An auction‐based MAC protocol for cognitive radio networks

Cognitive radio and dynamic spectrum sharing systems use innovative spectrum management techniques that allow different systems to share the same frequency band to utilize the radio spectrum in an efficient way. In this paper, we propose a novel cognitive media access control protocol for cognitive radio networks under the property‐rights model, in which secondary users are divided into several nonoverlapping groups, and each group uses the proposed auction algorithm to bid for required channels from the auctioneer appointed by primary users. Simulations indicate that our proposed media access control protocol can effectively utilize spectrum resources, achieve high system efficiency, and guarantee the fairness of channel allocation among groups. Copyright © 2011 John Wiley & Sons, Ltd.     

Spectrum redistribution for cognitive radios using discriminatory spectrum double auction

With the reformation of spectrum policy and the development of cognitive radio, secondary users will be allowed to access spectrums licensed to primary users. Spectrum auctions can facilitate this secondary spectrum access in a market‐driven way. To design an efficient auction framework, we first study the supply and demand pressures and the competitive equilibrium of the secondary spectrum market, considering the spectrum reusability. In well‐designed auctions, competition among participants should lead to the competitive equilibrium according to the traditional economic point of view. Then, a discriminatory price spectrum double auction framework is proposed for this market. In this framework, rational participants compete with each other by using bidding prices, and their profits are guaranteed to be non‐negative. A near‐optimal heuristic algorithm is also proposed to solve the auction clearing problem of the proposed framework efficiently. Experimental results verify the efficiency of the proposed auction clearing algorithm and demonstrate that competition among secondary users and primary users can lead to the competitive equilibrium during auction iterations using the proposed auction framework. Copyright © 2011 John Wiley & Sons, Ltd.     

Auction-Based Throughput Maximization in Cognitive Radio Networks Under Interference Constraint

Cognitive radio is an emerging technique to improve the utilization of radio frequency spectrum in wireless communication networks. That is, spectrum efficiency can be increased significantly by giving opportunistic access of the frequency bands to a group of cognitive users to whom the band has not been licensed. In this paper, as a cross layer application (MAC and physical layers) of graph theory, we consider the problem of throughput maximization of spectrum allocation in cognitive radio networks under interference constraint. We propose a novel auction-based channel allocation mechanism which tries to maximize both total and primary users’ utilities while satisfying signal to interference ratio constraint on primary receivers so that transmitted packets will be successfully received, without controlling secondary user powers. For comparison we discuss a greedy algorithm as well, however, one that does not handle interference issue. In order to compare results of proposed and greedy algorithms, we propose net throughput by taking into account outage probability of primary receiver. Simulation results show that exposing higher SINR (outage) threshold not only decreases total gain and primary users’ utilities but also worsens channel distribution performance. On the other hand adding auction mechanism significantly increases total gain throughput and primary user’ s utility. Particularly, up to SINR threshold values of 20 dBs, auction provides outstanding performance and proposed algorithm has total throughput results close to those of the greedy one even though no interference constraint is applied in the greedy algorithm. Another noticeable point of simulation results is crossover of net throughputs of proposed and greedy algorithms at a SINR threshold level after which results of ABSA-UNIC and NASA-UNIC are much better. This clearly shows superiority of proposed mechanism.     

On spectrum allocation in cognitive radio networks: a double auction-based methodology

Auction is often applied in cognitive radio networks due to its efficiency and fairness properties. An important issue in designing an auction mechanism is how to utilize the limited spectrum resource in an efficient manner. In order to achieve this goal, we propose a predictive double spectrum auction model in this paper. Our auction model first obtains the bidding range from statistical analysis, and then separates the interval into independent states and employees a Markovian prediction based algorithm to generate guidelines for the bidding range of primary and secondary users, respectively. Comparing with existing approaches, our proposed auction model is more efficient in spectrum utilization and satisfies the economic properties. Extensive simulation results show that our work achieves an utilization ratio up to 91 %.     

Spectrum leasing based on Nash Bargaining Solution in cognitive radio networks

Cognitive radio is becoming an emerging technology that has the potential of dealing with the stringent requirement and scarcity of the radio spectrum resource. In this paper, we focus on the dynamic spectrum access of cognitive radio networks, in which the primary user (PU) and secondary users (SUs) coexist. In property-rights model, the PU has property of the bandwidth and may decide to lease it to secondary network for a fraction of time in exchange for appropriate remuneration. We propose a cooperative communication-aware spectrum leasing framework, in which, PU selects SUs as cooperative relays to help transmit information, while the selected SUs have the right to decide their payment made for PU in order to obtain a proportional access time to the spectrum. Then, the spectrum leasing scheme is cast into a Nash Bargaining Problem, and the Nash Bargaining Solution (NBS) can be used to fairly and efficiently address the resource allocation between PU and secondary network, enhancing both the utility of PU and secondary network. Numerical results show that spectrum leasing based on NBS is an effective method to improve performance for cognitive radio networks.     

The Master-Slave Stochastic Knapsack Modeling for Fully Dynamic Spectrum Allocation

Scarcity problem of radio spectrum resource stimulates the research on cognitive radio technology, in which dynamic spectrum allocation attracts lots of attention. For higher access efficiency in cognitive radio context, we suggest a fully dynamic access scheme for primary and secondary users, which is modeled by a master-slave stochastic knapsack process. Equilibrium behavior of this knapsack model is analyzed: expressions of blocking probability of both master and slave classes are derived as performance criterion, as well as forced termination probability for the slave class. All the theoretic results are verified by numeric simulations. Compared to traditional opportunistic spectrum access (OSA), which can be regarded as half dynamic due to primary users?? rough preemption, our scheme leads to less termination events for the secondary users while keeping the same performance for the primary class, thus promotes the system access performance. Nonideal spectrum sensing algorithm with detection error is also taken into consideration to evaluate its impact on system access performance, which is a practical issue for implementation.     

认知无线电网络中基于跨层设计的能效优化算法

为提高认知无线电网络中次用户节点的能量有效性,该文基于连续时间马尔科夫理论对次用户的频谱感知和接入过程进行联合建模,对影响次用户传输能效的主要因素进行了分析,提出了一种基于跨层设计的能量有效优化算法。该算法可有效减小主用户非时隙返回信道对次用户能量有效性的影响,并通过联合优化感知时间和接入概率,使次用户在感知性能和传输能效间实现了有效折衷。仿真结果表明,本文算法相对于仅考虑频谱感知或接入策略的单层优化算法,可使次用户的能量有效性得到较大提高。      

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.     

Dynamic spectrum access in IEEE 802.22- based cognitive wireless networks: a game theoretic model for competitive spectrum bidding and pricing [accepted from open call]

The emerging IEEE 802.22-based wireless regional area network technology will use the same radio spectrum currently allocated for TV service. This standard will use the concept of cognitive radio based on dynamic spectrum access to provide wireless access services in a large coverage area. A brief overview of the current state of the IEEE 802.22 standard is provided with a particular emphasis on the spectrum management (i.e., spectrum sensing and dynamic spectrum access) in this standard. Key research issues related to spectrum trading among TV broadcasters, WRAN service providers, and IEEE 802.22-based cognitive radio users are identified. To this end, a hierarchical spectrum trading model is presented to analyze the interaction among WRAN service providers, TV broadcasters, and WRAN users. In this model a double auction is established among multiple TV broadcasters and WRAN service providers who sell and buy the radio spectrum (i.e., TV bands), respectively. Again, multiple WRAN service providers compete with each other by adjusting the service price charged to WRAN users. We propose a joint spectrum bidding and service pricing model for WRAN service providers to maximize their profits. A non-cooperative game is formulated to obtain the solution in terms of the number of TV bands and the service price of a service provider. Numerical results are presented on the performance of this joint spectrum bidding and pricing model.     

Cooperative relay to improve diversity in cognitive radio networks

Recent studies demonstrated that dynamic spectrum access can improve spectrum utilization significantly by allowing secondary unlicensed users to dynamically share the spectrum that is not used by the primary licensed users. Cognitive radio was proposed to promote the spectrum utilization by opportunistically exploiting the existence of spectrum ?holes.? Meanwhile, cooperative relay technology is regarded widely as a key technology for increasing transmission diversity gain in various types of wireless networks, including cognitive radio networks. In this article, we first give a brief overview of the envisioned applications of: cooperative relay technology to CRNs, cooperative transmission of primary traffic by secondary users, cooperative transmission between secondary nodes to improve spatial diversity, and cooperative relay between secondary nodes to improve spectrum diversity. As the latter is a new direction, in this article we focus on this scenario and investigate a simple wireless network, where a spectrum-rich node is selected as the relay node to improve the performance between the source and the destination. With the introduction of cooperative relay, many unique problems should be considered, especially the issue for relay selection and spectrum allocation. To demonstrate the feasibility and performance of cooperative relay for cognitive radio, a new MAC protocol was proposed and implemented in a universal software radio peripheral-based testbed. Experimental results show that the throughput of the whole system is greatly increased by exploiting the benefit of cooperative relay.     

A Survey of Cooperative Games for Cognitive Radio Networks

Cooperative cognitive radio networks are new cognitive radio paradigm. Cooperative communication approaches, such as cooperative spectrum sensing and cooperative spectrum sharing, are playing key roles in the development of cognitive radio networks. To achieve the high performance, a cooperative cognitive communication framework is often used to model various cooperative spectrum sensing or sharing scenarios. However, its implementation faces numerous challenges due to the complexity of mobility and traffic models, the needs of dynamic spectrum access, the heterogeneous requirements from different users, and the distributed structure of the network. Fortunately, cooperative game theory can be used to formulate and model the interactions among licensed and unlicensed users for spectrum sensing and spectrum sharing to efficiently allocate spectrum resource in the highly dynamic and distributed radio environment. In this paper, we first present the cooperative communication technologies and describe their existing challenges, then introduce different game solutions, after that, we discuss several cooperative game strategies, and analyze the associated their applications in cognitive radio networks, at final, some open directions for future research on economic strategies in cooperative communication in cognitive radio networks are proposed.     

A game theoretic approach for energy‐efficient communications in multi‐hop cognitive radio networks

In multi‐hop cognitive radio networks, it is a challenge to improve the energy efficiency of the radio nodes. To address this challenge, in this paper, we propose a two‐level Stackelberg game model, where the primary users and the secondary users act as the leaders and the followers, respectively. Based on the game model, our proposed scheme not only considers the power allocation problem for secondary users but also takes into account the price of spectrum. First, we give the cognitive radio network model, and show how to set up the game theoretic model in multi‐hop cognitive radio networks. We then analyze this problem and show the existence and uniqueness of the Nash equilibrium point for the game. We also study the impact of the spectrum price of the primary users in the cognitive radio network and study how to select the best price for the primary users to maximize their own profit. Finally, we implement simulations to show the performance of our schemes. Our work gives an insight on how to improve the energy efficiency and allocate spectrum resources in multi‐hop cognitive radio networks. Copyright © 2016 John Wiley & Sons, Ltd.     

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.     

A distributed network coded control channel for multihop cognitive radio networks

Designing a solution for multihop cognitive radio networks poses several challenges such as the realization of the control channel, the detection of primary users, and the coordination of secondary users for dynamic spectrum access purposes. In this article we discuss these challenges and propose a solution that aims to meet most of them. The proposed solution is completely distributed, and does not need dedicated spectrum resources for control purposes, but rather leverages on a virtual control channel that is implemented by having users exchange control information whenever they meet in a particular channel, using network coding techniques for better dissemination performance. Due to these aspects, our proposal represents a significant improvement over existing dynamic spectrum access and multichannel MAC solutions. We discuss the effectiveness of our scheme in multihop cognitive ad hoc networks, where secondary users need to opportunistically access the spectrum at those locations and times at which it is not used by primary users. Finally, we report the results of an evaluation study assessing the performance of the proposed scheme with respect to different system and scenario parameters.     

基于强化学习的合作频谱分配算法

为了解决认知无线电网络中的频谱分配问题,提出了一种基于用户体验质量的合作强化学习频谱分配算法,将认知网络中的次用户模拟为强化学习中的智能体,并在次用户间引入合作机制,新加入用户可以吸收借鉴其他用户的强化学习经验,能够以更快的速度获得最佳的频谱分配方案;并且在频谱分配过程中引入了主用户和次用户之间的价格博弈因素,允许主用...     

Optimization of Time-Domain Combining Cooperative Spectrum Sensing in Cognitive Radio Networks

In cognitive radio networks, the secondary users take chances to access the spectrum without causing interference to the primary users so that the spectrum access is dynamic and somewhat opportunistic. Therefore, spectrum sensing is of significant importance. In this paper, we propose a novel time-domain combining cooperative spectrum sensing framework, in which the time consumed by reporting for one secondary user is also utilized for other secondary users’ sensing. We focus on the optimal sensing settings of the proposed sensing scheme to maximize the secondary users’ throughput and minimize the average sensing error probability under the constraint that the primary users are sufficiently protected. Some simple algorithms are also derived to calculate the optimal solutions. Simulation results show that fundamental improvement of the achievable throughput and sensing performance can be obtained by optimal sensing settings. In addition, our proposed scheme outperforms the general frame structure on either achievable throughput or the performance of average sensing error probability.     

Dynamic cooperator selection in cognitive radio networks

The primary objective of cooperation in cognitive radio (CR) networks is to increase the spectrum access efficiency and improve the network performance. However, Byzantine adversaries or unintentional erroneous conduct in cooperation can lead to destructive behavior of CR users that can decrease their own and others’ performances. This work presents a dynamic solution for cooperation reliability in conditions with constraints typical for a CR network. Specifically, in CR networks, the information on the success of cooperation can be limited only to cases with interference; when malicious, cooperators can be completely non-correlated and can alter behavior; and the set of available cooperators can dynamically change in time. In order to face these challenges, each CR user autonomously decides with whom to cooperate by learning cooperators behavior with a reinforcement learning (RL) algorithm. This RL algorithm determines the suitability of the available cooperators, and selects the most appropriate ones to cooperate with the objective to increase the efficiency of spectrum access in CR networks. The simulation results demonstrate the learning capabilities of the proposed solution and especially its reliable behavior under highly unreliable conditions.     

A Parallel Repeated Auction for Spectrum Allocation in Distributed Cognitive Radio Networks

Cognitive radio (CR) is applied to solve spectrum scarcity. Although the auction theory and learning algorithm have been discussed in previous works, their combination is not yet researched in the distributed CR networks, where secondary users (SUs) can occupy several channels simultaneously by assuming that one channel can be accessed by at most one SU. A parallel repeated auction scheme is proposed to solve resource allocation in multi-user multi-channel distributed spectrum-overlay CR networks. A novel bid scheme in the light of the first-price sealed auction is designed to balance the system utility and allocation fairness. The proposed auction scheme can be developed based on a learning algorithm and be applied to the scenarios where the cooperation among SUs is unavailable. Under the assumption of limited entry budget, SUs can directly decide whether or not to participate in spectrum auction by comparing the possible bid with access threshold which can be applied into situations that SUs have different transmit power. Theoretical analysis and simulation results show that, compared with original myopic scheme and original genie-aided scheme, the proposed auction scheme can obtain a considerable improvement in efficiency and fairness, especially with adequate available resources.     

基于多智能体强化学习的动态频谱分配方法

针对认知无线电网络中多个异质用户具有不同的服务质量(QoS)要求,提出一种基于多智能体强化学习的动态频谱分配方法.该方法从用户满意度角度出发,以用户体验质量(QoE)作为系统的评价指标,构建多个虚拟智能体,模拟多个用户以合作方式与环境进行交互学习,融合各个用户的学习和频谱决策结果,实现频谱资源优化分配.仿真结果表明,在...     

Diffusing-CRN k-means: an improved k-means clustering algorithm applied in cognitive radio ad hoc networks

With increasing demand of new wireless applications and increasing number of wireless user’s, problem of spectrum scarcity arises. In this context, cognitive radio supports dynamic spectrum access to address spectrum scarcity problem. Cognitive radio defined the cognitive radio nodes by their ability to intelligently adapt the environment to achieve specific objectives through advanced techniques. The variance of channel availability for cognitive radio nodes degrades connectivity and robustness of this type of network; in this case the use of clustering is an effective approach to meet this challenge. Indeed, the geographical areas are homogeneous in terms of type of radio spectrum, radio resources are better allocated by grouping cognitive radio nodes per cluster. Clustering is interesting to effectively manage the spectrum or routing in cognitive radio ad hoc networks. In this paper, we aim to improve connectivity and cooperativeness of cognitive radio nodes based on the improvement of the k-means algorithm. Our proposed algorithm is applied in cognitive radio ad hoc networks. The obtained results in terms of exchange messages and execution time show the feasibility of our algorithm to form clusters in order to improve connectivity and cooperativeness of cognitive radio nodes in the context of cognitive radio ad hoc networks.