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This paper proposes a radio-protected area (RPA) estimation model that achieves full protection and avoids overprotection by adding an appropriate margin to the extended-Hata (EH) model, for realizing efficient spectrum sharing in the V-High-band. This additional margin, called location gain, is a location-dependent value that accounts for knife-edge losses calculated from topographic information. This study experimentally obtains the location gain by conducting VHF-band-based propagation experiments in urban and suburban areas. Subsequently, we developed an estimation formula for the location gain using topographic data, which include correction terms based on the experimental data. As a result, RPA can be estimated using only the topographic data, excluding the need for propagation experiments. The proposed model resolved the problems of the EH model (incomplete protection) and free-space (FS) model (overprotection). In urban and suburban areas, the proposed model achieved full protection and over 99.7% reduction in the RPA size of the FS model when the threshold of the received power for determining the RPA was set to –80 dBm.

The exponential growth of internet connected systems has generated numerous challenges, such as spectrum shortage issues, which require efficient spectrum sharing (SS) solutions. Complicated and dynamic SS systems can be exposed to different potential security and privacy issues, requiring protection mechanisms to be adaptive, reliable, and scalable. Machine learning (ML) based methods have frequently been proposed to address those issues. In this article, we provide a comprehensive survey of the recent development of ML based SS methods, the most critical security issues, and corresponding defense mechanisms. In particular, we elaborate the state-of-the-art methodologies for improving the performance of SS communication systems for various vital aspects, including ML based cognitive radio networks (CRNs), ML based database assisted SS networks, ML based LTE-U networks, ML based ambient backscatter networks, and other ML based SS solutions. We also present security issues from the physical layer and corresponding defending strategies based on ML algorithms, including Primary User Emulation (PUE) attacks, Spectrum Sensing Data Falsification (SSDF) attacks, jamming attacks, eavesdropping attacks, and privacy issues. Finally, extensive discussions on open challenges for ML based SS are also given. This comprehensive review is intended to provide the foundation for and facilitate future studies on exploring the potential of emerging ML for coping with increasingly complex SS and their security problems.

Spectrum sharing in radar bands with interference forecasting for enhanced radar protection can help design proactive resource allocation solutions which can achieve high data rates for wireless communication networks on one hand and help protect the incumbent radar systems. We consider radar spectrum sharing in 5.6GHz where a weather radar operates as a primary system and the dominant secondary system is an enterprise network consisting of access points (APs) in a university campus. Our work models transmit the power of the APs as a time series with multinomial distribution based on real collected data. The aggregated interference due to the transmissions from the APs at the radar is forecasted using a long short-term memory (LSTM) based neural network. Monte Carlo dropout is utilized to generate prediction intervals that capture the uncertainties in the interference from the APs. Finally, by using both average and upper limits of predicted interference time series a cloud-assisted efficient sharing and radar protection algorithm is proposed. Tracking the rotating radar is not required in the proposed system. The results show that the proposed efficient sharing and radar protection system ensures better radar protection and increased throughput for wireless communication users.

This paper investigates the challenges and opportunities for assigning spectrum for private 5G networks, with particular emphasis on the 3.5 GHz band and regulation issued by the Danish spectrum authority Energistyrelsen. We are chiefly interested in the dilemma between providing sufficient and clean spectrum for a private network versus ensuring that high network density can be supported. Indoor and outdoor scenarios are considered, and the performance impact of interference on different levels of service availability are investigated. We develop and propose new solutions for enhanced spectrum regulation options leveraging native 5G features, such as bandwidth part, to support denser outdoor and indoor deployments that can enhance best effort traffic and simultaneously protect spectrum for critical and delay sensitive traffic. System-level simulations show that our proposals can protect critical services and significantly increase the capacity per network in dense deployments.

In this letter, a reconfigurable intelligent surface (RIS)-enabled successive interference cancellation (SIC)-based spectrum sharing (SS) scheme is proposed for SS networks where multiple transceiver pairs communicate over the same spectrum at the same time. The key idea is to apply the SIC technique at each receiver and utilize RIS simultaneously, so as to reduce the interference among different transceiver pairs and to focus energy. Specifically, to minimize the total power consumption at all the transmitters under given data rate constraints, the decoding order at each receiver, the reflection coefficients at RIS, and the transmit power at each transmitter are jointly optimized. The formulated problem is a mixed-combinatorial-and-continuous optimization problem and thus is difficult to solve. To address this, a low-complexity but effective decoding order determining method is first proposed. Given the decoding orders, the reflection coefficients and the transmit power are alternately optimized with the help of the semidefinite relaxation method. Substantial performance gains are shown compared with traditional RIS-enabled SS scheme without SIC. Post-print / Final draft

Future deployment of 5G NR base stations in the 6425–7125 MHz band raises numerous concerns over the long-term impact on the satellite transponders located in geostationary orbit. To study this impact and understand whether 5G NR may cause adverse effect to the spaceborne receivers, the research which estimated the interference levels to the satellite bent pipe links was done. The study presents the evaluation of aggregate interference from 5G NR base stations located inside the victim satellites’ footprints using Monte-Carlo analysis and calculation of signal-to-noise degradation and bit error rates of the fixed-satellite service (FSS) bent-pipe transponders for each scenario. The results of the study showed the feasibility of co-existence between 5G NR and satellite systems in the 6425–7125 MHz bands, and that no negative impact on the performance of the satellite links is expected.

In this article, the dynamic spectrum accessing techniques-the overlay, underlay, and hybrid spectrum-sharing approaches-are exploited for the military communication. Furthermore, the importance of the energy efficiency of cognitive radio (CR) networks (CRNs) for military applications is discussed. We also emphasize security threats over the physical layer and their mitigation in CRNs. Finally, we explore why the cross-layer design of protocols is preferred for greater energy efficiency and security.

In spectrum sharing systems based on spectrum trading, user locations are vital for the efficiency of dynamic channel reuse. However, both primary users (PUs) and secondary users (SUs) undertake the risk of location information leakage: a malicious PU may illegally collect SUs’ location information to manipulate market decisions; a malicious SU would threat a PU’s operational privacy by inferring the PU’s location through seemingly inoffensive queries. To protect both PUs’ and SUs’ location information in spectrum trading, a bilateral privacy preservation framework is introduced in this paper. A game-theoretic approach based on the Stackelberg model is proposed to achieve the tradeoff between the privacy-preserving level and user utility. With the proposed approach, both PUs and SUs can maximize their utilities while maintaining their location privacy to desired levels. Simulation results demonstrate that the proposed approach can effectively enhance user utility gain and strengthen user privacy guarantee by flexibly adjusting their privacy levels in practice.

A proactive spectrum monitoring and spectrum monitoring data (SMD) transmission coexistence system is investigated in dynamic spectrum sharing network, where a spectrum monitor (SM) aims to monitor the spectrum information from the electromagnetic signal sent by the suspicious transmitter to the suspicious destination by using a portion of its antennas and transmit its SMD to the spectrum data fusion center by using the rest antennas. The SMD transmission of the SM can also be employed to jam the suspicious destination to realise the effective proactive spectrum monitoring. Thus, the precoding and antenna selection scheme are jointly designed at the SM to maximise the sum of the achievable spectrum monitoring rate and the SMD transmission rate. The scenario that the SM can assess the statistical channel state information of the suspicious links based on the spectrum information obtained from the spectrum database as the spectrum management node is then considered. The spectrum monitoring/SMD transmission success probability is also derived, and a trade‐off between them is further revealed. Simulation results show that the proposed schemes can obtain higher sum rate of the spectrum monitoring and the SMD transmission, which also verifies its effectiveness and above “security‐reliability” trade‐off.

6G communication research is currently in the early stage. A consensus on 6G has been achieved that ultra-reliable low latency communication (URLLC) is still an important application as it is in 5G. The spectrum resources are scarce to support the massive throughput demands, leading to unbearable latency. Also, the collisions in the shared spectrum make the channels unreliable. The problems in unlicensed bands are more severe due to interference among multiple communication technologies. Therefore, it is urgent to design efficient spectrum sharing algorithms to support URLLC in 5G and the emerging 6G. In this article, we explore the related 3GPP standards, recall the recent advances in spectrum sharing algorithms, and analyze the challenges of spectrum sharing in 5G/6G. We also provide potential research fields in future 5G/6G applications.

The main goal of vehicular communication is to provide a more safe and efficient vehicular operation. The challenge in a Vehicle-to-Everything (V2X) network is to provide reliable connectivity for the Vehicle-to-Vehicle (V2V) links and high data rate connectivity for the Vehicle-to-Infrastructure (V2I) links at the same time. This requirement leads to spectrum sharing in vehicular communication. As the vehicular systems increases, the transmit power levels increases in the environment which in turn causes harmful effects on the atmosphere. The objective of this paper is to analyze the graph-based spectrum sharing algorithms that are available for vehicular communication and to develop a power optimization algorithm based on Hidden Markov Model (HMM) and to incorporate it into these algorithms in such a way to achieve better sum capacity for the V2I links along with a guaranteed reliability for the V2V links.

In overlapping spectrum sharing, due to the complexity of cognitive environment, it is a real challenge for a secondary user (SU) to correctly sense the usage of the spectrum in real time. To tackle this challenge, a social awareness-aided transmit power control policy for SUs is developed. First, a social network composed of a group of third-party sensing nodes that do not share the spectrum with the PU is established, which helps an SU collect the power information of the PU. Then, we design a Dueling Deep Q-Network (DQN) model to achieve efficient dynamic spectrum sharing between the PU and the SU with the power information collected in the social network. Experimental results show that the spectrum sharing success rate is higher and the comprehensive performance is improved with the sensing nodes selected by the social relationship. Moreover, compared with other deep reinforcement learning (DRL) algorithms, the performance of Dueling DQN is more stable on our targeted spectrum sharing problem.

This letter analyzes the performance of a cellular system that shares spectrum with a nearby rotating radar. The analysis is based on stochastic geometry and combines opportunistic with concurrent spectrum sharing. We derive expressions for the cellular probability of coverage taking into consideration the radar guard zone and the operating parameters of both the radar and the cellular system. Results show that allowing eNBs inside the radar guard zone to operate when not in the radar beam improves the coverage and service of the cellular system compared to the case of a strictly silent guard zone.

To efficiently utilize nonexclusive underwater acoustic frequencies, we propose an Underwater Cooperative Spectrum Sharing (UCSS) protocol for a centralized underwater cognitive acoustic network that mainly consists of two parts. In the first part, to check the random occurrence of interferers periodically, the time domain is divided into frames that consist of a sensing and a non-sensing sub-frame. Then, we set the ratio of the two sub-frames to enhance the sensing rate via simulations. As a result, there exists the upper limit of the ratio, which can be used for determining the proportion of the sensing time within a frame. The second part is to design two heuristic resource allocation (RA) algorithms. One is a multiround RA (MRRA), where a central entity allocates a data channel (i.e., resource) to a CU each round so that multiple rounds are executed until no CUs need to be allocated or there is a lack of data channels. The other is a single-round RA (SRRA), where a CU is allocated to as many data channels as its QoS within a round. We also specify four rules to determine the allocation order of the CUs: random, fixed, high-QoS-based, and low-channel allocation-rate-based. In this study, we investigate the best RA allocation order pair supporting the highest channel allocation rate and fairness index via extensive simulations. It is shown that the MRRA outperformed the SRRA, regardless of allocation orders at any conditions, and the random and low-channel allocation-rate-based allocation orders with MRRA supported the best performance. In particular, even without the optimization process, the MRRA guarantees more than 95% fairness.

Ultra-narrowband (UNB) communications has become a signature feature for many emerging low-power wide-area (LPWA) networks. Specifically, using extremely narrowband signals helps the network connect more Internet-of-things (IoT) devices within a given band. It also improves robustness to interference, extending the coverage of the network. In this paper, we study the coexistence capability of UNB networks and their scalability to enable massive access. To this end, we develop a stochastic geometry framework to analyze and model UNB networks on a large scale. The framework captures the unique characteristics of UNB communications, including the asynchronous time-frequency access, signal repetition, and the absence of base station (BS) association. Closed-form expressions of the transmission success probability and network connection density are presented for several UNB protocols. We further discuss multiband access for UNB networks, proposing a low-complexity protocol. Our analysis reveals several insights on the geographical diversity achieved when devices do not connect to a single BS, the optimal number of signal repetitions, and how to utilize multiple bands without increasing the complexity of BSs. Simulation results are provided to validate the analysis, and they show that UNB communications enables a single BS to connect thousands of devices even when the spectrum is shared with other networks., This paper is accepted for publication in the IEEE Journal on Selected Areas in Communications. arXiv admin note: text overlap with arXiv:1811.11092

With a massive number of Internet-of-Things (IoT) devices connecting with the Internet via 5G or beyond 5G (B5G) wireless networks, how to support massive access for coexisting cellular users and IoT devices with quality-of-service (QoS) guarantees over limited radio spectrum is one of the main challenges. In this paper, we investigate the multi-operator dynamic spectrum sharing problem to support the coexistence of rate guaranteed cellular users and massive IoT devices. For the spectrum sharing among mobile network operators (MNOs), we introduce a wireless spectrum provider (WSP) to make spectrum trading with MNOs through the Stackelberg pricing game. This framework is inspired by the active radio access network (RAN) sharing architecture of 3GPP, which is regarded as a promising solution for MNOs to improve the resource utilization and reduce deployment and operation cost. For the coexistence of cellular users and IoT devices under each MNO, we propose the coexisting access rules to ensure their QoS and the priority of cellular users. In particular, we prove the uniqueness of the Stackelberg equilibrium (SE) solution, which can maximize the payoffs of MNOs and WSP simultaneously. Moreover, we propose an iterative algorithm for the Stackelberg pricing game, which is proved to achieve the unique SE solution. Extensive numerical simulations demonstrate that, the payoffs of WSP and MNOs are maximized and the SE solution can be reached. Meanwhile, the proposed multi-operator dynamic spectrum sharing algorithm can support more than almost 40% IoT devices compared with the existing no-sharing method, and the gap is less than about 10% compared with the exhaustive method.

Due to increasing demands for spectral resources in both communication and radar systems, the radio frequency electromagnetic spectrum is becoming more and more crowded with interfering nuisances. In order to tackle the scarcity of available spectral intervals, in recent years a multitude of sensing algorithms have been developed for improving spectrum sharing. Among these, two-dimensional (2-D) spectrum sensing can be used to obtain space-frequency electromagnetic spectrum awareness. Specifically, this approach makes it possible to optimize the spectrum usage of certain spectrum portions whose occupancy varies both temporally and spatially. In this article, we evaluate the effectiveness of certain space-frequency map recovery algorithms relying on the use of commercially available hardware. To this end, we employ an inexpensive four-channel coherent receiver, using software-defined radio components, for emitter localization. Hence, after proper calibration of the receiving system, the acquired samples are used to evaluate the performance of different signal processing strategies which exploits the inherent block-sparsity of the overall profile. At the analysis stage, results reveal the effectiveness of such algorithms.

Opportunistic availability of licensed frequency bands enables the secondary users (SUs) to avail the radio spectrum dynamically. Cognitive radio (CR) paradigm extends the dynamic spectrum access techniques to sense for free channels (called spectrum holes) which can be efficiently redistributed amongst SUs. Motivated by the adaptive technology in CR, this paper introduces a sealed-bid double auction mechanism which aims to obtain an effective allocation of the unused radio spectrum. The proposed auction model adopts multi-channel allocation where one SU can access more than one available channel, while imposing the constraints for dynamics in spectrum opportunities and varying channel availability time amongst SUs. Previously designed double auctions miss out the CR constraints which can further degrade the network performance. Also, multi-winner allocation is induced in the model which encourages spectrum reuse by allowing a common channel to be assigned to multiple non-interfering SUs. A preference list of channels is maintained at each SU using which SUs offer their bid values for the heterogeneous channels which the primary owners are competing to lease. To organize channel specific groups of non-interfering SUs, a bidder group formation algorithm is developed such that members of a winner group get access to a common channel. The auctioneer formulates a winner determination strategy and a pricing strategy which achieves truthfulness while assigning the idle spectrum. Effectiveness of the proposed model is studied by comparing it with an existing work which shows that channel allocation gets significantly improved on deploying the proposed model.

Rising popularity of 5G communications is making tremendous demands on the cellular network operators for providing true 5G services to the users. With limited numbers of 5G users initially, the investments for 5G services can be very high. In the early stage of 5G deployments, the 5G cells would not be lavishly spread and there would be 5G coverage holes. The operators can provide seamless services to the 5G users by inter working with the existing 4G Long-Term Evolution (LTE) network. The 5G inter working with fully deployed LTE would not only provide fast and seamless coverage but would also provide economic viability to the network operators. In this paper we survey and consolidate the 4G-5G inter working solutions that can assist in attaining the insight about various inter working possibilities and their challenges. It is important that a network operator is able to optimize its deployed infrastructure while being able to guarantee fast and seamless transition to 5G for its subscribers. To this regard, we evaluate the performance and radio resource management challenges for different 4G-5G dual connectivity options proposed by 3rd Generation Partnership Project (3GPP) standardization. We also discuss spectrum sharing possibilities between 4G and 5G wireless networks. Finally, various research challenges and discussions on path for migration to 5G standalone networks are also presented.

In this letter, we investigate an overlay cognitive satellite terrestrial network (OCSTN), where the secondary terrestrial network assists the primary satellite communication in exchange for the opportunities of spectrum access. To achieve a win-win cooperation of the satellite and terrestrial networks in the OCSTN, we propose a cognitive region to determine the conditions that terrestrial nodes can work as effective relays to cooperate with the satellite network in a time-splitting spectrum sharing manner. Specifically, we first analyze the ergodic rates of the satellite and terrestrial networks. On this basis, we design a cognitive region seeking the feasible location set of the secondary relay and the corresponding range of time splitting ratios, which can improve the satellite communication performance while enabling the transmission of terrestrial network.

Spectrum sensing aims to sense the potential spectrum resources available in the cognitive radio environment. It is also the premise of spectrum management and spectrum sharing in cognitive radio systems. To perceive the primary user’s activity and make full use of spectrum holes, rapid detection of a broad frequency span is an essential part of cognitive radio technology. Reducing the observation time for the data collection, the data storage requirements, and hardware/software computational complexity are urgent and challenging issues in wideband spectrum sensing. High accuracy power spectral density estimation is not the primary requirement; of course, the accuracy must be controlled within the appropriate range and can support the primary user activity’s determination. This paper proposes a sub-Nyquist wideband spectrum sensing method based on compressive covariance sensing for the rapid wideband spectrum sensing. Compared with the traditional Nyquist-rate method, this method can use low-speed ADC to detect wideband signals and effectively control the observation time and computational complexity. This paper’s main contributions include: (1) developing a sub-Nyquist sampling structure based on the multi-coset sampling banks, (2) proposing a coarse-grained power spectral density estimation method for wideband spectrum sensing with short observation time and low complexity. Simulations show that the proposed method exhibits this method is suitable for fast spectral detection. At the same time, the error of spectrum analysis is basically within the acceptable range.

We propose a new primary protection method for Dynamic Spectrum Access (DSA), in which a secondary system uses a frequency band assigned to a primary system. Following a DSA implementation plan in Japan, we take care of a practical scenario where a primary system’s transmission station (PTS) moves along a predefined course or area, and a corresponding primary reception station (PRS) keeps its antenna boresight facing towards the moving PTS. For accurate interference calculation from the secondary to the primary systems in this scenario, the proposed method takes the movement of the PTS into account and predicts a range of angle variation of the PRS’s antenna boresight based on received signal powers from the PTS to the PRS. We conducted computer simulations in three different practical scenarios to demonstrate the effectiveness of the proposed method. The simulation results show that the proposed method can increase the number of available secondary base stations (SBSs) by up to 1.93 times compared to a conventional method.

The emergence of beyond-licensed spectrum sharing in FR1 (0.45–6 GHz) and FR2 (24–52 GHz) along with the multi-antenna narrow-beam-based directional transmissions demand a wideband spectrum sensing in temporal and spatial domains. We referred to it as ultrawideband angular spectrum sensing (UWAS), and it consists of digitization followed by the characterization of the wideband spectrum. In this article, we design and develop a state-of-the-art UWAS prototype using universal software radio peripheral (USRPs) and LabVIEW NXG for validation in the real-radio environment. Since 5G is expected to co-exist with LTE, the transmitter generates the multidirectional multiuser wideband traffic via LTE specific single-carrier frequency division multiple access (SC-FDMA) approach. At the receiver, the first step of wideband spectrum digitization is accomplished using a novel approach of integrating sparse antenna-array with reconfigurable sub-Nyquist sampling (SNS). The reconfigurable SNS allows the digitization of noncontiguous spectrum via low-rate analog-to-digital converters, but it needs intelligence to choose the frequency bands for digitization. We explore a multiplay multi-armed bandit-based learning algorithm to embed intelligence. Compared with previous works, the proposed characterization (frequency band status and direction-of-arrival estimation) approach does not need prior knowledge of received signal distribution. The detailed experimental results for various spectrum statistics, power gains, and antenna array arrangements validate the functional correctness, superiority, and feasibility of the proposed UWAS over state-of-the-art approaches.

Traffic growth is anticipated to be 1000 times in future fifth generation (5G) networks, which necessitates dense deployment of small cells in a heterogeneous environment. Currently, heterogeneous networks (HetNets) are being considered as the most promising solution to improve coverage and capacity in both outdoor and indoor environments. However, to reap the benefits of HetNets, efficient spectrum sharing techniques are inevitable due to the scarcity of spectral resources. Traditionally, WiFi (2.4/5.0 GHz unlicensed spectrum) has been used to offload macrocells employing licensed bands in cellular networks. However, with the advent of Long Term Evolution in the unlicensed spectrum (LTE-U), offloading cellular networks has been more efficient. In this article, we describe LTE-U WiFi HetNet architecture along with deployment scenarios in detail. We outline the technical challenges that hinder the effective utilization of unlicensed bands in LTE-U WiFi HetNets. The primary challenge is to design an efficient spectrum sharing mechanism for the coexistence of different radio access technologies (i.e., LTE-U and WiFi). Continuous interference from LTE-U to WiFi results in starved WiFi users. We discuss potential solutions to this problem, and present a case study for a joint user association and power allocation method for LTE-U WiFi HetNets with the objective to maximize the sum rate.

The explosive growth on emerging Internet-of-Things (IoT) applications makes our telecommunications networks confront twofold challenges. One is to provide sufficient flexibility for service diversity. The other is the shortage on spectrum. Network slicing and spectrum sharing have been deemed as two prominent solutions, which, however, are barely jointly studied in the literature. In this article, standing on both aspects, we propose a service-oriented spectrum-aware RAN-slicing trading (SSRT) scheme to achieve a dynamic on-demand RAN slicing under the spectrum sharing scenario. For the SSRT scheme, we jointly slice multidimensional resources, including heterogeneous spectrums (licensed and shared), time, and network facilities (nodes, radios, and powers). In particular, considering the uncertainty of shared spectrums, we distinguish them from the traditional licensed ones to fulfill different types of sessions, which are classified into delay tolerant and delay sensitive. To achieve an effective isolation, we construct a 4-D conflict graph and formulate the slice generation problem into a mixed-integer nonlinear programming (MINLP) problem, where a cross-layer resource allocation based on a hybrid transmission mode is designed for the customization. To cope with the difficulties when solving the problem, we employ the column generation algorithm to obtain the final slicing result over all the resources. The simulation results have shown the effectiveness of the proposed scheme.

The cognitive radio (CR) opens new paradigms of opportunistic utilization of unused frequency spectrum through spectrum sharing. Dynamic spectrum access (DSA) provides an effective solution to chan...

Summary In the last five years, the satellite community has witnessed growing interest in the delivery of Broadband Services from non‐geostationary orbit (NGSO) systems. However, accessing the enti...

This letter investigates the effect of the interference due to spectrum sharing between terrestrial and satellite systems. Based on a realistic coexistence model, we provide an exact closed-form outage probability expression of the satellite link in the presence of the terrestrial interference. We assume Nakagami fading both for terrestrial and satellite links, with an additional consideration for the shadowed Rician fading satellite link. Numerical results show that uncontrolled terrestrial interference can significantly degrade the outage performance of the satellite link. The obtained formulas are useful in predicting and preventing harmful interference when designing coexistence mechanisms for terrestrial and satellite systems.

Extravagant demands for wireless communications have resulted in the shortage of spectrum, such that unlicensed spectrum bands are overcrowded, whereas licensed bands are not utilized efficiently. Moreover, content discovery and retrieval using the traditional host-centric approach of IP-based networks adds more burden on the wireless spectrum, such that, each time a request is initiated by the mobile service requester, a new routing path is discovered to retrieve the service from the service provider. Cognitive radio (CR) technology has been proposed to enable efficient and opportunistic spectrum band usage through the utilization of vacant licensed channels. This can offer huge spectrum to enable efficient large-scale deployment for IoT networks. Moreover, Information Centric Networking (ICN) has been proposed to decouple the service requester from the provider such that in-network content caching is used to allow for the retrieval of services within a mobile node’s proximity. The integration of CR and ICN will be essential for enabling envisioned IoT services within smart cities. In this article, we consider the multi-user single-transceiver coordinated spectrum access problem in CR-IoT networks under the overlay spectrum sharing model. We formulate the spectrum access problem as a multi-stage rate/channel assignment optimization problem. The objective is to maximize the overall network throughput by maximizing the achieved sum-rate over all contending CR-IoT devices. Specifically, we propose a novel resource-constrained channel assignment policy that provides a proper utilization of the available time–frequency units. The proposed policy also exploits the packet fragmentation capability to further enhance network throughput. Moreover, we envision a scenario where our proposed solution can be adapted to information-centric cognitive radio-based networking for IoT smart city applications. We showcase the significant improvement achieved by our proposed solution over state-of-the-art schemes through simulation results.

In this paper, we study a three-dimensional (3D) spectrum sharing between device-to-device (D2D) and unmanned aerial vehicles (UAVs) communications. We consider that UAVs perform spatial spectrum sensing to opportunistically access the licensed channels that are occupied by the D2D communications of ground users. The objective of the considered 3D spectrum sharing networks is to maximize the area spectral efficiency (ASE) of UAV networks while guaranteeing the required minimum ASE of D2D networks. Using the tools from machine learning, we obtain the probability of spatial false alarm and the probability of spatial missed detection at the UAV, which helps us to characterize the density of active UAVs. Then, based on the Neyman-Pearson criterion, we further derive the coverage probability of D2D and UAV communications by leveraging the tools from stochastic geometry. In addition, the ASE of the D2D and UAV networks are also obtained. Simulation results show that a decrease in the spatial spectrum sensing radius of UAVs reduces the coverage probability of UAV communications but improves the ASE of UAV networks. Furthermore, the proposed tools allow obtaining the optimal spatial spectrum sensing radius of UAVs given certain network parameters.

This paper explores a model on cooperative cognitive radio network (CCRN) to enable the in-band bidirectional device-to-device (D2D) communications by sharing the licensed spectrum of cellular system (CS) in a 5G heterogeneous networks (HetNets) framework. In this model, cellular nodes (CNs) are modelled as primary users (PUs) and devices involved in D2D communications are referred as secondary users (SUs). The D2D pair, as unlicensed users, access to the licensed spectrum originally assigned to the CN pair while assuring relaying action to assist two-way communications between the CNs. Further, the D2D pair exploits the information-bearing radio frequency (RF) signals transmitted by the CNs to energize their transceivers, using the principle of simultaneous wireless information and power transfer (SWIPT). Closed form outage expressions of both cellular and D2D communications are derived. Simulation results are used to validate our analytical results. Simulation results show that about ${\bf \sim 68\%}$ and ${\bf \sim 277\%}$ gains are achieved by the proposed system in terms of spectrum efficiency and energy efficiency, respectively as compared to another prominent study on spectrum sharing enabled two-way PU and two-way SU communications.

Database-driven Dynamic Spectrum Sharing (DSS) is the de-facto technical paradigm adopted by Federal Communications Commission for increasing spectrum efficiency, which allows licensed spectrum to be opportunistically used by secondary users. In database-driven DSS, a geo-location database administrator (DBA) maintains spectrum availability information over its service region in the form of a Radio Environment Map (REM), where the received signal strength from the primary user at every location is either directly measured via spectrum sensing or estimated via statistical spatial interpolation. Crowdsourcing-based spectrum sensing is a promising approach for periodically collecting spectrum measurements over a large geographic area but is unfortunately vulnerable to false spectrum measurements. Despite a large body of prior work on secure cooperative spectrum sensing, how to construct an accurate REM in the presence of false measurements remains an open challenge. In this paper, we introduce ST-REM, a novel spatiotemporal approach for securely constructing an REM in the presence of false spectrum measurements. Inspired by the self-label techniques developed for semi-supervised learning, ST-REM iteratively constructs an REM from a small number of spectrum measurements from trusted anchor sensors and many more measurements from mobile users. During each iteration, the DBA evaluates the trustworthiness of each measurement by jointly considering its spatial fitness with other trusted measurements and the mobile user’s long-term behavior. By gradually incorporating the most trustworthy spectrum measurements, the DBA is able to construct a REM with high accuracy. Extensive simulation studies using a real spectrum measurement dataset confirm the efficacy and efficiency of ST-REM.

In spectrum sharing, a spatial separation region is defined around a primary user (PU) where co-channel and/or adjacent channel secondary users (SUs) are not allowed to operate. This region is often called an Exclusion Zone (EZ), and it protects the PU from harmful interference caused by SUs. Unfortunately, existing methods for defining an EZ prescribe a static and an overly conservative boundary, which often leads to poor spectrum utilization efficiency. In this paper, we propose a novel framework—namely, Multi-tiered dynamic Incumbent Protection Zones (MIPZ)—for prescribing interference protection for PUs. MIPZ can be used to dynamically adjust the PU’s protection boundary based on the changing radio interference environment. MIPZ can also serve as an analytical tool for quantitatively analyzing a given protection region to gain insights on and determine the trade-off between interference protection and spectrum utilization efficiency. Using results from extensive simulations and a real-world case study, we demonstrate the effectiveness of MIPZ in protecting PUs from harmful interference and in improving the overall spectrum utilization efficiency.

Long-term evolution (LTE) deployment in the unlicensed band has been a promising solution to handle the ever-increasing data traffic growth. However, spectrum sharing on unlicensed band poses a significant challenge regarding the interaction between LTE licensed assisted access (LAA) and Wi-Fi. In this paper, a radio access technology (RAT) heterogeneous network that consists of an LAA tier and a Wi-Fi tier is constructed, to achieve the coexistence and alleviate the intra-RAT and inter-RAT interference, a listen-and-talk (LAT) scheme is utilized in Wi-Fi while LAA adopts the listen-before-talk (LBT). By leveraging the full-duplex (FD) techniques in Wi-Fi, the collision can be avoided and the utilization of unlicensed spectrum can be improved. Furthermore, the sensing errors are derived based on the FD strategy and an enhanced Markov model is presented to analyze the performance of the heterogeneous network with consideration of the residual self-interference (RSI). The fairness between LAA and Wi-Fi is also investigated. At last, to ensure the performance of Wi-Fi when serious RSI exists, a switched MAC (S-MAC) that can adaptively switch between the FD mode and half-duplex (HD) mode is presented.

The aeronautical spectrum band for air-to-ground (A/G) communications is severely underutilized at less than 12.5%, and yet anticipating scarcity in the near future because of the explosive growth in aeronautical service data. Air-to-air (A/A) communications allow aircraft in close proximity to communicate with each other directly without ground stations or satellites, and are regarded as an effective complement for A/G communications in terms of the spectrum utilization efficiency. In this article, to enable such spectral efficiency that A/A links reuse the spectrum of A/G communications, we propose a cognitive solution that A/A communications are regarded as secondary users which sense idle primary A/G communication channels and transmit data on these channels wherever possible. This results in two major issues: spectrum sensing and sharing between A/A and A/G communications. A coalitional manner is devised in which some A/A links are grouped together to perform cooperative spectrum sensing and sharing while an interference graph is used to address the interference that arises from spectrum sharing within a group. We then formulate the cooperative spectrum sensing and sharing into a coalitional graph game played by all the A/A links involved. Finally, a distributed coalitional graph game algorithm is developed to maximize the utility so as to optimize the schedule of the A/A transmissions on the available A/G channels. Extensive simulations show that the achievable sum rate approaches the results of the optimal exhausted searching with relatively low complexity.

Spectrum shortage is a fundamental problem in wireless networks, and this problem becomes increasingly acute with the rapid proliferation of wireless devices. To address this issue, spectrum sharing in the context of cognitive radio networks (CRNs) has been regarded as a promising solution. Although there is a large body of work on spectrum sharing in the literature, most existing work is limited to theoretical exploration and the progress in practical solution design remains scarce. In this paper, we propose a practical scheme to enable transparent spectrum sharing for a small CRN by leveraging recent advances in multiple-input multiple-output (MIMO) technology. The key components of our scheme are two MIMO-based interference management techniques: blind beamforming (BBF) and blind interference cancellation (BIC). These two techniques enable secondary users to mitigate cross-network interference in the absence of inter-network coordination, fine-grained synchronization, and mutual knowledge. We have built a prototype of our scheme on a wireless testbed and demonstrated its compatibility with commercial Wi-Fi devices (primary users). Experimental results show that, for a secondary device with two/three antennas, BBF and BIC achieve an average of 25 dB and 33 dB interference cancellation capabilities in real-world wireless environments, respectively.

We consider a three-tier spectrum sharing framework, recently adopted in the United States for the Citizens Broadband Radio Service, which enables commercial users to share this spectrum with the incumbent users. This sharing can be further assisted by environmental sensing capability operators (ESCs) that monitor the spectrum occupancy to determine when the incumbents are absent. Two key aspects of this framework that impact how spectrum access firms (SAs) using this spectrum may compete are the differences in information provided by different ESCs and how different firms bundle their services using the licensed and unlicensed band. We show that if the SAs tend to use the unlicensed band more, they will prefer to obtain information from different ESCs. On the other hand, if one of the SAs uses the licensed band more, both the SAs tend to obtain information from the same ESC. If both the SAs tend to differ more in accessing the unlicensed bandwidth, they tend to obtain information from the same ESC more. Our analysis reveals that regulation is required if there is a single ESC, as the unlicensed spectrum may be unused if the user's valuation is high.