Physical Layer Techniques Research Articles

A lossless quantization approach for physical-layer key generation in vehicular ad hoc networks based on received signal strength

Vehicular Ad Hoc Networks (VANETs) provide various benefits and play a crucial role in improving efficiency and ensuring human safety across different applications. However, these advantages also give rise to security challenges and privacy concerns, necessitating a thorough examination of security attacks. Current key generation schemes, particularly those based on the Physical-Layer Model (PLM), face limitations such as low key generation rates and inadequate randomness. This paper introduces an innovative key generation method that utilizes adaptive physical-layer techniques and lossless quantization. The method involves an eight-level quantization process, which enables precise granularity and adaptive selection of quantization thresholds to tailor the computation of Received Signal Strength (RSS) measurements to individual needs. The adaptive approach ensures the retention of information within RSS measurements, resulting in reduced bit disagreement rates and enhanced randomness of the generated keys. Simulated evaluations demonstrate the effectiveness of the proposed method, showing superior performance in terms of bit generation, entropy, and secrecy rates, while also minimizing the occurrence of unnecessary measurements. This advancement holds significant promise for strengthening the security framework within VANETs.

An Efficient Spoofing Attack Detection Using Deep Learning Based Physical Layer Security Technique

Spoofing attack detection plays a crucial role in the defence field, involving critical and highly secured data processing. The accurate attack detection mechanism prevents unauthorised access to sensitive information, thereby protecting National security. Physical Layer Security (PLS) is a promising emerging technique that uses the wireless channel’s randomness to secure the communication network. The spoofing attack is one of the severe threats to the wireless network, where the attacker imitates the legitimate user to launch an attack against the network. This paper investigates the channel characteristics-based physical layer technique to detect spoofing attacks. For static radio environments, the two-sample independent hypothesis testing is used to identify the spoofing attack, showing an improvement in detection accuracy of 97 %. The attack detection problem is considered a Reinforcement Learning (RL) based classification problem for a challenging dynamic radio environment. It is simulated using the actor-critic-based Deep Reinforcement Learning (DRL) technique with the help of the Reformed Deep Deterministic Policy Gradient (Re-DDPG) algorithm. The simulated results show that the proposed method performs better than the existing strategies and achieves a Receiver Operating Characteristics (ROC) value of 0.96. The detection accuracy of the proposed method can reach up to 98 %, with precision and recall of about 98 % and 99 %, respectively.

Signal transmission diversity based successive interference cancellation-slotted aloha

Efficient medium access protocols are crucial in leveraging the advancement in the physical layer techniques that have been proposed for the next-generation wireless networks. However, collisions among data packets in random access protocols reduce channel efficiency and hence the throughput. In this paper, we propose a MAC protocol based on both the signal transmission diversity and Successive interference cancellation (SIC) to improve the throughput. In the proposed Medium Access Control (MAC) protocol, the receiver receives two sets of signals from the transmitters over two uncorrelated time slots. Inter slot SIC is first carried out at the receiver over two independent sets of received interfered signals. Signals are decoded by canceling those signals that have already been decoded in one set from the other set. Closed-form expressions for the packet decoding probability, system throughput, average packet transmission delay, and energy efficiency have been derived by considering order statistics of received signal power. Analytical results are validated against simulation. Maximum achievable throughput of the proposed scheme is shown to be four times that of slotted Aloha and twice that of a slotted Aloha with SIC.

A Federated Learning-Based Resource Allocation Scheme for Relaying-Assisted Communications in Multicellular Next Generation Network Topologies

Growing and diverse user needs, along with the need for continuous access with minimal delay in densely populated machine-type networks, have led to a significant overhaul of modern mobile communication systems. Within this realm, the integration of advanced physical layer techniques such as relaying-assisted transmission in beyond fifth-generation (B5G) networks aims to not only enhance network performance but also extend coverage across multicellular orientations. However, in cellular environments, the increased interference levels and the complex channel representations introduce a notable rise in the computational complexity associated with radio resource management (RRM) tasks. Machine and deep learning (ML/DL) have been proposed as an efficient way to support the enhanced user demands in densely populated environments since ML/DL models can relax the traffic load that is associated with RRM tasks. There is, however, in these solutions the need for distributed execution of training tasks to accelerate the decision-making process in RRM tasks. For this purpose, federated learning (FL) schemes are considered a promising field of research for next-generation (NG) networks’ RRM. This paper proposes an FL approach to tackle the joint relay node (RN) selection and resource allocation problem subject to power management constraints when in B5G networks. The optimization objective of this approach is to jointly elevate energy (EE) and spectral efficiency (SE) levels. The performance of the proposed approach is evaluated for various relaying-assisted transmission topologies and through comparison with other state-of-the-art ones (both ML and non-ML). In particular, the total system energy efficiency (EE) and spectral efficiency (SE) can be improved by up to approximately 10–20% compared to a state-of-the-art centralized ML scheme. Moreover, achieved accuracy can be improved by up to 10% compared to state-of-the-art non-ML solutions, while training time is reduced by approximately 50%.

Fundamental Detection Probability vs. Achievable Rate Tradeoff in Integrated Sensing and Communication Systems

Integrating sensing functionalities is envisioned as a distinguishing feature of next-generation mobile networks, which has given rise to the development of a novel enabling technology – <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Integrated Sensing and Communication (ISAC)</i> . Portraying the theoretical performance bounds of ISAC systems is fundamentally important to understand how sensing and communication functionalities interact (e.g., competitively or cooperatively) in terms of resource utilization, while revealing insights and guidelines for the development of effective physical-layer techniques. In this paper, we characterize the fundamental performance tradeoff between the detection probability for target monitoring and the user’s achievable rate in ISAC systems. To this end, we first discuss the achievable rate of the user under sensing-free and sensing-interfered communication scenarios. Furthermore, we derive closed-form expressions for the probability of false alarm (PFA) and the successful probability of detection (PD) for monitoring the target of interest, where we consider both communication-assisted and communication-interfered sensing scenarios. In addition, the effects of the unknown channel coefficient are also taken into account in our theoretical analysis. Based on our analytical results, we then carry out a comprehensive assessment of the performance tradeoff between sensing and communication functionalities. Specifically, we formulate a power allocation problem to minimize the transmit power at the base station (BS) under the constraints of ensuring a required PD for perception as well as the communication user’s quality of service requirement in terms of achievable rate. It indicates that, on the one hand, there exists an intrinsic tradeoff between sensing and communication performance under the mutual-interfered scenarios; On the other hand, with prior knowledge of the baseband waveform, these two functionalities might mutually assist each other to enhance the performance. Finally, simulation results corroborate the accuracy of our theoretical analysis and the effectiveness of the proposed power allocation solutions showing the advantages of the ISAC system over the conventional radar and communication coexistence counterpart.

Considerations, Advances, and Challenges Associated with the Use of Specific Emitter Identification in the Security of Internet of Things Deployments: A Survey

Initially introduced almost thirty years ago for the express purpose of providing electronic warfare systems the capabilities to detect, characterize, and identify radar emitters, Specific Emitter Identification (SEI) has recently received a lot of attention within the research community as a physical layer technique for securing Internet of Things (IoT) deployments. This attention is largely due to SEI’s demonstrated success in passively and uniquely identifying wireless emitters using traditional machine learning and the success of Deep Learning (DL) within the natural language processing and computer vision areas. SEI exploits distinct and unintentional features present within an emitter’s transmitted signals. These distinctive and unintentional features are attributed to slight manufacturing and assembly variations within and between the components, sub-systems, and systems comprising an emitter’s Radio Frequency (RF) front end. Although sufficient to facilitate SEI, these features do not hinder normal operations such as detection, channel estimation, timing, and demodulation. However, despite the plethora of SEI publications, it has remained largely a focus of academic endeavors, primarily focusing on proof-of-concept demonstration and little to no use in operational networks for various reasons. The focus of this survey is a review of SEI publications from the perspective of its use as a practical, effective, and usable IoT security mechanism; thus, we use IoT requirements and constraints (e.g., wireless standard, nature of their deployment) as a lens through which each reviewed paper is analyzed. Previous surveys have not taken such an approach and have only used IoT as motivation, a setting, or a context. In this survey, we consider operating conditions, SEI threats, SEI at scale, publicly available data sets, and SEI considerations that are dictated by the fact that it is to be employed by IoT devices or IoT infrastructure.

A Survey on Physical Layer Techniques and Challenges in Underwater Communication Systems

In the past decades, researchers/scientists have paid attention to the physical layer of underwater communications (UWCs) due to a variety of scientific, military, and civil tasks completed beneath water. This includes numerous activities critical for communication, such as survey and monitoring of oceans, rescue, and response to disasters under the sea. Till the end of the last decade, many review articles addressing the history and survey of UWC have been published which were mostly focused on underwater sensor networks (UWSN), routing protocols, and underwater optical communication (UWOC). This paper provides an overview of underwater acoustic (UWA) physical layer techniques including cyclic prefix orthogonal frequency division multiplexing (CP-OFDM), zero padding orthogonal frequency division multiplexing (ZP-OFDM), time-domain synchronization orthogonal frequency division multiplexing (TDS-OFDM), multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM), generalized frequency division multiplexing (GFDM), unfiltered orthogonal frequency division multiplexing (UF-OFDM), continuous phase modulation orthogonal frequency division multiplexing (CPM-OFDM), filter bank multicarrier (FBMC) modulation, MIMO, spatial modulation technologies (SMTs), and orthogonal frequency division multiplexing index modulation (OFDM-IM). Additionally, this paper provides a comprehensive review of UWA channel modeling problems and challenges, such as transmission loss, propagation delay, signal-to-noise ratio (SNR) and distance, multipath effect, ambient noise effect, delay spread, Doppler effect modeling, Doppler shift estimation. Further, modern technologies of the physical layer of UWC have been discussed. This study also discusses the different modulation technology in terms of spectral efficiency, computational complexity, date rate, bit error rate (BER), and energy efficiency along with their merits and demerits.

Hybridization of OFDMand Physical Layer Techniques for Information Security in Wireless System

Due to quest for high data rate, reliable and secure communication, this has motivated both wired and wireless network access service providers to deploy a next-generation network with ability to meet the required need. The use orthogonal frequency division multiplexing(OFDM) enables reliable transmission of various data traffic by optimizing subcarrier, power, and allocation of bits among different users. Traditionally, securing data in wireless system is always at the upper layer of open system interconnection(OSI) Model by using data encryption techniques. However, such techniques may not be acceptable for future decentralized networks due to their high complexity in implementation and computation. In this work, an OFDM IEEE 802.11a wireless system is used and physical layer encryption (PLE) schemes are implemented in securing the information transfer between two legitimate parties. In the simulation, the source data are encrypted by obfuscation with dummy data in between the encrypted data of which 52 subcarriers were considered of which 25 subcarriers are reserved for dummy data and 27 were for data. The simulation was conducted for four different modulation techniques i.e., BPSK, QPSK, 16 QAM, and 64 QAM. The result obtained shown that for all the modulation schemes, the key rate increases with an increase in the reserved subcarrier bits. Also ,the security level increased when substantial percentages of the subcarriers are reserved for dummy data

A Multi-Antenna Pilot Predistortion Scheme and Channel Estimation Algorithm for LTE-Based Terrestrial Broadcast System

Multi-Antenna technology is a physical layer technique widely used in mobile communication and terrestrial broadcast systems. For fully utilizing the antenna diversity, conventional Multi-Antenna pilots usually meet the characteristic of orthogonality in terms of the pilot arrangement to avoid inter-pilot interference between different transmitting antennas. However, the scheme with orthogonality leads to the doubling of the pilot overhead, which seriously reduces the transmission efficiency. The latest LTE-based terrestrial broadcast system, Further evolved Multimedia Broadcast Multicast Service (FeMBMS), is probably to adopt the Multi-Antenna technique in the future, but no corresponding pilot scheme has been provided. This paper proposes a novel pilot pre-distortion scheme and Channel Estimation (CHE) algorithm for FeMBMS. The pre-distortion scheme does not require the pilot on different antennas to meet the restriction of orthogonality, so to address the problem of pilot overhead doubling. Meanwhile, it deals with the issue of inter-pilot interference by converting the interference into the white noise spreading over the whole OFDM symbol. Furthermore, the proposed CHE algorithm effectively eliminates the whitened interference by utilizing the processing of DFT-based windowing and Iterative Interference Cancellation (IIC). Simulation shows that the pre-distortion scheme and CHE algorithm could provide a CHE performance with accuracy same or close to that of the orthogonality scheme while significantly improving the transmission efficiency.

Developing NOMA to Next Generation Multiple Access: Future Vision and Research Opportunities

As a prominent member of the Next Generation Multiple Access (NGMA) family, Non-Orthogonal Multiple Access (NOMA) has been recognized as a promising multiple access candidate for the Sixth-Generation (6G) networks. This article focuses on applying NOMA in 6G networks, with an emphasis on proposing the so-called One Basic Principle Plus Four New concept. Successive Interference Cancellation (SIC) importance becomes evident, starting with the basic NOMA principle. In particular, this article discusses the advantages and drawbacks of channel-state-information-based SIC and quality-of-service-based-SIC. In addition, it explores applying NOMA to meet the new 6G performance requirements, especially for massive connectivity. Further, this article considers integrating NOMA with new physical layer techniques, followed by introducing new application scenarios for NOMA toward 6G. Finally, the article investigates applying machine learning in NOMA networks, ushering in the machine learning empowered NGMA era.

Physical Layer Famous Waveform Approaches for Fifth Generation Cellular Network

Many developments are taking place in the network to meet the 5G (Fifth generation) cellular network requirements; one of the very important research areas is the physical layer architecture and techniques. Studies related to the spectrum efficiency maximization indicate that the 5G air interface technology will also need to be flexible and capable of mapping various services to the best suitable combinations of frequency and radio resources.This paper investigates the physical layer waveform approaches as part of enhanced mobile broadband use case in 5G, and finds the Cyclic-Prefix Orthogonal Frequency Division Multiplexing (CP-OFDM) as a suitable approach by comparing performance parameters where the filtering and windowing can result in degradation of the quality of the signal which is measured via Error Vector Magnitude(EVM). It also attempts to enhance the down link performance between the base station and user equipment by using power amplifier clipping technique, while modelling the downlink channel by implementing channel coding, synchronization signal burst generation, different subcarrier spacing and frame numerologies for different propagation channel and different waveform approaches.

PLC Physical Layer Link Identification with Imperfect Channel State Information

This paper proposes an accurate physical layer technique to uniquely identify the links of a power line communication network. First, the power line communications (PLC) multipath channel characterization is presented and detailed. Then, a multipath channel delay detection technique is introduced to provide an accurate physical layer identification (PL ID) for the considered PLC links. The accuracy and efficiency are tested by evaluating the successful path detection probability (SPDP) in a simulated scenario under both perfect and imperfect channel state information conditions. The results confirm the advantages of the proposed scheme. Indeed, for a common PLC noise power around 90 dBuV, the provided accuracy reaches ≈90%, while for a noise power below 80 dBuV, the accuracy plateaus at 100%. Overall, the low complexity of the proposed approach and its staggering performance results pave the way for further possible applications in both the PLC and the security domain.

Detection and Blind Channel Estimation for UAV-Aided Wireless Sensor Networks in Smart Cities Under Mobile Jamming Attack

Unmanned aerial vehicles (UAVs) can be integrated into wireless sensor networks (WSNs) for smart city applications in several ways. Among them, a UAV can be employed as a relay in a "store-carry and forward" fashion by uploading data from ground sensors and metering devices and, then, downloading it to a central unit. However, both the uploading and downloading phases can be prone to potential threats and attacks. As a legacy from traditional wireless networks, the jamming attack is still one of the major and serious threats to UAV-aided communications, especially when also the jammer is mobile, e.g., it is mounted on a UAV or inside a terrestrial vehicle. In this paper, we investigate anti-jamming communications for UAV-aided WSNs operating over doubly-selective channels in the downloading phase. In such a scenario, the signals transmitted by the UAV and the malicious mobile jammer undergo both time dispersion due to multipath propagation effects and frequency dispersion caused by their mobility. To suppress high-power jamming signals, we propose a blind physical-layer technique that jointly detects the UAV and jammer symbols through serial disturbance cancellation based on symbol-level post-sorting of the detector output. Amplitudes, phases, time delays, and Doppler shifts - required to implement the proposed detection strategy - are blindly estimated from data through the use of algorithms that exploit the almost-cyclostationarity properties of the received signal and the detailed structure of multicarrier modulation format. Simulation results corroborate the anti-jamming capabilities of the proposed method, for different mobility scenarios of the jammer.

Rate-Splitting Multiple Access for Multi-Antenna Downlink Communication Systems: Spectral and Energy Efficiency Tradeoff

Rate-splitting (RS) has recently been recognized as a promising physical-layer technique for multi-antenna broadcast channels (BC). Due to its ability to partially decode the interference and partially treat the remaining interference as noise, RS is an enabler for a powerful multiple access, namely rate-splitting multiple access (RSMA), that has been shown to achieve higher spectral efficiency (SE) and energy efficiency (EE) than both space division multiple access (SDMA) and non-orthogonal multiple access (NOMA) in a wide range of user deployments and network loads. As SE maximization and EE maximization are two conflicting objectives in the moderate and high signal-to-noise ratio (SNR) regimes, the study of the tradeoff between the two criteria is of particular interest. In this work, we address the SE-EE tradeoff by studying the joint SE and EE maximization problem of RSMA in multiple input single output (MISO) BC with rate-dependent circuit power consumption at the transmitter. To tackle the challenges coming from multiple objective functions and rate-dependent circuit power consumption, we first propose two models to transform the original problem into two single-objective problems, namely, weighted-sum method and weighted-power method. A low-complexity algorithm with closed-form solution is proposed to solve each single-objective problem in the two-user system. For the generalized <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> -user system, a successive convex approximation (SCA)-based algorithm is then proposed to optimize the precoders of each transformed problem. Numerical results show that our algorithm converges much faster than existing algorithms. In addition, the performance of RSMA is superior to or equal to SDMA and NOMA in terms of SE, EE and their tradeoff.

A Computationally Efficient Gradient Algorithm for Downlink Training Sequence Optimization in FDD Massive MIMO Systems

Future wireless networks will require advance physical-layer techniques to meet the requirements of Internet of Everything (IoE) applications and massive communication systems. To this end, a massive MIMO (m-MIMO) system is to date considered one of the key technologies for future wireless networks. This is due to the capability of m-MIMO to bring a significant improvement in the spectral efficiency and energy efficiency. However, designing an efficient downlink (DL) training sequence for fast channel state information (CSI) estimation, i.e., with limited coherence time, in a frequency division duplex (FDD) m-MIMO system when users exhibit different correlation patterns, i.e., span distinct channel covariance matrices, is to date very challenging. Although advanced iterative algorithms have been developed to address this challenge, they exhibit slow convergence speed and thus deliver high latency and computational complexity. To overcome this challenge, we propose a computationally efficient conjugate gradient-descent (CGD) algorithm based on the Riemannian manifold in order to optimize the DL training sequence at base station (BS), while improving the convergence rate to provide a fast CSI estimation for an FDD m-MIMO system. To this end, the sum rate and the computational complexity performances of the proposed training solution are compared with the state-of-the-art iterative algorithms. The results show that the proposed training solution maximizes the achievable sum rate performance, while delivering a lower overall computational complexity owing to a faster convergence rate in comparison to the state-of-the-art iterative algorithms.

Multiuser MIMO Opportunistic Beamforming Communications: State-of-the-Art and Perspectives

Opportunistic beamforming (OBF) is a promising technique in multiuser multiple-input-multiple-output (MIMO) communications, which attracts many attentions. Because of opportunistic precoding and multiuser selection, OBF can achieve high spectrum efficiency under the limited channel status information (CSI) condition with low complexity. Therefore, in this article, we introduce the state-of-the-art researches of multiuser MIMO OBF, including fundamental architecture, physical layer techniques and multiple access schemes. Due to the complex user scheduling strategy, artificial intelligence OBF systems are proposed, which can simply and adaptively modulate the user scheduling strategy. Moreover, in order to provide the communication and Computing services with low latency and high reliability for users, OBF-based computing systems are presented. Then, some open issues are given for the future researches. Finally, we conclude this article.

Safeguarding Non-Orthogonal Multiple Access with Physical Layer Techniques

This article clarifies pivotal security issues in the context of non-orthogonal multiple access (NOMA) technology and presents potential methodologies to address them at the physical layer. Specifically, we first clarify the channel conditions for an external eavesdropper to use successive interference cancellation (SIC) for cancelling interference, which has recently been considered in the literature of physical layer security for NOMA. We then explicitly demonstrate the advantages and drawbacks of using NOMA to achieve wireless communication security; that is, NOMA improves the security of a strong user, but reduces the security of a weak user. Finally, we discuss a strategy to protect the confidentiality of a weak user's information from a strong user, while still allowing the latter to seek SIC for harnessing the benefits of NOMA. Research challenges and future works along the aforementioned three different aspects of security issues in NOMA are presented in this article.

LoRaWAN Physical Layer-Based Attacks and Countermeasures, A Review.

As LoRaWAN is one of the most popular long-range wireless protocols among low-power IoT applications, more and more focus is shifting towards security. In particular, physical layer topics become relevant to improve the security of LoRaWAN nodes, which are often limited in terms of computational power and communication resources. To this end, e.g., detection methods for wireless attacks improve the integrity and robustness of LoRaWAN access. Further, wireless physical layer techniques have potential to enhance key refreshment and device authentication. In this work, we aim to provide a comprehensive review of various vulnerabilities, countermeasures and security enhancing features concerning the LoRaWAN physical layer. Afterwards, we discuss the impact of the reviewed topics on LoRaWAN security and, subsequently, we identify research gaps as well as promising future research directions.

Evolution of NOMA Toward Next Generation Multiple Access (NGMA) for 6G

Due to the explosive growth in the number of wireless devices and diverse wireless services, such as virtual/augmented reality and Internet-of-Everything, next generation wireless networks face unprecedented challenges caused by heterogeneous data traffic, massive connectivity, and ultra-high bandwidth efficiency and ultra-low latency requirements. To address these challenges, advanced multiple access schemes are expected to be developed, namely next generation multiple access (NGMA), which are capable of supporting massive numbers of users in a more resource- and complexity-efficient manner than existing multiple access schemes. As the research on NGMA is in a very early stage, in this paper, we explore the evolution of NGMA with a particular focus on non-orthogonal multiple access (NOMA), i.e., the transition from NOMA to NGMA. In particular, we first review the fundamental capacity limits of NOMA, elaborate on the new requirements for NGMA, and discuss several possible candidate techniques. Moreover, given the high compatibility and flexibility of NOMA, we provide an overview of current research efforts on multi-antenna techniques for NOMA, promising future application scenarios of NOMA, and the interplay between NOMA and other emerging physical layer techniques. Furthermore, we discuss advanced mathematical tools for facilitating the design of NOMA communication systems, including conventional optimization approaches and new machine learning techniques. Next, we propose a unified framework for NGMA based on multiple antennas and NOMA, where both downlink and uplink transmissions are considered, thus setting the foundation for this emerging research area. Finally, several practical implementation challenges for NGMA are highlighted as motivation for future work.

Channel Impulse Response Multilevel Quantization for Power Line Communications

Physical layer security (PLS) has become a popular topic in the research community as a complement to traditional security schemes. Particularly, by taking advantage of the channel&#x2019;s symmetry, a robust ecosystem of security applications has developed in wireless communications. However, in power line communications (PLC), the general lack of channel symmetry has limited and hampered the development of physical layer techniques. In this paper, we address the cited constraint, by deriving a symmetric virtual channel impulse response (CIR) from the corresponding asymmetric PLC channel state information (CSI). In view of this, we propose a low-complexity and, to the best of our knowledge, the first CIR multilevel quantization algorithm that can be used in various PLC applications. While we contextualize our solution within the PLS domain, it has a wide applicability. Specifically, we start by analyzing the PLC channel path delays reciprocity, its relationship with topology changes, and its independence from all other power line characteristics. Then, the quality and viability of the proposed scheme are quantified, by comparing the bit mismatch rate (BMR) with its one-level quantization counterpart. The simulation results, under different topologies, confirm the performance of the proposed approach that can reduce the BMR by at least three orders of magnitude with respect to the one-level quantization, for noise levels below 90 dBuV. Finally, we conclude the paper by showing a few applications of the proposed solution and highlighting some future research directions.