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20 pages, 5771 KiB

Open AccessCommunication

Design and Implementation of an Indoor Warning System with Physiological Signal Monitoring for People Isolated at Home

by Chi-Huang Hung, Yong-Yi Fanjiang, Yi-Shiune Lee and Yi-Chao Wu

Sensors 2022, 22(2), 590; https://doi.org/10.3390/s22020590 - 13 Jan 2022

Cited by 5 | Viewed by 3388

Abstract

Due to the recent COVID-19 pandemic, many people have faced in-home isolation, as every suspected patient must stay at home. The behavior of such isolated people needs to be monitored to ensure that they are staying at home. Using a camera is a [...] Read more.

Due to the recent COVID-19 pandemic, many people have faced in-home isolation, as every suspected patient must stay at home. The behavior of such isolated people needs to be monitored to ensure that they are staying at home. Using a camera is a very practical method. However, smart bracelets are more convenient when personal privacy is a concern or when the blood oxygen value or heart rate must be monitored. In this study, a low-cost indoor positioning system that uses a Bluetooth beacon, a smart bracelet, and an embedded system is proposed. In addition to monitoring whether a person living alone is active in a specific environment and tracking the heart rate or blood oxygen value under particular conditions, this system can also send early warning signals to specific observation units or relatives through instant messaging software. Full article

(This article belongs to the Special Issue Communications and Computing in Sensor Network)

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16 pages, 2822 KiB

Open AccessArticle

A New Wearable System for Sensing Outdoor Environmental Conditions for Monitoring Hyper-Microclimate

by Roberta Jacoby Cureau, Ilaria Pigliautile and Anna Laura Pisello

Sensors 2022, 22(2), 502; https://doi.org/10.3390/s22020502 - 10 Jan 2022

Cited by 34 | Viewed by 4187

Abstract

The rapid urbanization process brings consequences to urban environments, such poor air quality and the urban heat island issues. Due to these effects, environmental monitoring is gaining attention with the aim of identifying local risks and improving cities’ liveability and resilience. However, these [...] Read more.

The rapid urbanization process brings consequences to urban environments, such poor air quality and the urban heat island issues. Due to these effects, environmental monitoring is gaining attention with the aim of identifying local risks and improving cities’ liveability and resilience. However, these environments are very heterogeneous, and high-spatial-resolution data are needed to identify the intra-urban variations of physical parameters. Recently, wearable sensing techniques have been used to perform microscale monitoring, but they usually focus on one environmental physics domain. This paper presents a new wearable system developed to monitor key multidomain parameters related to the air quality, thermal, and visual domains, on a hyperlocal scale from a pedestrian’s perspective. The system consisted of a set of sensors connected to a control unit settled on a backpack and could be connected via Wi-Fi to any portable equipment. The device was prototyped to guarantee the easy sensors maintenance, and a user-friendly dashboard facilitated a real-time monitoring overview. Several tests were conducted to confirm the reliability of the sensors. The new device will allow comprehensive environmental monitoring and multidomain comfort investigations to be carried out, which can support urban planners to face the negative effects of urbanization and to crowd data sourcing in smart cities. Full article

(This article belongs to the Special Issue Communications and Computing in Sensor Network)

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22 pages, 4684 KiB

Open AccessArticle

Algorithm for Evaluating Energy Detection Spectrum Sensing Performance of Cognitive Radio MIMO-OFDM Systems

by Josip Lorincz, Ivana Ramljak and Dinko Begusic

Sensors 2021, 21(20), 6881; https://doi.org/10.3390/s21206881 - 17 Oct 2021

Cited by 16 | Viewed by 2896

Abstract

Cognitive radio technology enables spectrum sensing (SS), which allows the secondary user (SU) to access vacant frequency bands in the periods when the primary user (PU) is not active. Due to its minute implementation complexity, the SS approach based on energy detection (ED) [...] Read more.

Cognitive radio technology enables spectrum sensing (SS), which allows the secondary user (SU) to access vacant frequency bands in the periods when the primary user (PU) is not active. Due to its minute implementation complexity, the SS approach based on energy detection (ED) of the PU signal has been analyzed in this paper. Analyses were performed for detecting PU signals by the SU in communication systems exploiting multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) transmission technology. To perform the analyses, a new algorithm for simulating the ED process based on a square-law combining (SLC) technique was developed. The main contribution of the proposed algorithm is enabling comprehensive simulation analyses of ED performance based on the SLC method for versatile combinations of operating parameter characteristics for different working environments of MIMO-OFDM systems. The influence of a false alarm on the detection probability of PU signals impacted by operating parameters such as the signal-to-noise ratios, the number of samples, the PU transmit powers, the modulation types and the number of the PU transmit and SU receive branches of the MIMO-OFDM systems have been analyzed in the paper. Simulation analyses are performed by running the proposed algorithm, which enables precise selection of and variation in the operating parameters, the level of noise uncertainty and the detection threshold in different simulation scenarios. The presented analysis of the obtained simulation results indicates how the considered operating parameters impact the ED efficiency of symmetric and asymmetric MIMO-OFDM systems. Full article

(This article belongs to the Special Issue Communications and Computing in Sensor Network)

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24 pages, 1562 KiB

Open AccessArticle

Energy-Efficient and Reliable Face-Routing Scheme in Wireless Networks

by Hyunchong Cho, Sangdae Kim, Seungmin Oh, Euisin Lee and Sang-Ha Kim

Sensors 2021, 21(8), 2746; https://doi.org/10.3390/s21082746 - 13 Apr 2021

Cited by 4 | Viewed by 1858

Abstract

Face-routing is one of the reliable recovery schemes when geographic routing fails to transmit data packets. Although studies on face-routing can overcome the failure of the data transmission, they lead to much energy consumption due to frequent data transmissions between adjacent nodes for [...] Read more.

Face-routing is one of the reliable recovery schemes when geographic routing fails to transmit data packets. Although studies on face-routing can overcome the failure of the data transmission, they lead to much energy consumption due to frequent data transmissions between adjacent nodes for carrying out the rule of face-routing. To avoid the frequent data transmissions, several face-routing schemes have been recently proposed to transmit data packets to the farthest-neighbor node. However, they happen with many data retransmissions because the farthest-neighbor node has a relatively low transmission success ratio. To solve this problem, we propose a new face-routing scheme that determines the most appropriate neighbor node to balance the trade-off between energy efficiency and transmission reliability with two viewpoints. The first viewpoint focuses on how to increase the distance progress of the data delivery in one-hop range to enhance energy efficiency. After that, the second viewpoint focuses on how to increase the success ratio of the data delivery to enhance the transmission reliability. As a result of the simulation, it was confirmed that the proposed method achieves better performance in terms of energy efficiency than existing face-routing research, and it is better than recent face-routing research in terms of reliability and retransmission. Full article

(This article belongs to the Special Issue Communications and Computing in Sensor Network)

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20 pages, 659 KiB

Open AccessEditor’s ChoiceArticle

Experimental Analysis of the Application of Serverless Computing to IoT Platforms

by Priscilla Benedetti, Mauro Femminella, Gianluca Reali and Kris Steenhaut

Sensors 2021, 21(3), 928; https://doi.org/10.3390/s21030928 - 30 Jan 2021

Cited by 30 | Viewed by 5144

Abstract

Serverless computing, especially implemented through Function-as-a-Service (FaaS) platforms, has recently been gaining popularity as an application deployment model in which functions are automatically instantiated when called and scaled when needed. When a warm start deployment mode is used, the FaaS platform gives users [...] Read more.

Serverless computing, especially implemented through Function-as-a-Service (FaaS) platforms, has recently been gaining popularity as an application deployment model in which functions are automatically instantiated when called and scaled when needed. When a warm start deployment mode is used, the FaaS platform gives users the perception of constantly available resources. Conversely, when a cold start mode is used, containers running the application’s modules are automatically destroyed when the application has been executed. The latter can lead to considerable resource and cost savings. In this paper, we explore the suitability of both modes for deploying Internet of Things (IoT) applications considering a low resources testbed comparable to an edge node. We discuss the implementation and the experimental analysis of an IoT serverless platform that includes typical IoT service elements. A performance study in terms of resource consumption and latency is presented for the warm and cold start deployment mode, and implemented using OpenFaaS, a well-known open-source FaaS framework which allows to test a cold start deployment with precise inactivity time setup thanks to its flexibility. This experimental analysis allows to evaluate the aptness of the two deployment modes under different operating conditions: Exploiting OpenFaaS minimum inactivity time setup, we find that the cold start mode can be convenient in order to save edge nodes limited resources, but only if the data transmission period is significantly higher than the time needed to trigger containers shutdown. Full article

(This article belongs to the Special Issue Communications and Computing in Sensor Network)

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27 pages, 3424 KiB

Open AccessArticle

System Performance Analysis for an Energy Harvesting IoT System Using a DF/AF UAV-Enabled Relay with Downlink NOMA under Nakagami-m Fading

by Anh-Nhat Nguyen, Van Nhan Vo, Chakchai So-In and Dac-Binh Ha

Sensors 2021, 21(1), 285; https://doi.org/10.3390/s21010285 - 4 Jan 2021

Cited by 24 | Viewed by 3587

Abstract

This paper investigates system performance in the Internet of Things (IoT) with an energy harvesting (EH) unmanned aerial vehicle (UAV)-enabled relay under Nakagami-m fading, where the time switching (TS) and adaptive power splitting (APS) protocols are applied for the UAV. Our proposed [...] Read more.

This paper investigates system performance in the Internet of Things (IoT) with an energy harvesting (EH) unmanned aerial vehicle (UAV)-enabled relay under Nakagami-m fading, where the time switching (TS) and adaptive power splitting (APS) protocols are applied for the UAV. Our proposed system model consists of a base station (BS), two IoT device (ID) clusters (i.e., a far cluster and a near cluster), and a multiantenna UAV-enabled relay (UR). We adopt a UR-aided TS and APS (U-TSAPS) protocol, in which the UR can dynamically optimize the respective power splitting ratio (PSR) according to the channel conditions. To improve the throughput, the nonorthogonal multiple access (NOMA) technique is applied in the transmission of both hops (i.e., from the BS to the UR and from the UR to the ID clusters). The U-TSAPS protocol is divided into two phases. In the first phase, the BS transmits a signal to the UR. The UR then splits the received signal into two streams for information processing and EH using the APS scheme. In the second phase, the selected antenna of the UR forwards the received signal to the best far ID (BFID) in the far cluster and the best near ID (BNID) in the near cluster using the decode-and-forward (DF) or amplify-and-forward (AF) NOMA scheme. We derive closed-form expressions for the outage probabilities (OPs) at the BFID and BNID with the APS ratio under imperfect channel state information (ICSI) to evaluate the system performance. Based on these derivations, the throughputs of the considered system are also evaluated. Moreover, we propose an algorithm for determining the nearly optimal EH time for the system to minimize the OP. In addition, Monte Carlo simulation results are presented to confirm the accuracy of our analysis based on simulations of the system performance under various system parameters, such as the EH time, the height and position of the UR, the number of UR antennas, and the number of IDs in each cluster. Full article

(This article belongs to the Special Issue Communications and Computing in Sensor Network)

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19 pages, 710 KiB

Open AccessArticle

Distributed Algorithm for Base Station Assignment in 4G/5G Machine-Type Communication Scenarios with Backhaul Limited Conditions

by Edgar A. Esquivel-Mendiola, Hiram Galeana-Zapién, David H. Covarrubias and Edwin Aldana-Bobadilla

Sensors 2020, 20(22), 6553; https://doi.org/10.3390/s20226553 - 17 Nov 2020

Cited by 1 | Viewed by 2190

Abstract

A progressive paradigm shift from centralized to distributed network architectures has been consolidated since the 4G communication standard, calling for novel decision-making mechanisms with distributed control to operate at the network edge. This situation implies that each base station (BS) must manage resources [...] Read more.

A progressive paradigm shift from centralized to distributed network architectures has been consolidated since the 4G communication standard, calling for novel decision-making mechanisms with distributed control to operate at the network edge. This situation implies that each base station (BS) must manage resources independently to meet the quality of service (QoS) of existing human-type communication devices (HTC), as well as the emerging machine type communication (MTC) devices from the internet of things (IoT). In this paper, we address the BS assignment problem, whose aim is to determine the most appropriate serving BS to each mobile device. This problem is formulated as an optimization problem for maximizing the system throughput and imposing constraints on the air interface and backhaul resources. The assignment problem is challenging to solve, so we present a simple yet valid reformulation of the original problem while using dual decomposition theory. Subsequently, we propose a distributed price-based BS assignment algorithm that performs at each BS the assignment process, where a novel pricing update scheme is presented. The simulation results show that our proposed solution outperforms traditional maximum signal to interference plus noise ratio (Max-SINR) and minimum path-loss (Min-PL) approaches in terms of system throughput. Full article

(This article belongs to the Special Issue Communications and Computing in Sensor Network)

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29 pages, 17142 KiB

Open AccessArticle

Fuzzy Adaptive-Sampling Block Compressed Sensing for Wireless Multimedia Sensor Networks

by Sovannarith Heng, Phet Aimtongkham, Van Nhan Vo, Tri Gia Nguyen and Chakchai So-In

Sensors 2020, 20(21), 6217; https://doi.org/10.3390/s20216217 - 31 Oct 2020

Cited by 9 | Viewed by 2812

Abstract

The transmission of high-volume multimedia content (e.g., images) is challenging for a resource-constrained wireless multimedia sensor network (WMSN) due to energy consumption requirements. Redundant image information can be compressed using traditional compression techniques at the cost of considerable energy consumption. Fortunately, compressed sensing [...] Read more.

The transmission of high-volume multimedia content (e.g., images) is challenging for a resource-constrained wireless multimedia sensor network (WMSN) due to energy consumption requirements. Redundant image information can be compressed using traditional compression techniques at the cost of considerable energy consumption. Fortunately, compressed sensing (CS) has been introduced as a low-complexity coding scheme for WMSNs. However, the storage and processing of CS-generated images and measurement matrices require substantial memory. Block compressed sensing (BCS) can mitigate this problem. Nevertheless, allocating a fixed sampling to all blocks is impractical since each block holds different information. Although solutions such as adaptive block compressed sensing (ABCS) exist, they lack robustness across various types of images. As a solution, we propose a holistic WMSN architecture for image transmission that performs well on diverse images by leveraging saliency and standard deviation features. A fuzzy logic system (FLS) is then used to determine the appropriate features when allocating the sampling, and each corresponding block is resized using CS. The combined FLS and BCS algorithms are implemented with smoothed projected Landweber (SPL) reconstruction to determine the convergence speed. The experiments confirm the promising performance of the proposed algorithm compared with that of conventional and state-of-the-art algorithms. Full article

(This article belongs to the Special Issue Communications and Computing in Sensor Network)

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13 pages, 2362 KiB

Open AccessArticle

Swarm-Intelligence-Centric Routing Algorithm for Wireless Sensor Networks

by Changsun Shin and Meonghun Lee

Sensors 2020, 20(18), 5164; https://doi.org/10.3390/s20185164 - 10 Sep 2020

Cited by 21 | Viewed by 3760

Abstract

The swarm intelligence (SI)-based bio-inspired algorithm demonstrates features of heterogeneous individual agents, such as stability, scalability, and adaptability, in distributed and autonomous environments. The said algorithm will be applied to the communication network environment to overcome the limitations of wireless sensor networks (WSNs). [...] Read more.

The swarm intelligence (SI)-based bio-inspired algorithm demonstrates features of heterogeneous individual agents, such as stability, scalability, and adaptability, in distributed and autonomous environments. The said algorithm will be applied to the communication network environment to overcome the limitations of wireless sensor networks (WSNs). Herein, the swarm-intelligence-centric routing algorithm (SICROA) is presented for use in WSNs that aim to leverage the advantages of the ant colony optimization (ACO) algorithm. The proposed routing protocol addresses the problems of the ad hoc on-demand distance vector (AODV) and improves routing performance via collision avoidance, link-quality prediction, and maintenance methods. The proposed method was found to improve network performance by replacing the periodic “Hello” message with an interrupt that facilitates the prediction and detection of link disconnections. Consequently, the overall network performance can be further improved by prescribing appropriate procedures for processing each control message. Therefore, it is inferred that the proposed SI-based approach provides an optimal solution to problems encountered in a complex environment, while operating in a distributed manner and adhering to simple rules of behavior. Full article

(This article belongs to the Special Issue Communications and Computing in Sensor Network)

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28 pages, 3748 KiB

Open AccessArticle

Characterization, Statistical Analysis and Method Selection in the Two-Clocks Synchronization Problem for Pairwise Interconnected Sensors

by Juan-Antonio Fernández-Madrigal, Angeles Navarro, Rafael Asenjo and Ana Cruz-Martín

Sensors 2020, 20(17), 4808; https://doi.org/10.3390/s20174808 - 26 Aug 2020

Cited by 1 | Viewed by 2166

Abstract

Time synchronization among sensor devices connected through non-deterministic media is a fundamental requirement for sensor fusion and other distributed tasks that need a common time reference. In many of the time synchronization methods existing in literature, the estimation of the relation between pairs [...] Read more.

Time synchronization among sensor devices connected through non-deterministic media is a fundamental requirement for sensor fusion and other distributed tasks that need a common time reference. In many of the time synchronization methods existing in literature, the estimation of the relation between pairs of clocks is a core concept; moreover, in applications that do not have general connectivity among its devices but a simple pairwise topology, such as embedded systems, mobile robots or home automation, two-clock synchronization is actually the basic form of the time estimation problem. In these kinds of applications, especially for critical ones, not only the quality of the estimation of the relation between two clocks is important, but also the bounds the methods provide for the estimated values, and their computational effort (since many are small systems). In this paper, we characterize, with a thorough parameterization, the possible scenarios where two-clock synchronization is to be solved, and then conduct a rigorous statistical study of both scenarios and methods. The study is based on exhaustive simulations run in a super-computer. Our aim is to provide a sound basis to select the best clock synchronization algorithm depending on the application requirements and characteristics, and also to deduce which ones of these characteristics are most relevant, in general, when solving the problem. For our comparisons we have considered several representative methods for clock synchronization according to a novel taxonomy that we also propose in the paper, and in particular, a few geometrical ones that have special desirable characteristics for the two-clock problem. We illustrate the method selection procedure with practical use-cases of sensory systems where two-clock synchronization is essential. Full article

(This article belongs to the Special Issue Communications and Computing in Sensor Network)

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19 pages, 745 KiB

Open AccessArticle

Control Plane Optimisation for an SDN-Based WBAN Framework to Support Healthcare Applications

by Khalid Hasan, Khandakar Ahmed, Kamanashis Biswas, Md. Saiful Islam, A. S. M. Kayes and S. M. Riazul Islam

Sensors 2020, 20(15), 4200; https://doi.org/10.3390/s20154200 - 28 Jul 2020

Cited by 13 | Viewed by 3760

Abstract

Software-Defined Networking (SDN) offers an abstract view of the network and assists network operators to control the network traffic and the associated network resources more effectively. For the past few years, SDN has shown a lot of merits in diverse fields of applications, [...] Read more.

Software-Defined Networking (SDN) offers an abstract view of the network and assists network operators to control the network traffic and the associated network resources more effectively. For the past few years, SDN has shown a lot of merits in diverse fields of applications, an important one being the Wireless Body Area Network (WBAN) for healthcare services. With the amalgamation of SDN with WBAN (SDWBAN), the patient monitoring and management system has gained much more flexibility and scalability compared to the conventional WBAN. However, the performance of the SDWBAN framework largely depends on the controller which is a core element of the control plane. The reason is that an optimal number of controllers assures the satisfactory level of performance and control of the network traffic originating from the underlying data plane devices. This paper proposes a mathematical model to determine the optimal number of controllers for the SDWBAN framework in healthcare applications. To achieve this goal, the proposed mathematical model adopts the convex optimization method and incorporates three critical SDWBAN factors in the design process: number of controllers, latency and number of SDN-enabled switches (SDESW). The proposed analytical model is validated by means of simulations in Castalia 3.2 and the outcomes indicate that the network achieves high level of Packet Delivery Ratio (PDR) and low latency for optimal number of controllers as derived in the mathematical model. Full article

(This article belongs to the Special Issue Communications and Computing in Sensor Network)

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25 pages, 2522 KiB

Open AccessArticle

A Distributed Stream Processing Middleware Framework for Real-Time Analysis of Heterogeneous Data on Big Data Platform: Case of Environmental Monitoring

by Adeyinka Akanbi and Muthoni Masinde

Sensors 2020, 20(11), 3166; https://doi.org/10.3390/s20113166 - 3 Jun 2020

Cited by 21 | Viewed by 8215

Abstract

In recent years, the application and wide adoption of Internet of Things (IoT)-based technologies have increased the proliferation of monitoring systems, which has consequently exponentially increased the amounts of heterogeneous data generated. Processing and analysing the massive amount of data produced is cumbersome [...] Read more.

In recent years, the application and wide adoption of Internet of Things (IoT)-based technologies have increased the proliferation of monitoring systems, which has consequently exponentially increased the amounts of heterogeneous data generated. Processing and analysing the massive amount of data produced is cumbersome and gradually moving from classical ‘batch’ processing—extract, transform, load (ETL) technique to real-time processing. For instance, in environmental monitoring and management domain, time-series data and historical dataset are crucial for prediction models. However, the environmental monitoring domain still utilises legacy systems, which complicates the real-time analysis of the essential data, integration with big data platforms and reliance on batch processing. Herein, as a solution, a distributed stream processing middleware framework for real-time analysis of heterogeneous environmental monitoring and management data is presented and tested on a cluster using open source technologies in a big data environment. The system ingests datasets from legacy systems and sensor data from heterogeneous automated weather systems irrespective of the data types to Apache Kafka topics using Kafka Connect APIs for processing by the Kafka streaming processing engine. The stream processing engine executes the predictive numerical models and algorithms represented in event processing (EP) languages for real-time analysis of the data streams. To prove the feasibility of the proposed framework, we implemented the system using a case study scenario of drought prediction and forecasting based on the Effective Drought Index (EDI) model. Firstly, we transform the predictive model into a form that could be executed by the streaming engine for real-time computing. Secondly, the model is applied to the ingested data streams and datasets to predict drought through persistent querying of the infinite streams to detect anomalies. As a conclusion of this study, a performance evaluation of the distributed stream processing middleware infrastructure is calculated to determine the real-time effectiveness of the framework. Full article

(This article belongs to the Special Issue Communications and Computing in Sensor Network)

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17 pages, 2561 KiB

Open AccessArticle

Message-Based Communication for Heterogeneous Internet of Things Systems

by Bogdan Oniga, Leon Denis, Vasile Dadarlat and Adrian Munteanu

Sensors 2020, 20(3), 861; https://doi.org/10.3390/s20030861 - 6 Feb 2020

Cited by 6 | Viewed by 3041

Abstract

The Internet of Things (IoT) domain presents a wide spectrum of technologies for building IoT applications. The requirements are varying from one application to another granting uniqueness to each IoT system. Each application demands custom implementations to achieve efficient, secure and cost-effective environments. [...] Read more.

The Internet of Things (IoT) domain presents a wide spectrum of technologies for building IoT applications. The requirements are varying from one application to another granting uniqueness to each IoT system. Each application demands custom implementations to achieve efficient, secure and cost-effective environments. They pose a set of properties that cannot be addressed by a single-based protocol IoT network. Such properties are achievable by designing a heterogeneous IoT system, which integrates diverse IoT protocols and provides a network management solution to efficiently manage the system components. This paper proposes an IoT message-based communication model applied atop the IoT protocols in order to achieve functional scalability and network management transparency agnostic to the employed communication protocol. The paper evaluates the proposed communication model and proves its functional scalability in a heterogeneous IoT system. The experimental assessment compares the payload size of the proposed system with respect to the LwM2M standard, a protocol designed specifically for IoT applications. In addition, the paper discusses the energy consumption introduced by the proposed model as well as the options available to reduce such impact. Full article

(This article belongs to the Special Issue Communications and Computing in Sensor Network)

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18 pages, 429 KiB

Open AccessArticle

Performance Analysis of Cooperative NOMA Networks with Imperfect CSI over Nakagami-m Fading Channels

by Xianli Gong, Xinwei Yue and Feng Liu

Sensors 2020, 20(2), 424; https://doi.org/10.3390/s20020424 - 11 Jan 2020

Cited by 26 | Viewed by 4493

Abstract

In this paper, we investigate a downlink cooperative non-orthogonal multiple access (NOMA) network with decode-and-forward relaying, where two scenarios of user relaying with direct link and user relaying without direct link are discussed in detail. More particularly, the performance of cooperative NOMA system [...] Read more.

In this paper, we investigate a downlink cooperative non-orthogonal multiple access (NOMA) network with decode-and-forward relaying, where two scenarios of user relaying with direct link and user relaying without direct link are discussed in detail. More particularly, the performance of cooperative NOMA system under the assumption of imperfect channel state information (ipCSI) is studied over Nakagami-m fading channels. To evaluate the outage performance of the above discussed two scenarios, the closed-form expressions of outage probability for a pair of users are derived carefully. The diversity orders of users are achieved in the high signal-to-noise region. An error floor appears in the outage probability owing to the existence of channel estimation errors under ipCSI conditions. Simulation results verify the validity of our analysis and show that: (1) NOMA is superior to conventional orthogonal multiple access; (2) The best user relaying location for cooperative NOMA networks should be near to the base station; and (3) The outage performance of distant user with direct link significantly outperforms distant user without direct link by comparing the two scenarios. Full article

(This article belongs to the Special Issue Communications and Computing in Sensor Network)

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15 pages, 2628 KiB

Open AccessArticle

Non-Fragile Robust H∞ Filtering of Takagi-Sugeno Fuzzy Networked Control Systems with Sensor Failures

by Hao Wang, Shousheng Xie, Bin Zhou and Weixuan Wang

Sensors 2020, 20(1), 27; https://doi.org/10.3390/s20010027 - 19 Dec 2019

Cited by 13 | Viewed by 2245

Abstract

The fault-tolerant robust non-fragile H∞ filtering problem for networked control systems with sensor failures is studied in this paper. The Takagi-Sugeno fuzzy model which can appropriate any nonlinear systems is employed. Based on the model, a filter which can maintain stability and [...] Read more.

The fault-tolerant robust non-fragile H∞ filtering problem for networked control systems with sensor failures is studied in this paper. The Takagi-Sugeno fuzzy model which can appropriate any nonlinear systems is employed. Based on the model, a filter which can maintain stability and H∞ performance level under the influence of gain perturbation of the filter and sensor failures is designed. Moreover, the gain matrix of sensor failures is converted into a dynamic interval to expand the range of allowed failures. And the sufficient condition for the existence of the desired filter is derived in terms of linear matrix inequalities (LMIs) solutions. Finally a simulation example is given to illustrate the effectiveness of the proposed method. Full article

(This article belongs to the Special Issue Communications and Computing in Sensor Network)

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Review

Jump to: Research, Other

41 pages, 11101 KiB

Open AccessReview

A Comprehensive Overview of TCP Congestion Control in 5G Networks: Research Challenges and Future Perspectives

by Josip Lorincz, Zvonimir Klarin and Julije Ožegović

Sensors 2021, 21(13), 4510; https://doi.org/10.3390/s21134510 - 30 Jun 2021

Cited by 36 | Viewed by 17245

Abstract

In today’s data networks, the main protocol used to ensure reliable communications is the transmission control protocol (TCP). The TCP performance is largely determined by the used congestion control (CC) algorithm. TCP CC algorithms have evolved over the past three decades and a [...] Read more.

In today’s data networks, the main protocol used to ensure reliable communications is the transmission control protocol (TCP). The TCP performance is largely determined by the used congestion control (CC) algorithm. TCP CC algorithms have evolved over the past three decades and a large number of CC algorithm variations have been developed to accommodate various network environments. The fifth-generation (5G) mobile network presents a new challenge for the implementation of the TCP CC mechanism, since networks will operate in environments with huge user device density and vast traffic flows. In contrast to the pre-5G networks that operate in the sub-6 GHz bands, the implementation of TCP CC algorithms in 5G mmWave communications will be further compromised with high variations in channel quality and susceptibility to blockages due to high penetration losses and atmospheric absorptions. These challenges will be particularly present in environments such as sensor networks and Internet of Things (IoT) applications. To alleviate these challenges, this paper provides an overview of the most popular single-flow and multy-flow TCP CC algorithms used in pre-5G networks. The related work on the previous examinations of TCP CC algorithm performance in 5G networks is further presented. A possible implementation of TCP CC algorithms is thoroughly analysed with respect to the specificities of 5G networks, such as the usage of high frequencies in the mmWave spectrum, the frequent horizontal and vertical handovers, the implementation of the 5G core network, the usage of beamforming and data buffering, the exploitation of edge computing, and the constantly transmitted always-on signals. Moreover, the capabilities of machine learning technique implementations for the improvement of TCPs CC performance have been presented last, with a discussion on future research opportunities that can contribute to the improvement of TCP CC implementation in 5G networks. This survey paper can serve as the basis for the development of novel solutions that will ensure the reliable implementation of TCP CC in different usage scenarios of 5G networks. Full article

(This article belongs to the Special Issue Communications and Computing in Sensor Network)

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Other

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14 pages, 526 KiB

Open AccessLetter

Beamforming Techniques for Over-the-Air Computation in MIMO IoT Networks

by Young-Seok Lee, Ki-Hun Lee and Bang Chul Jung

Sensors 2020, 20(22), 6464; https://doi.org/10.3390/s20226464 - 12 Nov 2020

Cited by 4 | Viewed by 2613

Abstract

In this paper, a novel beamforming technique is proposed as the over-the-air computation (AirComp) framework in a multiple-input multiple-output (MIMO) Internet-of-things (IoT) network consisting of multiple IoT sensors (STAs) and a single access point (AP). We assume that each IoT device has the [...] Read more.

In this paper, a novel beamforming technique is proposed as the over-the-air computation (AirComp) framework in a multiple-input multiple-output (MIMO) Internet-of-things (IoT) network consisting of multiple IoT sensors (STAs) and a single access point (AP). We assume that each IoT device has the channel state information (CSI) from itself to the AP and the AP has the global CSI of all IoT devices. We consider the mean squared error (MSE), which represents the reliability of function computation, as a performance metric. In short, each IoT device exploits maximum-ratio transmission (MRT) as a transmit beamforming technique to improve MSE performance by taking full advantage of multiple transmit antennae. Moreover, for the receive beamforming, we first consider a receive antenna selection (RAS) technique as the simplest beamforming method at the AP. Then, a semi-definite relaxation (SDR) method and a successive convex approximation (SCA) algorithm are considered and compared with each other in terms of MSE. Finally, we propose a novel two-step beamforming algorithm to further improve the MSE performance of the aforementioned techniques. We have numerically verified through computer simulations that the proposed framework has an improved MSE performance of about 6dB compared to the conventional single-input multiple-output (SIMO) AirComp, even with only two transmit antennae, and the modified MRT outperforms the other transmit beamforming techniques. Furthermore, the proposed receive beamforming technique, a two-step algorithm, shows the best performance in terms of MSE compared to prior studies. Full article

(This article belongs to the Special Issue Communications and Computing in Sensor Network)

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