Access Transmission Research Articles

StegoEDCA: An Efficient Covert Channel for Smart Grids Based on IEEE 802.11e Standard

Smart grids are continuously evolving, incorporating modern technologies such as Wi-Fi, Zigbee, LoRaWAN or BLE. Wi-Fi are commonly used to transmit data from measurement systems, distribution control and monitoring systems, as well as network protection systems. However, since Wi-Fi networks primarily operate on unlicensed frequency bands, this introduces significant security risks for sensitive data transmission. In this paper, we propose a novel and highly efficient covert channels that utilize IEEE 802.11 Enhanced Distributed Channel Access (EDCA) for data transmission. It is also the first ever covert channel that employ three or four independent covert mechanisms to enhance operational efficiency. The proposed mechanism is also the first to exploit the Transmission Opportunity (TXOP) period and the access categories of the EDCA function. The protocol was developed and tested using the ns-3 simulator, achieving excellent performance results. Its efficiency remains consistent even under heavy network load with additional background traffic. These covert channels provide an innovative solution for securely transmitting large volumes of data within the smart grid.

IRS assisted spectrum sensing in cognitive radio network with grey wolf optimization

Cognitive radio (CR) is of crucial importance in providing efficient management of limited spectrum resources. However, its performance relies on efficient spectrum sensing. This paper investigates a novel approach for CR networks that leverages intelligent reflecting surface (IRS) specifically for spectrum sensing and non-orthogonal multiple access (NOMA) for data transmission. We propose a Grey-Wolf Optimization (GWO) based IRS optimization approach to maximize spectrum sensing performance. Independent of the IRS, NOMA is employed to improve spectral efficiency during data transmission. The performance is evaluated in terms of throughput and spectrum sensing parameters, namely probability of false alarm and missed detection. Numerical and simulation results demonstrate that GWO-based IRS optimization significantly outperforms conventional nature-inspired algorithms, achieving approximately 97% improvement in spectrum sensing accuracy. Based on the improved spectrum sensing results, the effective data transmission throughput is evaluated and validated through extensive simulation.

Enhancing uplink NOMA cooperative networks with RIS-UAV assistance in Nakagami-[formula omitted] fading channels

Reconfigurable intelligent surfaces (RIS) emerges as a novel communication technology for the 6G networks, boasting advantages such as low cost, high energy efficiency, and wide coverage. To enhance spectrum utilization and ensure signal transmission stability in complex communication scenarios, this paper presents an uplink cooperative non-orthogonal multiple access (NOMA) transmission network assisted by unmanned aerial vehicles (UAV) equipped with RIS. Firstly, a direct link is established between near users and the base station, while a decode-and-forward (DF) relay R and RIS-UAV are deployed between far users and the base station to achieve reliable transmission in a dynamic environment through joint NOMA. Furthermore, an incremental cooperative NOMA scheme is proposed for the uplink transmission, where the relay R remains silent if the RIS-UAV successfully transmits the signal of distant users; if the RIS-UAV fails to transmit the signal to the base station, the relay R is activated to complete the communication between distant users and the base station. Then, the base station employs a selection combining (SC) scheme to process the received signals. Finally, exact expressions of the outage probability under various power allocation strategies are derived. The research results indicate that the outage performance improves with an increase in the number of RIS reflection elements. Moreover, the presence of RIS-UAV can reduce the impact of power allocation strategies on the performance of the uplink NOMA network compared to networks without RIS-UAV.

A Learning-Based Energy-Efficient Device Grouping Mechanism for Massive Machine-Type Communication in the Context of Beyond 5G Networks

With the increasing demand for high data rates, low delay, and extended battery life, managing massive machine-type communication (mMTC) in the beyond 5G (B5G) context is challenging. MMTC devices, which play a role in developing the Internet of Things (IoT) and smart cities, need to transmit short amounts of data periodically within a specific time frame. Although blockchain technology is utilized for secure data storage and transfer while digital twin technology provides real-time monitoring and management of the devices, issues such as constrained time delays and network congestion persist. Without a proper data transmission strategy, most devices would fail to transmit in time, thus defying their relevance and purpose. This work investigates the problem of massive random access channel (RACH) attempts while emphasizing the energy efficiency and access latency for mMTC devices with critical missions in B5G networks. Using machine learning techniques, we propose an attention-based reinforcement learning model that orchestrates the device grouping strategy to optimize device placement. Thus, the model guarantees a higher probability of success for the devices during data transmission access, eventually leading to more efficient energy consumption. Through thorough quantitative simulations, we demonstrate that the proposed learning-based approach significantly outperforms the other baseline grouping methods.

Understanding the Factors Promoting Mother to Child Transmission of HIV/AIDS in Nigeria

Mother-to-child transmission (MTCT) of HIV/AIDS remains a significant public health challenge in Nigeria. This review aimed to identify and understand key factors promoting MTCT and assess the effectiveness of current prevention interventions. A systematic literature search was conducted across multiple databases using relevant keywords and approximately 57 individual literatures was reviewed. Studies focusing on MTCT in Nigeria published after 2015 were included. Eligible studies were critically appraised for quality and relevance. Findings indicate significant knowledge gap (such as misconceptions about transmission routes, limited understanding of prevention methods, delay in seeking testing and care and inconsistent adherence to Antiretroviral therapy) among pregnant women regarding HIV transmission, persistent stigma and discrimination hindering access to PMTCT services, and challenges within the healthcare system such as geographical disparities and inadequate provider training. Cultural practices, including breastfeeding and postnatal rituals, further exacerbate MTCT risk. Male partner involvement emerges as a crucial yet often overlooked aspect of PMTCT. Existing interventions showed moderate effectiveness, highlighting the need for tailored approaches. Strengthening multi-level interventions addressing social, economic, and cultural determinants, alongside culturally sensitive approaches and increased male engagement, are crucial to address MTCT and improve maternal and child health outcomes in Nigeria. Future research should focus on developing and evaluating interventions tailored to specific contexts and populations.

Resource allocation and passive beamforming for IRS‐assisted short packet systems

AbstractThis paper investigates an intelligent reflecting surface (IRS) assisted downlink short packet transmission system, where an access point sends short packets to multiple devices with the help of an IRS. Specifically, a performance comparison between the frequency division multiple access and time division multiple access is conducted for the considered system, from the perspective of average age of information (AoI). To minimize the maximum average AoI among all devices, the resource allocation and passive beamforming are jointly optimized. However, the formulated problem is difficult to solve due to the non‐convex objective function and coupled variables. Thus, an alternating optimization based algorithm is proposed by exploiting the semidefinite relaxation and bisection search techniques. Simulation results show that time division multiple access can achieve lower AoI by exploiting the time‐selective passive beamforming of IRS for maximizing the signal to noise ratio of each device consecutively. Moreover, it also shows that as the length of information bits becomes sufficiently large as compared to the available bandwidth, the proposed frequency division multiple access transmission scheme becomes more favourable due to more flexible power allocation.

Lamb waves-based PCF-DMA: An anti-interference synchronous independent data transmission scheme for multiple cross-space users

Due to the high cost and safety risk brought about by wire penetration within the aerospace and underwater structure, reliable wireless cross-space multiple access transmission techniques become highly necessary. Lamb waves data transmission is recognized as a feasible solution, since it utilizes the solid structures as the transmission medium without being affected by electromagnetic radiation. However, in the case of synchronous transmission of multiple users, the aggravation of inter-access interference would severely weaken the reliability of the transmission system. Focusing on the issue of anti-interference synchronous independent data transmission for multiple cross-space users, this study proposes a Lamb waves-based pulse code frequency division multiple access (PCF-DMA) scheme. Firstly, a fast pulse position modulation strategy is established to improve the transmission rate. Considering the characteristics of the Lamb waves excitation pulses as the codeword, a PCF-DMA multiple access encoding method is designed. Secondly, by sparsely representing the Lamb waves physical transmission channel, a shift-invariant sparse deconvolution technology is proposed for decoding. Specially, to achieve reliable multiple access transmission with the PCF-DMA scheme, a normalized cross-correlation coefficient is used as the design criterion of the Lamb wave pulses. To validate these concepts, a three-user PCF-DMA data transmission system based on Lamb waves is built. The experimental results illustrate that the proposed design criterion can accurately predict the reliability of the multiple access transmission system. The bit error rate (BER) of the proposed PCF-DMA scheme is 30 % lower than that of conventional FDMA within a signal-to-noise ratio of −12 to 8 dB. Further, the influence factor analysis for the BER and communication rate are conducted. Finally, a synchronous independent data transmission for multiple cross-space users is achieved, with a maximum communication rate of 92.9 kbps per user and a BER below 0.17 %.

Modelling System Generation: Towards the New Model in Albania and SEE Countries

The electricity utility industry is undergoing rapid and irreversible changes resulting from volatile fuel costs, transmission access, less predictable load growth and a more complex regulatory environment. Due to the rising importance of renewable (and variable) energy sources, power systems are now more vulnerable to uncertainties and intermittent in supply. Hydropower plays an important role in the energy mix and power market, helping in providing base and peak load power as well as being the ‘fuel’ (water) not subject to fluctuations in the market; these paving the way toward a clean energy by 2030 and net-zero emissions by 2050 as part of de-carbonization agenda. All production and conversion processes in the energy sector require Water for nearly including fuel extraction and processing (fossil and nuclear fuels as well as biofuels) and electricity generation (thermoelectric, hydropower, and renewable technologies). This paper’s objective is to analyze cross-border trade in SEE through economic electricity exchange, while also exploring reasons for promoting Hydroelectricity. This is achieved through the following objectives: first, an overview is made of the available energy and economic data in the region; second, a model is developed for regional least cost expansion planning when allowing for cross-border trade. These aim to assess electricity supply and demand in the region with the purpose of making a comparative analysis regarding energy resource endowments.

Beamforming for the Successive Relaying-Based Cooperative Non-Orthogonal Multiple Access Transmission

In this paper, a set of cooperative non-orthogonal multiple access (NOMA) transmission schemes is proposed, in which two half-duplex relaying user terminals (UTs) successively deliver the AP signals toward two NOMA UTs. The successive relaying (SR) of two HD relays emulates the full-duplex (FD) relaying transmission such that the whole transmission of one data block is finished in one time slot. Different from FD relaying, where the removal of self-interference (SI) at the relay is challenging, the SR is suffering from cross-relay interference (CRI) between the two HD relays and the handling of this CRI is the key technical challenge. This CRI suppression is implemented by beamforming with multiple antennas at the relaying UTs, while the beamforming also does the role of maximizing the NOMA transmission efficiency. Two beamforming schemes are proposed, where the first method employs semi-definite relaxation (SDR) with four dimensional (4-D) search. Here, the four dimensions come from the four parameters reflecting the CRI levels at the relaying UTs and signal strengths at the NOMA UTs. This scheme alternates until the 4-D search range is reduced and the sum throughput rate saturates. The second method is computationally simpler than the first one since it avoids the SDR and alternation, and it finds the beamformer set in one shot calculation. Both schemes rely on zero forcing of the CRI. These two schemes along with the HDR relay-based cooperative NOMA scheme are compared in the numerical experiments, and the results exhibit their pros and cons in several aspects.

Multiple-Antenna Aided Aeronautical Communications in Air-Ground Integrated Networks: Channel Estimation, Reliable Transmission, and Multiple Access

To provide seamless coverage during all flight phases, aeronautical communications systems (ACS) have to integrate space-based, air-based, as well as ground-based platforms to formulate aviation-oriented space-air-ground integrated networks (SAGINs). In continental areas, L-band aeronautical broadband communications (ABC) are gaining popularity for supporting air traffic management (ATM) modernization. However, L-band ABC faces the challenges of spectrum congestion and severe interference due to the legacy systems. To circumvent these, we propose a novel multiple-antenna aided L-band ABC paradigm to tackle the key issues of reliable and high-rate air-to-ground (A2G) transmissions. Specifically, we first introduce the development roadmap of the ABC. Furthermore, we discuss the peculiarities of the L-band ABC propagation environment and the distinctive challenges of the associated multiple-antenna techniques. To overcome these challenges, we propose an advanced multiple-antenna assisted L-band ABC paradigm from the perspective of channel estimation, reliable transmission, and multiple access. Finally, we shed light on the compelling research directions of the aviation component of SAGINs.

DeepMA: End-to-End Deep Multiple Access for Wireless Image Transmission in Semantic Communication

DeepMA: End-to-End Deep Multiple Access for Wireless Image Transmission in Semantic Communication

Joint Trajectory Design and Resource Optimization in UAV-Assisted Caching-Enabled Networks with Finite Blocklength Transmissions

In this study, we design and analyze a reliability-oriented downlink wireless network assisted by unmanned aerial vehicles (UAVs). This network employs non-orthogonal multiple access (NOMA) transmission and finite blocklength (FBL) codes. In the network, ground user equipments (GUEs) request content from a remote base station (BS), and there are no direct connections between the BS and the GUEs. To address this, we employ a UAV with a limited caching capacity to assist the BS in completing the communication. The UAV can either request uncached content from the BS and then serve the GUEs or directly transmit cached content to the GUEs. In this paper, we first introduce the decoding error rate within the FBL regime and explore caching policies for the UAV. Subsequently, we formulate an optimization problem aimed at minimizing the average maximum end-to-end decoding error rate across all GUEs while considering the coding length and maximum UAV transmission power constraints. We propose a two-step alternating optimization scheme embedded within a deep deterministic policy gradient (DDPG) algorithm to jointly determine the UAV trajectory and transmission power allocations, as well as blocklength of downloading phase, and our numerical results show that the combined learning-optimization algorithm efficiently addresses the considered problem. In particular, it is shown that a well-designed UAV trajectory, relaxing the FBL constraint, increasing the cache size, and providing a higher UAV transmission power budget all lead to improved performance.

Dynamic Transmission and Delay Optimization Random Access for Reduced Power Consumption

Dynamic Transmission and Delay Optimization Random Access for Reduced Power Consumption

Secure Rate-Splitting Multiple Access Transmissions in LMS Systems

Secure Rate-Splitting Multiple Access Transmissions in LMS Systems

PM1, PM2.5 and PM10 size fraction distribution under steady-state conditions in a walk-in type 222Rn calibration chamber facility.

Attachment of 222Rn progenies, upon their formation, to the atmospheric aerosols and inhalation of these radioactive aerosols causes inhalation dose to the human being. Aerosols have the characteristics of small particle size, long-time suspension and long-distance transmission and easy access to the deep respiratory tract. Aerosols are responsible for viral infection risk such as the recent worldwide pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2, or COVID-19). Understanding the formation and behaviour of aerosols in a confined environment in various human habitations is essential to combat such detrimental exposures. Experiments have been performed to study the distribution of aerosol size fractions in the walk-in type 222Rn calibration chamber. The real-time applied particle technology monitors (APT-Maxima stationary monitors) were used for the simultaneous measurements of PM1, PM2.5, and PM10 size fractions. The variation of the mass densities (μgm-3) of different size fractions at different positions inside the chamber was monitored by placing APTs. The PM1, PM2.5, and PM10 sizes fractions were distributed homogeneously within the chamber volume and the concentration ratios of these fractions were 1:1.5:1.6 for concentration values of < 1500μgm-3, and 1:7:9 for the concentration values of > 1500μgm-3.

Diffusion-assisted quantum noise stream cipher for physical layer security in UFMC

Universal filtered multicarrier (UFMC) is a promising multicarrier technologies due to its ability to suppress inter symbol interference, increase frequency band utilization and provide flexible adaptation. However, it is vulnerable to illegal eavesdropping in the point-to-multipoint access transmission. Quantum noise stream cipher (QNSC), a classical physical layer encryption scheme, is inherent matched with the UFMC system. However, its security mainly depends on the length of the basis states, which is limited by the performance of commercial high-speed digital-to-analog converters (DACs). In this work, we propose a diffusion-assisted quantum noise stream cipher (DA-QNSC) scheme to enhance the security. Here, we introduce artificial noise generated by hyperchaotic system to pseudo expand the distribution of quantum noise, which will make it more difficult for eavesdroppers to crack plaintext information violently. We experimentally demonstrate the encrypted 16/4096-QAM, 16/16384-QAM, 16/65536-QAM DA-QNSC signals over 30-km standard single mode fiber (SSMF) transmission. Compared to the conventional QNSC systems, the proposed method achieves a 3.6 times improvement in the security with the same DAC resolution and has negligible impact on bit error ratio (BER) performance. For the 16/65536-QAM signal, the number of masked symbols (NMS) are increased from 910 to 3270.

Incentive Oriented Two-Tier Task Offloading Scheme in Marine Edge Computing Networks: A Hybrid Stackelberg-Auction Game Approach

With the increasing exploration of marine resources, various marine wireless devices have been rapidly deployed for different marine applications such as marine navigation, ocean environment monitoring, and seabed resource exploitation. However, due to long transmission delay and low data rate between marine wireless devices and the cloud, it is challenging to satisfy the service requirements of computing-intensive and delay-sensitive tasks. By migrating computing resources from cloud to the near side of ocean, the paradigm of marine edge computing networks, which integrates communication and computation capacities in marine wireless devices, is expected to support a variety of marine tasks (e.g., data collection, monitoring and processing) with low delay and high data rate. However, considering the rationality and selfishness of marine wireless devices and their limited computing-capacity, how to motivate marine wireless devices to conduct task processing becomes an important problem for improving computing efficiency. To address this issue, in this paper, we propose an incentive oriented two-tier task offloading scheme for marine edge computing networks via hybrid Stackelberg-auction game approach, with the objective of improving the offloading efficiency and maximizing marine wireless devices’ utilities. Specifically, for underwater acoustic transmission tier, we exploit multi-access task offloading scheme, in which underwater wireless sensor (UWS) uploads its workloads to an unmanned underwater vehicle (UUV) and a sea surface sink node (SN) via non-orthogonal multiple access (NOMA) transmission. We formulate the utility of each party and model the task offloading process among UWS, UUV and SN as a Stackelberg game to optimize the UWS’s offloading strategy, UUV’s and SN’s price strategies. For radio frequency transmission tier, SN can offload its partial workloads to an unmanned aerial vehicle (UAV) via frequency division multiple access (FDMA) transmission. We provide their utilities and model the offloading process between a SN and a UAV as a double auction game to optimize their bidding strategies. Extensive simulation results are provided to validate the performance of the proposed scheme. Numerical results demonstrate that the proposed algorithms can obtain the optimal solutions and increase the utilities for marine wireless devices.

Balancing the Data Transmission and Random Access Phases in 6G mMTC Radio Technologies

Balancing the Data Transmission and Random Access Phases in 6G mMTC Radio Technologies

Semi-Federated Learning: Convergence Analysis and Optimization of a Hybrid Learning Framework

Under the organization of the base station (BS), wireless federated learning (FL) enables collaborative model training among multiple devices. However, the BS is merely responsible for aggregating local updates during the training process, which incurs a waste of the computational resource at the BS. To tackle this issue, we propose a semi-federated learning (SemiFL) paradigm to leverage the computing capabilities of both the BS and devices for a hybrid implementation of centralized learning (CL) and FL. Specifically, each device sends both local gradients and data samples to the BS for training a shared global model. To improve communication efficiency over the same time-frequency resources, we integrate over-the-air computation for aggregation and non-orthogonal multiple access for transmission by designing a novel transceiver structure. To gain deep insights, we conduct convergence analysis by deriving a closed-form optimality gap for SemiFL and extend the result to two extra cases. In the first case, the BS uses all accumulated data samples to calculate the CL gradient, while a decreasing learning rate is adopted in the second case. Our analytical results capture the destructive effect of wireless communication and show that both FL and CL are special cases of SemiFL. Then, we formulate a non-convex problem to reduce the optimality gap by jointly optimizing the transmit power and receive beamformers. Accordingly, we propose a two-stage algorithm to solve this intractable problem, in which we provide the closed-form solutions to the beamformers. Extensive simulation results on two real-world datasets corroborate our theoretical analysis, and show that the proposed SemiFL outperforms conventional FL and achieves 3.2% accuracy gain on the MNIST dataset compared to state-of-the-art benchmarks.

Rate Splitting-Based Nonorthogonal Multiple Access Transmission in Satellite– Terrestrial Relay Networks

Rate Splitting-Based Nonorthogonal Multiple Access Transmission in Satellite– Terrestrial Relay Networks