In this paper we investigate in different scenarios the feasibility of using massive multiple-input multiple-output (mMIMO) with Reconfigurable Intelligent Surfaces (RISs) to boost the throughput and coverage performances with high energy efficiency, considering sub-6 GHz, mmWave and THz bands. With that objective, a centralized radio access network (C-RAN) suitable for beyond fifth generation (B5G) systems is considered, where we integrate the base stations (BSs) with multiple RISs and devices or user equipment. RISs with a large number of quasi-passive reflecting elements constitute a low-cost approach capable of shaping the radio wave propagation and improve wireless connectivity. We consider a scenario where multiple RISs are combined with mMIMO in the uplink in order to provide connectivity to Smart City (thousands of active low power devices) wirelessly, in the 3.6GHz and 28GHz bands. We also address a scenario where RISs are adopted with mMIMO in the downlink so as to offer connectivity to a Stadium with Pitch, (thousands of active user equipment) in the 28GHz band. Finally, we have also studied the connectivity at 100GHz of a Factory where several RIS panels replacing most of the BSs equipped with mMIMO assure improved throughput and coverage. We concluded that RISs are capable of improving the performance in any of these analyzed scenarios at the different frequency bands, justifying that they are a key enabling technology for 6G.

The limitations of conventional sensors have made phased array antennas increasingly crucial for gathering information and communication applications in intelligent transportation systems. Compact cylindrical arrays, in particular, are favored for their ability to achieve azimuth angle scan. However, the substantial mutual coupling effect between elements on curved surfaces and its implication in these arrays remains unclear, which is a crucial factor to consider when such arrays are used for multibeam applications. This study investigated the effect of mutual coupling in a dual-slant-polarized cylindrical array. The results showed that mutual coupling is essential for achieving an ultra-wide bandwidth. Mutual coupling is predominantly observed among elements that are closely positioned. The study also analyzes the impact of mutual coupling on scan impedance and radiation characteristics for multibeam applications and reveals that these arrays exhibit robust multibeam capability, hence having great potential for use in intelligent transportation systems.

The LED light source is an important light source for indoor visible light communication. It has the characteristics of a large divergence angle and a high transmission rate. Therefore, using LED as the light source for visible light full-duplex communication can not only satisfy the lighting requirements but also transmit information at high speed. To analyze the factors that affect the optical power of the indoor single-light source visible light communication uplink receiving end, an indoor visible light communication model was established, and mathematical calculation formulas were derived based on the model establishment, and the maximum movable range formula of the retroreflective end under specific conditions was derived; The reliability of the formula was verified with the help of Zemax simulation software. Theoretical analysis and experimental results show that increasing the movement range of the retroreflective end can be achieved by increasing the lens diameter, reducing the focal length, and increasing the link distance.

The rapid growth in the number of interconnected devices on the Internet (referred to as the Internet of Things – IoT), along with the huge volume of data that are exchanged and processed, has created a new landscape in network design and operation. Due to the limited battery size and computational capabilities of IoT nodes, data processing usually takes place on external devices. Since latency minimization is a key concept in modern era networks, edge servers that are in close proximity to IoT nodes gather and process related data, while in some cases data offloading in the cloud might have to take place. The interconnection of a vast number of heterogeneous IoT devices with the edge servers and the cloud, where IoT, edge and cloud converge to form a computing continuum, is also known as IoT-edge-cloud (IEC) continuum. Several key challenges are associated with this new computing systems architectural approach, including: i) design of connection and programming protocols aimed at properly manipulating a huge number of heterogeneous devices over diverse infrastructures; ii) design of efficient task offloading algorithms aimed at optimizing services execution; iii) support for security and privacy enhancements during data transfer to deal with the existent and even unforeseen attacks and threats landscape; iv) scalability, flexibility and reliability guarantees to face the expected mobility for IoT systems, and; v) design of optimal resource allocation mechanisms to make the most out of the available resources. These challenges become even more significant towards the new era of sixth generation (6G) networks, which will be based on the integration of various cutting edge heterogeneous technologies. Therefore, the goal of this survey paper is to present all recent developments in the field of IEC continuum systems, with respect to the aforementioned deployment challenges. In the same context, potential limitations and future challenges are highlighted as well. Finally, indicative use cases are also presented, from an IEC continuum perspective.

This paper studies a multihop amplify-and-forward (AF) simultaneous wireless information and power transfer (SWIPT) relaying system. Each relaying node harvests energy using power splitting (PS) scheme from a part of its received signal to amplify and forward the rest the received signal to the next relay. Based on this system model and signal flow, we derived and solved the convex energy minimization problem with optimal PS ratio. The influence of processing cost was then investigated for the AF-SWIPT system with the decode-and-forward SWIPT as benchmark, where AF-SWIPT was found to be superior.

Micro-gyroscopes based on the Coriolis principle are widely employed in inertial navigation, motion control, and vibration analysis applications. This paper presents our main contributions which include a novel dual-frame optomechanical gyroscope, a unique photonic crystal cavity design, and advanced numerical simulation and optimization methods. The proposed design utilizes an optical cavity formed between dual oscillating frames, whereby input rotation induces a measurable phase shift via optomechanical coupling. Actuation of the frames is achieved electrostatically via an interdigitated comb-drive design. Through theoretical modeling based on cavity optomechanics and finite element simulation, the operating principle and performance parameters are evaluated in detail. Results indicate an expected angular rate sensitivity of 22.8 mV/°/s and angle random walk of 7.1×10-5 °/h1/2, representing superior precision than to existing micro-electromechanical systems gyroscopes of comparable scale. Detailed analysis of the optomechanical transduction mechanism suggests this dual-frame approach could enable angular vibration detection with resolution exceeding state-of-the-art solutions.

Machine learning offers advanced tools for efficient management of radio resources in modern wireless networks. In this study, we leverage a multi-agent deep reinforcement learning (DRL) approach, specifically the Parameterized Deep Q-Network (DQN), to address the challenging problem of power allocation and user association in massive multiple-input multiple-output (M-MIMO) communication networks. Our approach tackles a multi-objective optimization problem aiming to maximize network utility while meeting stringent quality of service requirements in M-MIMO networks. To address the non-convex and nonlinear nature of this problem, we introduce a novel multi-agent DQN framework. This framework defines a large action space, state space, and reward functions, enabling us to learn a near-optimal policy. Simulation results demonstrate the superiority of our Parameterized Deep DQN (PD-DQN) approach when compared to traditional DQN and RL methods. Specifically, we show that our approach outperforms traditional DQN methods in terms of convergence speed and final performance. Additionally, our approach shows 72.2 % and 108.5 % improvement over DQN methods and RL method respectively in handling large-scale multi-agent problems in M-MIMO networks.

Optical network monitoring and soft failure identification such as optical filter shifting and filter tightening is increasingly significant in the future complex and dynamic optical networks. Center frequency shift of optical filtering device in optical network has a serious impact on the perfor-mance of multi-span transmission, especially in high spectrum efficiency faster-than-Nyquist (FTN) transmission systems with various optical switching and add/drop nodes. Existing moni-toring schemes generally have problem of high cost, high complexity and the inability to realize multi-channel online monitoring, which makes it difficult to be applied in wavelength division multiplexing (WDM) system with numerous nodes. In this paper, a monitoring scheme of fre-quency shift of optical filtering devices based on optical label (OL) is proposed and demonstrated. The signal spectrum of each channel is intentionally divided into many sub-bands with corre-sponding optical labels loading. The characters of spectrum power changing caused by frequency shift can be reflected on labels power changing of each sub-band, which are used to monitor and estimate the value of frequency shift by DSP algorithm. Simulation results shows that the that the monitoring errors of frequency shift can be kept below 0.5GHz reasonably after 10-span WDM transmission in FTN polarization multiplexing m-ary quadrature amplitude modulation (PM-mQAM) systems. In addition, 250km fiber transmission experiments are also carried out and the similar results are obtained, which further verify the feasibility of our proposed scheme. The characters of low cost, high reliability and efficiency make it a better candidate for practical ap-plication in the future FTN WDM networks.

In the Neighborhood Area Network (NAN), the Advanced Metering Infrastructure (AMI) enables a bidirectional connection between the Smart Meter (SM) and the Data Concentrator (DC). Sensors, such as smart meter node or Radio Frequency transceiver, play a crucial role in collecting and transmitting data from meters to central unit for advanced monitoring, management, and analysis of energy consumption. Wired and wireless communication technologies can be used to implement the AMI-NAN. This paper delves into a novel approach for optimizing the choice of communication medium, Radio Frequency (RF) or Power-Line Communication (PLC), between the SM and DC in the context of AMI-NAN. The authors methodically select the specific technologies, RF and NB-PLC (Narrow Band Power-Line Communication), and meticulously characterize their attributes. Then, a comparative analysis spanning rural, urban, and industrial settings is conducted to evaluate the proposed method. The overall reliability performance of the AMI-NAN system requires a Packet Error Rate (PER) lower than 10%. To this end, a comprehensive methodology is introduced to assess and enhance the reliability of NB-PLC and RF for AMI-NAN applications. Simulation results demonstrate that wireless communication is the optimal choice for the rural scenario, especially for Signal to Noise Ratio (SNR) lower than 25 dB. However, in urban environments characterized by higher SNR values and moderately dense networks, NB-PLC gains prominence. In denser networks, it outperforms wireless communication, exhibiting a remarkable 10 dB gain for a bit error rate (BER) of 10-3. Moreover, in industrial zones characterized by intricate network topologies and non-linear loads, the powerline channel emerges as the optimal choice for data transmission, affording a gain surpassing 20 dB.

This paper presents a design and performance analysis of a 10-element 5G massive MIMO antenna array for sub-6GHz mobile handsets, specifically for LTE bands 42 (3400-3600 MHz), 43 (3600-3800 MHz), 48/49 (3550-3700 MHz) applications. The proposed antenna array consists of 10 closely spaced linearly polarized inverted-F antennas with a compact size of 20 × 9 mm2 of a single element. The proposed antenna array provides high gain, high efficiency, and low correlation between the antenna elements, which results in improved channel capacity, increased data rate, and enhanced signal quality. The performance of the antenna array is evaluated in terms of the radiation pattern, gain, efficiency, and correlation coefficient. The simulation and measured results show that the proposed antenna array achieves an approximate peak gain of 3.1 dBi at the resonance frequency, a total efficiency of 65 %, and a low correlation coefficient of 0.06 between the antenna elements. Therefore, the proposed 5G massive MIMO antenna array is a promising candidate for sub-6 GHz mobile handsets, particularly for LTE bands 42/43/48/49 applications.

According to the cognitive radio (CR) paradigm, the efficient use of the radio spectrum is achieved by performing four main functions: spectral perception, spectral mobility, decision-making, and cooperation. In this work, a multivariable algorithm that considers geographic mobility (GM) is presented. The decision-making process includes a feedback mechanism for the dynamic selection of reservation channels in a wireless network with cognitive capabilities. Geographic mobility plays a crucial role in how radio takes advantage of its environment; however, it has been scarcely explored in the literature. In the present work, geographic mobility tests were carried out involving the interaction of CR and primary users (PU), where a measurement of the latency time of the proposed algorithm called: Algorithm for Decision-Making with Geographic Mobility (ATDeMoGeo) was evaluated and compared with other algorithms such as: Dijkstra's Algorithm, Analytic Hierarchical Process (AHP), Fuzzy Analytic Hierarchical Process (FAHP) and Decision-Making Algorithm with Modified Dijkstra (ATDDiM). It was found that the proposed algorithm is robust and that it considerably reduces the latency time to accurately determine the best communication channels, thanks to the decision-making function implemented to establish which channels the CRs can occupy. For the selection of the best reserve channels, a series of criteria were considered, such as: signal-to-interference plus noise ratio (SINR), bandwidth (BW), probability of channel availability (AP), estimated channel time of availability (ETA) using the random waypoint mobility model (RWPM). These criteria are evaluated for two types of service, i.e., real time (RT) and best effort (BE). For the evaluation and validation of the ATDeMoGeo algorithm, a network with cognitive characteristics in NS-3 was simulated. The simulation scenarios consisted of a base station (BS) with mobile CRs and PUs. Based on the previous criteria, i.e., BW, SINR, AP and ETA, the BS assesses the spectrum occupancy information obtained by the CRs. The results show that the proposed algorithm can be used without problem for the proposed scenarios with higher speed and accuracy for the selection of better communication channels.

In order to provide high capacity and universal access of telecommunication networks, this paper reviews and prospects the advanced multiplexing technology, physical layer digital signal processing technology, infrastructure sharing technology, security protection technology, intelligent control management and other key technologies for beyond 100G next generation passive optical network (NG-PON).

In this paper, we propose a pre-configured error pattern ordered statistics decoding (PEPOSD) algorithm and discuss its application to short cyclic redundancy check (CRC)-polar codes. Unlike the traditional OSD that changes the most reliable independent symbols, we regard the decoding process as testing the error patterns, like guessing random additive noise decoding (GRAND). Also, the pre-configurator referred from ordered reliability bits (ORB) GRAND can better control the range and testing order of EPs. Offline-online structure can accelerate the decoding process. Additionally, we also introduce two orders to optimize the search order for testing EPs. Compared with CRC-aided OSD and list decoding, PEPOSD can achieve a better trade-off between accuracy and complexity.

Physical layer secret key (SK) generation is known to be an efficient means to achieve high secrecy rate, on the condition that dynamic channel state information (CSI) is provided. For this reason, the secrecy performance is highly degraded in a static environment. The intelligent reflecting surface (IRS) is a promising solution to create dynamic randomness, and thus lead to enhanced secrecy performance regardless of the user environments. This paper proposes an IRS-assisted physical layer SK generation scheme, by efficiently combing phase information of the direct and reflected channel information in a hybrid way. In particular, the initial SKs are obtained by adopting efficient phase quantization method with symmetric bit allocation to complex numbered channel estimates. Simulation results show that the proposed hybrid phase quantization (PQ) can improve the SK generation rate and the key disagreement probability in a static environment.

The Mine Internet of Things (MIoT), as a key technology for reconstructing post-disaster communication networks, enables to realize the safety monitoring and controlling of the affected roadway. However, due to the challenging underground mine environment, the MIoT suffers from severe signal attenuation, vulnerable nodes, and limited energy, which result in low network reliability of the post-disaster MIoT. To improve the transmission reliability as well as to reduce energy consumption, a directional-area-forwarding-based energy-efficient opportunistic routing (DEOR) for the post-disaster MIoT is proposed. DEOR defines a forwarding zone (FZ) for each node to route packets toward the sink. The candidate forwarding set (CFS) is constructed by the nodes within the FZ that satisfy the energy constraint and the neighboring node degree constraint. The nodes in CFS are prioritized based on the routing quality evaluation by taking the local attributes of nodes into consideration, such as the directional angle, transmission distance, and residual energy. DEOR adopts a recovery mechanism to address the issue of void nodes. The simulation results validate that the proposed DEOR outperforms ORR, OBRN and ECSOR in terms of energy consumption, average hop count, packet delivery rate, and network lifetime.

Breakage and damage of fiber optic cable fibers seriously affect the normal operation of fiber optic networks and it is important to quickly and accurately determine the type and location of faults when they occur. The advantages of wavelet transform in singular signal detection and signal filtering are used to analyze Optical Time Domain Reflectometer (OTDR) curve signal and the fault detection method of fiber communication link with no relay and large span in high altitude area is given, which realizes the accurate detection and location of optical fiber communication link fault events under strong noise. The theoretical analysis is basically consistent with the experimental data. The accuracy of optical fiber fault location has been greatly improved in performance. The method has been directly applied to the field detection of ultra-long optical fiber links in high altitude areas, which has certain significance for the future real-time monitoring of optical fiber cables.

The goal of this paper is the performance evaluation of a deep learning approach when deployed in fifth-generation (5G) millimeter wave (mmWave) multicellular networks. To this end, the optimum beamforming configuration is defined by two neural networks (NNs) that are properly trained, according to mean square error (MSE) minimization. The first network has as input the requested spectral efficiency (SE) per active sector, while the second network the corresponding energy efficiency (EE). Hence, channel and power variations can now be taken into consideration during adaptive beamforming. The performance of the proposed approach is evaluated with the help of a developed system level simulator via extensive Monte Carlo simulations. According to the presented results, machine learning (ML)-adaptive beamforming can significantly improve EE compared to the standard non-ML framework. Although this improvement comes at the cost of increased blocking probability (BP) and radiating elements (REs) for high data rate services, the corresponding increase ratios are significantly reduced compared to the EE improvement ratio. In particular, considering 21.6 Mbps per active user and ML adaptive beamforming, then EE can reach up to 5.3 Mbps/W, which is significantly improved compared to the non-ML case (0.9 Mbps/W). In this context, BP does not exceed 2.6%, which is slightly worse compared to 1.7% in the standard non-ML case. Moreover, approximately 20% additional REs are required, with respect to the non-ML framework.

Keywords: Baseband, GeoSurf Constellation, Interference, Linear Distortions, Passband, Time Delay, Rain attenuation, Synthetic Storm Technique, ultra–wideband.

Spectrum distribution is a classical licensed spectrum accessing method in mobile communication networks. The licensed idle spectrum resources are authorized and distributed from spectrum owners to mobile users. However, the exponential growth of user capacity brings excessive load pressure on the traditional centralized network architecture. As lack of sufficient supervision and penalty measures, dishonest behaviors of spectrum owners and spectrum users will lead to the unfair status in the distribution process. As a result, the honest participants’ interest will be harmed. As an important supporting infrastructure of Internet of things technology, 6G cannot completely follow the existing spectrum distribution method. Towards 6G network spectrum distribution, an blockchain based licensed spectrum fair distribution method is proposed. A lightweight consensus mechanism named as proof of trust (PoT) is applied to reduce computational power consumption and consensus time overhead. We deploy the method on the Ethereum test chain, theoretical analysis and experimental results demonstrate the fairness, effectiveness and security of the method.

This study addresses the problem of accurately predicting azimuth and elevation angles of signals impinging on an antenna array employing Machine Learning (ML). Using the information obtained at a receiving system when a transmitter’s signal hits it, a Decision Tree (DT) model is trained to estimate azimuth and elevation angles simultaneously. Simulation results demonstrate the robustness of the proposed DT-based method, showcasing its ability to predict the Direction of Arrival (DOA) in diverse conditions beyond the ones present in the training dataset, i.e., the results display the model’s generalization capability. Additionally, the comparative analysis reveals that DT-based DOA estimation outperforms the state-of-the-art MUltiple SIgnal Classification (MUSIC) algorithm, establishing DTs as competitive alternatives for DOA estimation in signal reception systems.

We consider a coded compressed sensing protocol for unsourced massive random access (URA) that concatenates a shared Patterned Reed-Muller (PRM) inner codebook to an outer error-correction code. In this paper, an iterative list PRM projection algorithm is proposed to supplant the signal detector associated with the inner PRM sequences. In particular, we first propose an enhanced paths-saving algorithm called list PRM projection detection for the single-user scenario that keeps multiple candidates for the first few layers to remedy the risk of spreading errors. On this basis, we further propose an iterative list PRM projection algorithm for the multi-user scenario. The vectors for PRM codes and channel coefficients are jointly detected in an iterative manner, which offers significant improvements regarding the convergence rate for signal recovery. Furthermore, the performances of the proposed algorithms are analyzed mathematically, and we verified that the theoretical simulations are consistent with the numerical simulations. Finally, we concatenate the inner PRM codes that employ the iterative list detection to two practical error-correction outer codes. According to the simulation results, we conclude that the packetized URA with the proposed iterative list projection detection works better than benchmarks in terms of the number of active users it can support in each slot and the amount of energy needed per bit to meet an expected error probability.

In order to monitor the diversity of terrestrial biomes, the Earth Exploration Satellite Services demand a high data rate for downlink transmissions while sharing their frequency spectrum with, and suffering interferences from, cellular Base Stations. Both highlight the dilemmas of spectral efficiency (bps/Hz) and spectral coexistence. Our research aims to mitigate interference on low orbit satellite downlinks using Cognitive Radio (CR) and Adaptive MODulation and CODing (MODCOD) techniques. To fulfill this: 1) we present CR approaches to enhance spectrum exploitation. Next, 2) we detail Adaptive MODCOD (ACM) technique to increase RF power and spectral efficiencies. Then, 3) we suggest the solution by combining 1) and 2). Afterwards, 4) we analyze it by monitoring the signal to interference plus noise ratio and the CR/MODCOD strategy. Finally, 5) we provide case studies to demonstrate the strategy’s effectiveness through the practical operation of satellite services, and 6) we conduct a bench test of the communication system.

Deploying UAVs as aerial base stations is an exceptional approach to reinforce terrestrial infrastructure owing to their remarkable flexibility and superior agility. However, it is essential to design their flight trajectory effectively to make the most of UAV-assisted wireless communications. This paper presents a novel method for improving wireless connectivity between UAVs and terrestrial users through effective path planning. This is achieved by developing a goal-directed trajectory planning method using active inference. First, we create a global dictionary using TSPWP instances executed on various training examples. This dictionary contains letters representing available hotspots, tokens representing local paths, and words depicting complete trajectories and hotspot order. By using this world model, the UAV can understand the TSPWP’s decision-making grammar and how to use the available letters to form tokens and words at various levels of abstraction and time scales. With this knowledge, the UAV can assess encountered situations and deduce optimal routes based on the belief encoded in the world model. Our proposed method outperforms traditional Q-learning by providing fast, stable, and reliable solutions with good generalization ability.

The development of wireless sensor networks (WSNs) technology comes with inherent limitations and vulnerabilities that make it exploitable by intruders. The fundamental goal of this article is to solve security problems related to black hole attacks, which interfere with the proper performance of the network and can lead to data leakage and loss. The proposed solution in this article is to apply IDS to a WSN for the first time. We also used the NS2.35 simulator to compare the three routing protocols, AODV, AODV under Hacker Node (HNAODV), and the proposed solution (IDSHNAODV) in the WSN model to reduce the effects of black hole attacks.

Delay in data transmission is one of key performance indicators (KPIs) of a network. The planning and project value of delay in network management is of crucial importance for the optimal allocation of network resources and their performance focuses. To create optimal solutions, predictive models, which are currently most often based on machine learning (ML), are used. This paper aims to investigate the training, testing and selection of the best predictive delay model for a VoIP service in an Long Term Evolution (LTE) network using three ML techniques - Neural Networks (NN), Support Vector Machines (SVM) and k-Nearest Neighbors (k-NN). The space of model input variables is optimized by dimensionality reduction techniques: RReliefF algorithm, Backward selection via the recursive feature elimination algorithm and the Pareto 80/20 rule. A three-segment road in the geo-space between the cities of Banja Luka (BL) and Doboj (Db) in the Republic of Srpska (RS), Bosnia and Herzegovina (BiH), covered by the cellular network (LTE) of the M:tel BL operator was chosen for the case study. The results show that, in all three optimization approaches, the k-NN model is selected as the best solution. For the RReliefF optimization algorithm, the best model has 6 inputs and minimum relative error (RE), RE=0.109; for the Backward selection via the recursive feature elimination algorithm, the best model has 4 inputs and RE=0.041; and for the Pareto 80/20 rule, the best model has 11 inputs and RE= 0.049. The comparative analysis of the results concludes that according to observed criteria for the selection of the final model, the best solution is an approach to optimizing the number of predictors based on the Backward selection via the recursive feature elimination algorithm.

In this paper, possibilities for the bandwidth and wavelength utilization in future next-generation passive optical networks are presented and reasons for realizing and utilizing of extended dynamic wavelength and bandwidth algorithms for NG-PON2 networks are analyzed. Next, principles of the effective dynamic bandwidth allocation are introduced in details, focused on the importance of the decision criterion optimization. For achieving better bandwidth utilization of dedicated wavelengths, this paper is focused on the novel effective dynamic bandwidth allocation algorithm with adaptive allocation of wavelengths to ONU units and on the optimization of the decision criterion. For analyzing the novel extended DWBA algorithm utilizing for various wavelength allocation cases possible in NG-PON2 networks, a simulation program with the enhancement of the EDBA algorithm is realized. Finally, an optimization of the decision criterion defining a minimum bandwidth utilization of the actual wavelength is executed for NG-PON2 networks based on the hybrid TWDM technique.

This paper aims at trying to answer the question of whether a low cost drone equipped with a regular camera can serve as a simple device to estimate the size of objects. Ad-ditionally, it assesses if the accuracy of measurement is good enough for using a drone for measurements, relying solely on GPS position and camera. A review of the literature pertaining to ground object measurements was conducted. The availability of such in-struments was evaluated in terms of purchase and rental costs, the number of instru-ments on the market, and the time to obtain them. The most common measurement methods were considered and their unit costs were reviewed. The cost of professional surveying and measuring equipment was compared to the possibility of using low-cost, non-commercial drones to measure objects and surfaces. The quality of the images ob-tained was compared with high-resolution satellite systems. Is an ordinary drone with a standard camera suitable for length measurement without professional measuring equipment? Should the results be considered only in the category of size estimation?

Channel estimation is an important module to enhance the performance of orthogonal frequency division multiplexing (OFDM) systems. However, the presence of a large amount of noise in multipath fading time-varying channels significantly affects the channel estimation accuracy and thus the recovery quality of the received signals. Therefore, this paper proposes a double-threshold (DT) channel estimation method based on adaptive frame statistics (AFS). The method first adaptively determines the number of statistical frames based on the temporal correlation of the received signals, and preliminarily detects the channel structure by analyzing the distribution characteristics of multipath sampling points and noise sampling points during adjacent frames. Subsequently, a multi-frame averaging technique is used to expand the distinction between multipath and noise sampling points. Finally, the DT is designed to better recover the channel based on the preliminary detection results. Simulation results show that the proposed adaptive frame statistics-double-threshold (AFS-DT) channel estimation method is effective and has better performance compared with many existing channel estimation methods.

With the dramatic increase in the number of mobile users and wireless devices accessing the network, the performance of the fifth generation (5G) wireless communication systems has been severely challenged. Reconfigurable intelligent surfaces (RIS), one of the potential technologies for the sixth generation (6G), has received a lot of attention. Since it is easier to deploy, consumes less power, and is inexpensive. RIS is an electromagnetic metamaterial that serves to reconfigure the wireless environment by adjusting the phase, amplitude and frequency of the wireless signal. To maximize channel transmission efficiency and improve the reliability of communication systems, the acquisition of channel state information (CSI) is essential. Therefore, an effective channel estimation method guarantees the achievement of excellent RIS performance. This paper conducts a comprehensive investigation of the existing channel estimation methods of RIS, analysis and comparison of channel model building and CSI acquisition schemes in different frequency bands, in addition to a comprehensive description of generic channel estimation methods, with a focus on the application of deep learning. Finally, we conclude the paper and provide an outlook in the future development of RIS channel estimation.

Wireless sensor networks (WSN) are mostly utilized in many applications. Indeed, WSN is composed of sensors to evaluate some physical phenomena. However, the information brought by the sensor still missed if we don't know the exact location of the event. Several localization algorithms have been proposed in order to locate the nodes in WSN. The localization algorithms are categorized into range-based and range-free techniques. The range-based techniques use either distance or time to calculate the coordinates of unknown nodes. Nevertheless, those kinds of techniques need some additional material in computation purpose. Therefore, range-based techniques present an expensive solution for positioning in WSN. Alternatively, range-free techniques may do the same task without involving additional material. But they don’t offer a high precision of localization in comparison with range-based techniques. DVHOP is the most popular range-free technique that uses the hop count method in the localization process. In this work, we propose an improvement of DVHOP localization algorithm to create three improved versions of this algorithm and we have achieved that by adopting two meta-heuristic (simulated annealing, particle swarm optimization) and FMINCON solver dedicated to the optimization in the field of WSN nodes localization. The experimental results obtained in this work show clearly the gain and the good impact of our proposition.

The object of research is an optical-electronic system for recording and processing signals from fiber-optic sensors. Due to the use of optical fibers as sensitive elements, there is no influence on the measurement result of electromagnetic fields, spurious electromagnetic radiation, channel crosstalk, there are no problems, electrical safety is significantly increased, there are no problems of arcing and sparking. A scheme of a receiving-transmitting module has been developed, which is additionally equipped with a preliminary protection and filtering system. Further, measuring tracks, microcontroller software and functional tests were ordered to determine the metrological properties of the proposed system.Signal integrity analysis is presented, which allows you to check whether the signals present in the device are correctly transmitted between their sources and receivers. The analysis of signal integrity is investigated, which is performed in two stages of the device design process. Modeling of the studied module in the specialized program Altium Designer. With the help of this program, potential problems were found, such as the occurrence of crosstalk between paths, the exact values of some elements, accurate analytical calculation. Learned an impedance analysis trace for a given connection's parameters, where the value affects the shape of the given path, its physical dimensions, distance from other paths, and other physical properties of the board. Optoelectronic system for recording and processing signals from fiber optic sensors based on Bragg fiber gratings resistant to electromagnetic interference and temperature, for use in modern systems for monitoring building structures, bridges, tunnels, dams, high-rise buildings, railways, oil platforms, buildings, pipelines.

In recent years, drones have been used in a wide range of fields such as agriculture, transportation of goods, and security. Drones equipped with communication facilities are expected to play an active role as base stations in areas where ground base stations are unavailable, such as disaster areas. In addition, asynchronous operation is being considered for local 5G in order to support all kinds of use cases. In asynchronous operation, cross-link interference between base stations is an issue. This paper attempts to reduce the interference caused by the drone network by introducing circularly polarized antennas. Numerical analyses are conducted to validate the effectiveness of the proposed system, where SIRs (Signal-to-Interference Ratio) are shown to be improved significantly as the numerical evaluation results.

This paper presents the design and implementation of a versatile IoT testbed utilizing the openHab platform along with various wireless interfaces, including Z-Wave, ZigBee, WiFi, 4G-LTE, and IR, and an array of sensors for motion, temperature, luminance, humidity, vibration, UV, and energy consumption. First, the testbed architecture, setup, basic testing, and collected data results are described. Then, by showcasing a typical day in the laboratory, we illustrate the testbed's potential through the collection and analysis of data from multiple sensors. The study also explores the capabilities of the openHab platform, including its robust persistence layer, event management, real-time monitoring, and customization. The significance of the testbed in enhancing data-collection methodologies for energy assets and unlocking new possibilities in the realm of IoT technologies is particularly highlighted.

Cell-free massive multiple input multiple output (MIMO) has the potential of providing joint services including joint initial access, efficient clustering of access points (APs) and pilot allocation to user equipments (UEs) over large coverage area with reduced interference. In cell-free massive MIMO, large coverage area corresponds to provision and maintenance of scalable quality of service requirements for infinitely large number of UEs. The research in cell free massive MIMO is mostly focused on time division duplex mode due to availability of channel reciprocity which aids in avoiding feedback overhead. However, frequency division duplex (FDD) protocol still dominates the current wireless standards and the provision of angle reciprocity aids in reducing this overhead. The challenge of providing a scalable cell-free massive MIMO system in FDD setting is also prevalent, since computational complexity regarding signal processing tasks such as channel estimation, precoding/combining and power allocation, becomes prohibitively high with increase in number of UEs. In this work, we consider an FDD based scalable cell-free network with angular reciprocity and dynamic cooperation clustering approach. We have proposed scalability for our FDD cell-free and perform comparative analysis with reference to channel estimation, power allocation and precoding/combining techniques. We present expressions for scalable spectral efficiency, angle based precoding/combining schemes and provide comparison of overhead between conventional and scalable angle based estimation as well as combining schemes. Simulations confirm that the proposed scalable cell-free network based on FDD scheme outperforms the conventional matched filtering scheme based on non-scalable precoding/combiming schemes. The angle based LP-MMSE in FDD cell-free network provides 14.3% improvement in spectral efficiency and 11.11% improvement in energy efficiency compared to non-scalable MF scheme.

This work presents first time successfully fabricated silica few-mode microstructured optical fiber (MOF) with hollow GeO2-doped ring core and strongly induced twisting up to 790 revolutions per meter. Some technological issues for manufacturing of GeO2-doped supporting elements for large hollow cores as well as described above complicated spun MOFs are discussed. We introduce some results of tests, performed for pilot samples of designed and manufactured described above untwisted and twisted MOFs with outer diameter 65 µm and hollow ring core inner diameter 30.5 µm under wall thickness 1.7 µm and refractive index difference n=0.030, including their geometrical parameters, basic transmission characteristics and measurements of far-field laser beam profile patterns.

For the traditional indoor visible light communication heterogeneous network switching algorithm is only concerned with the research of vertical switching algorithm, however, the research of horizontal vertical collaborative switching combined with multi-carrier modulation technology is seldom mentioned, based on the above, this paper proposes a horizontal-vertical collaborative switching strategy based on the residency time of the communication blind area. Firstly, we use asymmetrically clipped optical OFDM (ACO-OFDM) for signal processing to reduce the bit error rate (BER) of the system by reducing the multipath interference generated during signal transmission.Secondly, the BER is used to determine the communication blind area and to calculate its dwell time. Finally, the threshold time is set as the channel interruption time in the communication blind zone, and the horizontal-vertical cooperative switching is performed by comparing with the dwell time. The simulation results show that the average network throughput is 195.28Mbps, and the average number of handovers is 1.35. Compared with instant vertical handover (IVHO) scheme and dwell vertical handover (DVHO) scheme, the average network throughput is improved by 37.21% and 28.45%, respectively, and the average switching times are reduced by 28.05% and 5.27%, respectively.

Laser-induced graphene (LIG) has gained considerable attention recently due to its unique properties and potential applications. In this study, we investigate using LIG in polyimide (PI) as a material for antenna applications. The LIG-PI composite material was prepared by a facile picosecond laser (1064 nm) irradiation process, which resulted in a conductive graphene network within the PI matrix. Furthermore, LIG formation was confirmed by Raman spectroscopy and sheet resistance measurements. Finally, a patch antenna from LIG for 2.45 GHz microwaves was simulated, produced and tested. These findings suggest that LIG-PI composites have great potential for use in high-frequency electronic devices and can provide a new avenue for the development of flexible and wearable electronics.

As most Korean OTT subscribers use mobile devices as their primary medium for watching OTT video content, mobile network traffic is soaring. However, the existing build-out of mobile communication technology – such as deploying more base stations or expanding the network bandwidth – is struggling to keep pace with the enormous increased demands of mobile network traffic. Accordingly, wireless device-to-device (D2D) caching networks are considered one of the most reliable alternatives for reducing the overload from mobile network traffic caused by streaming video content online. However, wireless D2D caching networks have pros and cons, like any other technology. Thus, this study aims to examine the practical decision-making process of mobile OTT service users in response to the application of wireless D2D caching networks on their mobile devices. An online survey of 94 respondents was conducted in South Korea during 19–23 May 2022; the data obtained were analyzed using the analytic hierarchy process (AHP) approach. The study finds that it was the risks, rather than the situational conditions and benefits, that mostly affected mobile OTT service users’ behavioral intentions and strategies. Streaming video content using mobile data or Wi-Fi was perceived as the most viable option. Mobile OTT service users were also willing to take the leap of shifts towards downloading video content in advance rather than adopting wireless D2D caching networks on a mobile device. However, mobile OTT service users’ decisions are heavily dependent on situational conditions related to use of mobile OTT services that make the quality of service consumption different. As one of the first to examine the responses of mobile OTT service users, this study provides meaningful implications for a timely and sensitive issue.

This study investigates the applications of reconfigurable intelligent surfaces (RIS) in heterogeneous downlink networks (HetNet). Due to the network densification, the small cell base station (SBS) interferes with the macrocell users (MUE). In this paper, we utilize RIS to mitigate cross-tier interference in an HetNet via directional beamforming by adjusting the phase shift of the RIS. We consider an RIS-assisted HetNet consisting of multiple SBS nodes and MUEs that utilize both direct paths and reflected paths. Therefore, the aim of this study is to maximize the sum rate of all MUEs by jointly optimizing the transmit beamforming of the macrocell base station (MBS) and the phase shift of the RIS. An efficient RIS reflecting coefficients-based optimization (RCO) is proposed based on a successive convex approximation approach. Simulation results are provided to show the effectiveness of the proposed scheme in terms of its sum rate in comparison with the scheme HetNet without RIS and the scheme HetNet with RIS but with random phase shifts.

This article presents a wide-band antenna designed for the Cube Satellite (CubeSat). Based on a quadrifilar structure, the antenna provides circular polarization radiation, which is suitable for satellite communication. Moreover, the antenna is designed and fabricated using two 1.6 mm thickness FR4-Epoxy boards that connect together by the metal pins. In order to improve the robustness, a ceramic spacer is placed in the centerboard, and four screws at the corners are added to fix the antenna with the CubeSat structure. These additional parts reduce antenna damage caused by vibrations in the launch vehicle lift-off stage. The proposal has a dimension of 77mm x 77mm x 10mm and covers the LoRa frequency bands of 868 MHz, 915 MHz, and 923 MHz. According to the measurements in an anechoic chamber, antenna gains are obtained with the values of 2.3 dBiC and 1.1 dBiC for the 870 MHz and 920 MHz, respectively. Finally, the antenna is integrated into a 3U CubeSat that was launched by a Soyuz launch vehicle. The terrestrial-to-space communication link was measured, and the antenna performance was confirmed in the real-life scenario.

Road infrastructure is a key public asset because it benefits the social and economic development of any country. It plays an important role for the development of the industrial complex, the production sector and the road surfaces of transport roads should be of high quality, have a long service life. Road infrastructure, as well as all infrastructure, requires preservation, maintenance and repair. There are special requirements for the roadway that must be observed during construction or repair. This article is devoted to a detailed study of the use of fiber optics sensors (FOS) based on the fiber Bragg grating (FBG) for road surface monitoring. Such a fiber sensor consisting of a fiber Bragg grid and a pair of grids can offer the possibility of simultaneous measurement of deformation and temperature for monitoring the pavement. Temperature and deformation measurements were carried out by installing a sensor on the surface of a made asphalt sample. The built-in fiber sensor based on FBG provides important information about how the pavement structure can withstand the load, subsidence of soil, timely implement road safety and stability measures evaluate and predict the service life of the pavement. The results of the study showed that the synchronicity, repeatability and linearity of the characteristics of the fiber sensor are excellent. The difference between the experimental and theoretical results is about 7%. Thus, based on the results of the obtained data, the fiber sensor on the FBG can be used for monitoring, designing road surfaces and in general transport infrastructure.

Next Generation IoT systems will allow sustainable performance in long-term monitoring systems. This sustainability concept is applicable to soundscape description, as it allows monitoring in urban environments. In this work, the implementation of psycho-acoustic annoyance models in a 5G-enabled IoT system is proposed applying two Edge Computing approaches. A modified Zwicker’s model is adopted in this research, introducing a term that takes into account the tonal component of the captured sound. These implementations have been validated in a measurement campaign where several IoT devices have been deployed to evaluate different sound environments of a University Campus. Then, the analysis of the sound quality metrics is done in different location showing that if tonality is present in a noisy environment, it results in greater subjective annoyance. Moreover, the Just Noticeable Difference of these results are derived for the Zwicker’s psycho-acoustic annoyance to establish a limitation for this metric.

Abstract- Cognitive radio (CR) play an important role in improving spectral efficiency (SE) of wireless communication, meanwhile, intelligent reflecting surface (IRS) is an effective technology to improve the secrecy performance of wireless communication system by adjusting the phase shift and amplitude of channel. Thus, we consider an IRS-aided multiple-input single-output (MISO) CR systems to enhance secrecy rate, which is consists of a single eavesdropping link, a primary network containing the primary receiver (PR), and secondary network including secondary receiver (SR) and the SR transmitter (SR-TX). Specifically, we minimize the transmit power of SR subject to secrecy capacity constraint and interference temperature (IT) constraint on PR, by jointly optimizing the beamforming vector and artificial noise (AN) constraints matrix at SR-TX as well as the phase shift matrix of IRS. Numerical results show that the different values of transmit antennas at the SR-TX and the number of IRS elements can significantly decrease the transmit power under the condition of ensuring secure communication.

The use of electronic means to support tasks such as pastoralism is a way of intelligently optimizing that activity. As any autonomous system, it requires human intervention in case of failure, and therefore it needs an autonomous mechanism that draws the attention of the human operator whenever the system or the animals evolve to undesired conditions. The present work progresses an existing alarm system, used in the SheepIT gateway, which can monitor the behavior of animals and equipment, warning human supervisors of the occurrence of unwanted events and the need for intervention. Concretely, given the lack of coverage of Internet access in rural areas, the system was integrated with a satellite interface to guarantee communication and the timely delivery of alarm messages. The paper compares the overall networking performance of the satellite link, against a Wi-Fi laboratorial baseline.

The Direction-of-Arrival (DoA) estimation methods are highly versatile and find extensive applications in satellite communication. The DoA methods are employed across a range of orbits, from Low Earth Orbits (LEO) to Geostationary Earth Orbits (GEO). They serve multiple applications, including altitude determination, geolocation and estimation accuracy, target localization, and relative and collaborative positioning. This paper presents a novel approach for modeling the DoA angle using a closed-form expression, incorporating the boresight angle and satellite and Earth station position data. The method uses the geographic coordinate system in the satellite communication system, precisely the latitude and longitude of the Earth station and altitude parameters of the satellite stations, to calculate the Earth station’s elevation angle and accurately model the DoA angle. Furthermore, this paper performs a comprehensive comparative analysis of various DoA methods to gain deeper insights into the performance of DoA estimation in multi-antenna systems operating under spatially correlated channels. Accordingly, this paper evaluates DoA estimation performance using root-mean-square-error (RMSE) statistics for uplink and downlink conditions through extensive Monte Carlo simulations. The simulation’s effectiveness is validated against the Cramer-Rao Bound (CRB) performance metric for the Additive white Gaussian noise (AWGN) case. (i.e., thermal noise). The simulation results demonstrate improved RMSE performance in satellite systems by incorporating spatial correlation into the system model.

In order to properly cover different scenarios, radiation patterns of antennas should be accordingly adjusted before fabrication. However, most antennas are unable to provide both broadside beam and designable conical beam which are usually-used radiation patterns for radio coverage. In this paper, a planar Circular Polarized (CP) annular Leaky-Wave Antenna (LWA) with conical beam is proposed, which is realized on annular Substrate-Integrated Waveguide (SIW). Broadside beam or conical beam could be easily obtained by fabricating the LWA with modified structural parameters. The central operating band is 5.8 GHz. The LWA allows only the -1th spatial harmonic to radiate, while the fundamental wave and other spatial harmonics are suppressed in slow wave mode. In order to validate the design effectiveness, two examples for broadside beam and conical beam radiation are fabricated and measured. The measurement results show good agreement with the simulation results. The proposed LWA presents a promising radiation performance and is a good candidate for wireless communication applications.

With the ongoing fifth-generation cellular network (5G) deployment, electromagnetic field exposure has become a critical concern. However, measurements are scarce, and accurate electromagnetic field reconstruction in a geographic region remains challenging. This work proposes a conditional Generative Adversarial Network to address this issue. The main objective is to reconstruct the electromagnetic field exposure map accurately according to the environment’s topology from a few sensors located in an outdoor urban environment. The model is trained to learn and estimate the propagation characteristics of the electromagnetic field according to the topology of a given environment. In addition, the conditional Generative Adversarial Network based electromagnetic field mapping is compared with simple kriging. Results show that the proposed method produces accurate estimates and is a promising solution for exposure map reconstruction.

We report world record high data transmission over standard optical fiber from a single optical source. We achieve a line rate of 44.2 Terabits per second (Tb/s) employing only the C-band at 1550nm, resulting in a spectral efficiency of 10.4 bits/s/Hz. We use a new and powerful class of micro-comb called soliton crystals that exhibit robust operation and stable generation as well as a high intrinsic efficiency that, together with an extremely low spacing of 48.9 GHz enables a very high coherent data modulation format of 64 QAM. We achieve error free transmission across 75 km of standard optical fiber in the lab and over a field trial with a metropolitan optical fiber network. This work demonstrates the ability of optical micro-combs to exceed other approaches in performance for the most demanding practical optical communications applications.

The use of Light Amplification by Stimulated Emission of Radiation (i.e., LASERs or lasers) by the U.S. Department of Defense is not new and includes laser weapons guidance, laser-aided measurements, even lasers as weapons (e.g., Airborne Laser). Lasers in support of telecommunications is also not new. The use of laser light in fiber optics shattered thoughts on communications bandwidth and throughput. Even the use of lasers in space is no longer new. Lasers are being used for satellite-to-satellite crosslinking. Laser communication can transmit orders-of-magnitude more data using orders-of-magnitude less power and can do so with minimal risk of exposure to the sending and receiving terminals. What is new is using lasers as the uplink and downlink between the terrestrial segment and the space segment of satellite systems. More so, the use of lasers to transmit and receive data between moving terrestrial segments (e.g., ships at sea, airplanes in flight) and geosynchronous satellites is burgeoning. This manuscript examines the technological maturation of employing lasers as the signal carrier for satellite communications linking terrestrial and space systems. The purpose of the manuscript is to develop key performance parameters (KPPs) to inform U.S. Department of Defense initial capabilities documents (ICDs) for near-future satellite acquisition and development. By appreciating the history and technological challenges of employing lasers rather than traditional radio frequency sources for satellite uplink and downlink signal carrier, this manuscript recommends ways for the U.S. Department of Defense to employ lasers to transmit and receive high bandwidth, large-throughput data from moving platforms that need to retain low probabilities of detection, intercept, and exploitation (e.g., carrier battle group transiting to a hostile area of operations, unmanned aerial vehicle collecting over adversary areas). The manuscript also intends to identify commercial sector early-adopter fields and those fields likely to adapt to laser employment for transmission and receipt.

Accurate channel estimation is of utmost importance for massive MIMO systems that allow providing significant improvements in spectral and energy efficiency. In this work, we investigate the spectral efficiency performance and present a channel estimator for multi-cell massive MIMO systems subjected to pilot-contamination. The proposed channel estimator performs well under moderate to aggressive pilot contamination scenarios without prior knowledge of the inter-cell large-scale channel coefficients and noise power. The estimator approximates the performance of a linear Minimum Mean Square Error (MMSE) as the number of antennas increases. Following, we derive a lower bound closed-form spectral efficiency of the Maximum Ratio Combining (MRC) detector in the proposed channel estimator. The simulation results highlight that the proposed estimator performance approaches the linear minimum mean square error (LMMSE) channel estimator asymptotically.

Accurate channel estimation is of utmost importance for massive MIMO systems to provide significant improvements in spectral and energy efficiency. In this work, we present a study on the distribution of a simple but yet effective and practical channel estimator for multi-cell massive MIMO systems suffering from pilot-contamination. The proposed channel estimator performs well under moderate to aggressive pilot contamination scenarios without previous knowledge of the inter-cell large-scale channel coefficients and noise power, asymptotically approximating the performance of the linear MMSE estimator as the number of antennas increases. We prove that the distribution of the proposed channel estimator can be accurately approximated by the circularly-symmetric complex normal distribution, when the number of antennas, M, deployed at the base station is greater than 10.

In this brief letter we report our initial results on the application of deep-learning to the massive MIMO channel estimation challenge. We show that it is possible to estimate wireless channels and that the possibility of mitigating pilot-contamination with deep-learning is possible given that the leaning model underwent an extensive training-phase and that it has been presented with a large number of different channel conditions.

Opportunistic routing is the latest technique that uses the broadcasting nature of the wireless medium to increase the number of potential forwarding nodes in the network. This, in turn improves the delivery rate and reliability of data transmission in the network. Compared to all previous classes of routing protocols, opportunistic routing offers numerous advantages which is exploited by the latest applications for efficient communication and resource sharing in dynamic ad hoc networks. These applications provide dynamic communication in disaster recovery environments. The objective of this research work is to review and classify all the major opportunistic routing protocols proposed for dynamic ad hoc networks. Further the issues and challenges with each of these existing protocol is discussed and future research directions are put forward

The Physical Random Access Channel (PRACH) plays an important role in LTE and LTE-A systems. It is through the PRACH channel that the user equipment (UE), based on eNodeB's timing estimates, aligns its uplink transmissions to the eNodeB's uplink and gain access to the network. One of the initial operations executed by the PRACH receiver at eNodeB side is the translation of the PRACH signal back to base band, $i.e.$, center the PRACH signal around DC. This operation is a necessary step for preamble detection and can be carried out through a time-domain frequency shift operation. Therefore, in this paper we present the hardware architecture and implementation details of a configurable and optimized FPGA-based time-domain frequency shifter. It is a hardware-efficient and accurate architecture for converting the relevant received PRACH signal into base band before further signal processing. The architecture is manly based on a customized Numerically Controlled Oscillator (NCO), which is used for generating complex exponentials employing only adders, a Look-Up Table (LUT) and plain logic resources. The main advantage of the proposed hardware architecture is that it completely eliminates the need for storing a large number of long complex exponential sequences by employing a single LUT and exploiting quarter wave symmetry of the basis waveform. Our simulation results show that the proposed customized NCO architecture provides high Spurious Free Dynamic Range (SFDR) signals using a minimal amount of FPGA resources. Moreover, the proposed architecture exhibits spur-suppression ranging from 62.13 to 153.58 dB without using Taylor Series correction.

In this letter, we advocate that it is possible to mitigate Pilot Contamination in Massive MIMO systems by scrambling the pilot sequences with a Base Station (BS) scrambling sequence. It is possible if a set of sequences is carefully designed to meet the orthogonality property defined in this letter. Each BS possesses its own scrambling sequence that can be reused the same way frequency reuse is applied to cell deployment. The main advantage of the prosed pilot generation scheme is that the frequency reuse factor can be set to 1, the most aggressive one, while the scrambling sequences can be reused with much less aggressive reuse factors (e.g. 4, 7, 9, 12, etc.), which in consequence results in pilot contamination mitigation and increased system's performance.

In the fifth generation communication system, millimeter wave (mmWave) networks will coexist with traditional micro wave (μWave) networks, which allows for higher data transmission rate and better user experience. In this paper, we give a comprehensive framework of mathematical models and analytical methods for multi-tier mmWave and μWave hybrid caching networks based on stochastic geometry. We propose an association strategy by assuming average biased-received power association and Rayleigh fading. Accordingly, by using a D-ball approximating blockage model of mmWave networks, expressions of the cell association probability and the coverage probability of the hybrid networks are derived. Also, we use the average successful delivery probability as the performance metric to analyze the existing caching placement strategies. Simulation results validate the accuracy of our analytical conclusions.

The superharmonic imaging of tissue has the potential for high spatial and contrast resolutions, compared to the fundamental and second harmonic imaging. For this technique, the spectral bandwidth of an ultrasound transducer is divided for transmission of ultrasound and reception of its superharmonics (i.e., higher than the second harmonic). Due to the spectral division for the transmission and reception, transmitted ultrasound energy is not sufficient to induce superharmonics in media without using contrast agents, and it is difficult that a transducer has a -6-dB fractional bandwidth of higher than 100%. For the superharmonic imaging of tissue, thus, multi-frequency array transducers are the best choice if available; transmit and receive elements are separate and have different center frequencies. However, the construction of a multi-frequency transducer for intravascular ultrasound (IVUS) imaging is particularly demanding because of its small size of less than 1 mm. Here, we report a recently developed dual-element focused IVUS transducer for the third harmonic imaging of tissue, which consists of a 35-MHz element for ultrasound transmission and a 105-MHz element for third harmonic reception. For high quality third harmonic imaging, both elements were fabricated to have the same focus at 2.5 mm. The results of tissue mimicking phantom tests demonstrated that the third harmonic images produced by the developed transducer had higher spatial resolution and deeper imaging depth than the fundamental images.

Supply chain management requires regular updates of the location of assets, which can be enabled by low power wide area networks, such as Sigfox. While it is useful to localize a device simply by its communication signals, this is very difficult to do with Sigfox because of wide area and ultra narrowband nature. On the other hand, installing a satellite localization element on the device greatly increases its power consumption. We investigated using information about nearby Wi-Fi access points as a way to localize the asset over the Sigfox network, so without connecting to those Wi-Fi networks. This paper reports the location error that can be achieved by this type of outdoor localization. By using a combination of two databases, we could localize the device on all 36 test locations with a median location error of 39 m. This shows that the localization accuracy of this method is promising enough to warrant further study, most specifically the minimal power consumption.