectrum sensing, data transmission, and energy harvesting simultaneously. We determine active probability of the SU transmitter, where the average energy consumption for both spectrum sensing and data transmission should not exceed the amount of harvested energy. Then, we formulate achievable throughput of secondary network as a convex optimization problem under average transmit and interference energy constraints. The optimal pair of controlled energy harvesting rate and data packet rate is derived for proposed model. Results indicate that no trade‐off is available among harvesting, sensing/receiving, and transmitting. The SU capability for self‐interference cancelation affects the maximum throughput. We develop this work under hybrid channels including overlay and underlay cases and propose a hybrid solution to achieve the maximum throughput. Simulation results verify that our proposed strategy outperforms the efficiency of the secondary network compared to the previous works.     

一种分布式认知MANET功率控制算法

对认知MANET的研究涉及到许多方面,其中认知MANET中的功率控制算法设计是目前的一个研究热点.为了实现认知MANET中的次用户网络和主用户网络频谱共享,从而提高频谱利用率,即次用户网络中的次用户可以机会接入授权主用户所在的频谱,且同时保证主用户和次用户的QoS需求.本文认知MANET中功率控制的目的就是在满足QoS...     

基于时间估计的动态频谱接入算法

基于先验知识模型,设计了基于信道剩余空闲时间估计的动态频谱接入算法：每个次用户根据感知历史维护信道剩余空闲时间的估计向量并周期进行更新,每个时隙开始时次用户选择剩余空闲时间估计最大的信道接入。对动态频谱接入算法的适应性问题进行了分析,并求得了次用户的最优传输时间长度。仿真结果表明,在给定的参数下,新算法的信道利用率比其他算法提高约5%-10%,同时对主用户的干扰保持最低。     

Analysis of secondary user performance in cognitive radio networks with reactive spectrum handoff

Cognitive radio networks use dynamic spectrum access of secondary users (SUs) to deal with the problem of radio spectrum scarcity . In this paper, we investigate the SU performance in cognitive radio networks with reactive-decision spectrum handoff. During transmission, a SU may get interrupted several times due to the arrival of primary (licensed) users. After each interruption in the reactive spectrum handoff, the SU performs spectrum sensing to determine an idle channel for retransmission. We develop two continuous-time Markov chain models with and without an absorbing state to study the impact of system parameters such as sensing time and sensing room size on several SU performance measures. These measures include the mean delay of a SU, the variance of the SU delay, the SU interruption probability, the average number of interruptions that a SU experiences, the probability of a SU getting discarded from the system after an interruption and the SU blocking probability upon arrival.     

感知不确定下卫星认知无线网络多频谱接入优化策略

针对卫星认知无线网络频谱感知不确定性较大导致传统频谱接入机制效率降低的问题,该文提出一种基于动态多频谱感知的信道接入优化策略。认知LEO卫星根据频谱检测概率与授权用户干扰门限之间的关系,实时调整不同频谱感知结果下的信道接入概率。在此基础上以系统吞吐量最大化为目标,设计了一种基于频谱检测概率和虚警概率联合优化的判决门限选取策略,并推导了最佳感知频谱数量。仿真结果表明,认知用户能够在不大于授权用户最大干扰门限的前提下,根据授权信道空闲状态动态选择最佳频谱感知策略,且在检测信号信噪比较低时以更加积极的方式接入授权频谱,降低了频谱感知不确定性对信道接入效率的影响,提高了认知系统吞吐量。     

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。      

On the Impacts of Channel Estimation Errors and Feedback Delay on the Ergodic Capacity for Spectrum Sharing Cognitive Radio

Spectrum sharing cognitive radio aims to improve the spectrum efficiency via sharing the spectrum band licensed to the primary user (PU) with the secondary user (SU) concurrently provided that the interference caused by the SU to the PU is limited. The channel state information (CSI) between the secondary transmitter (STx) and the primary receiver (PRx) is used by the STx to calculate the appropriate transmit power to limit the interference. We assume that this CSI is not only having channel estimation errors but also outdated due to feedback delay, which is different from existing studies. We derive closed-form expressions for the ergodic capacities of the SU with this imperfect CSI under the average interference power (AIP) constraint and the peak interference power (PIP) constraint. Illustrative results are presented to show the effects of the imperfect CSI. It is shown that the ergodic capacity of the SU is robust to the channel estimation errors and feedback delay under high feedback delay. It is also shown that decreasing the distance between STx and secondary receiver (SRx) or increasing the distance between STx and PRx can mitigate the impact of the imperfect CSI and significantly increase the ergodic capacity of the SU.     

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.     

Secrecy outage analysis in a hybrid cognitive relay network with energy harvesting

In this paper, we investigate the physical layer security of a hybrid cognitive relay network using an energy harvesting relay in presence of an eavesdropper. In the hybrid scheme, a secondary user (SU) as well as a cognitive relay works either in underlay or in overlay mode. In underlay, the transmit power of the SU as well as the relay is limited by the maximum acceptable interference at primary user (PU) receiver as required by an outage constraint of PU, a quality of service for PU. The secondary network consists of a decode and forward relay that harvests energy from radio frequency signal of secondary transmitter as well as PU transmitter to assist the SU in forwarding the information signal to the destination. A time switching relaying protocol is used at the relay. We evaluate the secrecy outage probability of secondary relay network assuming that channel state information of the interfering links from both the SU and relay transmitter to PU receiver is imperfect. Our results reveal the impact of imperfect channel state information, energy harvesting time, tolerable interference threshold, and PU outage constraint on the secrecy outage probability of SU.     

支持紧急通信的无线认知网络频谱接入方法

提出了支持应急通信的无线认知网络机会频谱接入模型。首先按照离散时间完全和限定(k=1)服务两级轮询策略实现主用户和次用户对频谱的共享。其次,通过在数据确认中捎带轮询列表信息方式实现数据传输和用户调度的并行处理,减少用户切换造成的时延浪费。通过建模分析得出网络吞吐量及用户平均等待时延的精确解析,结果表明本方案能有效抑制次用户对主用户通信质量的影响,又能增加网络吞吐量并为通信业务提供时延保障。     

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.     

主用户干扰约束下的机会频谱接入感知−传输时隙优化调度

提出一种基于主用户干扰约束的机会频谱接入感知-传输时隙调度优化方案。首先,推导切换机制下认知系统的吞吐量和主用户干扰率,建立感知时间和感知周期联合优化模型;然后,在主用户干扰率和次用户感知质量双重约束下,推导了可最大化认知系统吞吐量的最优感知时间和感知周期的闭合表达式;最后,阐述了时隙优化调度方案并计算了认知系统可获得的最大吞吐量。仿真结果表明,所提出的时隙调度方案可以为认知系统提供更高的吞吐量,并更好地适应主用户干扰率和感知质量约束的变化。     

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。