 Subjects -> ELECTRONICS (Total: 207 journals)
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- BER performance analysis for downlink NOMA systems over cascaded
Nakagami-m fading channels-
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Abstract: Abstract In this study, the downlink non-orthogonal multiple access (NOMA) system in which successive interference cancellation (SIC) errors exist is discussed. The new closed-form expressions for the bit error rate (BER) performance analysis over cascaded Nakagami-m fading channels are analytically derived for near and far users. In addition, new mathematical equations are obtained for the asymptotic BER as well as the diversity order to analyze the system performance. The theoretical results precisely match the simulations in all cases, validating the effectiveness of the theoretical analysis. The results demonstrate that the system performance decreases as the degree of N cascading increases. As for a fixed degree of cascading, BER performance increases as the m parameter increases. Moreover, for the power allocation coefficient \(\alpha \) influences the SIC operation performed on the near user, it also substantially affects the BER performance. Monte Carlo simulations using \(10^{6}\) iterations are presented to validate the derived analytical results.
PubDate: 2023-11-24
- Performance analysis of majority-based transmit antenna selection and
maximal ratio combining in MIMO-NOMA networks-
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Abstract: Abstract Non-orthogonal multiple access (NOMA) is paramount in modern wireless communication systems since it enables efficient multiple access schemes, allowing multiple users to share the same spectrum resources and thus improving overall network capacity. Multiple-input multiple-output (MIMO) technology is crucial in wireless communication as it leverages multiple antennas to enhance data throughput, increase link reliability, and mitigate signal interference, resulting in improved communication performance. The combination of MIMO and NOMA represents a transformative synergy that harnesses the benefits of both technologies, facilitating efficient spectrum utilization, higher data rates, and improved reliability in wireless networks. This makes it particularly valuable in the fifth-generation (5G) era and beyond. This paper investigates the performance of majority-based transmit antenna selection and maximal ratio combining (TAS-maj/MRC) in MIMO-NOMA networks. We derive a closed-form expression for the exact bit error rate (BER) for binary phase shift keying (BPSK) modulation in Nakagami-m fading channels. Moreover, asymptotic expressions are obtained in the high signal-to-noise ratio (SNR) region to get further insight into the BER behavior of the system. Finally, we verify the analytical results’ accuracy through simulations. The results demonstrate that diversity and code gains are achieved. In addition, the BER performance is significantly improved as the number of receive antennas increases or channel condition enhances.
PubDate: 2023-11-22
- Capacity aware Wi-Fi networks deployment
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Abstract: Abstract Wireless technologies are used in almost every application domain. Applications have different requirements in terms of quality of service and network performance. When designing a wireless network, it is important to know the expected performance of the system. Including the application needs in the design of the network would help achieve the required performance. This paper focuses on the high throughput required for a Smart Farming use case. Multiple-Input Multiple-Output (MIMO) technology had greatly boosted the performance of wireless networks by introducing beamforming, which provides many benefits allowing wider coverage and better data rates. We propose a capacity-aware coverage study for Wi-Fi networks deployment in rural areas. We make our coverage estimations based on link budget calculations. We compare different deployment strategies and discuss the added value of beamforming. Our results are based on an analytical link budget estimation and a simulation study using the NS-3 simulator. We added all the needed functionalities on top of the existing Wi-Fi Module in NS-3. Results in terms of capacity, coverage, and number of access points deployed are discussed. We also developed an empirical analytical model that is based on the simulation results, which helps in estimating performance results for any deployment field size.
PubDate: 2023-11-22
- Computing paradigms for smart farming in the era of drones: a systematic
review-
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Abstract: Abstract In the current era of agricultural robotization, it is necessary to use a suitable automated data collection system for constant plant, animal, and machine monitoring. In this context, cloud computing (CC) is a well-established paradigm for building service-centric farming applications. However, the huge amount of data has put an important burden on data centers and network bandwidth and pointed out issues that cloud-based applications face such as large latency, bottlenecks because of central processing, compromised security, and lack of offline processing. Fog computing (FC), edge computing (EC), and mobile edge computing (MEC) (or flying edge computing FEC) are gaining exponential attention and becoming attractive solutions to bring CC processes within reach of users and address computation-intensive offloading and latency issues. These paradigms from cloud to mobile edge computing are already forming a unique ecosystem with different architectures, storage, and processing capabilities. The heterogeneity of this ecosystem comes with certain limitations and challenges. This paper carries out a systematic review of the latest high-quality literature and aims to identify similarities, differences, and the main use cases in the mentioned computing paradigms, particularly when using drones. Our expectation from this work is to become a good reference for researchers and help them address hot topics and challenging issues related to this scope.
PubDate: 2023-11-18
- A lightweight, efficient, and secure identity-based authentication scheme
for underwater green transport systems-
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Abstract: Abstract The underwater green transport system (UwGTs) is a network of connected, intelligent underwater sensors or Internet of Things (IoT) devices. The sensor networks used in UwGTs are distinct from traditional territorial wireless sensor networks in many ways, including their lengthy propagation delays, restricted bandwidths, and poor reliability. UwGTs would face significant security difficulties due to these unique traits. The main goal of this paper is to resolve authentication issues across the entire UwGTs network. The more significant challenge in developing an authentication scheme for UwGTs is to develop a simple, efficient, and secure system that considers the sensor nodes’ resource limitations. In light of this, we suggest an identity-based signature-based authentication scheme based on elliptic curve cryptography that enhances network lifetime by reducing sensor node energy consumption. The security of the suggested scheme has also been confirmed using a formal security assessment technique like the Random Oracle Model (ROM) and Automated Validation of Internet Security Protocols and Applications (AVISPA) software tools. In addition, the proposed scheme is more effective and lightweight regarding computation costs, communication costs, energy consumption, and comparative energy efficiency than the existing identity-based authentication schemes.
PubDate: 2023-11-14
- On the capacity of multiple antenna systems
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Abstract: Abstract The significant role of multiple antenna techniques is vital to enable wireless systems to support the ever-rising demand for higher data rates and reliability. Thus, investigating these systems is continually important, and one of the essential aspects of this study is analyzing the capacity of such systems to gain insight into their performance. This paper presents several closed-form formulae to express the capacity of the multiple antenna system, by introducing newly derived finite and unconditionally valid solutions. It is also mathematically describing the outage probability of multiple antenna system in several scenarios. The numerical results show the tight fit between the obtained formulae and the Monte Carlo simulation outcomes.
PubDate: 2023-11-13
- Wi-Fi faces the new wireless ecosystem: a critical review
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Abstract: Abstract Over the last three decades, we have become more dependent on wireless connectivity to access services and applications from nearly anywhere. The overstated emergence of the all-encompassing fifth generation (5G) of mobile systems begs the question of the future of the new generation of IEEE 802.11 (Wi-Fi) solutions. However, Wi-Fi has certain advantages compared to cellular systems in different ways: (i) a fast-paced standardization process; (ii) a diverse, agile, and highly competitive manufacturer base; and (iii) a broad base of early adopters for both office and house wireless networks. In addition, the rise of enabling technologies, such as software-defined wireless networks, may allow more robust and reliable Wi-Fi networks to bridge gaps in Wi-Fi technology to reach several vertical sectors. This review provides a technical analysis of the relationship between broadband wireless and Wi-Fi technologies. Wi-Fi has taken decisive steps with the evolution of several standards, and there is already evidence that Wi-Fi may partially (or completely) fulfill 5G’s strict service requirements. Next, we discussed the Wi-Fi and 5G convergence, which allow more control over user experiences and provide better service. This review concludes with an analysis of open challenges in the convergence of 5G and Wi-Fi systems. We conclude that Wi-Fi technology has and will continue to have a decisive role as an access technology in the new ecosystem of wireless networks.
PubDate: 2023-11-09
- Low-latency remote-offloading system for accelerator
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Abstract: Abstract Specific workloads are increasingly offloaded to accelerators such as a graphic processing unit (GPU) and field-programmable gate array (FPGA) for real-time processing and computing efficiency. Because accelerators are expensive and consume much power, it is desirable to increase the efficiency of accelerator utilization by sharing accelerators among multiple servers over a network. However, task offloading over a network has the problem of latency due to network processing overhead in remote offloading. This paper proposes a low-latency system for accelerator offloading over a network. To reduce the overhead of remote offloading, we propose a system composed of (1) fast recombination processing of chunked data with a simple protocol to reduce the number of memory copies, (2) polling-based packet receiving check to reduce overhead due to interrupts in interaction with a network interface card, and (3) a run-to-completion model in network processing and accelerator offloading to reduce overhead with context switching. We show that the system can improve performance by 66.40% compared with a simple implementation using kernel protocol stack and confirmed the performance improvement with a virtual radio access network use case as a low-latency application. Furthermore, we show that this performance can also be achieved in practical usage in data center networks.
PubDate: 2023-11-03
- The role of SIC on the design of next generation multiple access
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Abstract: Abstract The interplay of physical layer enhancements and classic random access protocols is the objective of this paper. Successive interference cancellation (SIC) is among the major enhancements of the physical layer. Considering the classic representatives of random access protocols, Slotted ALOHA and Channel Sensing Multiple Access (CSMA), we show that two regimes can be identified as a function of the communication link spectral efficiency. In case of high levels of spectral efficiency, multi-packet reception enabled by SIC is of limited benefit. Sum-rate performance is dominated by the effectiveness of the Medium Access Control (MAC) protocol. On the contrary, for low spectral efficiency levels, sum-rate performance is essentially dependent on physical layer SIC capability, while the MAC protocol has a marginal impact. Limitations due to transmission power dynamic range are shown to induce unfairness among nodes. However, the unfairness issue fades away when the system is driven to work around the sum-rate peak achieved for low spectral efficiency. This can also be confirmed by looking at Age of Information (AoI) metric. The major finding of this work is that SIC can boost performance, while still maintaining a fair sharing of the communication channel among nodes. In this regime, the MAC protocol appears to play a marginal role, while multi-packet reception endowed by SIC is prominent to provide high sum-rate, low energy consumption, and low AoI.
PubDate: 2023-10-12
- An approach for detecting multi-institution attacks
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Abstract: Abstract We present Soteria, a data processing pipeline for detecting multi-institution attacks. Soteria uses a set of machine learning techniques to detect future attacks, predict their future targets, and rank attacks based on their predicted severity. Our evaluation with real data from Canada-wide academic institution networks shows that Soteria can predict future attacks with 95% recall rate, predict the next targets of an attack with 97% recall rate, and detect attacks in the first 20% of their life span. Soteria is deployed in production and is in use by tens of Canadian academic institutions that are part of the CANARIE IDS project.
PubDate: 2023-10-09
- A data infrastructure for heterogeneous telemetry adaptation: application
to Netflow-based cryptojacking detection-
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Abstract: Abstract The increasing development of cryptocurrencies has brought cryptojacking as a new security threat in which attackers steal computing resources for cryptomining. The digitization of the supply chain is a potential major target for cryptojacking due to the large number of different infrastructures involved. These different infrastructures provide information sources that can be useful to detect cryptojacking, but with a wide variety of data formats and encodings. This paper describes the semantic data aggregator (SDA), a normalization and aggregation system based on data modelling and low-latency processing of data streams that facilitates the integration of heterogeneous information sources. As a use case, the paper describes a cryptomining detection system (CDS) based on network traffic flows processed by a machine learning engine. The results show how the SDA is leveraged in this use case to obtain aggregated information that improves the performance of the CDS.
PubDate: 2023-10-03
- 5G, 6G, and Beyond: Recent advances and future challenges
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Abstract: Abstract With the high demand for advanced services and the increase in the number of connected devices, current wireless communication systems are required to expand to meet the users’ needs in terms of quality of service, throughput, latency, connectivity, and security. 5G, 6G, and Beyond (xG) aim at bringing new radical changes to shake the wireless communication networks where everything will be fully connected fulfilling the requirements of ubiquitous connectivity over the wireless networks. This rapid revolution will transform the world of communication with more intelligent and sophisticated services and devices leading to new technologies operating over very high frequencies and broader bands. To achieve the objectives of the xG networks, several key technology enablers need to be performed, including massive MIMO, software-defined networking, network function virtualization, vehicular to everything, mobile edge computing, network slicing, terahertz, visible light communication, virtualization of the network infrastructure, and intelligent communication environment. In this paper, we investigated the recent advancements in the 5G/6G and Beyond systems. We highlighted and analyzed their different key technology enablers and use cases. We also discussed potential issues and future challenges facing the new wireless networks.
PubDate: 2023-10-01
- Hidden Markov Model for early prediction of the elderly’s dependency
evolution in ambient assisted living-
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Abstract: Abstract The integration of information and communication technologies (ICT) can be of great utility in monitoring and evaluating the elderly’s health condition and its behavior in performing Activities of Daily Living (ADL) in the perspective to avoid, as long as possible, the delays of recourse to health care institutions (e.g., nursing homes and hospitals). In this research, we propose a predictive model for detecting behavioral and health-related changes in a patient who is monitored continuously in an assisted living environment. We focus on keeping track of the dependency level evolution and detecting the loss of autonomy for an elderly person using a Hidden Markov Model based approach. In this predictive process, we were interested in including the correlation between cardiovascular history and hypertension as it is considered the primary risk factor for cardiovascular diseases, stroke, kidney failure and many other diseases. Our simulation was applied to an empirical dataset that concerned 3046 elderly persons monitored over 9 years. The results show that our model accurately evaluates person’s dependency, follows his autonomy evolution over time and thus predicts moments of important changes.
PubDate: 2023-10-01
- Backscatter communication system efficiency with diffusing surfaces
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Abstract: Abstract In an ambient backscatter communication system, the waves generated by a source are reflected by a tag, in a variable manner in time. Therefore, the tag can transmit a message to a reader, without generating any radio wave and without battery. As a consequence, such a communication system is a promising technology for ultra-low energy wireless communications. In the simplest implementation of such a system, the tag sends a binary message by oscillating between two states and the reader detects the bits by comparing the two distinct received powers. In this paper, for the first time, we propose to analyze the impact of the shape of diffusing flat panel surfaces that diffuse in all directions, on an ambient backscatter communication system. We establish the analytical closed form expression of the power contrast in the presence of flat panels, by considering a rectangular surface and a disk-shaped surface, and we show that diffusing surfaces improve the power contrast. Moreover, our approach allows us to express the contrast to noise ratio, and therefore to establish the BER performance. Furthermore, we show that it makes it possible to improve the energetic performance, thanks to diffusing surfaces. For any configuration characterized by a fixed source, tag and reader, we moreover determine the precise locations of diffusing surfaces, which induce a maximum efficiency of the surfaces, whatever the wavelength. Furthermore, we show that it becomes possible to easily determine an optimal frequency which maximizes the contrast power, thanks to the expression of the contrast power.
PubDate: 2023-10-01
- Analysis of SNR penalty in coherent WDM receiver system for detection of
QPSK signal with component crosstalk-
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Abstract: Abstract We propose analytical modelling of component crosstalk on the performance of wavelength division multiplexed (WDM) receiver with generalized quadrature phase shift keying (QPSK) signal and coherent detection. A comprehensive study on the signal-to-noise ratio (SNR) penalty is conducted, which can be used to balance SNR values and the system's power budget in the presence of finite crosstalk sources. Results express that, in the presence of five crosstalk interferers, the crosstalk level leading to 1-dB of SNR penalty must be less than -23.8 to -26.5 dB for bit error rate (BER) from 10–7 to 10–13. For the BER of 10–9, the QPSK signal has a component crosstalk tolerance of -21.7 dB for a 1 dB SNR penalty with a single interferer. Furthermore, the study of spectral efficiency reveals that crosstalk level, SNR, and the number of active interferers perform a vital role in determining the bandwidth efficiency of the system. The analysis exploits the characteristic function method and Maclaurin series expansion to compute a closed form expression of BER over additive white Gaussian noise (AWGN) channel. Following the analysis, the SNR and bandwidth expenses of the system are examined numerically through the estimated BER and binary entropy function. The estimated values of the BER using the proposed model are in close agreement with a similar theoretical investigation for a single interferer.
PubDate: 2023-10-01
- Telephony speech system performance based on the codec effect
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Abstract: Abstract This paper is a part of our contribution to research on the enhancement of network automatic speech recognition system performance. We built a highly configurable platform by using hidden Markov models, Gaussian mixture models, and Mel frequency spectral coefficients, in addition to VoIP G.711-u and GSM codecs. To determine the optimal values for maximum performance, different acoustic models are prepared by varying the hidden Markov models (from 3 to 5) and Gaussian mixture models (8–16-32) with 13 feature extraction coefficients. Additionally, our generated acoustic models are tested by unencoded and encoded speech data based on G.711 and GSM codecs. The best parameterization performance is obtained for 3 HMM, 8–16 GMMs, and G.711 codecs.
PubDate: 2023-10-01
- DLT architectures for trust anchors in 6G
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Abstract: Abstract This manuscript investigates viable Distributed Ledger Technology (DLT) architecture approaches to be used as basis for the distribution of integrity verification data. We discuss what can be a Trust Anchor and how the property of trust can be enabled as a service for mobile communications infrastructures. This follows up on a preceding publication, in the course of which a service was developed that can be utilized to create trust and traceability in transactions between other services. Crucial for the integrity of such an audit trail is proof for which side was committing, in case a tampering was detected. For such verification in the aftermath, mechanisms for the distribution of meta data are necessary. Where our ultimate goal is to develop a versatile framework for Trust as a Service (TaaS), the work at hand contributes the investigation on header distribution. We put a major focus on providing Trust as a Service (TaaS) especially in the mobile communications domain since a reliable concept for trustworthiness is indispensable for the vision of organic infrastructures beyond 5G, which means that such networks are flexible regarding their composition and open for stakeholders.
PubDate: 2023-10-01
- Deep unfolding for energy-efficient resource allocation in mmWave networks
with multi-connectivity-
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Abstract: Abstract In millimeter-wave (mmWave) communications, multi-connectivity can enhance the communication capacity while at the cost of increased power consumption. In this paper, we investigate a deep-unfolding-based approach for joint user association and power allocation to maximize the energy efficiency of mmWave networks with multi-connectivity. The problem is formulated as a mixed integer nonlinear fractional optimization problem. First, we develop a three-stage iterative algorithm to achieve an upper bound of the original problem. Then, we unfold the iterative algorithm with a convolutional neural network (CNN)-based accelerator and trainable parameters. Moreover, we propose a CNN-aided greedy algorithm to obtain a feasible solution. The simulation results show that the proposed algorithm can achieve good performance and strong robustness but with much reduced computational complexity.
PubDate: 2023-10-01
- Social network malicious insider detection using time-based trust
evaluation-
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Abstract: Abstract In recent years, malicious insider attacks have become a common fraudulent activity in which an attacker is often perceived as a trusted entity in Social Networks (SNs). At present, machine learning (ML) approaches are widely used to identify the behavior of users in the network. From this perspective, this paper presents an integrated approach, namely, Social network malicious insider detection (SID), which consists of long short-term memory (LSTM) and time-based trust evaluation (TBTE). The proposed SID aims to identify deviations in SN user behavior by monitoring their data. The proposed SID uses LSTM, an advanced version of the recurrent neural network (RNN), which precisely predicts the behavior of users and identifies the anomaly pattern in SNs. A time-based trust evaluation method is integrated with LSTM, which not only differentiates the abnormal behavior of SN users but also precisely categorizes an anomaly node as a malicious node, a new user or a broken node. Moreover, the proposed SID detects insiders accurately and reduces false alarms by providing a novel quantitative analysis for computing the balancing factor according to time, which avoids the misinterpretation of normal user patterns as anomalies. The performance of the proposed SID is evaluated in real time, which demonstrates that the detection accuracy for attacks is 96% for normal users and 98% for new users with a smaller time span.
PubDate: 2023-10-01
- Robust adaptive beamforming algorithm for coherent signals based on
virtual array-
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Abstract: Abstract Aiming at the problem of beamforming performance degradation under the coherent signals model, this paper proposes an adaptive beamforming algorithm based on the virtual array. Compared with previous work, the creative construction of virtual arrays in this paper allows the algorithm to ensure strong coherent signal processing and superior output performance with no degradation in coherence capability. The proposed algorithm firstly constructs a virtual array symmetric to the physical array to form a virtual antenna array model; secondly, a full-rank covariance matrix is obtained by matrix reconstruction; then, the direction vector and power of the signals are estimated; finally, the estimated parameters are used to reconstruct the interference plus noise covariance matrix (INCM) and calculate the weight vector. Simulation analysis verifies the superiority of the algorithm and the validity of theoretical analysis.
PubDate: 2023-10-01
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