Optimal Resource Allocation for Spectrum Sensing Based Cognitive Radio Networks with Statistical QoS Guarantees

Resource allocation under spectrum sensing based dynamic spectrum sharing strategy is a critically important issue for cognitive radio networks (CRNs), because they need to not only satisfy the interference constraint caused to the primary users (PUs), but also meet the quality-of-service (QoS) requirements for the secondary users (SUs). In this paper, we develop the optimal spectrum sensing based resource allocation scheme for the delay QoS constrained CRNs. Specifically, we aim at maximizing the maximum constant arrival rate of the SU that can be supported by the time-varying service process subject to the given statistical delay QoS constraint. In our derived power allocation scheme, not only the average transmit and interference power constraints are considered, but also the impact of the PUs?? transmission to the CRNs and the PUs?? spectrum-occupancy probability are taken into consideration. Moreover, the spectrum sensing errors are also taken into consideration. Simulation results show that, (1) the effective capacity of the secondary link decreases when the statistical delay QoS constraint becomes stringent; (2) given the QoS constraint, the effective capacity of the secondary link varies with the interference power constraint and the SNR of the primary link.     

Energy-Efficient Power Allocation with Guaranteed QoS Under Imperfect Sensing for OFDM-Based Heterogeneous Cognitive Radio Networks

Wireless Personal Communications - This paper investigates the energy efficient resource allocation scheme for orthogonal frequency division multiplexing based heterogeneous cognitive radio network...     

Q-Learning Based Interference-Aware Channel Handoff for Partially Observable Cognitive Radio Ad Hoc Networks

Channel handoff is a crucial function for Cognitive radio ad hoc networks (CRAHNs). The ab-sence of centralized infrastructures and the limited power make the handoff design more challenging. A learning-based interference-aware handoff scheme is proposed for distributed CRAHNs. We model the channel handoff pro-cess as a Partially observable Markov decision process (POMDP) and adopt a Q-learning algorithm to find an optimal handoff strategy in a long term. The proposed algorithm obtains an efficient transmission performance by considering the interferences among SUs and PUs. To achieve PU awareness, the handoff scheme predicts the PU activities by using the historical channel usage statistics. In addition, we also propose a refined channel selection rule to compromise between learning speed and cumulative trans-mission reward. The simulation results show that the pro-posed handoff scheme can adapt to the PU activities and achieves a better performance in terms of high throughput and low collisions. And the learning process keeps a consid-erable balance between convergence time and cumulative reward.     

Opportunistic Scheduling with Reliability Guarantees in Cognitive Radio Networks

We develop opportunistic scheduling policies for cognitive radio networks that maximize the throughput utility of the secondary (unlicensed) users subject to maximum collision constraints with the primary (licensed) users. We consider a cognitive network with static primary users and potentially mobile secondary users. We use the technique of Lyapunov optimization to design an online flow control, scheduling, and resource allocation algorithm that meets the desired objectives and provides explicit performance guarantees.     

Supporting QoS Differentiation in Energy-Constrained Cognitive Radio Networks

Wireless Personal Communications - Routing protocols for cognitive radio ad hoc networks (CRNs) select a route between the source and destination nodes based on the spectrum opportunity at...     

MAC Protocol for Opportunistic Cognitive Radio Networks with Soft Guarantees

Cognitive radio (CR) is the key enabling technology for an efficient dynamic spectrum access. It aims at exploiting an underutilized licensed spectrum by enabling opportunistic communications for unlicensed users. In this work, we first develop a distributed cognitive radio MAC (COMAC) protocol that enables unlicensed users to dynamically utilize the spectrum while limiting the interference on primary (PR) users. The main novelty in COMAC lies in not assuming a predefined CR-to-PR power mask and not requiring active coordination with PR users. COMAC provides a statistical performance guarantee for PR users by limiting the fraction of the time during which the PR users' reception is negatively affected by CR transmissions. To provide such a guarantee, we develop probabilistic models for the PR-to-PR and the PR-to-CR interference under a Rayleigh fading channel model. From these models, we derive closed-form expressions for the mean and variance of interference. Empirical results show that the distribution of the interference is approximately lognormal. Based on the developed interference models, we derive a closed-form expression for the maximum allowable power for a CR transmission. We extend the min-hop routing to exploit the available channel information for improving the perceived throughput. Our simulation results indicate that COMAC satisfies its target soft guarantees under different traffic loads and arbitrary user deployment scenarios. Results also show that exploiting the available channel information for the routing decisions can improve the end-to-end throughput of the CR network (CRN).     

Resource Allocation in an OFDM-Based Cognitive Radio System

The problem of subcarrier, bit and power allocation for an OFDM based cognitive radio system in which one or more spectrum holes exist between multiple primary user (PU) frequency bands is studied. The cognitive radio user is able to use any portion of the frequency band as long as it does not interfere unduly with the PUs' transmissions. We formulate the resource allocation as a multidimensional knapsack problem and propose a low-complexity, greedy max-min algorithm to solve it. The proposed algorithm is simple to implement and simulation results show that its performance is very close to (within 0.3% of) the optimal solution.     

A MAC-Layer QoS Provisioning Protocol for Cognitive Radio Networks

Due to the proliferation of diverse network devices with multimedia capabilities, there is an increasing need for Quality of Service (QoS) provisioning in wireless networks. The MAC layer protocol with enhanced distributed channel access (EDCA) in the IEEE 802.11-2007 is able to provide differentiated QoS for different traffic types in wireless networks through varying the Arbitration Inter-Frame Spaces (AIFS) and contention window sizes. However, the performance of high priority traffic can be seriously degraded in the presence of strong noise over the wireless channels. Schemes utilizing adaptive modulation and coding (AMC) technique have also been proposed for the provisioning of QoS. They can provide limited protection in the presence of noise but are ineffective in a high noise scenario. Although multiple non-overlapped channels exist in the 2.4 and 5?GHz spectrum, most IEEE 802.11-based multi-hop ad hoc networks today use only a single channel at anytime. As a result, these networks cannot fully exploit the aggregate bandwidth available in the radio spectrum provisioned by the standards. By identifying vacant channels through the use of cognitive radios technique, the noise problem can be mitigated by distributing network traffic across multiple vacant channels to reduce the node density per transmission channel. In this paper, we propose the MAC-Layer QoS Provisioning Protocol (MQPP) for 802.11-based cognitive radio networks (CRNs) which combines adaptive modulation and coding with dynamic spectrum access. Simulation results demonstrate that MQPP can achieve better performance in terms of lower delay and higher throughput.     

Cross-Layer Based Opportunistic MAC Protocols for QoS Provisionings Over Cognitive Radio Wireless Networks

We propose the cross-layer based opportunistic multi-channel medium access control (MAC) protocols, which integrate the spectrum sensing at physical (PHY) layer with the packet scheduling at MAC layer, for the wireless ad hoc networks. Specifically, the MAC protocols enable the secondary users to identify and utilize the leftover frequency spectrum in a way that constrains the level of interference to the primary users. In our proposed protocols, each secondary user is equipped with two transceivers. One transceiver is tuned to the dedicated control channel, while the other is designed specifically as a cognitive radio that can periodically sense and dynamically use the identified un-used channels. To obtain the channel state accurately, we propose two collaborative channel spectrum-sensing policies, namely, the random sensing policy and the negotiation-based sensing policy, to help the MAC protocols detect the availability of leftover channels. Under the random sensing policy, each secondary user just randomly selects one of the channels for sensing. On the other hand, under the negotiation-based sensing policy, different secondary users attempt to select the distinct channels to sense by overhearing the control packets over the control channel. We develop the Markov chain model and the M/G^Y/1-based queueing model to characterize the performance of our proposed multi-channel MAC protocols under the two types of channel-sensing policies for the saturation network and the non-saturation network scenarios, respectively. In the non-saturation network case, we quantitatively identify the tradeoff between the aggregate traffic throughput and the packet transmission delay, which can provide the insightful guidelines to improve the delay-QoS provisionings over cognitive radio wireless networks.     

Delay QoS Guaranteed Cooperative Double-Threshold Sensing Scheme in Cognitive Radio Networks

In cognitive radio networks, cooperation can greatly improve the performance of spectrum sensing. This paper proposes a delay (QoS) quality-of-service guaranteed cooperative spectrum sensing frame structure in which secondary users (SUs) conduct spectrum sensing and data transmission concurrently over two different parts of the primary user spectrum band. A double-threshold sensing scheme is employed in the local sensing step, only the SUs with reliable sensing information are allowed to transmit their “one bit” local decisions to the fusion center. The sensing performance and the SU transmission delay are analyzed in detail in this paper. Computer simulations show that the delay QoS guaranteed cooperative double-threshold sensing scheme could not only decrease the SU transmission delay but also save the reporting overhead of the SUs compared with the conventional detection method with one threshold.     

Analysis of QoS Provisioning in Cognitive Radio Networks: A Case Study

Dynamic Spectrum Access (DSA) is a promising solution to the problem of spectrum inefficiency. Based on Cognitive Radio (CR) technology, DSA allows a CR device to opportunistically access unused or less crowded spectrum while ensuring protection for the incumbents. Though DSA shows great potential to enhance network performance, its adverse side-effects on application QoS may limit its usefulness. QoS support in a DSA-based network is not trivial due to the fact that in addition to unfavorable characteristics of the wireless medium, the secondary devices must face additional interference and interruption from incumbents that have to be protected. In this paper, we present a case study of key DSA protocol characteristics necessary for QoS provisioning. Specifically, we consider a personal/portable CR system that supports high quality multimedia (including HDTV) streaming over UHF frequency bands. We model and evaluate the QoS-oriented CR system together with the underlying QoS-Provisioned DSA Protocol (called QPDP) through extensive simulations. The results show the effectiveness of the proposed DSA QoS provisioning approach in sustaining high levels of QoS, e.g., supporting HDTV streaming in TV bands. This outcome is significant as FCC has recently approved UHF bands for unlicensed operations in the USA, and various DSA-based CR systems are being actively designed by the wireless industry. The techniques outlined in this work can be generalized to be applicable to generic DSA design in various spectrum bands.     

基于业务感知的认知网络QoS自适应控制技术

文章研究并提出了基于业务感知的认知网络服务质量(QoS)自适应控制架构。该架构在智能业务感知和分类模型的基础上对数据包进行分类和识别,并借鉴控制理论通过基于端路协同的认知网络业务流QoS自适应控制机制实现对网络流量的控制。在认知网络环境下,该架构可以构建QoS的自动感知、分析、关联、反馈、决策、配置和实施机制,进行资源的优化调整分配,适应网络环境的变化,优化网络端到端的性能,保证用户的服务质量。     

Tradeoffs in Designing Networks with End-to-End Statistical QoS Guarantees

Recent research on statistical multiplexing has provided many new insights into the achievable multiplexing gain in QoS networks. However, usually, these results are stated in terms of the gain experienced at a single switch, and evaluating the statistical multiplexing gain in a general network remains a difficult challenge. In this paper we describe two distinct network designs for statistical end-to-end delay guarantees, referred to as class-level aggregation and path-level aggregation. These designs illustrate an inherent trade-off between attainable statistical multiplexing gain and the ability to support delay guarantees. The key characteristic of both designs is that they do not require, and instead, intentionally avoid, consideration of the correlation between flows at multiplexing points inside the network. Numerical examples are presented for a comparison of the statistical multiplexing gain achievable by the two designs. The class-level aggregation design is shown to yield very high achievable link utilizations while simultaneously achieving desired statistical guarantees on delay.     

基于粗糙集的认知无线网络跨层学习

认知学习是认知无线网络(CRN)跨层设计中非常重要的一环,它要求通信网络能利用已知跨层环境参数进行知识提取学习,并根据需要重配置网络.本文提出了一种基于粗糙集的CRN跨层学习技术,构建了案例事件库、知识库与规则匹配器,该模型结合数据离散、属性约简、值约简与规则生成算法来解决CRN的跨层学习问题.通过典型测试数据集的仿真比较,选出一组适合于所提出模型的粗糙集算法集合.仿真结果表明,该算法集能有效解决CRN跨层学习中知识提取与规则生成的准确性及有效性等问题,提出的跨层学习模型能有效用于CRN中的知识学习.     

认知无线电网络基于F范数的频谱共享

针对多用户多输入多输出认知无线电网络的频谱共享问题,提出一种在保证授权用户服务质量要求的前提下,以认知网络容量最大化为目标的基于F范数的频谱共享方法.该方法利用信道矩阵的F范数选择认知用户以获得认知网络的多用户分集增益,并采用两次选择的方式降低算法的复杂度,通过将认知用户的发射信号投射到干扰信道的零空间来避免认知用户对...     

An Adaptive Multitaper-SVD Spectrum Sensing Method for OFDM-Based Cognitive Radio Systems

Cognitive radio (CR) has been proposed and widely investigated as an approach for increasing the spectrum efficiency. CR devices exploit so called white spaces in the spectrum allocated to the primary users (PU) by a process commonly referred to as the spectrum sensing. In this work, we use the singular value decomposition (SVD) for spectrum sensing in orthogonal frequency division multiplexing-based (OFDM) CR systems. A single input multiple output channel is assumed between the PU and the secondary user equipped with multiple antennas. At the CR side, the multitaper method (MTM) is used for the spectrum sensing in each antenna. As a first contribution, we aim at reducing the time necessary to perform spectrum sensing. To this end, we propose an adaptive MTM–SVD spectrum sensing method that decreases the sensing time. As a second contribution, we formulate a three dimensional SVD (referred to as 3-D SVD) scheme that efficiently processes signals and quantities related to multiple antenna traffic, OFDM multiple blocks and different tapers, simultaneously. Simulation results indicate that the proposed adaptive MTM–SVD decreases the sensing time by about 61–69 % for various proposed adaptive algorithms, compared to the conventional MTM–SVD method. Besides, performance improvement in probability of detection is achieved from 2–13 % for a predefined probability of false alarm by using adaptive MTM–SVD. In addition to further reduction of the sensing time, the proposed 3D-MTM–SVD outperforms conventional methods for the low probability of the false alarm.     

OFDM-Based TVWS-IEEE Standards: A Survey of PHY and Cognitive Radio Features

Cognitive radio (CR) has been recognized as future prospect for efficient and dynamic allocation of bandwidth among users of which dynamic spectrum access is an important aspect focusing on identification and opportunistic utilization of vacant spectrum in television broadcasting licensed bands, known as television white spaces (TVWS). TVWS has been selected by numerous IEEE standards spanning diverse operating zones for implementing CR technology. Specifically, we focus our attention to IEEE 802.22, IEEE 802.11af and IEEE 802.15.4m standards operating in TVWS pertaining to regional, local and personal area networks respectively. The PHY layer in each of these standards is depending on orthogonal frequency division multiplexing (OFDM) for spectrum-wise efficient communication as well as dynamic frequency allocation. Pertinent OFDM design challenges corresponding to IEEE standards in TVWS are revealed. PHY layer structure and cognitive techniques employed in cognition-aware IEEE standards in TVWS are reviewed in detail. Lastly, open research issues and implementation challenges for TVWS IEEE standards are highlighted.

     

Joint Power and Time Allocation Scheme with QoS Constraints in Overlay Multi-user Cognitive Radio Networks

This paper studies the case of an overlay cognitive radio network where the primary user leases spectral resources to the secondary user in exchange for cooperation, considering that both type of users have specific quality of service requirements. We investigate the problem of joint power and time allocation for the secondary access during the cooperative phase, with a view to optimizing the effective capacity of the primary user given an average energy constraint for the secondary user. Afterwards, the optimal power allocation of the secondary user for its own transmission phase is investigated in order to maximize the effective capacity of the secondary link. The proposed joint power and time allocation mechanism is compared with an optimal time/constant power allocation scheme and a less sophisticated baseline allocation scheme, i.e. power allocation under constant time and its superiority is proven for various network parameters. The reference model of one primary–one secondary user is extended to a general multi user cognitive radio network through the proposed pairing mechanism based on matching theory. Particularly, considering the remarks of the reference scenario, we propose two different matching schemes (with/without consideration of primary users’ quality of service requirements) and we confirm their superiority compared to other matching mechanisms.     

Opportunistic Channel Selection Strategy for Better QoS in Cooperative Networks with Cognitive Radio Capabilities

Mission-oriented MANETs are characterized by implicit common group objectives which make inter-node cooperation both logical and feasible. We propose new techniques to leverage two optimizations for cognitive radio networks that are specific to such contexts: opportunistic channel selection and cooperative mobility. We present a new formal model for MANETs consisting of cognitive radio capable nodes that are willing to be moved (at a cost). We develop an effective decentralized algorithm for mobility planning, and powerful new Altering and fuzzy based techniques for both channel estimation and channel selection. Our experiments are compelling and demonstrate that the communications infrastructure-specifically, connection bit error rates-can be significantly improved by leveraging our proposed techniques. In addition, we find that these cooperative/opportunistic optimization spaces do not trade-off significantly with one another, and thus can be used simultaneously to build superior hybrid schemes. Our results have significant applications in high-performance mission-oriented MANETs, such as battlefield communications and domestic response & rescue missions.     

基于QoS的认知无线网络低复杂度宽带频谱接入算法

为解决认知无线网络中宽带频谱感知模式的计算量大和感知时间延长等问题,提出了一种基于QoS的认知无线网络低复杂度宽带频谱感知算法。在宽带频谱感知的基础上,设定最优感知信道顺序,同时为了保证次用户之间的同步性,该算法设定次用户不能在检测某一条子信道的同时,在另外的子信道传输数据。信道若是没有被选择进行感知,则其需要等到别的信道感知完之后,再进行数据传输。在该信道选择标准下,并不是所有的信道都被选择感知,故系统总的计算量能得到有效的减小。经过仿真实验分析对比表明,该算法可以有效地平衡次用户系统吞吐量最大化和主用户系统的干扰之间的矛盾。