Unoccupied Spectrum Research Articles

Unmanned aerial vehicle-assisted wideband cognitive radio network based on DDQN-SAC

Cognitive radio (CR) systems have emerged as effective tools for improving spectrum efficiency and meeting the growing demands of communication. This study focuses on a flexible CR system based on opportunistic spectrum access technology, which enables secondary networks to efficiently utilize unoccupied spectrum resources for information transmission by actively sensing the spectrum utilization of primary networks. Specifically, we introduce unmanned aerial vehicles (UAV) technology into the CR system to further enhance its flexibility and adaptability, which enables the transmission efficiency of low-altitude UAV networks. In this CR system, UAVs are employed for more flexible spectrum management. The objective of this research is to maximize the average achievable rate of SUs by jointly optimizing the trajectories of secondary UAV, the trajectories of primary UAV, the beamforming of secondary UAV, subchannel allocation and sensing time. To achieve this goal, we employ deep reinforcement learning (DRL) algorithms to optimize these variables. Compared to traditional optimization algorithms, DRL algorithms not only have lower computational complexity but also achieve faster convergence. To address the mixed-action space problem, we propose a Dueling DQN-Soft Actor Critic algorithm. Simulation results demonstrate that the proposed approach in this paper significantly enhances the performance of the CR system compared to traditional baseline schemes. This is manifested in higher spectrum efficiency and data transmission rates, while minimizing interference with the primary network. This innovative research combines drone technology and DRL algorithms, bringing new opportunities and challenges to the future development of cognitive communication systems.

A Systematic Review on Non-Orthogonal Multiple Access (NOMA) Based on Visible Light Communication for Intelligent Transportation Systems

Non-Orthogonal Multiple Access (NOMA) is a cutting-edge technology that permits several users to use the same frequency resources and transfer data at once. Visible light communication also known as VLC, is an innovative technology that offers access to an unoccupied spectrum, enables fast data transmission speeds, thereby making it a complementary addition to current radio frequency technology. Although VLC has its advantages, it also comes with some downsides. One major issue is the modulation bandwidth of LEDs, which can be quite challenging when creating high speed VLC systems. Non-orthogonal multiple access (NOMA), particularly power-domain NOMA (PD-NOMA), has become a viable multiple access approach, ensuring sufficient bandwidth allocation for VLC systems. This study delves into multiple access techniques in VLC systems, in particular NOMA, and discusses its fundamental principles, key ideas and practical implementations like vehicular communication. It also addresses the associated hurdles, such as ensuring equitable distribution of optical power among users, leveraging MIMO technology, and grappling with LED nonlinearity issues. In summary, we underscore the significance of utilizing NOMA-VLC technology to enhance wireless communication systems and optimize spectral efficiency.

Innovative Spectrum Handoff Process Using a Machine Learning-Based Metaheuristic Algorithm.

A cognitive radio network (CRN) is an intelligent network that can detect unoccupied spectrum space without interfering with the primary user (PU). Spectrum scarcity arises due to the stable channel allocation, which the CRN handles. Spectrum handoff management is a critical problem that must be addressed in the CRN to ensure indefinite connection and profitable use of unallocated spectrum space for secondary users (SUs). Spectrum handoff (SHO) has some disadvantages, i.e., communication delay and power consumption. To overcome these drawbacks, a reduction in handoff should be a priority. This study proposes the use of dynamic spectrum access (DSA) to check for available channels for SU during handoff using a metaheuristic algorithm depending on machine learning. The simulation results show that the proposed "support vector machine-based red deer algorithm" (SVM-RDA) is resilient and has low complexity. The suggested algorithm's experimental setup offers several handoffs, unsuccessful handoffs, handoff delay, throughput, signal-to-noise ratio (SNR), SU bandwidth, and total spectrum bandwidth. This study provides an improved system performance during SHO. The inferred technique anticipates handoff delay and minimizes the handoff numbers. The results show that the recommended method is better at making predictions with fewer handoffs compared to the other three.

An Efficient Distributed Approach for Cooperative Spectrum Sensing in Varying Interests Cognitive Radio Networks.

The rapid growth in wireless communications, coupled with insufficient utilization of the spectrum, led to the development of new wireless services and the promising technology of cognitive radio (CR) networks, which facilitate periodic access to the unoccupied spectrum bands and thus increases spectral efficiency. A fundamental task in CR networks is spectrum sensing, through which unauthorized secondary users (SUs) detect unoccupied bands in the spectrum. To achieve this, an accurate estimate of the power spectrum is necessary. From this perspective, and given that many other factors can affect individual detection, such as pathloss and receiver uncertainty, we aim to improve its estimate by exploiting the spatial diversity in the SUs’ observations. Spectrum sensing is treated as a parameters estimation problem, assuming that the parameters’ vector of each SU consists of some global and partially common parameters. To exploit this modeling, distributed and cooperative spectrum sensing is the subject of interest in this study. Diffusion techniques, and especially the Adapt-Then-Combine (ATC) method will be exploited, where each SU cooperates with a group of nodes in its neighborhood that share the same parameters of interest. We consider a network of three static PUs with overlapping power spectrums, and thus, frequency bands. The performance of the employed method will be evaluated under two scenarios: (i) when the PUs spectrum varies, since some frequency bands are not yet utilized, and (ii) when the frequency bands of the PUs are fixed, but there is a mobile SU in the network, changing regions and parameters of interest. Experimental results and performance analysis reveal the ATC algorithm robustness and efficiency.

Mixed Mott–Hubbard and charge transfer nature of 4H–SrMnO3 thin film on Si (100)

Room temperature electronic structure of polycrystalline 4H–SrMnO3 thin film grown on Si (100) substrate has been studied using resonance photo emission spectroscopy and soft x-ray absorption spectroscopy measurements. Presence of charge transfer screen Mn 3d n L final state along with the 3d n-1 final state at the valence band edge of 4H–SrMnO3 thin film confirms that the ground state is strongly mixed between Mn 3d and O 2p states. The estimated equivalent values of on-site Coulomb interaction energy (U) and O 2p to Mn 3d- charge transfer energy (Δ) (U ≈ Δ ≈ 4.8 eV) from the combination of occupied and unoccupied spectra further confirm the intermediate Mott–Hubbard and charge transfer insulator nature of 4H–SrMnO3 film. Despite having similar Mn 4+ valence state in 4H–SrMnO3 and cubic SrMnO3, 4H phase is observed to reveal much higher band gap ∼1.5 eV than the cubic phase (0.3 eV), which arises due to different MnO6 octahedra environment.

CR-IoTNet: Machine learning based joint spectrum sensing and allocation for cognitive radio enabled IoT cellular networks

In recent years, the Internet of Things (IoT) paradigm has gained much popularity due to its potential ability to integrate the physical world with the digital world. However, this digital revolution is driving an insatiable demand for wireless spectrum, leading the upcoming novel personal, social and industrial IoT applications competing for limited spectrum resources. One of the main challenges that may hinder the vision of IoT is the scarcity of radio spectrum. Therefore, in order to cope with the challenge of spectrum scarcity brought about by the unprecedented number of IoT devices, this paper proposes to integrate cognitive radio (CR) technology with the IoT paradigm (CR-IoTNet). The CR is realized as a promising solution to improve the spectrum utilization and alleviate the spectrum scarcity in wireless networks. In CR, spectrum sensing is widely recognized as a key technology that enables secondary users (SUs) to detect spectrum holes and have the opportunity to access unoccupied spectrum. The CR-IoTNet, which is composed of multiple primary user (PU) base-stations and SU devices as IoT smart objects, performs the joint spectrum sensing and optimal allocation of spectrum to the requesting SU-IoT devices in the network through an intelligent fusion center (IFC). Furthermore, we employ support vector machines (SVM) in CR-IoTNet, enabling it to learn and adapt to the changing network dynamics, and identify the PU spectrum usage based on the established multi-class (J×6)-D feature set. The performance of CR-IoTNet is evaluated across several key factors, where simulation results validate the efficacy of the proposed framework in achieving high reliable identification, classification and allocation of unoccupied frequency bands in PU spectrum, especially in key areas of low signal-to-noise ratio (SNR). In addition, the trained SVM classifier obtained 95.11% accuracy, with 92.67% true positive rate and 96.34% true negative rate in CR-IoTNet, reflecting the optimal allocation of PU nodes for spectrum access.

Radar Sensing-Throughput Tradeoff for Radar Assisted Cognitive Radio Enabled Vehicular Ad-Hoc Networks

In cognitive radio enabled vehicular ad-hoc networks (CR-VANETs), the secondary users, i.e., the secondary intelligent vehicles have the ability to perceive the driving environment and use the unoccupied spectrum of primary users for data transmission. In this paper, we consider the radar assisted CR-VANETs, in which the secondary users firstly sense the surroundings using radar modules periodically and Swerling 0, Swerling 2 and Swerling 4 target models are considered respectively. Note that the secondary users access the spectrum of primary users and communicate with their corresponding receivers when no one is detected by the low range radar module. Moreover, we design the joint radar sensing and data transmission frame structure and formulate the radar sensing-throughput tradeoff problem mathematically. It is proved that the formulated tradeoff indeed has the optimal radar sensing time which yields the maximum throughput for the secondary networks. Numerical results and simulations verify that the optimal radar sensing time achieving the maximum throughput for Swerling 0 target model is 0.05 ms when the radius of the radar sensing region is 320 meters, the densities of the primary users and secondary users are λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> = 0.01/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> = 0.2/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , the received radar SNR is 10 dB and the detection probability is 99.9%. For the Swerling 2 and Swerling 4 target models, the optimal radar sensing times achieving the maximum throughput is 0.14 ms and 0.08 ms respectively when the detection probability is 99%.

Ultra-Wideband Spectrum Hole Identification Using Principal Components and Eigen Value Decomposition

Ultra-Wideband Spectrum Hole identification using Principal Components and Eigen Value Decomposition evolve a method of detecting spectrum hole from complex and corrupted wide band spectrum signal, due to the effect of noise spectrum hole detection is usually a challenge in wideband signal, as the presence of noise give rise to error alert, that is, noise can be misconstrued for signal. Dimensionality reduction was first used as the first level of denoising technique, Principal component Analysis (PCA) was used in dimensioning Wide Band Spectrum Data; this was able to reduce the noise level in the signal which made it convenient for Fast Fourier Transform (FFT) to act on it. FFT was used to decompose the signal to 64 sub band channels and on further reduction using principal Component Analysis (PCA), a 32 Level sub-band decomposition was carried out. Eigen Value generated shows that the magnitude of the signal to Noise ratio between Eigen Value 1 to 19 was high enough to show the that there exist a signal, while between 20 to 32 shows no signal by implication it indicates that these areas have high possibility of unoccupied spectrum holes.

Ultra-Wideband Spectrum Hole Identification Using Principal Components and Eigen Value Decomposition

Ultra-Wideband Spectrum Hole identification using Principal Components and Eigen Value Decomposition evolve a method of detecting spectrum hole from complex and corrupted wide band spectrum signal, due to the effect of noise spectrum hole detection is usually a challenge in wideband signal, as the presence of noise give rise to error alert, that is, noise can be misconstrued for signal. Dimensionality reduction was first used as the first level of denoising technique, Principal component Analysis (PCA) was used in dimensioning Wide Band Spectrum Data; this was able to reduce the noise level in the signal which made it convenient for Fast Fourier Transform (FFT) to act on it. FFT was used to decompose the signal to 64 sub band channels and on further reduction using principal Component Analysis (PCA), a 32 Level sub-band decomposition was carried out. Eigen Value generated shows that the magnitude of the signal to Noise ratio between Eigen Value 1 to 19 was high enough to show the that there exist a signal, while between 20 to 32 shows no signal by implication it indicates that these areas have high possibility of unoccupied spectrum holes.

Study on the Properties of Organic–Inorganic Hole Transport Materials in Perovskite Based on First-Principles

Newport Inc. was licensed recently by the National Renewable Energy Laboratory of the United States to update the highest efficiency of the perovskite solar cell (PSC) certification of PSCs by 23.7%. Exploring new hole transfer layer is the key to the future development of PSC. In this paper, we constructed seven organic hole transport material molecules such as copper-phthalocyanine (CuPc), 2',7'-bis(bis(4-methoxyphenyl)amino)spiro[cyclopenta-[2,1-b:3,4-b']dithiophene-4,9'-fluorene] (FDT), Poly-triarylamine (PTAA), poly(3,4-ethylenedioxy thiophene)/poly(styrenesulfonate) (PEDOT/PSS) poly(3-hexylthiophene) (P3HT) and six in-organic hole transport material molecules such as CuCSN, CuI, InCuS2, CuO, Cu2O, NiO with Material Studio software. By the structure optimization, their energy band, density of state (DOS), HOMO/lowest unoccupied orbit (LUMO) energy level and absorption spectrum were calculated. Furthermore, the HOMO/LUMO electron cloud distribution map of FDT molecule was analyzed in detail. The results show that the electron cloud is closer to the nucleus with the increase of the isopotential surface value. From the absorption spectra, the absorption wavelengths of most inorganic hole transport materials are mainly concentrated at about 200 nm, which is relatively short. But the absorption wavelengths of organic hole transport materials are distributed in long wavelength region, most of them are above 2000 nm. Only the absorption spectra of PTAA, Spiro OMetad and CuPc are in the range of solar spectrum. The HOMO energy levels of seven organic hole transport materials are slightly higher than the values of valence band of CH3NH3PbI3 and NH2CH = NH2PbI3, which are favorable for carrier injection and transport. The band gap of inorganic hole transport materials CuCSN and CuI is wider. From the energy band structure curve, the effective mass of NiO, CuO, Cu2O carriers is smaller, which the carrier transport rate is relatively high. The hole transport material must have high hole mobility and hole conductivity so as to ensure the effective transport of the hole at the interface between the hole transport layer and the perovskite layer.

Resource-partitioned spectrum assignment to realize efficient multicasting for flexible grid optical networks

Abstract With the increasing demand of some novel point-to-multi-point services, such as live video delivering and interactive distance learning, efficient multicasting is highly desirable in flexible grid optical networks (FGONs). Thus, many sophisticated multicast-enabled routing and resource allocation algorithms have been proposed to realize efficient multicasting in FGONs. These algorithms, known as multicast routing and spectrum assignment (MRSA) algorithms, optimized the light-trees and the allocated spectrum resources for multicast services in FGONs. But, most of them ignored some small-sized, isolated, and un-occupied spectrum bands, which are remained after multicast services being accommodated. Due to the continuity and the contiguity constraints in service accommodation, these remained spectrum bands can hardly be allocated to subsequent multicast services and are thus known as spectrum fragments. Their existence and accumulation may exhaust available spectral resources and affect the networking performance (e.g. service blocking performance) for the multicast traffic in FGONs. In this way, the efficiency of FGONs in supporting multicast traffic may be greatly deteriorated. Therefore, the spectrum fragments generated in accommodating multicast services has become an important issue in FGONs. In this paper, we propose a resource-partitioned interval-maximized (RPIM) MRSA algorithm to restrain the generation of spectrum fragments for the multicast traffic in FGONs. The proposed RPIM MRSA algorithm does not utilize the metric, “cut”, to reduce spectrum fragments via avoiding splitting the whole spectrum band into too many band pieces as in fragmentation-aware MRSA algorithms. Instead, the proposed RPIM MRSA algorithm partitions the spectrum resources on each sought light-tree into several elastic groups according to the types of multicast services, and maximizes the group interval between two adjacent groups on the sought light-trees. Since the spectrum resources in each group can always be utilized by the multicast services of the same type, the proposed algorithm restricts the generation of spectrum fragments in group intervals. In this way, the proposed RPIM MRSA algorithm can remarkably reduce spectrum fragments generated in accommodating multicast services. Note that, different from previous group-based algorithms, the proposed RPIM algorithm allows one elastic group for the multicast services of a certain type to contain different amount of spectrum resources on different light-trees. This helps guarantee the flexibility in constructing elastic groups on diverse light-trees. Additionally, the proposed RPIM MRSA algorithm maximizes the group intervals on the sought light-trees, which helps reserve more vacant spectrum resources between two adjacent groups on the light-trees. Since these vacant spectrum resources can be merged into their adjacent groups if needed, the proposed algorithm can reduce not only the spectrum fragments generated in group intervals but also the blocked multicast services in groups by maximizing group intervals on the light-trees. Simulation results verify that the proposed RPIM algorithm can realize efficient multicasting with significantly reduced spectrum fragments and low service blocking probability in FGONs.

Actor–Critic-Algorithm-Based Accurate Spectrum Sensing and Transmission Framework and Energy Conservation in Energy-Constrained Wireless Sensor Network-Based Cognitive Radios

Spectrum sensing is of the utmost importance to the workings of a cognitive radio network (CRN). The spectrum has to be sensed to decide whether the cognitive radio (CR) user can transmit or not. Transmitting on unoccupied spectrum becomes a hard task if energy-constrained networks are considered. CRNs are ad hoc networks, and thus, they are energy-limited, but energy harvesting can ensure that enough energy is available for transmission, thus enabling the CRN to have a theoretically infinite lifetime. The residual energy, along with the sensing decision, determines the action in the current time slot. The transmission decision has to be grounded on the sensing outcome, and thus, a combined sensing–transmission framework for the CRN has to be considered. The sensing–transmission framework forms a Markov decision process (MDP), and solving the MDP problem exhaustively through conventional methods cannot be a plausible solution for ad hoc networks such as a CRN. In this paper, to solve the MDP problem, an actor–critic-algorithm-based solution for optimizing the action taken in a sensing–transmission framework is proposed. The proposed scheme solves an optimization problem on the basis of the actor–critic algorithm, and the action that brings the highest reward is selected. The optimal policy is determined by updating the optimization problem parameters. The reward is calculated by the critic component through interaction with the environment, and the value function for each state is updated, which then updates the policy function. Simulation results show that the proposed scheme closely follows the exhaustive search scheme and outperforms a myopic scheme in terms of average throughput achieved.

Spectrum Sensing in Cognitive Radio Using Actor–Critic Neural Network with Krill Herd-Whale Optimization Algorithm

Spectrum sensing is the active research area in the Cognitive radio networks that initiates the effective data sharing between the licensed and the unlicensed users of Cognitive Network. Maximizing the detection probability for a provided false alarm rate is a hectic challenge of most of the spectral sensing methods. The paper proposes a spectral sensing method, termed as Krill-Herd Whale optimization-based actor critic neural network. The unoccupied spectrum is optimally determined using the proposed method that allocates the free spectrum bands to the primary users instantly such that the delay is minimized due to the effective functioning of the fusion center. For the effective sensing, the Eigen-value-based cooperative sensing is activated in the cognitive radio. The analysis of the proposed method is progressed based on the performance metrics, such as false alarm probability and detection probability. The proposed spectral sensing method outperforms the existing methods that yield a maximum probability of detection and minimum probability of false alarm at a rate of 0.9805 and of 0.009.

Spectrum and dissociation properties of fluoro trichloro methane molecule in radiational field

The ozone layer in the stratosphere of the earth’s atmosphere, which can be destroyed by CFC-11 molecule, plays a crucial role in human survival because it can absorb most of the harmful radiation from the sun and effectively protect the earth’s biology. Therefore, it is of evident significance to investigate the properties of CFC-11 molecule. By Motivated by this and the adoption of B3LYP complex function at a level of 6-311++g(3df, 3pd) basis set, we carry out a series of theoretical studies of the Freon material CFC-11 (CFCl3) molecules, including the studies of the equilibrium structure, electric dipole moment, total energy, the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO) level, energy gap, infrared and Raman spectrum, C—F dissociation characteristics of CFC-11 molecule, and the effect of the applied electric field on CFC-11 molecule as well. The results show that the maximum error between the theoretical calculation value and the experimental value is less than 2% for an optimized ground state structure; the C—F bond length and C—Cl bond length extend with the increase of electric field intensity, but the degree of change of C—F bond length is much stronger than that of C—Cl; the HOMO energy level and total energy go up and then come down as the external field rises, while the LUMO energy level goes up as the field increases. The energy gap &lt;i&gt;E&lt;/i&gt;&lt;sub&gt;g&lt;/sub&gt; first increases and then decreases with the variation of &lt;i&gt;E&lt;/i&gt;&lt;sub&gt;H&lt;/sub&gt; and &lt;i&gt;E&lt;/i&gt;&lt;sub&gt;L&lt;/sub&gt;. The dipole moment without electric field is a minimum value, and the external electric field leads the molecular polarity to increase and the molecular activity to strengthen. The electric field influences the absorption intensity of infrared and Raman spectrum. The infrared and Raman spectrum move toward the long wave under the action of positive electric field, while they move toward the short wave under the action of negative electric field. The red- or blue-shift of infrared and Raman spectrum occur with the change of electric field. The electric field can be adopted as an auxiliary means to separate the overlapping or quasi-overlapping spectral lines. The potential well depth decreases with the increase of the reverse electric field until it vanishes, which causes the bound state ability of C—F bond of CFC-11 molecule to gradually degrade. This paper is expected to provide a feasible and effective tunable means for the final dissociation and degradation of CFC-11 molecules.

Performance of Cognitive Radio Sensor Networks Using Hybrid Automatic Repeat ReQuest: Stop-and-Wait

The enormous developments in the field of wireless communication technologies have made the unlicensed spectrum bands crowded, resulting uncontrolled interference to the traditional wireless network applications. On the other hand, licensed spectrum bands are almost completely allocated to the licensed users also known as Primary users (PUs). This dilemma became a blackhole for the upcoming innovative wireless network applications. To mitigate this problem, the cognitive radio (CR) concept emerges as a promising solution for reducing the spectrum scarcity issue. The CR network is a low cost solution for efficient utilization of the spectrum by allowing secondary users (SUs) to exploit the unoccupied licensed spectrum. In this paper, we model the PU’s utilization activity by a two-state Discrete-Time-Markov Chain (DTMC) (i.e., Free and busy states), for identifying the temporarily unoccupied spectrum bands,. Furthermore, we propose a Cognitive Radio Sense-and-Wait assisted HARQ scheme, which enables the Cluster Head (CH) to perform sensing operation for the sake of determining the PU’s activity. Once the channel is found in free state, the CH advertise control signals to the member nodes for data transmission relying on Stop-and-Wait Hybrid- Automatic Repeat-Request (SW-HARQ). By contrast, when the channel is occupied by the PU, the CH waits and start sensing again. Additionally, the proposed CRSW assisted HARQ scheme is analytical modeled, based on which the closed-form expressions are derived both for average block delay and throughput. Finally, the correctness of the closed-form expressions are confirmed by the simulation results. It is also clear from the performance results that the level of PU utilization and the reliability of the PU channel have great influence on the delay and throughput of CRSW assisted HARQ model.

Analysis of Wideband Microstrip Antenna based Spectrum Occupancy Measurement Campaign for Cognitive Radio Application

Frequency scarcity due to demand of bandwidth in wireless communication can be resolved by knowledge of spectrum occupancy. Therefore different measurement campaigns were conducted for spectrum occupancy worldwide. It has been observed that large numbers of bands is underutilized. These bands can be utilized by a secondary user without interference. In this paper, Spectrum utilization has determined by conducting a campaign for measurement of spectrum occupancy in the Solapur city, India for 0.7 to 2.4 GHz frequency region. As per the analysis, Telecom cellular service band has highest spectrum occupancy while aeronautical radio, fixed satellite doesn’t have any utilization. Total average spectrum occupancy is 15.77%. These results are obtained by using circularly polarized wideband microstrip antenna in place of commercially available antennas for measurement campaign, which shows good agreement with occupancy results but with lower system complexity. The results propose that Solapur city would be a better choice for deployment of cognitive radio as emerging technology to share the unoccupied spectrum.

Advanced Multiresolution Wavelet Based Wideband Spectrum Sensing Technique for Cognitive Radio

An advance multiresolution wavelet based approach for wideband spectrum sensing for cognitive radio system is proposed in this paper. Prime focus is made on the coarse detection part for interweaved system, in which unoccupied spectrum can be used efficiently by the cognitive users. Quick and immediate shifting over the sensed vacant channel is extremely vital and is a challenging task. To overcome this issue, fast and efficient spectrum sensing technique is proposed for cognitive radios by improvising the Discrete Wavelet Packet Transform (DWPT) for multiresolution interweaved systems. This proposed scheme not only increases the system speed but also reduces complexity. Simulation results are used to analyse the system performance and numerical analysis for computing system complexity.

Unlocking the potential of unoccupied spectrum in developing countries: Southern African Development Community – case study

ABSTRACTThe lack of adequate telecommunications infrastructure in developing regions makes wireless systems the most feasible solution for providing Internet connectivity. With the global migration of television (TV) systems from analogue to digital, the TV spectrum is expected to be shared between broadcasting and broadband services. However, the absence of suitable regulatory policies for TV band sharing and low average revenue per user experienced by wireless network operators makes it difficult to deploy broadband networks in developing regions, especially in rural areas. This article presents a co-evolution analysis of three key domains of change (policy, technology and business) in providing broadband connectivity focusing on the Southern African Development Community region. Furthermore, the article proposes public–private partnership and public–private–people partnership models for deploying wireless broadband networks in developing regions. This article is useful to various stakeholders, including policy-makers, governments, the wireless communications industry and academia, by addressing the digital divide in developing regions.

SMART: Coordinated Double-Sided Seal Bid Multiunit First Price Auction Mechanism for Cloud-Based TVWS Secondary Spectrum Market

Spectrum trading is an important aspect of television white space (TVWS) and it is driven by the failure of spectrum sensing techniques. In spectrum trading, the primary users lease their unoccupied spectrum to the secondary users for a market fee. Although spectrum trading is considered as a reliable approach, it is confronted with a spectrum transaction completion time problem, which negatively impacts on end-users Quality of Service and Quality of Experience metrics. Spectrum transaction completion time is the duration to successfully conduct TVWS spectrum trading. To address this issue, this paper proposes simple mechanism auction reward truthful (SMART), a fast and iterative machine learning-assisted spectrum trading model to address this issue. Simulated results indicate that SMART out-performs referenced VERUM algorithm in three key performance indicators: bit-error rate, instantaneous throughput, and probability of dropped packets by 10%, 5%, and 15%, respectively.

Energy dissipation from a correlated system driven out of equilibrium.

In complex materials various interactions have important roles in determining electronic properties. Angle-resolved photoelectron spectroscopy (ARPES) is used to study these processes by resolving the complex single-particle self-energy and quantifying how quantum interactions modify bare electronic states. However, ambiguities in the measurement of the real part of the self-energy and an intrinsic inability to disentangle various contributions to the imaginary part of the self-energy can leave the implications of such measurements open to debate. Here we employ a combined theoretical and experimental treatment of femtosecond time-resolved ARPES (tr-ARPES) show how population dynamics measured using tr-ARPES can be used to separate electron–boson interactions from electron–electron interactions. We demonstrate a quantitative analysis of a well-defined electron–boson interaction in the unoccupied spectrum of the cuprate Bi2Sr2CaCu2O8+x characterized by an excited population decay time that maps directly to a discrete component of the equilibrium self-energy not readily isolated by static ARPES experiments.