In this work, we propose an Accurate and Robust Matching Network (ARM-Net) to facilitate the point cloud regis-tration through accurate and robust point matching. The ARM-Net adopts two drastically different design concepts concerning network architectures. For one thing, ARM-Net utilizes dynamic graph convolution to extract features from evolving topology around a target point, where the neighboring information of that point is continuously changing. For another thing, ARM - N et uses the multi-layer perceptron (MLP) architecture to acquire “global” encoding of each local topology of the same point whose local topology remains constant. After extracting the features, the back-to-back transformers are used to identify self-attention and cross-attention between the two point clouds to be registered, and the matching subnetwork is then used to identify the points that correspond. Moreover, to obtain more local information and improve the distinctness of the extracted features, we propose a simple but effective module of local aggregation based on the K-Nearest Neighbor (KNN) algorithm before the extraction of the features. Providing noise-independent local information and improving registration performance is possible when K is sufficiently large for the local aggregation. For rotation and translation errors, simulation results demonstrate that ARM-Net outperforms other networks in terms of the MSE, RMSE and MAE. For rotation errors, ARM-Net has Root Mean Square Errors (RMSEs) of 0.0639 and 2.08962 for full and partial registration, respectively. For translation errors, ARM-Net has RMSEs of 2×10−6and 0.025574 for full and partial registration, respectively.

In this article, two-hop transmissions in channel-hopping (CH) cognitive-radio wireless networks (CRWNs) with buffer-aided relays are studied. The two-hop relay (rendezvous) model is improved using symmetric CH sequences, which are more suitable for practical CRWNs than the old model using asymmetric ones. A proper buffer storage size in the relays is formulated to minimize the two-hop data-transfer latency. The lower and upper bounds of the steady-state maximum-time-to-rendezvous (MTTR) and throughput with relays are derived with formal proofs. Using the proper buffer size, both metrics can be better controlled and found no worse than twice the original MTTR and throughput without relays. To explore the impacts of utilization probability of Internet of Things (IoT) devices to their performances in a small-scale CRWN, the single-region rendezvous-success (RS) rate and throughput are formulated. For a large-scale CRWN, the model is extended to formulate the multiregion RS rate and throughput with and without relays for the first time. Numerical studies of these analytical models are performed and validated with computer simulations. In summary, the transmission range and number of rendezvousing IoT devices are improved in the large-scale CRWN with relays, and the multiregion RS rate and throughput with relays are found better than those without relays.

We investigate the performance of reactive opportunistic hybrid relaying protocol for two-way relaying communication systems. Many previous works focus on the proactive opportunistic relaying, reactive opportunistic two-way relaying and reactive opportunistic one-way relaying. This work investigates the possibility of combining two-way and one-way relaying for two-way communications. In this work, the outage performance of opportunistic hybrid two-way and one-way relaying protocol is derived and the simulation validates its correctness. From the simulation, we find that the reactive opportunistic hybrid relaying works better when the number of relays is small or when the relays has very limited transmission power such as IoT devices and sensors.

We first investigate the accumulated loopback self-interference (ALSI) under amplify-and-forward (AF) protocol in two-way full-duplex (TWFD) relaying systems with simultaneous wireless information and power transfer (SWIPT). We analyze how SWIPT affects ALSI and establish the condition for ALSI to converge when there is no energy buffer. Unlike ALSI in TWFD relaying without SWIPT (Chang et al., 2019), ALSI in TWFD relaying with SWIPT always converges and does not grow unbounded. In addition, we study the delay performance in such a system under AF and decode-and-forward (DF) protocols. In AF protocol, the condition for successful signal transmissions is provided. When that condition is met, the received signals at the relay can always get through the channels but experience delays. Otherwise, the outage event occurs. In DF protocol, the best-effort scenario (having no energy buffer) and the QoS scenario (having energy buffer) are discussed. The probability of successful transmissions and the distribution of the delay in both scenarios are derived. Simulation results of DF protocol show that the best-effort scenario is suitable for the delay-tolerant service and the QoS scenario is suitable for the delay-sensitive service. Furthermore, AF protocol is more suitable for the service with less QoS demanding.

Two-way full-duplex (TWFD) transmissions in cooperative amplify-and-forward (AF) relaying systems provide a promising way of communications with the improved spectral efficiency by concurrently transmitting/receiving data in the same frequency band and by the two-way transmission protocol. However, the loopback self-interference, caused by the imperfect channel estimation in the loopback link, at the AF relay accumulates and is forwarded to the end users recurrently, which substantially degrades the end users' error performance if this accumulated loopback self-interference (ALSI) does not converge. It is therefore of critical importance to analyze the convergence behavior of the ALSI in the TWFD systems with AF relaying. In this paper, we establish sufficient conditions on the relay power to ensure the convergence of the ALSI, with which the average limiting signal-to-interference-plus-noise ratio at the infinite time horizon is derived. In addition, we specify the relay power at which the signal-to-noise ratio reaches the maximal value under different scenarios and obtain an upper bound to the symbol error rate. Finally, extensive computer simulations results are provided to corroborate the analytic derivations.

In this work, we acknowledge the existence of the accumulation of the loopback self-interference when AF protocol is made used of in FDTW relaying and the channel estimation of the loopback channel is not done perfectly as will seen in the section to follow. The accumulation of the loopback self-interference comes from the functionality of FD antenna, which will bring back the transmitted signal to interfere with the current incoming signal. The accumulation of the loopback self-interference can be mathematically expressed as the summation of the series of random variables correlated with all the previous channel gains. In this work, we provide the condition when such a summation converges and verify that through simulations.

Besides designing channel-hopping (CH) sequences, finding good methods of communication rendezvous is important for improving spectral efficiency and alleviating traffic load of cognitive radio (CR) networks. In this paper, new asynchronous-symmetric CH sequences are constructed and their (channel overlap, even-channel-use, and pairwise shift invariance) properties are investigated. Their operations in three transmission scenarios involving different basic collision-avoidance mechanisms are analyzed and compared in terms of maximum time-to-rendezvous, rendezvous-success (RS) rate, and RS variance. This paper shows that the new sequences have shorter period, larger cardinality, and smaller RS variations than other CH sequences, thus supporting greater number of secondary users and more frequent and uniform rendezvous in the CR networks.

Protocol sequences have recently been studied in collision channels without feedback for dynamic multiple-access mobile applications, such as wireless sensor and vehicular ad hoc networks. In this paper, a method of systematically adding mark chips into some families of prime sequences for the construction of protocol sequences with adjustable duty factors is investigated. Not relying on computer simulation only, new theoretical models of throughput and its variance are formulated to analyze the sequence performance by means of average hit probabilities. Numerical studies and computer simulations are performed to validate the new analytical models. With adjustable duty factors, these protocol sequences support flexible exchange between throughput and the number of active users.

Power and on-off control problems are examined for renewable energy enabled base-stations (BSs) and relay nodes (RNs) in cooperative multicast networks. Renewable energy is utilized at BSs and RNs to reduce the overall grid energy cost. By considering a practical energy consumption model and the statistics of the renewable energy arrival, the optimal transmit powers are first determined by minimizing the expected grid energy consumption subject to an average outage probability constraint at MUs. The optimal solution is found via line search in the general case and is obtained in closed-form at high SNR. In addition, an on-off control policy is also proposed to further reduce the basic operational energy costs. The joint on-off and power control problems are solved approximately using two sequential deflation techniques, namely, the subset-search and the convex-relaxation-based approaches. The power control problem is also extended to the multicarrier scenario with unequal transmit powers and is solved using successive convex approximation. Simulations using the photovoltaic energy arrival model are provided to demonstrate the effectiveness of the proposed schemes. The results show that expending more power at RNs allows for more efficient use of renewable energy and, thus, increases energy-savings.

The grid-connected photovoltaic (PV) power generator has been demonstrated as a promising solution of hybrid energy to leverage instantaneous renewable energy generation for reducing the energy acquired from electrical grid. In light of this technology trend and opportunity, this paper takes an initial attempt to explore the relay selection and power allocation for green cooperative cellular networks with grid-connected PV power generators. By properly considering the distributions of PV power, we propose an opportunistic relay selection scheme to minimize the grid power consumption. We also analyze the performance on the expected total grid power consumption in the whole network and derive a corresponding upper bound. The simulation results demonstrate that more than 53% of grid power can be saved by the exploitation of PV power with the proposed scheme.

We first investigate when it is possible for two nodes in a wireless network to communicate with each other. Based on the result from bond percolation in a two-dimensional lattice, as long as the probability that a sub-square is close is less than 0.5 and each sub-square contains at least four nodes, percolation occurs. Following that, we establish the conditions for full connectivity in a network graph. How two adjacent sub-squares are connected differentiates this work from others. Two adjacent sub-squares are connected if there exists a communicating path between them instead of a direct communication link. The full connectivity occurs almost surely if each sub-square contains at least one node and the probability of having an open sub- edge is no less than 0.3822. Simulations are conducted to validate the proposed conditions for percolation and full connectivity. We also apply the results to SINR model [1]. We find each node can tolerate more interference than that stated in [1]. Last, we extend the results to the case of unreliable transmission. Under this situation, increasing nodes per sub-square or maintaining the probability of successful transmission above a certain threshold seems to be two possible approaches to achieve percolation and full connectivity.

In this work, we will focus on which modulation scheme should be supported given the knowledge of SNRs of all links in a simple DF cooperative communication system where only one relay is present. Two rules are proposed, namely the exact rule and the approximate rules. The exact rule is derived based on the exact SER. However, the decision of which modulation scheme in the exact rule is used for current transmission is not straightforward. This motivates us to derived the approximate rule based on three key observations. The conducted simulation shows that the performance of the exact rule and the proposed approximated rule are similar in terms of average rate.

In this paper, we propose a passive-blind scheme for detecting forged images. The scheme leverages quantization table estimation to measure the inconsistency among images. To improve the accuracy of the estimation process, each AC DCT coefficient is first classified into a specific type; then the corresponding quantization step size is measured adaptively from its energy density spectrum (EDS) and the EDS's Fourier transform. The proposed content-adaptive quantization table estimation scheme is comprised of three phases: pre-screening, candidate region selection, and tampered region identification. In the pre-screening phase, we determine whether an input image has been JPEG compressed, and count the number of quantization steps whose size is equal to one. To select candidate regions for estimating the quantization table, we devise a candidate region selection algorithm based on seed region generation and region growing. First, the seed region generation operation finds a suitable region by removing suspect regions, after which the selected seed region is merged with other suitable regions to form a candidate region. To avoid merging suspect regions, a candidate region refinement operation is performed in the region growing step. After estimating the quantization table from the candidate region, an maximum-likelihood-ratio classifier exploits the inconsistency of the quantization table to identify tampered regions block by block. To evaluate the scheme's performance in terms of tampering detection, three common forgery techniques, copy-paste tampering, inpainting, and composite tampering, are used. Experiment results demonstrate that the proposed scheme can estimate quantization tables and identify tampered regions effectively.

Cooperative communication has been drawn much attention recently due to the benefit of diversity; however, this technique also reduces the spectral efficiency. To aim at this problem, adaptive modulation is a possible remedy to achieve better efficiency especially for the multinode cooperative communication system. In this work, the Gilbert channel model is adopted to emulate the behavior of the decode-and-forward protocol at the relay nodes. At the destination node, three commonly used combining methods are evaluated, such as the maximum ratio combination (MRC), the equal gain combination (EGC), and the pre-weighted maximum ratio combination (Pre-MRC). The mathematical analysis of the total SNR of each case is also conducted, including the exact results for MRC and proper upper bounds for EGC and Pre-MRC. Based on this analysis, the improvement of multinode cooperation is validated. Meanwhile, the diversity benefit of this system will be also studied via the comparison with the traditional multiple-input single-output (MISO) system.

OFDM-based communication systems have been widely used in several wireless network applications. In order to achieve a more efficient resource allocation, an novel bit and power allocation algorithm with lifetime consideration is proposed. In this work, the lifetime is specified by the portion of power or energy that a particular user can enjoy during the entire transmission. The proposed algorithm aims at the maximization of total transmission rate so that the lifetime constraint can be fulfilled in the long run. The proposed algorithm consists of two steps. In the first step, the optimal solution is found via the Lagrange multiplier method. However, the optimal solution is infeasible. In the second step, a suboptimal solution is achieved based on the optimal solution in the first step. Through the rigorous mathematical proof, the proposed algorithm is shown to be able to fulfill the lifetime requirement. Also, the simulation results show the validation of the theoretical derivation and the feasibility of the proposed algorithm.

In this paper, we proposed a passive scheme to achieve image tampering detection. To correctly estimate the quantization table, each AC DCT coefficient is classified into different types and then the corresponding quantization stepsize is adaptively measured from its power spectrum density (PSD) and PSD's Fourier transform. Based on the quantization table estimation, the proposed scheme is composed of pre-screening, candidate region selection, and tampering region identification. The pre-screening is developed to decide whether an image had been JPEG compressed. To select candidate regions for estimating quantization table, a seed region is first selected by finding a suitable region by removing suspicious regions. Based on the seed region, the candidate region can be obtained by suitably merging other regions into the seed. To avoid merging the suspect regions, a candidate region refinement is performed in the region growing. After estimating the quantization table from the candidate region, a MLR classifier based on the inconsistency of quantization table is exploited to identify tampered regions block by block. The experimental results demonstrate that our proposed scheme can not only estimate the quantization table but also identify tampered regions well.

We investigate a commonly used power control scheme called single-step power control (SSPC) in finite state Markov channel (FSMC). The performance of SSPC is highly affected by two major factors, the power control error (PCE) and the imperfect feedback of the SSPC commands. In the first part of this work, we aim at modelling the behavior of PCE in FSMC. Based on the proposed PCE model, BER and PER performance are evaluated. Simulation results have shown the validity of the proposed PCE model, derived PER and BER in this work. In the second part of this work, SSPC models under different scenarios are established in order to understand the impact of the imperfect feedback on SSPC commands and to obtain the interactions between SSPC and FSMC. We consider four scenarios, perfect feedback, command error, command loss and command delay. The associated transitional probabilities of each scenario are given. Extensive simulation has shown the accuracy of the proposed SSPC models in these four scenarios.

In this paper, we propose a feature-based scheme for detecting different genres of video shot transitions based on spatio-temporal analysis and model parameter estimation. We use the histogram difference and a modified version of it to detect cuts and reduce the impact of fleeting lights. To deal with dissolves, a hybrid algorithm composed of adaptive thresholding, parameter calculation, and transition duration refinement is proposed. In addition, to find a precise duration, we develop a transition duration refinement method to examine each dissolve candidate. The associated model parameters of the dissolve are also estimated as features. After feature extraction, a fuzzy classifier integrates the features to distinguish non-transitions, cuts, and dissolves from one to another. The results of experiments demonstrate that the proposed scheme not only detects cuts and dissolves well, but also accurately locates the duration of each dissolve transition. In addition, the proposed scheme outperforms existing methods in terms of cut and dissolve detection.

In this paper, we propose a feature-based scheme for detecting different genres of video shot transitions based on spatio-temporal analysis and model parameter estimation. In feature extraction, the histogram difference and its modified versions are calculated from the effectiveness of detecting cuts and reducing the impact of fleeting lights. We propose a hybrid algorithm composed of adaptive thresholding, parameter calculation, and transition duration refinement to measure model parameters. Some properties of the associated model parameters of each transition are computed as features. A feature measuring the time gap between two consecutive shots is also adopted. After feature extraction, a fuzzy classifier integrates these features to distinguish nontransitions, cuts, and dissolve-type features from one to another. Many test videos having different types of shots are used for performance evaluation. The experimental results demonstrate that the proposed scheme not only detects cuts, dissolves, and fades well, but also accurately locates the duration of each dissolve-type transition. In addition, the proposed scheme outperforms some existing methods in terms of cut and dissolve detection.

Much attention had been devoted to study the bit error rate (BER) of hierarchical modulation on point-to-point transmissions in recent years. But few mention the error performance of hierarchical modulation on cooperative communication systems. Thus, in this paper, we derive the explicit closed-form expressions of the exact bit error rate computation for cooperative communication systems with hierarchical modulation over additive white Gaussian noise (AWGN) channels and Rayleigh fading channels. To obtain the theoretical formulas of error rate performance, an analyzing model is proposed to clearly express all possibilities of each transmission. For error rate performance, the expression for BER is a function of distance parameters. Based on this relationship, a criterion is proposed to choose the optimal distance parameters for minimizing the BER of the refinement bits while guaranteeing the BER requirement of the base bits. Simulation results validate the correctness of the derived BERs of the base bits and the refinement bits. Also from simulation results, the performance with optimal distance parameters is greatly improved compared to the non-optimal distance parameters.

The analysis regarding the impact of the single-step power control (SSPC) scheme on the system performance such as bit error rate, packet error rate and queueing variation is hard to access. In this work, we propose an approach to analyze that impact when being in finite state Markov channel (FSMC). To achieve the understanding of the relationship between SSPC, FSMC, and the queueing variation, power control error (PCE), error rate, and PDF of queueing length are first calculated. PCE variation is modelled, which then benefits the evaluation of packet error rate (PER) and bit error rate (BER). Furthermore, based on these results, a queueing model is proposed to describe the variation of queueing length, which is an embedded Markov chain. The proposed queueing model can help determine the optimal queueing buffer size and the optimal target SNR for a specific overflow probability under. Simulation results have shown the validation of the proposed PCE variation model and queueing variation model.

The analysis regarding the impact of the single-step power control (SSPC) scheme on the system performance such as bit error rate, packet error rate, and queueing variation is hard to access. In this work, we propose an approach to analyze that impact when being in finite state Markov channel (FSMC). To achieve the understanding of the relationship between SSPC, FSMC, and the queueing variation, power control error (PCE), error rate, and the PDF of queueing length are first calculated. PCE variation is modelled, which then benefits the evaluation of packet error rate (PER) and bit error rate (BER). Furthermore, based on these analysis, a SSPC model is proposed to simplify the overall system. The behavior of SSPC in FSMC can be better understood with the help of the proposed SSPC model. Simulation results have shown the validation of the proposed PCE variation model and SSPC model.

A cross-layer approach to contour nodes inference of monitored physical phenomena with data fusion in wireless sensor networks is investigated in this work. The authors first analyze three sources of signal distortion: sensing noise, data quantization error and data communication noise. The sensing noise is often negligible. We need to choose the proper data quantization levels to balance the communication cost and the desired signal quality. Besides, data fusion at a local fusion center can be used to mitigate the communication noise due to the poor wireless channel. Instead of making a hard binary decision, the probability for a sensor node to be a contour node is calculated at the local fusion center. An adaptive data fusion scheme is proposed to avoid excessive packet retransmissions. Simulation results are given to show the effects of different system parameters on the overall system performance.

Cross-layer design has been drawing much attention recently. However, few works are related to how traditional power control schemes, like single-step and multiple-step power control schemes, affect the queueing performance. In light of this, we will compare the queueing performance of single-step and multiple-step power control schemes in finite state Markov channel (FSMC) through simulation in this work. Along with this comparison, we will propose an approach to estimate the power control error (PCE) in the single-step power control scheme. Based on the estimated PCE, the theoretical performance of single-step power control scheme is given. Simulation results have shown that the multiple-step power control scheme is superior to the single-step power control scheme regarding queueing length, service time and throughput. Simulations also validates the proposed PCE estimation and the theoretical performance based on the estimated PCE.

A statistical approach to distributed edge region detection in wireless sensor networks, which is optimized under the Neyman-Pearson (NP) criterion, is proposed in this work. The concept of edge nodes is adopted to label the defined edge region. Even though statistical methods have been proposed to detect edge nodes, a rigorous way to select the threshold value is lacking. Based on the NP criterion, a decision-fusion approach is developed to address the problem of threshold selection. Performance comparison of the proposed approach and the classifier-based approach is conducted. Simulation results show that the proposed approach is more stable and outperforms the classifier-based approach when there is a location error.

In this paper, we present a switch-based algorithm locating subchannels and an adaptive modulation in multi-service stream orthogonal frequency division multiplexing (OFDM) systems. Conventional schemes were proposed to optimize the system performance, such as bandwidth efficiency, Bit error rate (BER), and etc. However, these schemes could result in the unfairness in resource allocation. Thus, in this work, a new resource allocation algorithm based on weighted round robin (WRR) is proposed to conquer this unfairness, improve the system throughput and maintain the queueing length of each individual stream to a predefined region. Meanwhile, combining the adaptive assignment in diverse subchannels not only augments the bandwidth efficiency but also suboptimizes the entire performance in the environment with the limited resource. The ability of maintaining the queueing length could guarantee the queueing delay according to Little's law. This feature makes the proposed approach suitable for delay constraint services. The preliminary simulation results demonstrate the aforementioned ability.

A distributed approach to contour line extraction in a multi-modal field using wireless sensor networks is proposed in this work. In contrast with previous work on edge or boundary estimation, which is primarily concerned with the region of a certain phenomenon, contour lines offer more detailed information about the underlying phenomenon. To effectively utilize the limited resources of sensors, a cluster-based data fusion technique is adopted so that the phenomenon of interest can be monitored in the base station (BS) without demanding excessive raw data transmission. Simulation results are given to demonstrate the efficiency of the proposed approach. Furthermore, some analysis is conducted to understand the impact of the sensor density and noise on the performance of the proposed approach.

An algorithm to extract contour lines using wireless sensor networks is proposed for environmental monitoring in this work. In contrast to previous work on edge detection that is primarily concerned with the region of a certain phenomenon, contour lines offer more detailed information about the underlying phenomenon such as signal amplitude, density and source location. A distributed algorithm to extract the contour line information from local measurements is developed so that the phenomenon can be monitored in the basestation without demanding excessive raw data transmission. Simulation results are provided to demonstrate the efficiency of the proposed algorithm.

A statistical approach to distributed edge sensor detection with wireless sensor networks is proposed in this research. The objective is to determine whether a target sensor is located in the edge area of a certain phenomenon or not, based on data from its neighboring sensors. Due to the nature of wireless sensor networks, it is desirable to have a distributed algorithm that has a low computational complexity and a low data communication cost among sensors. With some reasonable assumptions and the aid of composite hypothesis testing, we propose data fusion as well as decision fusion methods for edge sensor detection to fulfill the aforementioned constraints. Numerical experiments are used to demonstrate the efficiency of the proposed algorithm.

A statistical approach to distributed edge sensor detection is proposed for wireless sensor networks. Edge sensor detection is a technique to decide whether a target sensor is an edge sensor and is based on data from its neighboring sensors. It is desirable that the computational complexity be low and the amount of data transferred among sensors be small. With some reasonable assumptions and the maximal likelihood technique, we propose both one-level and two-level decision methods to fulfil the above two constraints.

A power control scheme for packet-based wireless communication systems is proposed in this paper. The proposed power control scheme aims at minimizing the total number of transmissions that a packet needs before it is received successfully over a Rayleigh fading channel subject to two constraints. One is that the transmission power should be greater than zero. The other is imposed by the constraint on the total transmission power at the base station. We use the augmented Lagrangian multiplier method to solve this problem and provide a theoretical solution. The simulation results show that, with the proposed power control scheme, the number of re-transmission can be reduced and the delay of a packet wasted in the channel can be decreased as well.

The downlink SINR performance for multi-rate W-CDMA systems is derived in this research when the concatenated OVSF/truncated PN code is used. The derivation is complicated by the fact that the auto-correlation term of the concatenated OVSF/truncated PN code is not a random noise. It is shown that this auto-correlation term can be approximated as a binomial random variable. The analytic SINR performance can be obtained based on this approximation, and it matches well with the numerical result.