Interference‐aware spectrum handover for cognitive radio networks

Cognitive radio (CR) is a promising technique for future wireless networks, which significantly improves spectrum utilization. In CR networks, when the primary users (PUs) appear, the secondary users (SUs) have to switch to other available channels to avoid the interference to PUs. However, in the multi‐SU scenario, it is still a challenging problem to make an optimal decision on spectrum handover because of the the accumulated interference constraint of PUs and SUs. In this paper, we propose an interference‐aware spectrum handover scheme that aims to maximize the CR network capacity and minimize the spectrum handover overhead by coordinating SUs’ handover decision optimally in the PU–SU coexisted CR networks. On the basis of the interference temperature model, the spectrum handover problem is formulated as a constrained optimization problem, which is in general a non‐deterministic polynomial‐time hard problem. To address the problem in a feasible way, we design a heuristic algorithm by using the technique of Branch and Bound. Finally, we combine our spectrum handover scheme with power control and give a convenient solution in a single‐SU scenario. Experimental results show that our algorithm can improve the network performance efficiently.Copyright © 2012 John Wiley & Sons, Ltd.     

Performance analysis of dynamic spectrum handoff scheme with variable bandwidth demand of secondary users for cognitive radio networks

Cognitive radio (CR) has attracted considerable attention as a promising technology for solving the current inefficient use of spectrum. In CR networks, available sub-channels are dynamically assigned to secondary users (SUs). However, when a primary user accesses a primary channel consisting of multiple sub-channels, data transmissions of the SUs already using the sub-channels may be terminated. In this paper, we analyze the performance of dynamic spectrum handoff scheme with channel bonding, in which the number of sub-channels used by an SU are variable. We model the multichannel CR network as a multiserver priority queueing system without waiting facility, deriving the blocking probability, the forced termination probability and the throughput for SUs. In terms of the way of forced termination, we consider two policies; one is that SUs using the largest number of sub-channels are forced to terminate their transmissions, and the other is that SUs using the smallest number of sub-channels are chosen for termination. The analysis is also validated by simulation. Numerical examples show that in both forced-termination policies, the throughput of SUs that are forced to terminate their transmissions degrades as the offered load to the system increases.     

A novel approach for energy‐efficient resource allocation in double threshold‐based cognitive radio network

This paper mainly focuses on solving the energy efficiency (EE) maximization problem in double threshold‐based soft decision fusion (SDF) cooperative spectrum sensing (CSS) in the cognitive radio network (CRN). The solution to this objective problem starts with the selection of suitable secondary users (SUs) both for the spectrum sensing and data transmission. Here, energy efficiency is maximized under the constraints of interference to the primary user (PU), an acceptable outage of SUs, the transmission power of the SUs and the probability of false alarm. We propose a novel algorithm called iterative Dinkelbach method (IDM) which jointly optimizes the sensing time and transmission power allocation to the SUs. Further, Lagrangian duality theorem is employed to find the exact power assigned to the SUs. Finally, simulation results are carried out to validate the effectiveness of our proposed scheme by comparing with the other existing schemes. The performance is also analyzed for different system parameters.     

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.     

Modeling and Performance Analysis of Cognitive Radio Networks Using Stochastic Timed Colored Petri Nets

Cognitive radio (CR) is currently one of the most promising information transmission technologies to deal with the problem of spectrum scarcity and spectrum underutilization in wireless communications. CR networks aim to enhance spectrum efficiency to meet the ever-increasing demands of end users. The principle is to provide the opportunity for unlicensed users (secondary users, SUs) to temporarily and dynamically access the unused or sparsely used bandwidth while ensuring that it never interferes or degrades the performance of the incumbent license holders, commonly called primary users (PUs). This raises several challenges to be addressed in CR networks and performance of secondary users is one of the critical issues tackled in this paper. That is, we propose to devise CR networks as a retrial queueing system where PUs have preemptive priority over SUs. To calculate performance measures of the devised model under quite general assumptions about the model parameters, analytical methods are known to require hard calculations and the obtained results are generally not exploitable. For this reason, simulation modeling becomes the last resort to assess the dependability indicators. To this extend, we build the simulation model of the queueing system using Timed Stochastic Colored Petri Nets. Various useful results will be hence drawn while varying network conditions. Both exponential and Erlang distributions are considered for modeling service time of SUs. The obtained results with restrictive assumptions fit the analytical outcomes experienced for quite similar queuing models, which demonstrate the effectiveness of the proposed STCPN simulation model.

     

Transceiver Designs for Interference Alignment Based Cognitive Radio Networks with Energy Harvesting

Cognitive radio (CR) can improve the usage of spectrum resources, although the secondary users (SUs) will cause interference. Interference alignment (IA) is a prospective technique that can manage the interference effectively and has been applied to CR networks. However, interference can be used as an energy source by wireless energy harvesting techniques. In this paper, we consider an underlay CR network consisting of a primary user (PU) and SUs that are either energy harvesting users or information transmission users. The normal IA scheme neglects the priority of the PU, which leads to poor performance, particularly at low signal noise ratio (SNR) values. Three transceiver designs are proposed to improve the information rate of the PU and these benefit from the existence of energy harvesting users, by aligning the interference created by those energy harvesting users at information transmission users. Simulation results are presented to show the proposed designs can significantly improve the performance especially in low SNR situations.     

CATECAS: a content-aware transmission efficiency based channel allocation scheme for cognitive radio users with improved QoE

Cognitive radio (CR) is a promising technology for the upcoming 5G communication which addresses opportunistic channel usage for enhanced spectrum utilization. However, Quality of Service (QoS) provisioning is a major challenge for CR Network due to the service interruption and packet error caused by random primary activities. In addition to this, periodic spectrum sensing for primary user protection reduces the effective throughput of the secondary users (SUs). However, to ensure QoS of SUs especially for video application, throughput enhancement is necessary which can be achieved by efficient spectrum sensing and channel allocation policy. As the QoS requirements are different for different secondary applications, we propose a novel content aware channel allocation scheme that enhances the Quality of Experience (QoE) of SUs. At first, the proposed scheme analyzes the QoS requirements of different SUs and prioritizes them. Consequently, the optimum sensing duration is determined to maximize the transmission efficiency and throughput of SUs. Finally, a novel content aware transmission efficiency-based channel assignment scheme (CATECAS) is proposed for SUs, considering the estimated channel quality and QoS requirements concurrently. Extensive performance analysis of CATESCAS on real-time video and file download applications confirms significant QoE improvement for SUs especially for rapid movement type of video application, which is considered as the most critical among different secondary applications.

     

Optimal Resource Allocation in Heterogeneous MIMO Cognitive Radio Networks

The optimal resource allocation in MIMO cognitive radio networks with heterogeneous secondary users, centralized and distributed users, is investigated in this work. The core aim of this work is to study the joint problems of transmission time and power allocation in a MIMO cognitive radio scenario. The optimization objective is to maximize the total capacity of the secondary users (SUs) with the constraint of fairness. At first, the joint problems of transmission time and power allocation for centralized SUs in uplink is optimized. Afterwards, for the heterogeneous case with both the centralized and distributed secondary users, the resource allocation problem is formulated and an iterative power water-filling scheme is proposed to achieve the optimal resource allocation for both kinds of SUs. A dynamic optimal joint transmission time and power allocation scheme for heterogeneous cognitive radio networks is proposed. The simulation results illustrate the performance of the proposed scheme and its superiority over other power control schemes.     

Energy-Efficiency-Based Power Allocation Scheme in Multi-user Single-DF-Relay Cognitive Networks

Due to the enhancement in both spectral efficiency and energy efficiency, cognitive radio (CR) being combined with relay cooperation technique is deemed as a promising way to realize green-broadband communication in the fifth generation (5G) networks. In this paper, for such CR-relay networks operating in underlay mode, when multiple secondary cognitive users (SUs) share a common cognitive relay in decode-and-forward manner to complete their physical transmissions, system power consumption is investigated. For the scenarios where the co-channel interference to primary users and the peak transmit power of SUs and cognitive relay are constrained, the problem of power allocation in CR-relay network is formulated to minimizing sum-system-consumption. Then, based on the principle that power-consumption minimization is equivalent to energy-efficiency maximization, a novel power allocation scheme is proposed. Further numerical simulation is used to verify the optimality of the proposed power allocation scheme.

     

Joint power allocation and beamforming with users selection for cognitive radio networks via discrete stochastic optimization

Cognitive radio is a promising technique to dynamic utilize the spectrum resource and improve spectrum efficiency. In this paper, we study the problem of mutual interference cancellation among secondary users (SUs) and interference control to primary users (PUs) in spectrum sharing underlay cognitive radio networks. Multiple antennas are used at the secondary base station to form multiple beams towards individual SUs, and a set of SUs are selected to adapt to the beams. For the interference control to PUs, we study power allocation among SUs to guarantee the interference to PUs below a tolerable level while maximizing SUs?? QoS. Based on these conditions, the problem of joint power allocation and beamforming with SUs selection is studied. Specifically, we emphasize on the condition of imperfect channel sensing due to hardware limitation, short sensing time and network connectivity issues, which means that only the noisy estimate of channel information for SUs can be obtained. We formulate the optimization problem to maximize the sum rate as a discrete stochastic optimization problem, then an efficient algorithm based on a discrete stochastic optimization method is proposed to solve the joint power allocation and beamforming with SUs selection problem. We verify that the proposed algorithm has fast convergence rate, low computation complexity and good tracking capability in time-varying radio environment. Finally, extensive simulation results are presented to demonstrate the performance of the proposed scheme.     

Efficient Spectrum Sensing with Minimum Transmission Delay in Cognitive Radio Networks

In cognitive radio (CR) networks, the secondary users (SUs) need to find idle channels via spectrum sensing for their transmission. In this paper, we study the problem of designing the sensing time to minimize the SU transmission delay under the condition of sufficient protection to primary users (PUs). Energy detection sensing scheme is used to prove that the formulated problem indeed has one optimal sensing time which yields the minimum SU transmission delay. Then, we propose a novel cooperative spectrum sensing (CSS) framework, in which one SU’s reporting time can be used for other SUs’ sensing. The analysis focuses on two fusion strategies: soft information fusion and hard information fusion. Under soft information fusion, it is proved that there exists one optimal sensing time that minimizes the SU transmission delay. Under hard information fusion, for time varying channels, the novel multi-slot CSS is derived. The performance of SU transmission delay is studied in both perfect and imperfect reporting channels. Some simple algorithms are derived to calculate the optimal sensing settings that minimize the SU transmission delay. Computer simulations show that fundamental improvement of delay performance can be obtained by the optimal sensing settings. In addition, the novel multi-slot CSS scheme shows a much lower transmission delay than CSS based on general frame structure.     

A unified spectrum sensing and throughput analysis model in cognitive radio networks

Cognitive radio (CR) is a newly developed technology for increasing spectral efficiency in wireless communication systems. In the CR networks, there exist two traditional spectrum‐sharing technologies called spectrum overlay and spectrum underlay. A new hybrid overlay/underlay paradigm has also been discussed in the literature. In this work, we create a unified spectrum sensing and throughput analysis model, which is suitable for overlay, underlay, and hybrid overlay/underlay paradigms in the CR networks. In the proposed model, the energy detection scheme is employed for the spectrum sensing in the network in which the co‐channel interference is present among primary users and secondary users (SUs). The SUs' throughput in the proposed CR system model is then analyzed. The simulations are also carried out for demonstrating the performance of overlay, underlay, and hybrid overlay/underlay paradigms. Copyright © 2013 John Wiley & Sons, Ltd.     

Attack Detection Scheme Against Cooperative Spectrum Sensing Data Falsification on Common Control Channel in Cognitive Radio Networks

Cognitive radio is an intelligent technology designed to help secondary users (SUs) increase their opportunity to access unused spectrum channels while avoiding interference with the primary users. In cognitive radio networks (CRNs), to find the available channels, SUs execute cooperative spectrum sensing and exchange channels-related control information, namely an available channels list (ACL), on a common control channel (CCC) before determining which channels they may transmit. However, some SUs, defined as attackers, could create a security issue by sharing false ACL information with other SUs to increase their own utilization of the available channels, which significantly decreases the performance of CRNs. In this paper, we propose an efficient detection scheme for CCC security to identify any attacker among the cooperating SUs. In the proposed scheme, all SUs share their ACL information on the CCC, with an associated reputation, which is updated according to its own behavior in each cooperation round, to cooperatively identify attackers. An attacker will be excluded from cooperating group with the result that its updated reputation value exceeds a certain threshold. Simulation results show how to further improve the performance of the proposed scheme by choosing optimized thresholds. In addition, we also illustrate that the proposed scheme can achieve considerable performance improvement compared with a attack detection technique COOPON for secure ACL information exchange.     

Optimal Transmission Strategies for Dynamic Spectrum Access in Cognitive Radio Networks

Cognitive radio offers a promising technology to mitigate spectrum shortage in wireless communications. It enables secondary users (SUs) to opportunistically access low-occupancy primary spectral bands as long as their negative effect on the primary user (PU) access is constrained. This PU protection requirement is particularly challenging for multiple SUs over a wide geographical area. In this paper, we study the fundamental performance limit on the throughput of cognitive radio networks under the PU packet collision constraint. With perfect sensing, we develop an optimum spectrum access strategy under generic PU traffic patterns. Without perfect sensing, we quantify the impact of missed detection and false alarm, and propose a modified threshold-based spectrum access strategy that achieves close-to-optimal performance. Moreover, we develop and evaluate a distributed access scheme that enables multiple SUs to collectively protect the PU while adapting to behavioral changes in PU usage patterns. Our results provide useful insight on the trade-off between the protection of the primary user and the throughput performance of cognitive radios.     

Spatiotemporal Sensing in Cognitive Radio Networks

Cognitive radio networks need to continuously monitor spectrum to detect the presence of the licensed users. In this paper, we have exploited spatial diversity in multiuser networks to improve the spectrum sensing capabilities of centralized cognitive radio (CR) networks. We develop a fixed and a variable relay sensing scheme. The fixed relay scheme employs a relay that has a fixed location to help the cognitive network base station detect the presence of the primary user. The variable relay sensing scheme employs cognitive users distributed at various locations as relays to sense data and to improve the detection capabilities. This effectively reduces the average detection time by exploiting spatial diversity inherent in multiuser networks. Finally, we study the network outage probabilities to compare the performances of the fixed and variable relay schemes.     

Resource management with probabilistic performance guarantees in opportunistic networks

This letter proposes a multi-channel parallel transmission mechanism for channel assignment in cognitive radio (CR) networks. The proposed mechanism enables secondary users (SUs) to effectively utilize the spectrum. The main novelty in our mechanism lies in utilizing the parallel transmission capability of CRs while considering the randomness of their operating environment to provide soft guarantees on the performance of SUs. Simulation results show that utilizing CR's parallel transmission capability while considering the time-varying nature of their operating environment allows for higher spectrum utilization and more energy saving.     

Accurate Bluetooth Positioning Using Weighting and Large Number of Devices Measurements

One of the most efficient methods to reduce the dropping and blocking probabilities of the secondary users (SUs) in cognitive radio networks is channel sub-banding strategy. This means that when all the channels are occupied by the primary and secondary users, then the SUs’ channels can be divided into two sub-bands, and two SUs can use a sub-band, simultaneously. In this paper, we propose an opportunistic spectrum sharing system in cognitive radio networks in which, the channel sub-banding strategy is implemented. Furthermore, we describe the problem of channel sub-banding considering the spectrum sensing errors such as false alarm and miss-detection events for both initial and on-going SUs’ calls. Due to unreliable spectrum sensing by the SUs and subsequently possible interference with the primary users, we assume that both primary and secondary users may lose the channel due to the collision. The proposed model is analyzed by a two-dimensional Markov chain model and for performance evaluation, metrics such as blocking and dropping probabilities and channel utilization are derived. Numerical and simulation results show the accuracy of the proposed model which can be used in the evaluation of future cognitive radio networks’ performance.     

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.     

Energy Harvesting in Cognitive Networks with Cooperative Beamforming: Power Allocation and Stability Analysis

Energy harvesting (EH) is a promising technology to improve both energy efficiency and spectral efficiency in cognitive radio (CR) networks. However, due to the randomness of the harvested energy and the interference constraint at the primary users (PUs), the limited transmission power of secondary users (SUs) may reduce the service rate of SUs. To solve this problem, this paper investigates a cooperative transmission method where a zero-forcing beamforming method is used in the EH based secondary network. Considering the transmission power constraint and energy causality, we derive the closed-form solution of the optimal transmission power for the secondary source and relays, which achieves the maximal stable throughput of the secondary network. Numerical results show the impact of different system parameters to the maximal stable throughput. In addition, compared with the traditional decode-and-forward (DF) scheme, the cooperative beamforming method achieves higher stable throughput under an high quality source-to-relay channel.     

认知中继协同无线通信系统功率分配和混合频谱接入方案

文章首先对Underlay 认知-中继协作（cognitive radio relay cooperation, CR-RC）系统信源和中继的功率分配问题进行了研究,获得了Underlay CR-RC系统信源、中继独立功率分配(independent power allocation, IPA）和联合功率分配（joint power allocation, JPA）方案,并给出了基于IPA和JPA的CR-RC系统的中断概率和各态历经容量的封闭解析解;其次通过对Underlay CR-RC系统中断性能的比较分析,提出了高频谱效率、高能量效率的混合Interweave-Underlay CR-RC方案。在该方案中,定义了主、从用户中断概率约束,充分考虑了主、从系统的服务质量(quality of service, QoS),当即使从用户的发射功率为零,主系统的QoS仍不能满足时,从用户以最大功率发送信号,无需考虑其对主用户的影响;当由于很强的主用户干扰,使得从用户的QoS不能得到满足时,从用户不再发射信号,发信功率为零;当主、从系统的QoS能够同时满足时,以Underlay模式工作。