Neighbor Hopping Research Articles

Approximating Common Control Channel Problem in Cognitive Radio Networks

Cognitive radio networks (CRNs) involve an extensive exchange of control messages to coordinate spectrum sensing, medium access, routing, etc. Static control channel allocation uses preassigned common control channel (CCC) contrary to the opportunistic access paradigm. We propose a k-hop clustering scheme for the optimal CCC assignment problem (k-CCCP) for CRNs. We prove that the k-CCCP problem is NP-hard (nondeterministic polynomial-time hard) by reduction using minimum dominating set problem. We also found that the k-CCCP problem is approximable hard. We propose a ln Δ approximation algorithm for the k-CCCP problem, where Δ is the largest cardinality among all khop neighborhood in a CRN. To account for primary user dynamics, we propose a distributed ranking algorithm for the k-CCCP problem with message complexity O(nδk), where n, δ, and k are number of nodes, the largest node degree, and hop parameter, respectively. To address the negative effect of multihop clustering, we also propose a mechanism to find the optimal k value in multihop clustering. For performance comparison, extensive simulations are performed and the results show that our proposed scheme outperforms with the competitive schemes.

Manipulating quantum materials with quantum light

We show that the macroscopic magnetic and electronic properties of strongly correlated electron systems can be manipulated by coupling them to a cavity mode. As a paradigmatic example we consider the Fermi-Hubbard model and find that the electron-cavity coupling enhances the magnetic interaction between the electron spins in the ground-state manifold. At half filling this effect can be observed by a change in the magnetic susceptibility. At less than half filling, the cavity introduces a next-nearest neighbour hopping and mediates a long-range electron-electron interaction between distant sites. We study the ground state properties with Tensor Network methods and find that the cavity coupling can induce a new phase characterized by a momentum-space pairing effect for electrons.

A Black-Burst Based Time Slot Acquisition Scheme for the Hybrid TDMA/CSMA Multichannel MAC in VANETs

In the hybrid time division multiple access (TDMA)/carrier sense multiple access multichannel medium access control protocols for vehicular ad hoc networks, each vehicle randomly selects a time slot from available ones for the transmission of safety message in the TDMA-based part. However, the access collision will occur when two or more vehicles within two-hop range of each other attempt to acquire an identical idle slot, which degrades the performance of access process. In this letter, we propose a novel time slot acquisition scheme based on jamming signal, also known as black-burst. To reduce access collisions, each vehicle tries to send a randomly shifted black-burst to inform its one and two hop neighbors when it reserves an idle time slot. Simulation results show that the proposed scheme outperforms the state-of-the-art scheme in terms of time slot acquisition efficiency.

Learning Automaton-Based Neighbor Discovery for Wireless Networks Using Directional Antennas

This letter studies the problem of neighbor discovery (i.e., finding 1-hop neighbor nodes) in a wireless adhoc network, with exclusive use of directional antennas. We model the neighbor discovery process as a learning automaton, operating in a non-stationary learning environment with unknown dynamics. The node learns about its environment from its past observations and adjusts its strategy to achieve a faster discovery rate. The asymptotic behavior of the proposed learning scheme is analyzed and is shown to converge to an equi-probable probability distribution. The proposed scheme achieves significantly faster network-wide neighbor discovery in densely populated networks.

The effect of boundaries and impurity on a system with non-local hop dynamics

We study a one-dimensional lattice model of particles which interact with each other via hard-core repulsion, and which can make long hops in addition to the usual nearest neighbour hopping dynamics. The parameter p gives the probability for long hops and the p = 0 limit leads to the well studied totally asymmetric simple exclusion process (TASEP). The first part of this study describes the combined effect of open boundaries and long hops on the steady state of the system. Apart from the usual low density (LD), high density (HD) and maximum current (MC) phases, the introduction of a finite p leads to a new possibility-an empty road (ER) phase with particles clearing out faster than they enter. The variation in the phase diagram with p is interesting, with the LD and MC phases vanishing at large values of p while the ER and HD phases divide the parameter space into 1/2. In the second part of this study, we look at the combined effect of long hops and static/dynamic impurities. The boundaries are taken to be periodic for simplicity. We see that the system with a static impurity and with 0 < p < 1 shows a phase transition from a shock phase characterised by finite densities on either side of the shock (HD–LD phase) to a phase where the density on one side of the shock is zero (HD-ER phase). We also study the effect of a dynamic impurity, introduced via a slow particle. Here, the system undergoes a phase transition from a homogeneous phase to a shock phase depending on the density, the speed of the particle, as well as the probability p. The shock phase dominates the phase diagram at large values of p. All our studies involve numerical simulations which are supported by mean field theory arguments. The mean field approximation works well qualitatively and correctly identifies the possible phases, while the quantitative agreement with numerics varies, depending on parameter values.

Significant improvement of reverse leakage current characteristics of Si-based homoepitaxial InGaN/GaN blue light emitting diodes

The nature of reverse leakage current characteristics in InGaN/GaN blue light emitting diodes (LEDs) on freestanding GaN crystals detached from a Si substrate is investigated for the first time, using temperature-dependent current-voltage (T-I-V) measurement. It is found that the Si-based homoepitaxial InGaN/GaN LEDs exhibit a significant suppression of the reverse leakage current without any additional processes. Their conduction mechanism can be divided into variable-range hopping and nearest neighbor hopping (NNH) around 360 K, which is enhanced by Poole-Frenkel emission. The analysis of T-I-V curves of the homoepitaxial LEDs yields an activation energy of carriers of 35 meV at −10 V, about 50% higher than that of the conventional ones (Ea = 21 meV at −10 V). This suggests that our homoepitaxial InGaN/GaN LEDs bears the high activation energy as well as low threading dislocation density (about 1 × 106/cm2), effectively suppressing the reverse leakage current. We expect that this study will shed a light on the high reliability and carrier tunneling characteristics of the homoepitaxial InGaN/GaN blue LEDs produced from a Si substrate and also envision a promising future for their successful adoption by LED community via cost-effective homoepitaxial fabrication of LEDs.

Temperature-filling phase diagram of the two-dimensional Holstein model in the thermodynamic limit by self-consistent Migdal approximation

We study the temperature-filling phase diagram of the single-band Holstein model in two dimensions using the self-consistent Migdal approximation, where both the electron and phonon self-energies are treated on an equal footing. By employing an efficient numerical algorithm utilizing fast Fourier transforms to evaluate momentum and Matsubara frequency summations, we determine the charge-density-wave (CDW) and superconducting transition temperatures in the thermodynamic limit using lattice sizes that are sufficient to eliminate significant finite size effects present at lower temperatures. We obtain the temperature-filling phase diagrams for a range of coupling strengths and phonon frequencies for the model defined on a square lattice with and without next-nearest neighbor hopping. We find the appearance of a superconducting dome with a critical temperature that decreases before reaching the $\mathbf{q}_{\text{max}} = (\pi,\pi)$ CDW phase boundary. For very low phonon frequencies, we also find an incommensurate CDW phase with the ordering vector $\mathbf{q}_{\text{max}} \approx (\pi,\pi)$ appearing between the commensurate CDW and superconducting phases. Our numerical implementation can be easily extended to treat momentum-dependent electron-phonon coupling, as well as dispersive phonon branches, and has been made available to the public.

Exploiting Layered Multi-Path Routing Protocols to Avoid Void Hole Regions for Reliable Data Delivery and Efficient Energy Management for IoT-Enabled Underwater WSNs.

The key concerns to enhance the lifetime of IoT-enabled Underwater Wireless Sensor Networks (IoT-UWSNs) are energy-efficiency and reliable data delivery under constrained resource. Traditional transmission approaches increase the communication overhead, which results in congestion and affect the reliable data delivery. Currently, many routing protocols have been proposed for UWSNs to ensure reliable data delivery and to conserve the node’s battery with minimum communication overhead (by avoiding void holes in the network). In this paper, adaptive energy-efficient routing protocols are proposed to tackle the aforementioned problems using the Shortest Path First (SPF) with least number of active nodes strategy. These novel protocols have been developed by integrating the prominent features of Forward Layered Multi-path Power Control One (FLMPC-One) routing protocol, which uses 2-hop neighbor information, Forward Layered Multi-path Power Control Two (FLMPC-Two) routing protocol, which uses 3-hop neighbor information and ’Dijkstra’ algorithm (for shortest path selection). Different Packet Sizes (PSs) with different Data Rates (DRs) are also taken into consideration to check the dynamicity of the proposed protocols. The achieved outcomes clearly validate the proposed protocols, namely: Shortest Path First using 3-hop neighbors information (SPF-Three) and Breadth First Search with Shortest Path First using 3-hop neighbors information (BFS-SPF-Three). Simulation results show the effectiveness of the proposed protocols in terms of minimum Energy Consumption (EC) and Required Packet Error Rate (RPER) with a minimum number of active nodes at the cost of affordable delay.

Position Certainty Propagation: A Localization Service for Ad-Hoc Networks

Location services for ad-hoc networks are of indispensable value for a wide range of applications, such as the Internet of Things (IoT) and vehicular ad-hoc networks (VANETs). Each context requires a solution that addresses the specific needs of the application. For instance, IoT sensor nodes have resource constraints (i.e., computational capabilities), and so a localization service should be highly efficient to conserve the lifespan of these nodes. We propose an optimized energy-aware and low computational solution, requiring 3-GPS equipped nodes (anchor nodes) in the network. Moreover, the computations are lightweight and can be implemented distributively among nodes. Knowing the maximum range of communication for all nodes and distances between 1-hop neighbors, each node localizes itself and shares its location with the network in an efficient manner. We simulate our proposed algorithm in a NS-3 simulator, and compare our solution with state-of-the-art methods. Our method is capable of localizing more nodes (≈90% of nodes in a network with an average degree ≈10).

Geographic opportunistic routing protocol based on two-hop information for wireless sensor networks

To improve energy efficiency and packet delivery ratio in WSNs. We propose a two-hop geographic opportunistic routing (THGOR) protocol that selects a subset of 2-hop neighbours of node which have higher packet reception ratio and residual energy as the next forwarder node, it also selects 1-hop neighbours that have excellent coverage of 2-hop neighbours as relay nodes. The proposed protocol is compared with geographic opportunistic routing (GOR) and efficient QoS-aware geographic opportunistic (EQGOR). GOR and EQGOR select a forwarding sensor node on the basis of distance. However, GOR and EQGOR results in lower packet delivery rate, and quick depletion of energy. The THGOR is comprehensively evaluated through NS-2 and compared results with EQGOR and GOR. Simulation results show that THGOR significant improvement in packet advancement, reliable transmission, energy efficiency and optimises packet transmission delay.

2-Hopper: Accurately Estimate Individual and Social Attributes of Social Networks With Fewer Repeats via Random Walk

Random-walk based sampling is widely used to characterize large graphs by producing samples in the form of nodes. However, existing random-walk based sampling methods only focus on the estimation accuracy of structural properties but suffer from repetitive samples which have adverse effects on obtaining accurate information about the structures over social networks represented by large graphs. Furthermore, these existing methods mainly characterize individual attributes while ignoring the social attributes of the nodes. In this paper, a new random-walk based method, called 2-hop neighbors based random walk or 2-Hopper, is proposed to obtain accurate estimations of both basic and social attributes with fewer repetitive samples. Specifically, 2-Hopper is able to greatly reduce redundant paths among nodes during the sampling process and thus produces few repeats. Based on 2-Hopper’s sampling process, a re-weighted estimator is proposed to accurately obtain both the individual and social properties while the latter is obtained by a newly proposed algorithm. Experimental results driven by real-world datasets show that on average 2-Hopper can reduce 4.5 times repetitive samples of the state-of-the-art random-walk based methods and obtain more accurate information about the individual and social attributes while 2-Hopper is able to estimate the structural properties of these attributes accurately over large graphs.

Hybrid Self-Organized Clustering Scheme for Drone Based Cognitive Internet of Things

Network management by using a cognitive approach is an attractive solution for drone-based Internet of Things (IoT) environment to provide many modern facilities to IoT users. In this paper, we try to minimize the networking related issues for drone-based IoT by providing a self-organized cluster-based networking solution. We propose a Hybrid Self-organized Clustering Scheme (HSCS) for drone-based cognitive IoT which utilizes a hybrid mechanism of glowworm swarm optimization (GSO) and dragonfly algorithm (DA). The proposed scheme contains cluster formation and cluster head selection mechanism based on GSO. Furthermore, we propose an effective cluster member tracking methodology using the behavioral study of DA which ensures efficient cluster management. The cluster maintenance is performed by a mechanism to identify dead cluster member which improves the stability of the network. Further routing mechanism is proposed for HSCS in which next hop neighbor for data transmission is selected by using the route selection function which ensures efficient communication. The performance of HSCS is evaluated in terms of cluster building time, energy consumption, cluster lifetime, and the probability of delivery success with existed hybrid bio-inspired clustering algorithm.

Determination of polaronic conductivity in disordered double perovskite La2CrMnO6

Double perovskite La2CrMnO6 ceramics was sintered using standard high temperature route in ambient air. The orthorhombic Pbnm cell characterized by a total disorder between Cr and Mn ions was determined using an XRD powder test. The grain morphology, porosity and chemical composition were determined using scanning electron microscopy. The X-ray photoemission spectroscopy showed several contributions to O 1 s, La 3d, Mn 2p, and Cr 2p core lines related to the occurrence of multiple ionic states. The electrical permittivity, modulus, AC and DC conductivity were measured in ranges of f = 20 Hz – 1 MHz and 76–440 K. The electrical transport mechanism was attributed to the small polarons. The nearest neighbor hopping occurred in the range 170 to 440 K. The variable range hoping, attributed to the Fermi glass features and disorder, was detected in the range 100 to 160 K. The relaxation process related to the temperature-independent activation energy was deduced from the electric modulus scaling.

Extremely correlated Fermi liquid of the t−J model in two dimensions

We study the two-dimensional $t$-$J$ model with second neighbor hopping parameter $t'$ and in a broad range of doping $\delta$ using a closed set of equations from the {\em Extremely Correlated Fermi Liquid} (ECFL) theory. We obtain asymmetric energy distribution curves and symmetric momentum distribution curves of the spectral function, consistent with experimental data. We further explore the Fermi surface and local density of states for different parameter sets. Using the spectral function, we calculate the resistivity, Hall number and spin susceptibility. The curvature change in the resistivity curves with varying $\delta$ is presented and connected to intensity loss in Angle Resolved Photoemission Spectroscopy (ARPES) experiments. We also discuss the role of the super-exchange $J$ in the spectral function and the resistivity in the optimal to overdoped density regimes.

Study on similarity indices for link prediction in opportunistic networks

Link prediction aims to estimate the existence of links between nodes, using information of network structures and node properties. According to the characteristics of node mobility, node intermittent contact, and high delay of opportunistic network, novel similarity indices are constructed based on CN, AA, and RA. The indices CN, AA, and RA do not consider the historic information of networks. Similarity indices, T_CN, T_AA, and T_RA, based on temporal characteristics are proposed. These take the historic information of network evolution into consideration. Using historic information of the evolution of opportunistic networks and 2-hop neighbor information of the nodes, similarity indices based on the temporal-spatial characteristics, O_CN, O_AA, and O_RA, are proposed. Based on the imote traces cambridge (ITC) and detected social network (DSN) datasets, the experimental results indicate that similarity indices O_CN, O_AA, and O_RA outperform CN, AA, and RA. Furthermore, index O_AA has superior performance.

Fermi surface pockets in electron-doped iron superconductor by Lifshitz transition

The Fermi surface pockets that lie at the corner of the two-iron Brillouin zone in heavily electron-doped iron selenide superconductors are accounted for by an extended Hubbard model over the square lattice of iron atoms that includes the principal 3dxz and 3dyz orbitals. At half filling, and in the absence of intra-orbital next-nearest neighbor hopping, perfect nesting between electron-type and hole-type Fermi surfaces at the the center and at the corner of the one-iron Brillouin zone is revealed. It results in hidden magnetic order in the presence of magnetic frustration within mean field theory. An Eliashberg-type calculation that includes spin-fluctuation exchange finds that the Fermi surfaces undergo a Lifshitz transition to electron/hole Fermi surface pockets centered at the corner of the two-iron Brillouin zone as on-site repulsion grows strong. In agreement with angle-resolved photoemission spectroscopy on iron selenide high-temperature superconductors, only the two electron-type Fermi surface pockets remain after a rigid shift in energy of the renormalized band structure by strong enough electron doping. At the limit of strong on-site repulsion, a spin-wave analysis of the hidden-magnetic-order state finds a ‘floating ring’ of low-energy spin excitations centered at the checkerboard wavenumber . This prediction compares favorably with recent observations of low-energy spin resonances around (π, π) in intercalated iron selenide by inelastic neutron scattering.

Origin of Mott Insulating Behavior and Superconductivity in Twisted Bilayer Graphene

A remarkable recent experiment has observed Mott insulator and proximate superconductor phases in twisted bilayer graphene when electrons partly fill a nearly flat mini-band that arises a `magic' twist angle. However, the nature of the Mott insulator, origin of superconductivity and an effective low energy model remain to be determined. We propose a Mott insulator with intervalley coherence that spontaneously breaks U(1) valley symmetry, and describe a mechanism that selects this order over the competing magnetically ordered states favored by the Hunds coupling. We also identify symmetry related features of the nearly flat band that are key to understanding the strong correlation physics and constrain any tight binding description. First, although the charge density is concentrated on the triangular lattice sites of the moir$\text{\'e }$ pattern, the Wannier states of the tight-binding model must be centered on different sites which form a honeycomb lattice. Next, spatially localizing electrons derived from the nearly flat band necessarily breaks valley and other symmetries within any mean-field treatment, which is suggestive of a valley-ordered Mott state, and also dictates that additional symmetry breaking is present to remove symmetry-enforced band contacts. Tight-binding models describing the nearly flat mini-band are derived, which highlight the importance of further neighbor hopping and interactions. We discuss consequences of this picture for superconducting states obtained on doping the valley ordered Mott insulator. We show how important features of the experimental phenomenology may be explained and suggest a number of further experiments for the future. We also describe a model for correlated states in trilayer graphene heterostructures and contrast it with the bilayer case.

Synthesis and Characterization of Porous Carbon/Nickel Oxide Nanocomposites for Gas Storage and Negatronic Devices

Porous organic/inorganic nanocomposites were synthesized by sol–gel technique after the incorporation of nickel oxide (NiO) nanoparticles in carbon composite based on pyrogallol and formaldehyde (PF) using picric acid as catalyst. After a drying step, the samples were heated during 2 h at different pyrolysis temperatures from 600 to 1000 °C in tubular furnace under nitrogen atmosphere. The XRD pattern exhibit that PF composite is amorphous even after thermal treatment at 1000 °C. On the other hand, the PF/NiO nanocomposites are crystallized with the appearance of the graphite structure at high pyrolysis temperature. The gas adsorption capacities for CO2 indicate that the PF composite has a tendency to adsorb CO2 higher than PF/NiO nanocomposite. In fact, the maximum value of capacity is of the order 7.5 mmol/g in PF composite and 6.5 mmol/g in PF/NiO nanocomposite. The dc conductivity shows the dominance of percolation phenomenon and explained by two models; the three dimensions variable range hopping and the nearest neighbor hopping. The voltage–current V(I) characteristics show the presence of negative differential resistance at room measurement temperature in PF/NiO-625 °C sample. The ac conductance is attributed to different origins, so it is decried by two models, like hopping conduction mechanism in PF-675 °C composite and small polaron hopping model in PF/NiO-625 °C nanocomposite.

Role of topology on the work distribution function of a quenched Haldane model of graphene

We investigate the effect of equilibrium topology on the statistics of non-equilibrium work performed during the subsequent unitary evolution, following a sudden quench of the Semenoff mass of the Haldane model. We show that the resulting work distribution function for quenches performed on the Haldane Hamiltonian with broken time reversal symmetry (TRS) exhibits richer universal characteristics as compared to those performed on the time-reversal symmetric massive graphene limit whose work distribution function we have also evaluated for comparison. Importantly, our results show that the work distribution function exhibits different universal behaviors following the non-equilibrium dynamics of the system for small $\phi$ (argument of complex next nearest neighbor hopping) and large $\phi$ limits, although the two limits belong to the same equilibrium universality class.

Nonresonant Raman scattering in extremely correlated Fermi liquids

We present theoretical results for the optical conductivity and the non-resonant Raman susceptibilities for three principal polarization geometries relevant to the square lattice. The susceptibilities are obtained using the recently developed extremely correlated Fermi liquid theory for the two-dimensional t-t'-J model, where t and t' are the nearest and second neighbor hopping. Our results are sensitively depending on t, t'. By studying this quartet of related dynamical susceptibilities, and their dependence on t, t', doping and temperature, we provide a useful framework for interpreting and planning future Raman experiments on the strongly correlated matter.