Distributed cooperative spectrum sensing in cognitive radio for ad hoc networks

Cognitive radio refers to an intelligent radio with the capability of sensing the radio environment and dynamically reconfiguring the operating parameters. Recent research has focused on using cognitive radios in ad hoc environments. Spectrum sensing is the most important aspect of successful cognitive radio ad hoc network deployment to overcome spectrum scarcity. Multiple cognitive radio users can cooperate to sense the primary user and improve sensing performance. Cognitive radio ad hoc networks are dynamic in nature and have no central point for data fusion. In this paper, gradient-based fully distributed cooperative spectrum sensing in cognitive radio is proposed for ad hoc networks. The licensed band used for TV transmission is considered the primary user. The gradient field changes with the energy sensed by cognitive radios, and the gradient is calculated based on the components, which include energy sensed by secondary users and received from neighbors. The proposed scheme was evaluated from the perspective of reliable sensing, convergence time, and energy consumption. Simulation results demonstrated the effectiveness of the proposed scheme.     

Joint beamforming and scheduling in the downlink of cognitive radio networks

Cognitive radio has been recently proposed as a promising technology to improve the spectrum utilization. In this paper, we consider a system where a licensed radio spectrum is shared by a primary network and a secondary network. Based on the subspace theory, a novel low-complexity algorithm for secondary user selection has been proposed. On the basis of the scheduling scheme, we jointly consider transmit beamforming, scheduling and power allocation, and subsequently present a complete set of solution for secondary network downlink. Simulation results has shown that our proposed scheme not only can limit the introduced interference at primary users within the tolerable range, but also can achieve high sum-rate throughput of secondary network, simultaneously. Furthermore, as is proved by simulation results, our scheme is very robust due to the fact that only a little tolerable performance drop is introduced when simple but nonoptimal equal power allocation is adopted.     

认知无线网络中基于进化博弈的动态频谱接入*

研究了认知无线网络环境中基于价格动态性的动态频谱接入,即不同的授权网络服务商以不同的价格将空闲频谱出售给认知网络,且认知用户可以根据自己获得的报酬动态地接入不同的网络。为最大化认知网络的效用,提出了基于进化博弈的动态频谱接入方案。仿真结果表明,当认知用户群体到达进化均衡时,接入每个主网络的认知用户数量的比例达到稳定状态,最大化了认知用户和网络的效用。     

一种新型面向频谱高利用率的认知MAC协议

认知无线电是无线访问领域出现的新技术,目的在于大幅度提高无线频谱的使用.其基本思想是:次用户(非授权用户)在不干扰主用户(授权用户)的条件下允许使用授权频谱.提出一种新的基于独占模式的认知MAC协议.在该协议中,次用户被划分为若干不重叠的组,每个组使用特定的拍卖算法来对其需要租用的信道进行投标.实验表明,这种新协议能够最大化利用频谱资源,并且保证信道在组间分配的公平性和动态性.     

一种公平的认知无线电系统下行频谱分配策略

目前关于认知无线电频谱分配的研究大多以最大化系统容量为目标,很少考虑认知用户的QoS需求,频谱分配方案设计缺乏公平性。针对主用户干扰限制和保障认知用户QoS需求,结合OFDM技术,研究了认知无线电场景中下行多用户分配算法。该算法构建不等式约束下的目标函数以最大化系统容量,通过拉格朗日(Lagrange)对偶优化法给出近似最优解。仿真结果表明,所提算法在牺牲系统和容量的前提下充分保证了次用户的QoS需求,提高了系统的公平性。     

感知无线云网络中基于传输时间的节能优化方案

在感知无线云网络中,本文针对感知用户数据传输时发生冲突造成能量浪费问题,给出了一种移动云计算辅助下基于感知数据传输时间优化的终端节能方案。通过云平台强大的计算处理能力对感知用户业务量进行统计分析,并导出了不可靠检测区域;在此基础上,采用感知用户不可靠检测概率为目标函数,使不可靠检测概率最小的同时,计算出感知用户最佳的数据传输时间,并根据业务量对感知用户的传输时间进行自适应调整,实现对感知用户的宏观调控,从而节约系统中感知终端的能耗。仿真结果表明该方案使得感知用户的碰撞概率降低,在提高了感知用户数据传输可靠性,并降低由于数据碰撞造成的终端能耗。     

大规模认知无线电网络的时延分析

时延作为无线网络的最基本的性能之一,对网络信息分发、路由协议设计、节点部署等都具有重要意义。与传统的无线网络不同,认知无线电网络的频谱资源具有动态变化性,该特性会对网络时延产生极大的影响。因此,如何对动态频谱环境下的大规模认知无线电网络进行时延分析,是一项很具挑战性的课题。为此,首先对动态频谱环境进行建模,将认知用户的频谱接入过程建模为一个连续时间的马尔可夫链,并建立认知用户的生存函数来量化授权用户活动以及信道数量对频谱环境的影响;其次,将上述模型与首次通过渗流理论结合起来,研究了大规模认知无线电网络时延的伸缩规律,并获取了更为精确的时延与距离比的上限值。理论分析及仿真结果表明,动态频谱环境与密度一样会对时延产生极大影响。研究结论对认知无线电网络的设计具有重要的指导意义。     

An Efficient Optimized Handover in Cognitive Radio Networks Using Cooperative Spectrum Sensing

Cognitive radio systems necessitate the incorporation of cooperative spectrum sensing among cognitive users to increase the reliability of detection. We have found that cooperative spectrum sensing is not only advantageous, but is also essential to avoid interference with any primary users. Interference by licensed users becomes a chief concern and issue, which affects primary as well as secondary users leading to restrictions in spectrum sensing in cognitive radios. When the number of cognitive users increases, the overheads of the systems, which are meant to report the sensing results to the common receiver, which becomes massive. When the spectrum, which is in use becomes unavailable or when the licensed user takes the allocated band, these networks have the capability of changing their operating frequencies. In addition, cognitive radio networks are seen to have the unique capability of sensing the spectrum range and detecting any spectrum, which has been left underutilized. Further this capability of recognizing the spectrum range based on the dimensions detected, allows for determination of the band, which may be utilized. The main objective of this paper is to analyze the cognitive radio’s spectrum sensing ability and evolving a self-configured system with dynamic intelligence networks without causing any interference to the primary user. The paper also brings focus to the quantitative analysis of the two spectrum sensing techniques namely; Energy Detection and Band Limited White Noise Detection. The estimation technique for detecting spectrum noise is based on the detection of probability and probability of false alarms at different Signal-to-Noise Ratio (SNR) levels using Additive White Gaussian Noise signal (AWGN). The efficiency of the proposed Cooperative CUSUM spectrum sensing algorithm performs better than existing optimal rules based on a single observation spectrum sensing techniques under cooperative networks.     

Analytical modeling for spectrum handoff decision in cognitive radio networks

Cognitive Radio (CR) is an emerging technology used to significantly improve the efficiency of spectrum utilization. Although some spectrum bands in the primary user’s licensed spectrum are intensively used, most of the spectrum bands remain underutilized. The introduction of open spectrum and dynamic spectrum access lets the secondary (unlicensed) users, supported by cognitive radios; opportunistically utilize the unused spectrum bands. However, if a primary user returns to a band occupied by a secondary user, the occupied spectrum band is vacated immediately by handing off the secondary user’s call to another idle spectrum band. Multiple spectrum handoffs can severely degrade quality of service (QoS) for the interrupted users. To avoid multiple handoffs, when a licensed primary user appears at the engaged licensed band utilized by a secondary user, an effective spectrum handoff procedure should be initiated to maintain a required level of QoS for secondary users. In other words, it enables the channel clearing while searching for target vacant channel(s) for completing unfinished transmission. This paper proposes prioritized proactive spectrum handoff decision schemes to reduce the handoff delay and the total service time. The proposed schemes have been modeled using a preemptive resume priority (PRP) M/G/1 queue to give a high priority to interrupted users to resume their transmission ahead of any other uninterrupted secondary user. The performance of proposed handoff schemes has been evaluated and compared against the existing spectrum handoff schemes. Experimental results show that the schemes developed here outperform the existing schemes in terms of average handoff delay and total service time under various traffic arrival rates as well as service rates.     

基于时频资源分配的认知无线中继网络物理层安全研究

提出了一种在认知无线中继网络物理层安全意义下的最优时频资源分配方案。在该方案中,主用户通过次用户的协作进行通信;作为回馈,允许次用户接入该频段传输信息。在次用户网络中,选择两个最优次用户,一个用作协作转发,一个用作协作干扰,同时在保证次用户网络传输速率的条件下,通过寻求系统的最优带宽分配因子、时隙分配因子以及次用户的协作功率,来最大化主用户的安全容量。仿真结果表明,提出的方案切实可行,能够显著提高主用户的安全容量。     

动态主用户流量模型的跨层优化设计

为适应主用户流量变化较快的场景,在不完美频谱感知的情况下最大化认知用户的吞吐量,提出了一种基于集中式Overlay认知无线网络中感知时间与资源分配跨层优化算法。将优化目标分解为信道分配和检测时间同功率分配联合优化两个子问题,通过子算法迭代,最终得到感知时间与资源分配的联合最优解。仿真结果表明,相对于仅考虑频谱感知或资源分配的单层优化算法,该算法可在兼顾公平的前提下使次用户吞吐量得到有效提升。     

基于两步决策与ε-greedy探索的增强学习频谱分配算法

在认知无线网络中,认知基站需要进行频谱管理来提升非授权用户的服务质量。基站在寻找频谱空洞分配给非授权用户的过程中,需要做出最好的选择,但极可能是局部最优解,从而造成非授权用户频繁的频谱切换和吞吐率的下降。针对此问题,本文提出基于两步决策与探索的集中式增强学习频谱分配算法。通过设计新型状态动作集,认知基站进行信道分配的两步决策,并应用探索模式,解决认知基站在增强学习过程中探索环境和利用经验进行决策的平衡问题,防止决策的局部最优,提升频谱管理的性能。仿真结果表明,该算法在提升非授权用户吞吐率以及降低频谱切换方面明显优于现有的一些频谱分配策略。     

基于频谱感知的认知Ad hoc网络分簇算法

为了提高认知Ad hoc网络频谱感知效率,解决认知Ad hoc网络分簇问题,本文提出一种基于频谱感知的认知Ad hoc网络分簇算法。通过引入检测因子,综合考虑多个主用户信号交叠与阴影衰落的情况,将认知Ad hoc网络中的次用户节点与需要检测的主用户信道建模为二部图模型,使得分簇问题简化为最大权边二部图（Constraint maximum-weight edge biclique, C-MWEB）分解问题,并设计一种贪婪算法对其求解。仿真结果表明,在多个主用户信号交叠与阴影衰落并存的情况下,相较于传统算法,本文算法分簇更为合理,具有更好的有效性与可靠性。     

Multi-leader multi-follower Stackelberg model for cognitive radio spectrum sharing scheme

Radio spectrum is one of the most scarce and variable resources for wireless communications. Therefore, the proliferation of devices and rapid growth of wireless services continue to strain the limited radio spectrum resource. Cognitive Radio (CR) paradigm is a promising technology to solve the problem of spectrum scarcity. In this paper, a new fair-efficient spectrum sharing scheme is proposed for cognitive radio networks. Based on the multiple-leader multiple-follower Stackelberg game model, the proposed scheme increases opportunistic use of the licensed radio spectrum. To adaptively use the spectrum resource, control decisions are coupled with one another; the result of the each user’s decisions is the input back to the other user’s decision process. Under widely diverse network environments, this adaptive feedback process approach can provide an effective way of finding a suitable solution. The simulation results demonstrate that the proposed scheme has excellent network performance, while other schemes cannot offer such an attractive performance balance.     

认知无线传感器网络的吞吐量分析

为了实现认知无线传感器网络(CRSN)在授权频段的连续可靠通信,结合协作感知和宽带感知策略,提出了一种CRSN架构.通过在网络中部署专门负责频谱感知的认知节点,将频谱感知与数据传输功能进行了合理分配.在最大化感知和传输时间的同时,实现了频谱的实时感知和数据的连续传输,进而提高了频谱检测率和网络吞吐量.同时,由认知节点协作对宽带进行多信道联合检测,除了可以提高检测的可靠性,还有利于实现CRSN对授权频段的连续接入,进一步保证网络数据传输的连续性.通过仿真对不同硬融合准则下的平均网络吞吐量进行了分析和比较,结果表明该网络架构可以获得更高的吞吐量.     

A cross-layer protocol of spectrum mobility and handover in cognitive LTE networks

Cognitive radio technique is the next step toward efficient wireless bandwidth utilization. While some of the spectrum bands (unlicensed band) have been increasingly used, most of the other spectrum resources (licensed band) are underutilized. This drives the challenges of open spectrum and dynamic spectrum access concepts, which allows unlicensed users (or called secondary users, SUs) equipped with cognitive radios to opportunistically access the spectrum not used by licensed users (or called primary users, PUs). Most existing results mainly focus on designing the lower-layer cognitive radio problems. In the literature, this is the first result to investigate the higher-layer solution for cognitive radio networks. In this paper, we present a cross-layer protocol of spectrum mobility (layer-2) and handover (layer-3) in cognitive LTE networks. With the consideration of the Poisson distribution model of spectrum resources, a cross-layer handoff protocol with the minimum expected transmission time is developed in cognitive LTE networks. Performance analysis of the proposed handoff protocol is investigated. Finally, simulation results illustrates the proposed handoff protocol significantly reduces the expected transmission time and the spectrum mobility ratio.     

Joint throughput and transmission range optimization for triple-hop networks with cognitive relay

The optimization of the network throughput and transmission range is one of the most important issues in cognitive relay networks (CRNs). Existing research has focused on the dual-hop network, which cannot be extended to a triple-hop network due to its shortcomings, including the limited transmission range and one-way communication. In this paper, a novel, triple-hop relay scheme is proposed to implement time-division duplex (TDD) transmission among secondary users (SUs) in a three-phase transmission. Moreover, a superposition coding (SC) method is adopted for handling two-receiver cases in triple-hop networks with a cognitive relay. We studied a joint optimization of time and power allocation in all three phases, which is formulated as a nonlinear and concave problem. Both analytical and numerical results show that the proposed scheme is able to improve the throughput of SUs, and enlarge the transmission range of primary users (PUs) without increasing the number of hops.     

OFDMA认知无线电网络中面向功率控制的频谱定价与分配

针对OFDMA认知无线电网络,提出一种基于Stackelberg博弈的频谱定价和分配模型.对于次基站控制次网络传输功率来保护主网络通信的场景,主基站可通过该模型获得最优的频谱定价方案.从功率控制的角度,重新设计次用户的效用函数,运用Stackelberg博弈对单个主基站和多个次用户在频谱租赁市场中的交易行为进行建模.通过逆向归纳法,求解市场均衡下的最优频谱定价,使得主基站在考虑主网络QoS降级的同时获得最大收益.此外,对于主基站只能获取本地信息的情形,提出了基于动态Stackelberg博弈的分布式频谱定价和分配模型.仿真实验表明,该模型能够在控制次网络传输功率的基础上,提供最优频谱定价和频谱分配方案.     

混合保护准则下基于NC-OFDM的认知无线电系统功率分配

针对主用户采用OFDM通信体制,认知用户采用NC-OFDM通信体制,认知用户共享主用户授权频谱的工作场景,研究了认知无线电系统功率分配策略。提出依据主用户不同工作状态,采用不同的约束准则:对认知用户工作信道,引入功率泄漏干扰因子约束认知用户的发射功率,以限制对主用户工作信道的泄漏功率强度;对主用户工作信道,设置主用户速率损失上限,以确保主用户正常工作。功率分配算法以混合约束准则为基础,最大化认知无线电系统的传输速率。仿真结果表明,与干扰功率约束机制相比较,本算法能显著提升传输速率。     

认知无线网络中基于凸优化的功率分配研究

主要研究认知无线网络中基于OFDM（orthogonal frequency dinsion multiplexing）的功率分配问题。为将认知用户(secondary user,SU)对主用户(primary user,PU)的干扰功率限制在主用户可容忍的范围内,同时最大化认知用户的传输速率,提出了基于凸优化理论的功率分配方案。仿真结果表明,在主用户可容忍的干扰极限和认知用户总功率约束下,该方案能最大化认知用户的传输速率。