Spectrum Access Techniques Research Articles

Enhanced Wireless Network Usage and Loading on Network Delay using Cognitive Radio Network

Wireless communication is one of the fastest-growing fields of communication. Because the user can access and share information anywhere at any time. The communication process will suffer from an overload of traffic. If the node gets overloaded because of heavy traffic, then the performance of the whole network is degraded. So, the usage of the network will be delayed. The proposed work uses the intellectual load balancing approach for Cognitive Radio Network to focus on automatic monitoring of network activity, and the node will continuously balance among numerous nodes. In Cognitive Radio Network the Dynamic Spectrum Access techniques are used to avoid spectrum scarcity and underutilization. The CR base station collect the surrounding about the active primary user and waiting secondary user. To determine the principal user's on/off status of availability, the Markov chain model is employed. The waiting secondary user utilize the spectrum when the primary user is not using it. The secondary user leaves the spectrum and uses the spectrum of another primary user if the primary user is on status. It will assist with dynamic spectrum access method and it will help increase the overall performance of the network. The suggested Load balancing Cognitive Radio Network (LBCRN) sorts the nodes and uses spectrum identification before allocating the node to the secondary user. So that minimise transaction delays, prevent overcrowding of a specific node, automatically lower the level of packet drops, and enhance packet delivery radio levels. As a result, this strategy has helped to lessen the issue of spectrum shortages in the wireless communication industry.

Secondary User Access Control in Cognitive Radio Networks: Concept, Design, and Analysis

Cognitive radio (CR), an important part of nextgeneration wireless communications networks, has been extensively studied to improve the spectrum utilization. The spectrum sensing and access functions are especially crucial for ensuring the secure and efficient spectrum sharing needs of CR networks. In this article, the secondary user access control (SUAC) based spectrum access technique is investigated to improve spectrum efficiency and network safety, by which a jamming signal is carefully designed to break down unauthorized secondary users (UA-SUs) sensing result and keep reliable sensing result from authorized secondary users (A-SUs). First, SUAC techniques are described, and a jamming cancellation method based on an oblique projection approach is proposed to guarantee the sensing result of authorized secondary users. Second, a prioritized SUAC approach is examined to ensure A-SUs with distinct spectrum access levels. Third, quadratic programming in massive multipleinput multiple-output based SUAC is presented to effectively design a jamming signal that combines minimizing jammer's influences on A-SUs and maximizing influences on UA-SUs. Finally, some open research areas and challenges in SUAC are discussed.

Enhancing Hybrid Spectrum Access in CR-IoT Networks: Reducing Sensing Time in Low SNR Environments

The current utilization of the licensed spectrum band is not optimal. the abundance of Internet of Things (IoT) gadgets could lead to congestion in the unlicensed spectrum band. A potential solution is to integrate cognitive radios into IoT devices, specifically by developing CR-IoT (cognitive-radio-enabled IoT) devices that leverage the hybrid spectrum access (HSA) technique to access the licensed spectrum band and employ energy detectors for spectrum sensing. While HSA can enable high data throughput for CR-IoT networks, environments with low signal-to-noise ratio (SNR) may experience reduced performance. Particularly, in low SNR environments with SNR values ranging from -20dB to -24dB, the high level of noise uncertainty can cause the energy detector to spend more time sensing, which results in a significant reduction in transmission time and overall throughput. In this study, a novel approach is presented to address the challenge of noise uncertainties on the energy detector by implementing an adaptive sensing threshold. The simulation outcomes reveal that the proposed technique can significantly improve the throughput in scenarios characterized by low signal-to-noise ratio (SNR), with a maximum enhancement of up to 28%. This innovative approach can pave the way for more robust and efficient energy detectors in the presence of noise uncertainties .

Automatic modulation recognition based on a multiscale network with statistical features

Automatic modulation recognition (AMR) can be used in dynamic spectrum access (DSA) techniques to reduce the pressure on spectrum resources. In this paper, we propose a multiscale convolution-based network model called MSNet-SF, which combines traditional statistical features and deep learning (DL) to balance recognition accuracy and complexity. In the model, the feature information is extracted by two multiscale modules, which consist of unit convolution and three different sizes of convolution kernels arranged in parallel. Additionally, the sparse connectivity of unit convolution enables the network to be more lightweight. Five statistical features (four higher-order cumulants (HOCs) and one zero-centered normalized instantaneous magnitude tightness) are also input into the model and are fully fused with the main feature map by multiplication to achieve complementarity of long-term and short-term features. This approach yields a large performance gain at a small cost and greatly reduces the confusion between QAM16 and QAM64. Simulation results in the RML2018.10A dataset show that the average recognition accuracy of the model improved by 4% after adding the statistical features and achieved an accuracy of more than 97% from 12 dB.

Design and Development of Hybrid Spectrum Access Technique for CR-IoT Network

The radio spectrum is an underutilized natural resource with significant untapped potential. The rapid proliferation of Internet of Things (IoT) devices is driving a dramatic increase in radio spectrum demand. These devices can utilize cognitive radio (CR) technology to access the bandwidth left unused by licensed spectrum users, also known as primary users (PUs), to meet end users spectrum requirements efficiently. However, because PUs are given priority, CR-enabled Internet of Things (CR-IoT) devices, also known as secondary users (SU), must frequently communicate with one another in an opportunistic manner or under stringent power constraints. This can complicate CR-IoT device communication, render it unstable, and restrict its throughput. This paper proposes a hybrid spectrum access algorithm that combines underlay and interweave spectrum access methods to address this issue. When a PU is detected, under the proposed scheme, CR-IoT devices utilize underlay spectrum access. In contrast, when no PU is detected, CR-IoT devices employ interweave spectrum access. In addition, a proposed iterative algorithm permits CR-IoT devices to adapt their sensing thresholds, and sensing time based on the Signal-to-Noise ratio (SNR) received from Pus to strike a balance between achievable throughput and fairness among PUs and CR-IoT devices in extremely noisy channel. Simulation results demonstrate that the throughput for CR-IoT devices increases by 28% in proposed scheme when compared to the conventional spectrum access schemes.

A Usage Aware Dynamic Spectrum Access Scheme for Interweave Cognitive Radio Network by Exploiting Deep Reinforcement Learning.

Future-generation wireless networks should accommodate surging growth in mobile data traffic and support an increasingly high density of wireless devices. Consequently, as the demand for spectrum continues to skyrocket, a severe shortage of spectrum resources for wireless networks will reach unprecedented levels of challenge in the near future. To deal with the emerging spectrum-shortage problem, dynamic spectrum access techniques have attracted a great deal of attention in both academia and industry. By exploiting the cognitive radio techniques, secondary users (SUs) are capable of accessing the underutilized spectrum holes of the primary users (PUs) to increase the whole system’s spectral efficiency with minimum interference violations. In this paper, we mathematically formulate the spectrum access problem for interweave cognitive radio networks, and propose a usage-aware deep reinforcement learning based scheme to solve it, which exploits the historical channel usage data to learn the time correlation and channel correlation of the PU channels. We evaluated the performance of the proposed approach by extensive simulations in both uncorrelated and correlated PU channel usage cases. The evaluation results validate the superiority of the proposed scheme in terms of channel access success probability and SU-PU interference probability, by comparing it with ideal results and existing methods.

Underwater Cognitive Acoustic Networks Architecture, Development and Deployment

To develop eco-friendly Underwater Cognitive Acoustic Networks (UCANs) with high spectrum utilization. A huge number of sensor networks are installed Underwater to enable applications for oceanographic data collection, pollution, and corrosion monitoring, offshore exploration, disaster prevention, assisted navigation, and tactical surveillance applications. For feasible applications, there is a need to enable underwater communications among the underwater devices. The latest developments in wireless communications cause spectrum shortage problems in the oceans. Cognitive Acoustic (CA) is the enabling technology for supporting dynamic spectrum access techniques in wireless communication. The CA provides the solution for the spectrum scarcity problem that is encountered in many countries. In oceans, both natural acoustic systems and artificial acoustic systems use acoustic signals for communication. To efficiently utilize the spectrum without interference with other acoustic systems, a smart UAN should be designed with awareness of the surrounding environment and the ability to reconfigure their operation parameters such as frequency band, modulation schemes, and transmission power.

A Survey on Dynamic Spectrum Access Techniques in Cognitive Radio Networks

The idea of Cognitive Radio (CR) is to share the spectrum between a user called primary, and a user called secondary. Dynamic Spectrum Access (DSA) is a new spectrum sharing paradigm in cognitive radio that allows secondary users to access the abundant spectrum holes in the licensed spectrum bands. DSA is an auspicious technology to alleviate the spectrum scarcity problem and increase spectrum utilization. While DSA has attracted many research efforts recently, in this paper, a survey of spectrum access techniques using cooperation and competition to solve the problem of spectrum allocation in cognitive radio networks is presented.

Transmit power control and data rate enhancement in cognitive radio network using computational intelligence

Underutilized radio frequencies are the chief apprehension in advance radio communication. The radio recourses are sparse and costly and their efficient allocation has become a challenge. Cognitive radio networks are the ray of hope. Cognitive radio networks use dynamic spectrum access technique to opportunistically retrieve and share the licensed spectrum. The licensed users are called primary users and the users that opportunistically access the licensed spectrum all called secondary users. The proposed system is a feedback system that work on demand and supply concept, in which secondary receivers senses the vacant spectrum and shares the information with the secondary transmitters. The secondary transmitters adjust their transmission parameters of transmit power and data rate in such a way that date rate is maximized. Two methods of spectrum access using frequency division multiple access (FDMA) and Time division multiple access (TDMA) are discussed. Interference temperature limit and maximum achievable capacity are the constraints that regulate the entire technique. The aim of the technique is to control the transmitter power according to the data requirements of each secondary user and optimizing the resources like bandwidth, transmit power using machine learning and feed forward back propagation deep neural networks making full use of the network capacity without hampering the operation of primary network.

Development of Database Accessibility for Frequency Scheduling of TVWS Broadband Connectivity in Rural Areas Using Dynamic Spectrum Access Technique

As a result of the switchover from analogue to digital transmission, Television White Space (TVWS) presented itself as good opportunity to supplement the existing licensed spectrum to ease the spectrum scarcity. Rural communities were usually not connected due to poor returns to the internet providers to provide broadband access to the areas. This research has prepared the framework and feasibility study for deploying broadband internet services using Television White Space (TVWS) technology in Ugbawka, a rural area in Enugu state, Nigeria. In this work, a Network Ping was run on five websites using three major internet service providers as backhaul to establish facts of poor or even non-existent internet services. Using Ping Plotter 5 Pro, accessing ieee.com using MTN yielded a Round Trip (RT) average of 846.433 ms, with a loss of 83.8% packet over 10mins count. Radio Frequency (RF) Explorer and Carlson transceiver, Customer Premise Equipment (CPE) were used for field trials to determine availability of TVWS Frequencies. A database app was developed by writing some codes in the Basic for Android (B4A) Intermediate Development Environment (IDE). Empirical outdoor propagation model was developed with a 2.15 pathloss exponent while the indoor propagation model gave a pathloss exponent of 3.47 . An algorithm was developed, titled, TVWS Optimization Quadrature Amplitude Algorithm, (TOQA), where throughput of this project performed better by giving 60Mbps and 70 Mbps at Signal-Noise-Ratio (SNR) of 5dB while the conventional algorithm gave 30Mbps and 25 Mbps at same SNR value. The Bit Error Rate was lower than the conventional models used, giving the TOQA values of 10-3 at SNR of 5 dB and 10-6 at SNR of 30 dB while the conventional method gave 10-1 and 10-3 respectively at the same SNR values. With an Average of 56.2% network latency recorded in Ugbawka, TVWS will make a great impact on Internet connectivity if deployed.

Seven Defining Features of Terahertz (THz) Wireless Systems: A Fellowship of Communication and Sensing

Wireless communication at the terahertz (THz) frequency bands (0.1–10 THz) is viewed as one of the cornerstones of tomorrow’s 6G wireless systems. Owing to the large amount of available bandwidth, if properly deployed, THz frequencies can potentially provide significant wireless capacity performance gains and enable high-resolution environment sensing. However, operating a wireless system at high-frequency bands such as THz is limited by a highly uncertain and dynamic channel. Effectively, these channel limitations lead to unreliable intermittent links as a result of an inherently short communication range, and a high susceptibility to blockage and molecular absorption. Consequently, such impediments could disrupt the THz band’s promise of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">high-rate communications and high-resolution sensing</i> capabilities. In this context, this paper panoramically examines the steps needed to efficiently and reliably deploy and operate next-generation THz wireless systems that will synergistically support a fellowship of communication and sensing services. For this purpose, we first set the stage by describing the fundamentals of the THz frequency band. Based on these fundamentals, we characterize and comprehensively investigate <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">seven unique defining features of THz wireless systems</i> : 1) Quasi-opticality of the band, 2) THz-tailored wireless architectures, 3) Synergy with lower frequency bands, 4) Joint sensing and communication systems, 5) PHY-layer procedures, 6) Spectrum access techniques, and 7) Real-time network optimization. These seven defining features allow us to shed light on how to re-engineer wireless systems as we know them today so as to make them ready to support THz bands and their unique environments. On the one hand, THz systems benefit from their quasi-opticality and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">can turn every communication challenge into a sensing opportunity</i> , thus contributing to a new generation of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">versatile wireless systems</i> that can perform multiple functions beyond basic communications. On the other hand, THz systems can capitalize on the role of intelligent surfaces, lower frequency bands, and machine learning (ML) tools to guarantee a robust system performance. We conclude our exposition by presenting the key THz 6G use cases along with their associated major challenges and open problems. Ultimately, the goal of this article is to chart a forward-looking roadmap that exposes the necessary solutions and milestones for enabling THz frequencies to realize their potential as a game changer for next-generation wireless systems.

Autonomous Interference Mapping for Industrial Internet of Things Networks Over Unlicensed Bands: Identifying Cross-Technology Interference

The limited coexistence capabilities of current Internet-of-things (IoT) wireless standards produce inefficient spectrum utilization and mutual performance impairment. The entity of the issue escalates in industrial IoT (IIoT) applications, which instead have stringent quality-of-service requirements and exhibit very-low error tolerance. The constant growth of wireless applications over unlicensed bands mandates then the adoption of dynamic spectrum access techniques, which can greatly benefit from interference mapping over multiple dimensions of the radio space. In this article, the authors analyze the critical role of real-time interference detection and classification mechanisms that rely on IIoT devices only, without the added complexity of specialized hardware. The trade-offs between classification performance and feasibility are analyzed in connection with the implementation on low-complexity IIoT devices. Moreover, the authors explain how to use such mechanisms for enabling IIoT networks to construct and maintain multidimensional interference maps at run-time in an autonomous fashion. Lastly, the authors give an overview of the opportunities and challenges of using interference maps to enhance the performance of IIoT networks under interference.

Power‐Domain Based Dynamic Millimeter‐Wave Spectrum Access Techniques for In‐Building Small Cells in Multioperator Cognitive Radio Networks toward 6G

Power‐domain based dynamic spectrum access (PDSA) techniques are proposed for sharing 28 GHz spectrum of any Mobile Network Operator (MNO) with in‐building small cells (SCs) of the other countrywide. By controlling the transmission power of SCs, PDSA techniques explore the traditional interweave access by operating an SC at the maximum transmission power and the underlay access by allowing to operate an SC at a lowered transmission power separately, as well as jointly. Average capacity, spectral efficiency, energy efficiency, cost efficiency, and throughput per SC user equipment (UE) are derived for an arbitrary number of MNOs in a country. By varying the spectrum reuse factor for the millimeter‐wave spectrum in each building of SCs, extensive numerical and simulation results and analyses for an illustrative scenario of a country consisting of four MNOs are carried out for the interweave and underlay techniques when applying separately, as well as the hybrid interweave‐underlay technique and the static licensed spectrum allocation (SLSA) technique. It is shown that, due to gaining more shared spectra, the hybrid interweave‐underlay technique provides the best, whereas the SLSA provides the worst, performances of all techniques in terms of the average capacity, spectral efficiency, energy efficiency, cost efficiency, and throughput per UE of an SC. Moreover, we show that the hybrid interweave‐underlay technique, the interweave technique, and the underlay technique, respectively, can satisfy the expected requirements of spectral and energy efficiencies for Sixth‐Generation (6G) networks by reusing each MNO’s 28 GHz spectrum to SCs of about 33.33%, 50%, and 50% less number of buildings than that required by the SLSA for a spectrum reuse factor of six per building of small cells.

Millimeter-Wave Spectrum Utilization Improvement in Multi-Operator Networks: A Framework Using the Equal Likelihood Criterion

In this paper, we present a framework to give a comprehensive review of how to improve the spectrum utilization of millimeter-wave (mmWave) systems using indoor small cells in multi-operator network scenarios. More specifically, the framework concerns with the improvement of the utilization of the 28 GHz mmWave spectrum allocated to an arbitrary number of mobile network operators (MNOs) in a country using numerous spectrum allocation techniques, namely Static and Equal Spectrum Allocation (SESA), Flexible and Unequal Spectrum Allocation (FUSA), and Countrywide Full Spectrum Allocation (CFSA). A number of spectrum utilization improvement mechanisms such as spectrum trading, spectrum sharing, and spectrum reusing are then exploited into SESA, FUSA, and CFSA techniques in four major-interconnected domains, including time, frequency, power, and space. Using the Equal Likelihood Criterion and the properties of left-justified Pascal’s triangle, the average capacity, spectral efficiency (SE), and energy efficiency (EE) performance metrics for each spectrum allocation technique in each domain are derived. Extensive system-level numerical and simulation results and analyses are carried out to evaluate the performance of each technique in each domain for example scenario of a country with four MNOs. Overall, it is shown that, in the power-domain, CFSA outperforms SESA and FUSA (when operating either at the interweave or at the underlay spectrum access technique), whereas, in the time-domain and frequency-domain, SESA and FUSA outperform CFSA, in terms of the average capacity, SE, and EE. Finally, we show that CFSA in the power-domain outperforms SESA and FUSA operating in any domain to achieve the prospective SE and EE requirements for the sixth-generation (6G) mobile networks.

A Double Auction Framework for Multi-Channel Multi-Winner Heterogeneous Spectrum Allocation in Cognitive Radio Networks

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.

Secrecy Outage Performance of Cognitive Radio Network with Selection Combining at Eavesdropper

Background: Based on the idea of cooperative communication, recently a lot of attention has been drawn to cooperative spectrum access for the secure information transmission in a Cognitive Radio Network (CRN). Security is one of the most important aspects of these networks, as due to their open and dynamic nature, they are extremely vulnerable to malicious behavior. Cooperative cognitive radio has emerged as a dynamic spectrum access technique, where an unlicensed (secondary) user is allowed to simultaneously access the licensed channels dedicated to a Primary User (PU), as long as the Quality of Service (QoS) of primary communication is not affected. Method: This paper investigates the secrecy outage performance of threshold-based cognitive decode-andforward relay network, with interference constraints from primary licensed user. Threshold-based relaying is considered where; the source message is successfully decoded by the relay, only if the received SNR satisfies the particular threshold. Outage probability expressions have been derived for the worst-case scenario, where only the eavesdropper can achieve the advantage of diversity. The Selection Combining (SC) diversity scheme is employed only at the secondary eavesdropper. Results: The system secrecy performance is better for SC diversity scheme at the eavesdropper than Maximal Ratio Combining (MRC) diversity scheme, as MRC has better diversity performance than SC. We have shown that the improvement in desired secrecy rate, predetermined threshold, eavesdropper channel quality and interference constraints affect the secrecy performance of the cognitive radio system. The outage probability decreases accordingly with an increase in the maximum tolerable interference level at primary destination. The outage probability of Optimal relay Selection (OS) scheme is derived for a multi-relay system, when either the Instantaneous Channel State Information (ICSI) or the Statistical Channel State Information (SCSI) is available. We have shown that the secrecy performance of the OS with ICSI of the system is better than with SCSI. Also, the OS improves the performance of the multi-relay system, when the number of relays is increased. Conclusion: The secrecy outage probability of threshold-based DF underlay cognitive relay network is evaluated. Both interference and maximum transmit power constraints are considered at secondary source and secondary relay. Also, the relay can successfully decode the message, only if it meets the pre-defined threshold. We have investigated the performance of MRC and SC diversity schemes at the secondary eavesdropper and have shown that the system secrecy performance is better for SC than MRC, as MRC has better diversity performance than SC. We have shown that the system secrecy performance is significantly affected by the required secrecy rate, pre-defined threshold, interference constraints and choice of diversity scheme (MRC/SC) at the eavesdropper. The outage probability of OS scheme is derived for a multi-relay system, when either the ICSI or the SCSI is available. We have shown that the secrecy performance of the OS with ICSI of the system is better than with SCSI. Also, the OS improves the performance of the multi-relay system, when the number of relays is increased.

Enhanced physical layer security for cognitive radio systems through joint spectrum access and power allocation

Physical layer (PHY) security is an important issue in wireless communication systems. In this study, the authors investigate the interactions between the PHY security performance and the spectrum access technique in a cooperative cognitive radio (CR) network. In the classical spectrum access, if the measured energy on a given subchannel is less than a threshold, the subband is dedicated for CR transmission. Here, they consider a probabilistic spectrum access (PSA), which assigns to each primary subchannel a probability which is determined according to the measured energy on that subchannel. In addition, both spectrum access and CR power allocation are performed simultaneously. They formulate the general outage probability and some important PHY security performance metrics, such as average secrecy rate, secrecy outage probability, and probability of positive secrecy rate in terms of the spectrum access and optimal power allocation functions. The authors' numerical analysis indicates that the PSA method achieves a superior PHY security and outage performance compared to the classical threshold-based spectrum sensing and power allocation method.

Hidden Markov model technique for dynamic spectrum access

Dynamic spectrum access is a paradigm used to access the spectrum dynamically. A hidden Markov model (HMM) is one in which you observe a sequence of emissions, but do not know the sequence of states the model went through to generate the emissions. Analysis of hidden Markov models seeks to recover the sequence of states from the observed data. In this paper, we estimate the occupancy state of channels using hidden Markov process. Using Viterbi algorithm, we generate the most likely states and compare it with the channel states. We generated two HMMs, one slowly changing and another more dynamic and compare their performance. Using the Baum-Welch algorithm and maximum likelihood algorithm we calculated the estimated transition and emission matrix, and then we compare the estimated states prediction performance of both the methods using stationary distribution of average estimated transition matrix calculated by both the methods.

A Hybrid Interweave–Underlay Countrywide Millimeter-Wave Spectrum Access and Reuse Technique for CR Indoor Small Cells in 5G/6G Era

In this paper, we propose a hybrid interweave–underlay spectrum access and reuse technique for the dynamic spectrum access and reuse of the countrywide 28 GHz millimeter-wave (mmWave) spectrum to in-building small cells of each mobile network operator (MNO) in a country. For the spectrum access, the proposed technique explores both interweave and underlay spectrum access techniques, whereas, for the spectrum reuse, it considers reusing the countrywide spectrum to each three-dimensional (3D) cluster of small cells in a building. To access the countrywide spectrum, each MNO is considered by paying a licensing fee following its number of subscribers. We present the 3D clustering of in-building of small cells and derive average capacity, spectral efficiency (SE), and energy efficiency (EE). We then perform extensive numerical and simulation results and analyses for an MNO of a country consisting of four MNOs. It is shown that, for no spectrum reuse to in-building small cells, the proposed technique improves average capacity and SE by 3.63 and 2.42 times, respectively, whereas EE improves by 72.79%. However, for vertical spatial reuse of six times (as an example) to small cells in a building, average capacity, SE, and EE improve further by 21.77 times, 14.51 times, and 95.66%, respectively. Moreover, the proposed technique can satisfy SE and EE requirements for sixth-generation (6G) mobile systems by horizontal spatial reuse of the countrywide spectrum to small cells of about 40.62%, 9.37%, and 6.25% less buildings than that required by the traditional static licensed spectrum access (SLSA) technique.

A review of industrial wireless communications, challenges, and solutions: A cognitive radio approach

AbstractIntegral and crucial to performance of wireless sensor networks (WSNs), and specifically industrial wireless sensor network (IWSN) is stable, robust, reliable, and ubiquitous communications system. Though, wired communications system is suitable for industrial communications and is resilient to shadowing and multipath fading effects of industrial‐WSN environments, yet its wireless counterpart is a much preferred industrial communications technology due to reduced cost and high flexibility which it offers in comparison to wired communications. However, overcrowding of the industrial, scientific, and medical band, where IWSN is deployed together with other heterogeneous technologies, as well as resultant scarcity of usable frequency spectrum has restrained exclusive application of wireless technology for industrial communications. Nonetheless, cognitive radio (CR) has ability to increase spectrum utilization efficiency and channel capacity for industrial wireless communications (IWC) through opportunistic/dynamic spectrum access (DSA) technique. In this review article, we examine how DSA can benefit IWC through exploitation of new perspectives of white space definitions in the licensed bands as well as unlicensed bands. While discussing the potential of DSA for IWC, we have considered the unique characteristics of IWC as well as technical challenges and issues imposed by industrial‐WSN. Accordingly, we have suggested and proffered appropriate CR‐based solutions in mitigating some of the challenges where necessary.