认知无线网络中基于博弈的频谱共享*

研究了认知无线网络环境中基于价格动态性的频谱共享,主要用户服务提供商以不同的频谱价格向认知用户服务提供商出售空闲频谱,认知用户根据获得的收益调整对频谱的需求。在全体服务提供商对频谱价格满意的基础上,为最大化认知用户的收益,提出了基于静态博弈和动态博弈的频谱共享方案。仿真结果表明,通过合理设置学习速率,动态博弈达到了接近静态博弈的性能,最大化认知用户的收益。     

认知无线电网络中多目标频谱分配与功率控制

针对Underlay接入方式的认知无线电网络中的功率控制问题进行了研究,提出同时考虑频谱分配和功率控制两个因素。并且为了同时满足用户的多种需求,将网络容量和功耗效率构建成一个多目标优化问题,然后提出了一种基于NSGA-Ⅱ的改进多目标优化算法对该问题进行建模求解,得到了适合用户不同需求的Pareto最优解集。最后将所提方法与SPEA-Ⅱ算法进行了实验对比,仿真结果表明,所提方法能够有效地搜索到优化解,并且能够满足不同情况下的频谱和功率分配要求。     

Spectrum sharing in cognitive radio networks with imperfect sensing: A discrete-time Markov model

An efficient and utmost utilization of currently scarce and underutilized radio spectrum resources has stimulated the introduction of what has been coined Cognitive Radio (CR) access methodologies and implementations. While the long-established approach has been based on licensed (or primary) spectrum access, this new communication paradigm enables an opportunistic secondary access to shared spectrum resources provided mutual interference is kept below acceptable levels. In this paper we address the problem of primary-secondary spectrum sharing in cognitive radio access networks using a framework based on a Discrete Time Markov Chain (DTMC) model. Its applicability and advantages with respect to other approaches is explained and further justified. Spectrum awareness of primary activity by the secondary users is based on spectrum sensing techniques, which are modeled in order to capture sensing errors in the form of false-alarm and missed-detection. Model validation is successfully achieved by means of a system-level simulator which is able to capture the system behavior with high degree of accuracy. Parameter dependencies and potential tradeoffs are identified enabling an enhanced operation for both primary and secondary users. The suitability of the specified model is justified while allowing a wide range of extended implementations and enhanced capabilities to be considered.     

Adaptive power allocation with quality-of-service guarantee in cognitive radio networks

This paper proposes a novel power control policy for a cognitive radio network as an effort to maximize throughput under the average interference power constraint. The underlined policy ensures delay-related quality of service (QoS) requirements with reduced interference to the primary user. In this work we also take into account the peak and average transmit power constraints for the secondary user. An optimization problem associated with the power control policy is formulated based on a cross-layer framework, where the queue on data link layer is serviced by the power control policy at the physical layer. A recursive algorithm under the power constraints is developed to solve for the optimal solution. It is shown that the reduction of average interference to the primary user is related closely to the QoS requirements. The analysis derives the average interference power limits to the primary user in fading channels with guaranteed QoS requirements for the secondary user. The numerical results show the effectiveness of the proposed power control policy.     

认知无线网络中基于价格的频谱共享模型

为了使用户可以根据信道质量的变化动态调整带宽价格,从而改变用户收益,提出考虑用户移动性的频谱共享模型。该模型中信道质量随着用户的位置变化,主用户提出的带宽价格综合考虑所有次用户请求的带宽和信道质量的影响;同时,请求的带宽又受到带宽价格的制约,从而用户收益也随着用户位置而变化。仿真结果表明,在用户运动过程中,可以选择最佳位置使用户收益最大。     

QoS provisioning wireless multimedia transmission over cognitive radio networks

The rapid growing of wireless multimedia applications increases the needs of spectrum resources, but today’s spectrum resources have become more and more scarce and large part of the assigned spectrum is in an inefficiency usage. Cognitive Radio (CR) technologies are proposed to solve current spectrum inefficiency problems and offer users a ubiquitous wireless accessing environment, relying on dynamic spectrum allocation. However, there are two unsolved problems in previous work: 1) based on the simplified Quality of Service (QoS) uniform assumption, specific requirements of different wireless multimedia applications cannot be satisfied; 2) aiming at single-objective optimization of spectrum utilization or handoff rate, the co-optimization of these two necessary objectives in CR networks has not been achieved. In this paper, we propose a Two-tier Cooperative Spectrum Allocation method (TCSA) to solve these two problems. TCSA consists of two functional parts: one is a Spectrum Adjacency Ranking algorithm implemented at the secondary users’ terminals to satisfy the QoS requirements for different wireless multimedia applications; and the other is a Max Hyper-weight Matching algorithm implemented at the cognitive engines of CR networks to co-optimize spectrum utilization and secondary users’ spectrum handoff rate. Simulation results show that, compared with the other Random matching algorithm and Cost minimized algorithm, TCSA can significantly improve the performance of CR networks in terms of secondary users’ throughput and spectrum handoff rate.     

Matching game-based hierarchical spectrum sharing in cooperative cognitive radio networks

The Journal of Supercomputing - In a cooperative cognitive radio network (CCRN), primary users (PUs) select secondary users (SUs) as cooperative relays for increasing their transmission rates,...     

认知无线电网络动态QoS保证机制研究

针对认知无线电网络提出了一种基于中间件的分布式动态QoS保证机制DQAM,当网络对应用承诺的QoS保证发生变化,或者应用对网络的QoS要求发生变化时,通过网络和应用之间的反馈和协商,在分析当前网络状态和应用需求的基础上,根据特定的策略对网络和应用进行动态干预,在保证一定QoS的前提下,使应用最大程度的适应网络,网络最大限度的支持应用,以提高认知无线电网络对应用的支持能力和应用对网络的适应能力。对DQAM的原理、系统组成以及运行方式等,进行了讨论;从体系结构、工作过程、信息收集与策略生成和节点（任务）重构等4个方面,给出了DQAM的基本框架,并通过一个典型场景就DQAM的应用问题进行了探讨。     

QoS constrained resource allocation to secondary users in cognitive radio networks

In this paper, we consider a multi-channel cognitive radio network (CRN) where multiple secondary users share a single channel and multiple channels are simultaneously used by a single secondary user (SU) to satisfy their rate requirements. In such an environment, we attempt to evaluate the optimal power and rate distribution choices that each secondary user has to make in order to maintain their quality of service (QoS). Our measures for QoS include signal to interference plus noise ratio (SINR)/bit error rate (BER) and minimum rate requirement. We propose two centralized optimization frameworks in order to solve for the optimal resource management strategies. In the first framework, we determine the minimum transmit power that SUs should employ in order to maintain a certain SINR and use that result to calculate the optimal rate allocation strategy across channels. In the second framework, both transmit power and rate per channel are simultaneously optimized with the help of a bi-objective problem formulation. Unlike prior efforts, we transform the BER constraint into a convex constraint in order to guarantee optimality of the resulting solutions. Simulation results demonstrate that in both frameworks, optimal transmit power follows “reverse water filling” process and rate allocation follows SINR. We also observe that, due to the ability to adapt both power and rate simultaneously to attain a certain BER, the joint optimization framework results in a lower total transmit power than the two-stage approach.     

Spectral efficiency of cognitive radio networks under interference constraint and QoS guarantees

We study the problem of maximizing spectral efficiency of cognitive radio network deployments subject to an interference constraint and under specific quality of service (QoS) guarantees. The interference constraint corresponds to the upper limit of the received power that can be tolerated at the licensed users’ due to transmissions from unlicensed users. The QoS guarantees stem from the requirements imposed by the applications running at the users’ terminals. A cross-layer design is adopted that maps the user’s requirements into delay related QoS guarantees at the data link layer and error probability QoS guarantees at the physical layer. The obtained numerical results provide important insights regarding the impact of the considered constraint and guarantees on the achievable spectral efficiency of cognitive radio networks.     

Efficient spectrum utilization via cross-layer optimization in distributed cognitive radio networks

In this paper, we propose a novel spectrum allocation approach for distributed cognitive radio networks. Cognitive radio systems are capable of sensing the prevailing environmental conditions and automatically adapting its operating parameters in order to enhance system and network performance. Using this technology, our proposed approach optimizes each individual wireless device and its single-hop communication links using the partial operating parameter and environmental information from adjacent devices within the wireless network. Assuming stationary wireless nodes, all wireless communication links employ non-contiguous orthogonal frequency division multiplexing (NC-OFDM) in order to enable dynamic spectrum access (DSA). The proposed approach will attempt to simultaneously minimize the bit error rate, minimize out-of-band (OOB) interference, and maximize overall throughput using a multi-objective fitness function. Without loss in generality, genetic algorithms are employed to perform the actual optimization. Several assisting processes have also been devised to make the approach more efficient and robust. Such procedure is able to reduce BER by an order of magnitude.     

Detection probability maximization through optimization of samples in cognitive radio networks

Multimedia Tools and Applications - Cognitive radio technology is widely used to identify the underutilized spectrum bands through spectrum sensing. In this paper, energy detection method is used...     

基于粒子群算法的认知无线电频谱分配算法

针对认知无线电空闲频谱分配过程中整体性能优化问题,建立了频谱资源受限情况下实现系统总带宽收益最大化、认知用户接入公平性最优的多目标模型,并结合问题特点设计了基于粒子群优化算法的智能求解算法,给出了具体的实施步骤。从系统总带宽收益、用户接入公平性和系统整体性能3个方面,仿真比较分析了所提算法同协作最大化带宽总收益和协作最大化比例公平性准则下的敏感图着色算法的性能,结果表明该方法实现了系统总带宽收益和用户公平性的折中,整体性能优于敏感图着色算法。     

支持QoS保障的Ad hoc网络多信道MAC协议

提出了一种提供QoS保障的多信道MAC协议,该协议把不同种类业务划分优先级和帧 间隔时间,以保障优先级高的数据较早接入信道,同时把高层数据按目的地址的不同建立发送链表,采用自动重传技术,实现数据信道上连续的帧交换过程.仿真结果表明,该方法大大提高了数据信道利用率,改善了系统性能.     

认知Mesh网络中基于免疫多目标优化的频谱分配

针对认知无线Mesh网络(CWMN)的频谱分配问题,提出了一种基于免疫多目标优化的实现算法。该算法将要求解的频谱分配建模为最大化总带宽和最小化占用频谱数的多目标优化问题,设计了适合问题求解的抗体编码方式、整体克隆算子和非支配抗体选择算子。仿真实验结果表明,所提算法可以求得CWMN频谱分配问题的Pareto最优解,提高了最大化总带宽,减少了最小化占用频谱,优化了频谱分配性能。     

Joint spectrum allocation and scheduling for fair spectrum sharing in cognitive radio wireless networks

Cognitive radio and Dynamic Spectrum Access (DSA) enable wireless users to share a wide range of available spectrums. In this paper, we study joint spectrum allocation and scheduling problems in cognitive radio wireless networks with the objectives of achieving fair spectrum sharing. A novel Multi-Channel Contention Graph (MCCG) is proposed to characterize the impact of interference under the protocol model in such networks. Based on the MCCG, we present an optimal algorithm to compute maximum throughput solutions. As simply maximizing throughput may result in a severe bias on resource allocation, we take fairness into consideration by presenting optimal algorithms as well as fast heuristics to compute fair solutions based on a simplified max–min fairness model and the well-known proportional fairness model. Numerical results show that the performance given by our heuristic algorithms is very close to that of the optimal solution, and our proportional fair algorithms achieve a good tradeoff between throughput and fairness. In addition, we extend our research to the physical interference model, and propose effective heuristics for solving the corresponding problems.     

Differentiation, QoS guarantee, and optimization for real-time traffic over one-hop ad hoc networks

Nodes having a self-centrically broadcasting nature of communication form a wireless ad hoc network. Many issues are involved to provide quality of service (QoS) for ad hoc networks, including routing, medium access, resource reservation, mobility management, etc. Previous work mostly focuses on QoS routing with an assumption that the medium access control (MAC) layer can support QoS very well. However, contention-based MAC protocols are adopted in most ad hoc networks since there is no centralized control. QoS support in contention-based MAC layer is a very challenging issue. Carefully designed distributed medium access techniques must be used as foundations for most ad hoc networks. In this paper, we study and enhance distributed medium access techniques for real-time transmissions in the IEEE 802.11 single-hop ad hoc wireless networks. In the IEEE 802.11 MAC, error control adopts positive acknowledgement and retransmission to improve transmission reliability in the wireless medium (WM). However, for real-time multimedia traffic with sensitive delay requirements, retransmitted frames may be too late to be useful due to the fact that the delay of competing the WM is unpredictable. In this paper, we address several MAC issues and QoS issues for delay-sensitive real-time traffic. First, a priority scheme is proposed to differentiate the delay sensitive real-time traffic from the best-effort traffic. In the proposed priority scheme, retransmission is not used for the real-time traffic, and a smaller backoff window size is adopted. Second, we propose several schemes to guarantee QoS requirements. The first scheme is to guarantee frame-dropping probability for the real-time traffic. The second scheme is to guarantee throughput and delay. The last scheme is to guarantee throughput, delay, and frame-dropping probability simultaneously. Finally, we propose adaptive window backoff schemes to optimize throughput with and without QoS constraints.