Profit maximization for secondary users in dynamic spectrum auction of cognitive radio networks

As a powerful economic theory, auction mechanism has been extensively studied in dynamic spectrum allocation for cognitive radio networks (CRNs) recently. Different from most of existing works that focused on the mechanism design from the spectrum owner's side, we study from a new perspective on profit maximization of the secondary users (SUs). Because the spectrum auction mechanism has already been designed by the spectrum owner, we derive SUs' optimal bid strategies, which maximize their profits. First, we relax the limitation of SU's value on spectrum band, which is formerly defined as the transmission rate on channel, and introduce the affiliated value considering the impacts from other SUs. Further, the optimal value determination function is derived, which maximizes SU's expected profit; second, we analyze the auctioneer cheating issue, which has great influence on SU's profit, and the Nash equilibrium strategies for both spectrum owner and SUs are derived. Moreover, the repeated auction game mechanism is proposed that resists the auctioneer cheating effectively. Copyright © 2013 John Wiley & Sons, Ltd.     

A novel spectrum handoff switching decision scheme for improved performance of secondary users in cognitive radio network

Spectrum handoff (SH) in the cognitive radio network (CRN) is considered as a key challenging area to enhance the performance of secondary users (SUs) in CRN. If the primary user is detected, the SU may pause and stay on the same channel or may perform SH to another idle channel. An accurate and precise handoff decision improves the overall throughput and quality of experience of end-users. In this paper, we introduce a new SH algorithm and continuous short-sensing strategy to improve the overall throughput of SUs. In addition, we have derived the minimum length of the target channel sequence based on network-specific parameters like desired call dropping probability. Further, an optimum channel search time is obtained to minimize the handoff delay. The simulation result shows that the proposed scheme improves the overall throughput of CRN, and the mean opinion score of different video applications increases by 10%, 4.6%, and 1% for rapid motion, gentle walk, and slight motion types of video applications. In the case of VoIP applications, the maximum simultaneous call is improved by 2 times in the case of G.711, 1.72 times in the case of G.729, and 1.66 times in the case of iLBC.     

Performance analysis of cognitive radio networks for secondary users with slotted central control

This paper deals with analysis, performance evaluation and optimization of cognitive radio networks with central controller. The main principle of this technology is that secondary users are enabled to make opportunistic use of the spectrum part, which is actually unused by the primary users. The considered network enables heterogeneous slotted structure for the channel, in which the secondary user’s packets are transmitted on a slot basis, while the primary user’s packets are forwarded in super-slots, i.e. in fixed length slot-blocks. This heterogeneous slotted channel structure enables more flexible operation leading to more realistic system model of cognitive radio network. We model the cognitive radio networks by preemptive priority queueing model with two classes of customers. We solve the model by applying Markov chain technique and derive the steady-state distributions of the number of primary user’s packets and secondary user’s packets in the system. We provide the formulas for several performance measures including the interruption rate, loss rate, throughput, and average latency of secondary users. After validating the analysis by simulation the influence of the secondary user’s buffer capacity on various system performance measures is investigated. In the last part of the paper we address the question of optimal design of secondary user’s buffer capacity.     

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.     

分布式认知无线电网络中的主动频谱切换

主要研究分布式认知无线电网络中的频谱切换,并提出一种主动的频谱切换方案。认知用户通过感知结果与历史信息建立授权用户的活动模型,预测频谱的使用情况。在不对授权用户产生干扰的前提下,提前安排频谱切换。同时,采用基于蚁群任务分工算法的频谱选择方法,使得认知用户综合考虑通信参数,实现认知用户的按需切换,保证不间断的传输。仿真表明,提出的方案能够提前执行切换,并在较短的时间内完成业务量的传输,同时具备较高的灵活性,适用于分布式认知无线电网络。     

Stochastic spectrum handoff protocols for partially observable cognitive radio networks

Recent studies have been conducted to indicate the ineffective usage of licensed bands due to static spectrum allocation. In order to improve spectrum utilization, cognitive radio (CR) is therefore suggested to dynamically exploit the opportunistic primary frequency spectrums. How to provide efficient spectrum handoff has been considered a crucial issue in the CR networks. Existing spectrum handoff algorithms assume that all the channels can be correctly sensed by the CR users in order to perform appropriate spectrum handoff process. However, this assumption is impractical since excessive time will be required for the CR user to sense the entire spectrum space. In this paper, the partially observable Markov decision process (POMDP) is applied to estimate the network information by partially sensing the frequency spectrums. A POMDP-based spectrum handoff (POSH) scheme is proposed to determine the optimal target channel for spectrum handoff according to the partially observable channel state information. Moreover, a POMDP-based multi-user spectrum handoff (M-POSH) protocol is proposed to exploit the POMDP policy into multi-user CR networks by distributing CR users to frequency spectrum bins opportunistically. By adopting the policies resulted from the POSH and M-POSH algorithms for target channel selection, minimal waiting time at each occurrence of spectrum handoff can be achieved which will be feasible for multimedia applications. Numerical results illustrate that the proposed spectrum handoff protocols can effectively minimize the required waiting time for spectrum handoff in the CR networks.     

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.     

Optimization techniques for spectrum handoff in cognitive radio networks using cluster based cooperative spectrum sensing

Wireless Networks - Spectrum handoff has an undesirable effect in utilizing the space for Secondary user (SU) in the spectrum, which causes a handoff delay in cognitive radio network. The SU...     

A distributed spectrum handoff MSRV protocol for the cognitive radio ad hoc networks

Wireless Networks - Cognitive radio technology provides opportunistic wireless spectrums access for the secondary users (SUs) while primary users (PUs) are dormant. By emergence of a PU in the...     

An adaptive handoff strategy for cognitive radio networks

Spectrum handoff plays an important role in spectrum management as it is the process of seamlessly shifting the on-going transmission of a secondary user (SU) to a free channel without degrading the quality of service. In this paper, we develop an adaptive handoff algorithm that allows an SU to detect the arrival of a primary user (via sensing) and adapt to a reactive or a proactive handoff strategy accordingly. The adaptive handoff scheme first allows an SU to decide whether to stay and wait on current channel or to perform handoff. Then, in case of handoff, an SU intelligently shifts between proactive or reactive handoff modes based on primary use (PU) arrival rate. Further, a PU prioritized Markov approach is presented in order to model the interactions between PUs and SUs for smooth channel access. Numerical results show that the proposed handoff scheme minimizes the blocking probability, number of handoffs, handoff delay and data delivery time while maintaining channel utilization and system throughput at maximal level compared to simple reactive and proactive schemes.     

Impact of secondary user mobility on spectrum handoff under generalized residual time distributions in cognitive radio networks

Cognitive Radio is an emerging technology to accommodate the growing demand for wireless technology via dynamic spectrum access to enhance spectrum efficiency. Spectrum handoff is an important component of Cognitive Radio technology for practical implementation of radio frequency access strategy and better utilization of spectrum in both primary and secondary networks. The probability of spectrum handoff and expected number of spectrum handoffs are key parameters in performance analysis and design of the cognitive radio network. This work presents an analytical model to evaluate the impact of secondary users’ mobility on intra-cell spectrum handoff considering primary users’ activity model in a cognitive radio network. A standard form of intra-cell spectrum handoff probability and expected number of intra-cell spectrum handoffs are derived for complete call duration of a non-stationary secondary user. The probability and expected number of intra-cell spectrum handoffs of a post inter-cell handoff call are also derived for generalized residual time distributions of call holding time and spectrum holes. A detailed analysis of these performance measuring metrics is presented under the impact of departure rate and cell crossing rate of secondary users. The accuracy of the derived analytical result is validated by Monte-Carlo simulation of the model.     

Low-complexity hierarchical spectrum sharing scheme in cognitive radio networks

Fair and efficient spectrum sharing is an important problem in cognitive radios. In view of the clustering cognitive radio network with capacity-limited common channels, this letter proposes a low-complexity hierarchical spectrum sharing method, which is carried out in two steps. First, the spectrum holes are allocated to clusters in a fair and distributed way by using the list-coloring method. Then, all the channels in every spectrum hole are allocated by cluster head to minimize the outage probability by using the maximum matching method. Such a scheme not only takes a great advantage of the low signaling overhead and computation complexity, but also achieves the suboptimal outage performance which is close to that of the exhaustive search.     

Spectrum handoff scheme with multiple attributes decision making for optimal network selection in cognitive radio networks

It is envisaged that in future Cognitive Radio (CR) networks deployment, multiple radio access networks may coexist. The networks may have different characteristics in terms of multiple attributes. CRs will have choices of selecting the optimal network out of the available networks. Optimal network selection is a challenging task that can be performed by spectrum handoff with Multiple Attribute Decision Making (MADM). The spectrum handoff decision with MADM provides wider and optimal choice with quality of service. This motivates the devolopment of a spectrum handoff scheme with MADM methods such as simple additive weighting, a technique for order preference by similarity to the ideal solution, a grey relational analysis and a cost function based method, which is the objective of this study. The CR preferences are based on voice, video and data services, called triple play services. The numerical results show that all MADM methods are effective for selecting the optimal network for spectrum handoff with a reduced complexity for the spectrum handoff decision. The paper shows that the proposed spectrum handoff scheme can be effectively implemented to select the optimal network according to triple play services in CR networks.     

Performance evaluation of sequential spectrum handoff in cognitive radio networks: a single‐user case

Powerful spectrum handover schemes enable cognitive radios to exploit transmission opportunities in primary users’ channels appropriately. In this paper, modeling and performance evaluation of sequential spectrum sensing strategy are addressed. To this end, the average number of handovers required for finding a transmission opportunity is evaluated assuming that a prior knowledge of the presence and absence probabilities of the primary users is available. Moreover, the average throughput maximization of a secondary user by optimizing its spectrum sensing time is formulated, and a set of illustrative numerical results is then presented to validate the analytical analysis.Copyright © 2013 John Wiley & Sons, Ltd.     

Performance analysis of a dynamic handoff scheme in wireless networks with heterogeneous call arrival processes

The Guard Channel Scheme (GCS) and Handoff Queueing Scheme (HQS) are the popular and practical strategies to prioritize handoff calls in wireless cellular networks. A key issue of giving handoff calls the higher priority is how to achieve a tradeoff among the handoff call blocking probability, new call blocking probability and handoff delay. This paper extends GCS and HQS and presents an efficient handoff scheme that dynamically manages the channels reserved for handoff calls depending on the current status of the handoff queue. A three-dimensional Markov model is developed to analyze the performance of this scheme and investigate the desirable performance tradeoff. The Poisson process and Markov-Modulated-Poisson-Process (MMPP) are used to model the arrival processes of new and handoff calls, respectively. The accuracy of this model is evaluated through the extensive comparison of the analytical results to those obtained from discrete-event simulation experiments. Performance measures in terms of the mean number of calls in the system, aggregate response time, aggregate call blocking probability, handoff call blocking probability, new call blocking probability and handoff delay are evaluated. The analytical model is used to investigate the effects of the number of channels originally reserved for handoff calls, the number of dynamic channels, and the ratio of the rate of handover calls to the aggregate arrival rate on the system performance.     

Efficient secondary access with intelligent spectrum sensing in cognitive radio networks

In cognitive radio networks, cooperative sensing can significantly improve the performance in detection of a primary user via secondary users (SUs) sharing their detection results. However, a large number of cooperative SUs may induce great sensing delay, which degrades the performance of secondary transmissions. In this paper, we jointly consider cooperative sensing and cognitive transmission in cognitive radio networks, aiming to achieve efficient secondary access with low sensing overhead under both the sensing time and reporting power limitations, where primary users are guaranteed to be sufficiently protected. We first propose an adaptive sensing scheme to lower the detection time while not degrading the detection probability. Then, based on the proposed adaptive sensing scheme, an efficient cognitive transmission protocol is well designed, which improves the throughput of secondary transmissions while ensuring the QoS of primary transmissions. We analyze the performance for the proposed secondary access framework in terms of misdetection probability, average detection time and normalized secondary throughput, respectively, and derive their closed‐form expressions over Rayleigh fading channels with considering the reporting errors accordingly. We also study the problems of optimizing the number of cooperative SUs to minimize the misdetection probability and average detection time, and maximize the normalized secondary throughput for proposed framework. Simulation results reveal that the proposed framework outperforms the traditional case significantly. Copyright © 2013 John Wiley & Sons, Ltd.     

A reliable cooperative spectrum detection scheme in cognitive radio networks

Reliable spectrum detection of the primary user (PU) performs an important role in the cognitive radio network since it’s the foundation of other operations. Spectrum sensing and cognitive signal recognition are two key tasks in the development of cognitive radio (CR) technology in both commercial and military applications. However, when the CR terminals receiving signals have little knowledge about the channel or signal types, these two tasks will become much more difficult. In this paper, we propose a reliable cooperative spectrum detection scheme, which combines the cooperative spectrum sensing with distributed cognitive signal recognition. A novel improved cooperative sensing algorithm is achieved by using a credibility weight factor and the “tug-of-war” rule, which is based on the double threshold detection and Dempster–Shafer theory, to determine whether the PU signals exist. In this scheme, cognitive signal recognition can be used to identify the signal type when the PU signal is present. During the cognitive signal recognition processing, the CR terminals make local classification of the received signals by using Daubechies5 wavelet transform and Fractional Fourier Transform, and send their recognition results to the globe decision making center. A distributed processing uses these cognitive terminals’ local results to make final decisions under the Maximum Likelihood estimation algorithm. Simulation results show that the proposed method can achieve good sensing probability and recognition accuracy under the Additive White Gaussian Noise channel.     

Spectrum auction with interference constraint for cognitive radio networks with multiple primary and secondary users

Extensive research in recent years has shown the benefits of cognitive radio technologies to improve the flexibility and efficiency of spectrum utilization. This new communication paradigm, however, requires a well-designed spectrum allocation mechanism. In this paper, we propose an auction framework for cognitive radio networks to allow unlicensed secondary users (SUs) to share the available spectrum of licensed primary users (PUs) fairly and efficiently, subject to the interference temperature constraint at each PU. To study the competition among SUs, we formulate a non-cooperative multiple-PU multiple-SU auction game and study the structure of the resulting equilibrium by solving a non-continuous two-dimensional optimization problem, including the existence, uniqueness of the equilibrium and the convergence to the equilibrium in the two auctions. A distributed algorithm is developed in which each SU updates its strategy based on local information to converge to the equilibrium. We also analyze the revenue allocation among PUs and propose an algorithm to set the prices under the guideline that the revenue of each PU should be proportional to its resource. We then extend the proposed auction framework to the more challenging scenario with free spectrum bands. We develop an algorithm based on the no-regret learning to reach a correlated equilibrium of the auction game. The proposed algorithm, which can be implemented distributedly based on local observation, is especially suited in decentralized adaptive learning environments as cognitive radio networks. Finally, through numerical experiments, we demonstrate the effectiveness of the proposed auction framework in achieving high efficiency and fairness in spectrum allocation.     

认知频谱切换延时及用户容量的排队论分析

为了分析认知无线电系统中授权用户享有更高优先级对认知用户频谱切换造成的影响,提出了一种虚拟排队切换模型,对有强制中断率限制系统中的认知频谱切换延时进行了分析;并利用分段近似的方法给出了在切换超时概率较小环境下强制中断率和认知用户容量的解析表达. 仿真与数值计算验证了虚拟排队切换模型的有效性,同时也比较了不同授权用户行为对认知频谱切换延时及用户容量造成的影响。     

Artificial bee colony–based spectrum handoff algorithm in wireless cognitive radio networks

In this work, we proposed a new artificial bee colony–based spectrum handoff algorithm for wireless cognitive radio systems. In our wireless cognitive radio system, primary users, secondary users, and related base stations exist in the same communication environment. For our artificial bee colony–based algorithm, secondary users that always struggle to discover an idle channel have a leading role. While honey bees work hard to find the best‐quality nectar source for foraging, secondary users try to find idle channels for making communication. In this way, secondary users are organized for different missions such as sensing and handoff similar to honey bees to minimize spectrum handoff delay by working together. In the spectrum handoff stage, some secondary users must sense the spectrum so that the interrupted secondary user may perform the spectrum handoff process. In our developed spectrum handoff algorithm, the spectrum availability characteristic is observed on the basis of the missions of the bees in the artificial bee colony algorithm with the aim of minimizing the spectrum handoff delay and maximizing probability of finding an idle channel. With the help of the algorithm that is developed using the artificial bee colony, spectrum handoff delay of secondary users is considerably decreased for different number of users without reducing probability of finding an available channel.