Blockchain-Based MCS Detection Framework of Abnormal Spectrum Usage for Satellite Spectrum Sharing Scenario

In this paper, the problem of abnormal spectrum usage between satellite spectrum sharing systems is investigated to support multi-satellite spectrum coexistence. Given the cost of monitoring, the mobility of low-orbit satellites, and the directional nature of their signals, traditional monitoring methods are no longer suitable, especially in the case of multiple power level. Mobile crowdsensing(MCS), as a new technology, can make full use of idle resources to complete a variety of perceptual tasks. However, traditional MCS heavily relies on a centralized server and is vulnerable to single point of failure attacks. Therefore, we replace the original centralized server with a blockchain-based distributed service provider to enable its security. Therefore, in this work, we propose a blockchain-based MCS framework, in which we explain in detail how this framework can achieve abnormal frequency behavior monitoring in an inter-satellite spectrum sharing system. Then, under certain false alarm probability, we propose an abnormal spectrum detection algorithm based on mixed hypothesis test to maximize detection probability in single power level and multiple power level scenarios, respectively. Finally, a Bad out of Good(BooG) detector is proposed to ease the computational pressure on the blockchain nodes. Simulation results show the effectiveness of the proposed framework.

Covert Communication with a Spectrum Sharing Relay in the Finite Blocklength Regime

In this paper,we investigate the feasibility and performance of the covert communication with a spectrum sharing relay in the finite blocklength regime.Specifically,the relay opportunistically forwards the source's messages to the primary receiver or conveys the covert messages to its own receiver via the sharing spectrum,while the warden attempts to detect the transmission.First,we derive a lower bound on the covertness constraint,and the analytical expressions of both the primary average effective covert throughput(AECT)and sum AECT are presented by considering the overall decoding error performance.Then,we formulate two optimization problems to maximize the primary and sum AECT respectively by optimizing the blocklength and the transmit power at the source and the relay.Our examinations show that there exists an optimal blocklength to maximize the primary and sum AECT.Besides,it is revealed that,to maximize the primary AECT,the optimal transmit power of each hop increases as its channel quality deteriorates.Furthermore,in the optimization for maximizing the sum AECT,the optimal transmit power at the source equals to zero when the channel quality from relay to the secondary receiver is not weaker than that from relay to the primary receiver.

Directed Acyclic Graph Blockchain for Secure Spectrum Sharing and Energy Trading in Power IoT

Peer-to-peer(P2P)spectrum sharing and energy trading are promising solutions to locally satisfy spectrum and energy demands in power Internet of Things(IoT).However,implementation of largescale P2P spectrum sharing and energy trading confronts security and privacy challenges.In this paper,we exploit consortium blockchain and Directed Acyclic Graph(DAG)to propose a new secure and distributed spectrum sharing and energy trading framework in power IoT,named spectrum-energy chain,where a set of local aggregators(LAGs)cooperatively confirm the identity of the power devices by utilizing consortium blockchain,so as to form a main chain.Then,the local power devices verify spectrum and energy micro-transactions simultaneously but asynchronously to form local spectrum tangle and local energy tangle,respectively.Moreover,an iterative double auction based micro transactions scheme is designed to solve the spectrum and energy pricing and the amount of shared spectrum and energy among power devices.Security analysis and numerical results illustrate that the developed spectrum-energy chain and the designed iterative double auction based microtransactions scheme are secure and efficient for spectrum sharing and energy trading in power IoT.

Optimal Energy-Efficient Transmission for Hybrid Spectrum Sharing in Cooperative Cognitive Radio Networks

In order to improve the energy efficiency(EE)in cognitive radio(CR),this paper investigates the joint design of cooperative spectrum sensing time and the power control optimization problem for the secondary user systems to achieve the maximum energy efficiency in a cognitive network based on hybrid spectrum sharing,meanwhile considering the maximum transmit power,user quality of service(QoS)requirements,interference limitations,and primary user protection.The optimization of energy efficient sensing time and power allocation is formulated as a non-convex optimization problem.The Dinkelbach’s method is adopted to solve this problem and to transform the non-convex optimization problem in fractional form into an equivalent optimization problem in the form of subtraction.Then,an iterative power allocation algorithm is proposed to solve the optimization problem.The simulation results show the effectiveness of the proposed algorithms for energy-efficient resource allocation in the cognitive network.

Inter-Operator Interference Coordination for CoPrimary Spectrum Sharing in UDN

Co-primary spectrum sharing for multiple operators has been utilized to fully explore the spectrum resources and thus improve the spectrum efficiency. The inter-operator interference(IOI) problem should be seriously considered in order to achieve the mentioned target, especially under the scenario of the ultradense network(UDN) in the fifth generation(5G) wireless systems. To solve this problem, we propose an asymmetrical power levels based soft IOI coordination mechanism. The shared spectrum pool is consisted of three separated parts, where each part can be dynamically adjusted according to the minimal spectrum demand from each operator. Furthermore, different power masks are configured to different parts for each operator. The simulation results show that the proposed mechanism can improve the network spectrum efficiency significantly.

Improved spectrum sharing algorithm based on feedback control information in cognitive radio networks

In order to avoid the system performance deterioration caused by the wireless fading channel and imperfect channel estimation in cognitive radio networks, the spectrum sharing problem with the consideration of feedback control information from the primary user is analyzed. An improved spectrum sharing algorithm based on the combination of the feedback control information and the optimization algorithm is proposed. The relaxation method is used to achieve the approximate spectrum sharing model, and the spectrum sharing strategy that satisfies the individual outage probability constraints can be obtained iteratively with the observed outage probability. Simulation results show that the proposed spectrum sharing algorithm can achieve the spectrum sharing strategy that satisfies the outage probability constraints and reduce the average outage probability without causing maximum transmission rate reduction of the secondary user.

Intelligent Spectrum Management Based on Radio Map for Cloud-Based Satellite and Terrestrial Spectrum Shared Networks

Cloud-based satellite and terrestrial spectrum shared networks(CB-STSSN)combines the triple advantages of efficient and flexible net-work management of heterogeneous cloud access(H-CRAN),vast coverage of satellite networks,and good communication quality of terrestrial networks.Thanks to the complementary coverage characteristics,any-time and anywhere high-speed communications can be achieved to meet the various needs of users.The scarcity of spectrum resources is a common prob-lem in both satellite and terrestrial networks.In or-der to improve resource utilization,the spectrum is shared not only within each component but also be-tween satellite beams and terrestrial cells,which intro-duces inter-component interferences.To this end,this paper first proposes an analytical framework which considers the inter-component interferences induced by spectrum sharing(SS).An intelligent SS scheme based on radio map(RM)consisting of LSTM-based beam prediction(BP),transfer learning-based spec-trum prediction(SP)and joint non-preemptive prior-ity and preemptive priority(J-NPAP)-based propor-tional fair spectrum allocation is than proposed.The simulation result shows that the spectrum utilization rate of CB-STSSN is improved and user blocking rate and waiting probability are decreased by the proposed scheme.

Proactive Spectrum Monitoring for Suspicious Wireless Powered Communications in Dynamic Spectrum Sharing Networks

This paper studies the proactive spec-trum monitoring with one half-duplex spectrum moni-tor(SM)to cope with the potential suspicious wireless powered communications(SWPC)in dynamic spec-trum sharing networks.The jamming-assisted spec-trum monitoring scheme via spectrum monitoring data(SMD)transmission is proposed to maximize the sum ergodic monitoring rate at SM.In SWPC,the suspi-cious communications of each data block occupy mul-tiple independent blocks,with a block dedicated to the wireless energy transfer by the energy-constrained suspicious nodes with locations in a same cluster(symmetric scene)or randomly distributed(asymmet-ric scene)and the remaining blocks used for the in-formation transmission from suspicious transmitters(STs)to suspicious destination(SD).For the sym-metric scene,with a given number of blocks for SMD transmission,namely the jamming operation,we first reveal that SM should transmit SMD signal(jam the SD)with tolerable maximum power in the given blocks.The perceived suspicious signal power at SM could be maximized,and thus so does the correspond-ing sum ergodic monitoring rate.Then,we further reveal one fundamental trade-off in deciding the op-timal number of given blocks for SMD transmission.For the asymmetric scene,a low-complexity greedy block selection scheme is proposed to guarantee the optimal performance.Simulation results show that the jamming-assisted spectrum monitoring schemes via SMD transmission achieve much better perfor-mance than conventional passive spectrum monitor-ing,since the proposed schemes can obtain more accu-rate and effective spectrum characteristic parameters,which provide basic support for fine-grained spectrum management and a solution for spectrum security in dynamic spectrum sharing network.

Rayleigh Quotient Based Interference Alignment Spectrum Sharing in MIMO Cognitive Radio Networks

An interference alignment(IA)spectrum sharing method based on Rayleigh quotient is proposed for distributed multi-user multi-antenna cognitive radio(CR) networks.The interference from cognitive users(CUs)to the primary(PR) system is constrained through the Rayleigh quotients of channel matrices to deal with the absence of PR users(PUs) in the IA process.As a result,the IA scheme can be applied in CR networks without harmful interference to PUs.Compared with existing IA based spectrum sharing methods,the proposed method is more general because of breaking the restriction that CUs can only transmit on the idle sub-channels of the PR system.Moreover,in comparison to other four spectrum sharing methods applicable in general scene,the proposed method leads to improved performance of achievable sum rate of the CR system as well as guarantees the transmission of PUs.

A Novel Two-Stage Dynamic Spectrum Sharing Scheme in Cognitive Radio Networks

In order to enhance the efficiency of spectrum utilization and reduce communication overhead in spectrum sharing process, we propose a two-stage dynamic spectrum sharing scheme in which cooperative and noncooperative modes are analyzed in both stages. In particular, the existence and the uniqueness of Nash Equilibrium(NE) strategies for noncooperative mode are proved. In addition, a distributed iterative algorithm is proposed to obtain the optimal solutions of the scheme. Simulation studies are carried out to show the performance comparison between two modes as well as the system revenue improvement of the proposed scheme compared with a conventional scheme without a virtual price control factor.

Achievement of Interference Alignment in General Underlay Cognitive Radio Networks: Scenario Classification and Adaptive Spectrum Sharing

Interference alignment(IA) is suitable for cognitive radio networks(CRNs).However, in IA spectrum sharing(SS) process of general underlay CRNs, transmit power of cognitive radio transmitters usually should be reduced to satisfy interference constraint of primary user(PU), which may lead to low signalto-noise-ratio at cognitive radio receivers(CRRs). Consequently, sum rate of cognitive users(CUs) may fall short of the theoretical maximum through IA. To solve this problem,we propose an adaptive IA SS method for general distributed multi-user multi-antenna CRNs. The relationship between interference and noise power at each CRR is analyzed according to channel state information, interference requirement of PU, and power budget of CUs. Based on the analysis, scenarios of the CRN are classified into 4 cases, and corresponding IA SS algorithms are properly designed. Transmit power adjustment, CU access control and adjusted spatial projection are used to realize IA among CUs. Compared with existing methods, the proposed method is more general because of breaking the restriction that CUs can only transmit on the idle sub-channels. Moreover, in comparison to other five IA SS methods applicable in general CRN, the proposed method leads to improved achievable sum rate of CUs while guarantees transmission of PU.

IRS-Enabled Spectrum Sharing:Interference Modeling,Channel Estimation and Robust Passive Beamforming

Intelligent reflecting surface(IRS),with its unique capability of smartly reconfiguring wireless channels,provides a new solution to improving spectrum efficiency,reducing energy consumption and saving deployment/hardware cost for future wireless networks.In this paper,IRS-enabled spectrum sharing is investigated,from the perspectives of interference modeling,efficient channel estimation and robust passive beamforming design.Specifically,we first characterize the interference in a spectrum sharing system consisting of a single primary user(PU)pair and a single secondary user(SU)pair,and extend it to the large-scale network by leveraging the Poisson point process(PPP).Then,we propose an efficient channel estimation framework based on decoupling the cascaded IRS channels.Moreover,the tradeoff between spectrum efficiency and energy efficiency is derived from the view of channel estimation accuracy.Finally,we discuss the robust passive beamforming design in presence of imperfect channel estimation and nonideal/discrete phase shifts.It is hoped that this paper provides useful guidance for unlocking the full potential of IRS for achieving efficient spectrum sharing for future wireless networks.

Hierarchical Spectrum Sharing Networks

A spectrum heterogeneity analysis in the cognitive radio network is conducted in this paper. Subsequently,a spectrum-heterogeneity-based hierarchical spectrum sharing(HSS) network for cognitive radio is proposed.The corresponding method of classifying available spectrums and communication based on the proposed architecture is also presented. Based on the above network architecture,we propose a reference protocol architecture.Research on these protocol function blocks,such as spectrum sensing,spectrum manager,and so on,is conducted. Numerical results show that HSS can provide a considerable extension to available spectrums so that the spectral utility may be further improved.

Performance Analysis of Wireless Network with Opportunistic Spectrum Sharing via Cognitive Radio Nodes

Cognitive radio （CR） is found to be an emerging key for efficient spectrum utilization. In this paper, spectrum sharing among service providers with the help of cognitive radio has been investigated. The technique of spectrum sharing among service providers to share the licensed spectrum of licensed service providers in a dynamic manner is considered. The performance of the wireless network with opportunistic spectrum sharing techniques is analyzed. Thus, the spectral utilization and efficiency of sensing is increased, the interference is minimized, and the call blockage is reduced.

Opportunistic spectrum sharing in software defined wireless network

Over the past few decades, the world has witnessed a rapid growth in mobile and wireless networks（MWNs） which significantly change human life. However, proliferating mobile demands lead to several intractable challenges that MWN has to face. Software-defined network is expected as a promising way for future network and has captured growing attention. Network virtualization is an essential feature in software-defined wireless network（SDWN）, and it brings two new entities, physical networks and virtual networks. Accordingly, efficiently assigning spectrum resource to virtual networks is one of the fundamental problems in SDWN. Directly orienting towards the spectrum resource allocation problem, firstly, the fluctuation features of virtual network requirements in SDWN are researched, and the opportunistic spectrum sharing method is introduced to SDWN. Then, the problem is proved as NP-hardness. After that, a dynamic programming and graph theory based spectrum sharing algorithm is proposed.Simulations demonstrate that the opportunistic spectrum sharing method conspicuously improves the system performance up to around 20%–30% in SDWN, and the proposed algorithm achieves more efficient performance.

A Novel Cooperative Spectrum Sharing Algorithm Based on Optimal Cognitive Radio User Selection

In this paper, we consider the problem of cognitive radio (CR) user selection to maximize overall CR network (CRN) throughput when the available spectrum bandwidth is less than the demand by all CR users. We formulate optimal CR user selection problem. Then, based on approximation of the average received signal to interference plus noise ratio (SINR) and adaptive modulation and coding (AMC), we estimate the required bandwidth of CR users with different required quality of services (QoSs). Using the principle of optimality, we propose a novel cooperative spectrum sharing algorithm for a CRN. The proposed algorithm not only achieves exhaustive search performance but also its complexity is in the order of N × M versus 2N for exhaustive search, where N is the number of CR users, and M is the spectrum pool size. Extensive simulation results illustrate that the proposed algorithm significantly outperforms the existing algorithms that ignore optimal CR user selection. Also, these results illustrate a better fairness criterion than those of previous works.

Cooperative spectrum sharing of multiple primary users and multiple secondary users

This paper proposes a multiple-input multiple-output （MIMO） based cooperative dynamic spectrum access （DSA） framework that enables multiple primary users （PUs） and multiple secondary users （SUs） to cooperate in spectrum sharing. By exploiting MIMO in cooperative DSA, SUs can relay the primary traffic and send their own data at the same time, which greatly improves the performance of both PUs and SUs when compared to the non- MIMO time-division spectrum sharing schemes. Especially, we focus on the relay selection optimization problem among multiple PUs and multiple SUs. The network-wide cooperation and competition are formulated as a bargaining game, and an algorithm is developed to derive the optimal PU-SU relay assignment and resource allocation. Evaluation results show that both primary and secondary users achieve significant utility gains with the proposed framework, which gives all of them incentive for cooperation.

Joint utility optimization algorithm for secure hybrid spectrum sharing

As the rapid development of wireless communication networks has resulted in better user experiences,the spectrum resources occupied and energy consumption have increased considerably and resulted in great costs.To address the energy consumption and cost problems of spectrum sharing in cognitive radio networks,a hybrid spectrum sharing model combining the free spectrum of authorized users and the leased spectrum of mobile network operators is given.Based on the hybrid model,a function of throughput and costs,including energy consumption and transaction costs,is constructed,and a joint utility optimization problem is analyzed.The transactions between secondary users and primary users are performed on the consortium blockchain on which users can directly trade spectrum and the transaction information is recorded.In order to improve the joint utility,the Lagrange multiplier method is used to achieve the optimal solution for the sensing time,the number of secondary users involved in sensing,and the transmission power.The simulation results show that the joint utility optimization algorithm proposed in this paper can achieve higher joint utility under the constraints of the minimum throughput requirement and maximum transmission power.

Relay Selection and Power Allocation in Amplify-and-Forward Cognitive Radio Systems Based on Spectrum Sharing

In this paper, we consider a spectrum sharing scheme that is a joint optimization of relay selection and power allocation at the secondary transmitter, which aims to achieve the maximum possible throughput for the secondary user. This paper considers the scenario where the primary user is incapable of supporting its target signal-to-noise ratio (SNR). More especially, the secondary transmitter tries to assist the primary user with achieving its target SNR by cooperative amplify-and-forward (AF) relaying with two-phase. By exhaustive search for all candidate secondary transmitters, an optimal secondary transmitter can be selected, which not only can satisfy the primary user’s target SNR, but also maximize the secondary user’s throughput. The optimal secondary transmitter acts as a relay for the primary user by allocating a part of its power to amplify-and-forward the primary signal over the primary user’s licensed spectrum bands. At the same time, as a reward, the optimal secondary transmitter uses the remaining power to transmit its own signal over the remaining licensed spectrum bands. Thus, the secondary user obtains the spectrum access opportunities. Besides, there is no interference between the primary user and the secondary user. We study the joint optimization of relay selection and power allocation such that the secondary user’s throughput is maximized on the condition that it satisfies the primary user’s target SNR. From the simulation, it is shown that the joint optimization of relay selection and power allocation provides a significant throughput gain compared with random relay selection with optimal power allocation (OPA) and random relay selection with water-filling power allocation (WPA). Moreover, the simulation results also shown that our spectrum sharing scheme obtains the win-win solution for the primary system and the secondary system.

A Spectrum Sharing Model that Counters Eavesdropping:An Energy Efficiency View

Wireless transmission is subject to eavesdropping.When wireless transmission ceases,the assigned frequency channel is unused,wasting the spectral opportunity given.In this study,a spectrum sharing model that reduces spectral wastage and protects against eavesdropping is proposed.First,cognitive radio(CR)shares the channel access with primary user(PU).When the CR senses that the channel is idle,CR can seize the unoccupied channel for its own use.If the channel is detected to be occupied by PU,CR transmits artificial noise to jam any potential eavesdropper.To what extent is this operation beneficial to the CR?The main concern of this study is the energy efficiency(μ)of CR,i.e.,the ratio of channel throughput to its energy consumption.The relationship betweenμand the percentage of frame duration allocated for sensing(τ)was investigated.This study contributes a novel theoretical expression that allows us to find the optimalμandτvalues,denoted byμ∗andτ∗.With the availability of this expression,the relationships between(μ∗,τ∗)and other important system parameters can be understood thoroughly.Our investigation reveals that strong CR signal will result in highμ∗without the need of increasingτ∗.On the other hand,a strong primary signal allows a shortτ∗and it improvesμ∗.High sampling rate for sensing may be unnecessary,as it does not improveμ∗significantly.A more demanding target probability of detection requires a higher sensing duration,but it has insignificant impact onμ∗.