Physically Research Articles

Clock synchronization based on pulse with propagation delay eliminated in wireless sensor networks

AbstractClock synchronization is indispensable for numerous applications of wireless sensor networks (WSNs). When no common reference clock is available, the nodes must employ distributed synchronization techniques. This paper proposes, a distributed pulse‐based clock synchronisation approach, wherein the propagation delay is eliminated through signal ping‐pongs between neighbouring nodes. Such an approach can jointly estimate the clock skew and offset without requiring any reference clock. The whole synchronization process is completed at the physical (PHY) layer, effectively avoiding the random delay caused by packet queuing and retransmission. Simulation results show that the proposed approach can achieve higher synchronization accuracy compared with other existing methods.

Traffic Load Learning Towards Early Detection of Intrusion in Industrial mMTC Networks

The fifth generation (5G) network offers a powerful infrastructure for Industrial IoT in that its support on massive machine-type communications (mMTC). Recently, grant-free (GF) access has been recognized as the promising new access approach for mMTC, however, it also introduces the potential risk. To timely discover intrusion, in this paper we propose a learning network by extracting traffic-load information from the states (success, collision, and idle) of access resources observed at media access control (MAC) and physical (PHY) layers. In particular, our learning network consists of three concatenated function modules, i.e., traffic-load estimation, traffic-load prediction, and intrusion identification. Moreover, our proposed learning network is able to identify two types of intrusion: false data dissemination and congestion attack. Simulation results indicate that the proposed scheme can effectively capture the number of active devices, provide reasonable prediction by using history records, and eventually, achieve more accurate detection compared with baseline approaches.

Seed dormancy diversity of the mangrove plant community in Sri Lanka to assist in direct seeding and seedling transplanting restoration

AbstractMangroves are one of the most important ecosystems in the world being found in the tropical–subtropical belt. Despite their significance, they have been highly disturbed due to many anthropogenic and natural causes. A significant effort has been made to restore mangroves around the world. However, a lack of information on the seed biology of mangrove species has impeded restoration. Thus, this study aimed to produce a seed dormancy profile for selected plant species of mangroves in Sri Lanka. This profile would allow restoration ecologists to better understand what kinds of dormancy are present, how to alleviate dormancy and how to best stimulate germination to generate seedlings for nursery stock or out-planting. Mature fruits/seeds were collected from coastal zone mangroves in Sri Lanka. Germination and imbibition of non-scarified and manually scarified seeds and embryo:seed length (E:S) ratio of fresh and radicle-emerged seeds were evaluated to assess the class of dormancy. Of the 30 species, seeds from 12 (40%) were non-dormant and 18 (60%) were dormant. Three dormancy classes [physiological (PD), physical (PY) and morphophysiological (MPD)] and presence of epicotyl dormancy were identified. Among species producing dormant seeds, most of them showed PD (44%). PY, MPD and presence of epicotyl dormancy were represented by 28, 17 and 11% of the species, respectively. These findings aid practitioners to craft strategies to effectively break dormancy and germinate seeds for conservation and restoration activities of mangroves.

Childhood Maltreatment in Patients Undergoing Bariatric Surgery: Implications for Weight Loss, Depression and Eating Behavior

We aimed to explore the relationships between childhood maltreatment and changes in weight, depressive symptoms and eating behavior post-bariatric surgery (BS). Participants (n = 111, 85% females) were evaluated pre-surgery, and at 6 months (6 M) and 12 months (12 M) post-BS. History of maltreatment was assessed at baseline (Childhood Trauma Questionnaire), and depressive symptoms (Beck Depression Inventory-II) and eating behavior (Dutch Eating Behavior Questionnaire) were assessed at all time points. Participants’ mean age and median BMI were 45.1 ± 11.7 years and 46.7 (IQR 42.4–51.9) kg/m2, respectively. Histories of emotional (EA), physical (PA) and sexual abuse (SA) and emotional (EN) and physical (PN) neglect were reported by 47.7%, 25.2%, 39.6%, 51.4% and 40.5%, respectively, with 78.4% reporting at least one form of maltreatment. Changes in weight and depressive symptoms were not different between patients with vs. without a history of maltreatment. However, those with vs. without SA demonstrated limited changes in emotional eating (EE) at 12 M, while those without showed improvements. Conversely, patients with vs. without EN showed greater improvements in external eating (ExE) at 6 M, but differences were no longer observed by 12 M. Results indicate that histories of SA and EN are associated with changes in eating behaviors post-BS and have implications for assessment, monitoring and potential intervention development.

Investigation of reconfigurable hardware platformsfor 5Gprotocol stack functions acceleration

Open RAN and 5G are two key technologies designed to qualitatively improve network infrastructure and provide greater flex-ibility and efficiency to mobile operators and users. 5G creates new capabilities for high-speed Internet, Internet of Things, telemedi-cine and many other applications, while Open RAN enables open and standardized network architectures, which reduces cost and risk for operators and promotes innovations. Given the growing number of users and data volumes, the purely software implementa-tion of certain functions of the 5G protocol, and especially computationally complex ones, requires significant computer resources and energy.These, for example, arelow-density parity-check (LDPC)coding,FFTandiFFT algorithms on physical (PHY)layer, and NEA and NIA security algorithms on Packet Data Convergence Protocol (PDCP)layer. Therefore, one of the activity areas in the development of means for 5G systems isthe hardware acceleration of such functions execution, which provides the possibility of processing large volumes of data in real time and with high efficiency. The high-performance hardware basis for implementing these functions today is field-programmable gate array(FPGA)integrated circuits.Along with this, the efficiency of the 5G protocol stack functions hardware acceleration depends significantly on the size of the data packets transmitted to the hardware accelerator. As ex-perience shows, for certain types of architecture of computer systems with accelerators, the acceleration value can take even a nega-tive value. This necessitates the search for alternative architectural solutions for the implementation of such systems.In this article the approaches for hardware acceleration using reconfigurable FPGA-based computing components are explored, their comparative analysis is performed, and architectural alternatives are evaluated for the implementation of a computing platform to perform the functions ofthe 5G protocol stack with hardware acceleration of PHY and medium access control(MAC)layers functions.

Power Division for Green Cellular Network

As the trend of Internet of Everything becomes a reality, there have been massive wireless devices all over the world, each of which contributes to the huge CO2 emission for our earth every-time. To protect environment, green communications has been a key technology in 5G system, driven by today's economical and ecological requirements. In this article, the power division technique is introduced in the view of green communications. When compared with time and frequency division solutions, we show that the power division could save distinct energy/power across physical(PHY), medium access control (MAC), and network (NET) layers. Additionally, it not only alleviates the strict requirement of powerful power amplify in user equipment but also reduces the computational complexity of power control. Accordingly, the power division has the potential to provide a new direction for green communications.

The mitigating role of physical activities on emotions is gender-specific: An experience during “lenient” COVID-19 prevention protocols

The researchers examined emotional status subsequent to changes in physical (PA) and sedentary (SA) activities during “lenient” COVID-19 prevention protocols that allowed being outdoors. Emotions, PA, and SA were collected from 272 women and 145 men in Qatar. The researchers showed a decrease (p < 0.05) in PA and an increase (p < 0.05) in SA participation during the pandemic. These alterations were different (p < 0.05) between genders and associated (p < 0.05) with emotional status during the COVID-19-induced confinement, but only (p < 0.05) in men. The “mitigating” role of PA for the adverse emotional effects of the pandemic is demonstrated, especially among men. Therefore, “lenient” regulations should be considered around the globe during future pandemics for adequate PA and emotional wellbeing. However, plans should incorporate additional tactics to PA to manage emotional status among women.

Analysis of the quality of life in the population living under post-war conditions

Introduction. Biomedical assessment of the quality of life (QOL) is a methodological tool that allows identifying the degree of human adaptation to changing functional states and environmental factors. For the first time we tried to analyze the population’s QOL in post-war conditions. Methods and materials. The study was managed within the framework of scientific project over 2021-2022 (a year after the end of the military events in the region), one hundred eighty Nagorno-Karabakh 16 to 60 years residents of both genders have been tested using a modified version of SF-36 questionnaire. Results. The average values of the population’s QOL indicators for the SF-36 questionnaire scales varies from 59.5 (the vital activity and mental health) to 84.2 points (physical functioning). Gender-age features of the QOL level declined the role-playing emotional functioning in females and a diminished the values of general health, vitality and social functioning by the second adulthood. Having grouped all the scales into two indicators - the physical (PH) and mental (MH) components of health, the latter turned out to be lower than the values of the separate components of these elements. In general, the entire population had a low level of MH (43.7 points), compared with PH (49.7 points). Limitations. The study has age (youthful and middle), regional (Nagorno-Karabakh) and temporary (at the present stage) limitations. Conclusion. The obtained regional population QOL standards in the post-war conditions can be designated as the phenomenon of Nagorno-Karabakh, which can serve as a scientific and practical basis for further research.

Adaptive Preamble Embedding With MIMO to Support User-Defined Functionalities in WLANs

As the Wi-Fi technology transitions into its sixth generation (Wi-Fi 6), there is a growing consensus on the need to support security and coordination functions at the Physical (PHY) layer. In contrast to the costly approach of extending the PHY-layer header to support new functions (e.g., Spatial Reuse field in the Wi-Fi 6 frame), we propose to turn specific parts of the frame preamble into a reliable data field while maintaining its primary functions. Specifically, in this paper, we develop a scheme called <i>extensible preamble modulation (eP-Mod)</i> for 802.11n/ac/ax protocols that are built on multiple-input-multiple-output (MIMO) and orthogonal frequency-division multiplexing (OFDM). For each frame, <i>eP-Mod</i> can embed up to 144 user bits into the 802.11ac preamble of an <inline-formula><tex-math notation="LaTeX">$8\times 8$</tex-math></inline-formula> MIMO <inline-formula><tex-math notation="LaTeX">$40\;$</tex-math></inline-formula> MHz transmission. The proposed scheme is adaptive to channel conditions and enables several promising PHY-layer services, such as PHY-layer encryption and channel/device authentication, and PHY-layer signaling. At the same time, it allows legacy ( <i>eP-Mod</i> -unaware) devices to continue to process the received preamble as normal by guaranteeing that the proposed preamble waveforms satisfy the structural properties of a standardized preamble. Through numerical analysis, extensive simulations, and hardware experiments, we validate the practicality and reliability of <i>eP-Mod</i> .

Performance Analysis of IEEE 802.11p MAC with Considering Capture Effect under Nakagami-m Fading Channel in VANETs

Vehicular ad hoc networks (VANETs) have recently drawn a large amount of attention because of their enormous potential in road safety improvement and traffic management as well as infotainment service support. As the standard of medium access control (MAC) and physical (PHY) layers for VANETs, IEEE 802.11p has been proposed for more than a decade. Though performance analyses of IEEE 802.11p MAC have been performed, the existing analytical methods still need to be improved. In this paper, to assess the saturated throughput and the average packet delay of IEEE 802.11p MAC in VANETs, a two-dimensional (2-D) Markov model is introduced by considering the capture effect under Nakagami-m fading channel. Moreover, the closed-form expressions of successful transmission, collided transmission, saturated throughput, and average packet delay are carefully derived. Finally, the simulation results are demonstrated to verify the accuracy of the proposed analytical model, which also proves that this analytical model is more precise than the existing ones in terms of saturated throughput and average packet delay.

Effects of computer-based cognitive training combined with physical training for older adults with cognitive impairment: A four-arm randomized controlled trial.

Combined physical (PHY) and cognitive (COG) training in sequential (SEQ) and simultaneous (SIMUL) sessions may delay the progression of cognitive impairment. To date, no study has directly compared in older adults with cognitive impairment the effects of COG training, PHY training, SEQ motor-cognitive training and SIMUL motor-cognitve training on specific indices of cognitive performance and activities of daily living (ADL). The purpose of this study was to determine whether SEQ and SIMUL motor-cognitive training can improve treatment outcomes compared with PHY or COG training alone. We also aimed to compare the effects of SEQ versus SIMUL motor-cognitive training on cognitive functions and instrumental ADL (IADL) in older adults with cognitive impairment. A cluster randomized controlled trial was conducted. Eighty older adults with cognitive impairment were randomly assigned to COG, PHY, SEQ or SIMUL training groups. The intervention consisted of 90-min training sessions, totaling 36 sessions. Outcome measures were the Montreal Cognitive Assessment, three subtests of the Wechsler Memory Scale (WMS) and the Lawton IADL scale. Significant interaction effects between group and time were found in WMS-spatial span (p = 0.04) and WMS-word lists (p = 0.041). For WMS-spatial span, the SIMUL group showed outperformed the COG (p = 0.039), PHY (p = 0.010) and SEQ groups (p = 0.017). For WMS-word lists, the SEQ group improve more than COG (p = 0.013), PHY (p = 0.030) and SIMUL (p = 0.019) groups. No significant differences were found in IADL performance among four groups (p = 0.645). Our study showed SEQ and SIMUL motor-cognitive training led to more pronounced improvements in visuospatial working memory or verbal memory compared with isolated COG or PHY training for community-based older adults with cognitive impairment. For enhancing effects on IADL, we suggest the use of sensitive measurement tools and context-enriched cognitive training involving real-life task demands.

Reinforcement Learning-Based Physical Cross-Layer Security and Privacy in 6G

Sixth-generation (6G) cellular systems will have an inherent vulnerability to physical (PHY)-layer attacks and privacy leakage, due to the large-scale heterogeneous networks with booming time-sensitive applications. Important wireless techniques including non-orthogonal multiple access, mobile edge computing, millimeter-wave, massive multiple-input and multiple-output, visible light communication, terahertz, and intelligent reflecting surface can improve the spectrum efficiency and quality-of-service but will raise challenges for the 6G PHY and cross-layer security and privacy protection. Existing optimization based PHY and cross-layer security and privacy protection schemes such as the convex optimization method have to rely on accurate attack patterns and strategies and thus suffer from performance degradation in 6G systems that have shorter communication latency, more devices and higher spectrum efficiency than 5G. Reinforcement learning (RL) algorithms help wireless devices optimize their security policies to enhance the security performance in dynamic networks against smart attacks without depending on the attack model. Therefore, this article provides a comprehensive survey on the RL based 6G PHY cross-layer security and privacy protection. In this article, we investigate the potential attacks in 6G systems and discuss the PHY cross-layer security solutions. A brief overview of reinforcement learning algorithms is provided. Afterward, we review the RL based PHY-layer security and privacy protection and discuss how to apply RL algorithms in 6G security scenarios, especially focusing on the game with jammers, eavesdroppers, spoofers and inference attackers. The RL based security solutions for unmanned aerial vehicles (UAVs) and cross-layer scenarios are also reviewed. The future research directions are identified and the corresponding RL based potential solutions are discussed for 6G.

Millimeter-Wave Feasibility in 5G Backhaul: A Cross-Layer Analysis of Blockage Impact

The wireless backhaul has become a key enabler for 5G technology by presenting a cost-effective and scalable alternative to the typical fiber backhaul. WiGig protocols, such as IEEE 802.11ad and later IEEE 802.11ay, have been considered for backhaul connectivity of 5G mobile networks, thanks to the availability of high bandwidths capable of achieving fiber-like data rates. However, this band suffers from high propagation loss that can only be compensated using highly directional antennas, making mmWave links more susceptible to blockage and errors. Thus, to effectively evaluate the viability of WiGig-based technologies in wireless backhaul scenarios, it is crucial to characterize the impact of obstruction across the different network layers. This article presents an extensive measurement campaign and cross-layer analysis of physical (PHY), medium access control (MAC), and transport layers metrics measured for outdoor WiGig-based hardware submitted to short-term and long-term blockage. This study found that maintaining constant and higher modulation and coding schemes (MCSs) in long-term blocked channels may induce packet errors as high as 100%, round-trip-time (RTTs) that can be in the order of a few seconds, and packet losses as high as 90%. Even dynamically adjusting the MCS, the performance can be highly degraded. This effect was exacerbated in short-term links, as they suffered from more extreme MCS changes upon sudden obstructions. Temporary line of sight (LOS) obstruction was shown to cause maximum delays of half a second and a PER of around 20%; in more extreme cases, it has even led to temporary link failures.

Optimal Embedding of Heterogeneous RAN Slices for Secure and Technology-Agnostic RANaaS

A key challenge related to Radio Access Network (RAN) slicing is deciding how to efficiently map radio resources from the physical radio to realise RAN slices, known as the virtual wireless network embedding problem. To the best of our knowledge, this is the first paper to model and derive an analytical solution for embedding heterogeneous RAN slices with different waveforms, numerologies and Radio Access Technologies (RATs) with resources isolated down to the Physical (PHY) layer, ultimately enabling secure technology-agnostic RAN as a Service (RANaaS). First, we assess how current virtual wireless network embedding solutions model the allocation of radio resources to realise RAN slices. Then, we propose a graph-based model for embedding heterogeneous RAN slices that considers the guard bands required to ensure isolation in the frequency domain. This approach is transparent to the type and granularity of radio resources of each RAN slice, and can be extended to support RAN slices with new waveforms, numerologies and RATs. Next, we introduce a resource management optimisation problem solved at the Network Provider (NP) to determine the optimal embedding of RAN slices that maximises the total useful bandwidth occupied by tenants; and we propose three different heuristic algorithms to obtain solutions in near real-time. We compare their performance against the analytical solution using different metrics, and our results show that the best heuristic depends on the NP’s business model, e.g., using the Greedy Algorithm (GA) to increase resource utilisation or the Nearest Neighbour Algorithm (NNA) to increase the number of allocated RAN slices.

Performance Analyses of Uplink MU-OFDMA Hybrid Access MAC in IEEE 802.11ax WLANs

Future wireless local area networks (WLANs) are expected to have numerous stations (STAs) with diverse Quality of Service requirements. IEEE 802.11ax is the current WLAN standard proposed to meet these requirements. This article analyzes the uplink-multiuser-orthogonal frequency division multiple access-hybrid access (HA) mechanism of the 802.11ax system under error-prone channel conditions. We propose an enhanced Markov chain model for analyzing such a WLAN system. By solving the system model, we derive vital systems performance metrics, such as aggregate and per-STA throughput, random access (RA) capability packet loss probability, mean delay, jitter, fairness, and worst-case delay bounds. Our analysis also considers different physical (PHY) and medium access control (MAC) layer aspects, such as channel bandwidth, the number of resource units (RUs), packet aggregation feature, fading, path-loss, modulation and coding schemes (MCS), etc. Furthermore, we have studied the MCS link adaptation-based dynamic HA process where the RUs are dynamically adapted between scheduled access and RA mechanisms. Additionally, to capture the role of PHY and MAC layer parameters on multi-Basic service set scenarios, we have integrated the Markov chain-based modeling with the stochastic geometry-based model. Our analytical model has been validated against extensive simulations, and the tradeoff between the metrics is studied.

A Methodology for Abstracting the Physical Layer of Direct V2X Communications Technologies

Recent advancements in vehicle-to-everything (V2X) communications have greatly increased the flexibility of the physical (PHY) and medium access control (MAC) layers. This increases the complexity when investigating the system from a network perspective to evaluate the performance of the supported applications. Such flexibility, in fact, needs to be taken into account through a cross-layer approach, which might lead to challenging evaluation processes. As an accurate simulation of the signals appears unfeasible, a typical solution is to rely on simple models for incorporating the PHY layer of the supported technologies based on off-line measurements or accurate link-level simulations. Such data are, however, limited to a subset of possible configurations, and extending them to others is costly when not even impossible. The goal of this paper is to develop a new approach for modeling the PHY layer of V2X communications that can be extended to a wide range of configurations without leading to extensive measurement or simulation campaigns at the link layer. In particular, given a scenario and starting from results in terms of the packet error rate (PER) vs. signal-to-interference-plus-noise ratio (SINR) related to a subset of possible configurations, we first approximated the curves with step functions characterized by a given SINR threshold, and we then derived one parameter, called implementation loss, that was used to obtain the SINR threshold and evaluate the network performance under any configuration in the same scenario. The proposed methodology, leading to a good trade-off among the complexity, generality, and accuracy of the performance evaluation process, was validated through extensive simulations with both IEEE 802.11p and LTE-V2X sidelink technologies in various scenarios. The results first show that the curves can be effectively approximated by using an SINR threshold, with a value corresponding to 0.5 PER, and then demonstrate that the network-level outputs derived from the proposed approach are very close to those obtained with complete curves, despite not being restricted to a few possible configurations.

Adaptive chaotic map-based key extraction for efficient cross-layer authentication in VANETs

Vehicle-to-everything (V2X) communication is expected to offer users available and ultra-reliable transmission, particularly for critical applications related to safety and autonomy. In this context, establishing a secure and resilient authentication process with low latency and high functionality may not be achieved using conventional cryptographic methodologies due to their significant computation costs. Recent research has focused on employing the physical (PHY) characteristics of wireless channels to develop efficient discrimination techniques to overcome the shortcomings of crypto-based authentication. This paper presents a cross-layer authentication scheme for multicarrier communication, leveraging the spatially/temporally correlated wireless channel features to facilitate key verification without exposing its secrecy. By mapping the time-stamped hashed key and masking it with channel phase responses, we create a PHY-layer signature, allowing for verifying the sender's identity while employing the correlated channel responses between subcarriers to verify messages' integrity. Furthermore, we developed a Diffie-Hellman secret key extraction algorithm that employs the computationally intractable problems of the Chebyshev chaotic mapping for channel probing. Thus, terminals can extract high entropy shared keys that can be used to create dynamic PHY-layer signatures, supporting forward and backward secrecy. We evaluated the scheme's security strength against active/passive attacks. Besides theoretical analysis, we designed a 3-Dimensional (3D) scattering Doppler emulator to investigate the scheme's performance at different speeds of a moving vehicle and signal-to-noise ratios (SNRs) for a realistic vehicular channel. Theoretical and hardware implementation analyses proved the capability of the proposed scheme to support high detection probability at SNR ≥ 0 dB and speed ≤ 45 m/s.

Nigerian indigenous hens show more discomfort-related behavior with visual separation than physical separation from their chicks: An exploratory study.

The Nigerian indigenous hens exhibit their full natural behavior repertoires, including maternal care. The strong maternal bond between the hen and her chicks is established prior to hatching. Maternal care of chickens is essential for both exotic and indigenous chickens. This study compared the behaviors of six hen-chick pairs in a physical (PHY) and visual (VIS) separation test for 10 min. All the six hen-chick pairs were subjected to PHY separation on the 8th day of post-hatch and a VIS separation on the 12th day of post-hatch. The PHY separation involved the use of a wire mesh to separate the hen from her chicks, while the VIS separation involved the use of a trampoline to separate the hen from her chicks. The hen's behavior was recorded during the 10-min separation period. Behaviors recorded included sitting, body shaking, pecking, movements toward the chicks, jumping, pacing, defecation, movements away from the chicks, and preening. We further grouped these nine behaviors into two categories: discomfort-related (pacing, movement toward chicks, body shaking, defecation, and jumping) and comfort-related (sitting, pecking, preening, and movement away from the chicks) behaviors. Before and after each separation, the hens were gently restrained, and a drop of blood was sampled from the wing vein to determine the blood glucose level. Their heart rate and eye temperature were also measured. A two-related samples test (Wilcoxon) was used to compare the behavior of the hens when subjected to the PHY and VIS separation. Eight out of the nine behaviors monitored did not differ between the separation types. However, the frequency of pacing by the hens was greater (z = -2.201, P = 0.028) in the VIS separation than in the PHY separation. Also, discomfort-related behavior was greater (t (5) = -2.717, P = 0.042) during the VIS separation than the PHY separation. Comfort-related behavior did not differ between the separation types. The change in eye temperature, heart rate, and blood glucose was similar in the two separation types. In conclusion, Nigerian indigenous hens displayed more discomfort-related behavior to the VIS separation from their chicks, but this was not associated with physiological responses indicative of stress.

Physical Layer Anonymous Precoding Design: From the Perspective of Anonymity Entropy

In the era of e-Health, privacy protection has become imperative in applications that carry personal and sensitive data. Departing from the data-perturbation based privacy-preserving techniques that reduce the fidelity of the disclosed data, in this paper we investigate anonymous communications, which mask the identity of the data sender while providing high data reliability. Focusing on the physical (PHY) layer, we first explore the break of privacy through a statistical attribute based sender detection (SD) from the receiver. Compared to the existing literature, this enables a much enhanced SD performance, especially when the users are equipped with different numbers of antennas. To counteract the advanced SD approach above, we formulate explicit anonymity constraints for the design of the anonymous precoder, which mask the sender’s PHY attributes that can be exploited by SD, while at the same time preserving the reliability of the data. Then, anonymity entropy-oriented precoders are proposed for different antenna configurations at the users, which adaptively construct a maximum number of aliases while obeying users’ signal-to-noise-ratio requirements for data accuracy. Simulation results demonstrate that the proposed anonymous precoders provide the highest level of anonymity entropy over the benchmarks, while achieving reasonable symbol error rate for the communication signal.

Autonomous Wireless Technology Detection in Seamless IoT Applications

The ever-increasing use of Internet of Things (IoT) devices results in the implementation of multiple wireless technologies that would not only cater their data rate requirements but also support various applications. To optimize the energy efficiency and security of the wireless transmission, it is imperative to identify the wireless technologies in various IoT implementations. Many of the existing approaches are based on measuring only the receiving signal strength indicator (RSSI). However, such approaches may not work well because of transmit power control and complex channel variations among different wireless technologies. In this article, we propose an autonomous wireless detection scheme that considers multiple distinguishable physical (PHY)-layer settings for real-time identification of wireless technologies for real-time applications. Specifically, the proposed scheme relies on the PHY-layer measurements of the targeted spectrum. Transmission settings, such as bandwidth, carrier frequency, and RSSI are estimated from the raw in-phase and quadrature-phase (I/Q) measurements. In addition, a symbol-level extraction scheme is implemented to extract unique features of modulation settings. These aforementioned features are applied to a machine learning process to identify the received wireless technologies. Compared with raw I/Q measurements, the extracted features are much simplified and, thus, the machine learning classifier can be designed with a simple structure for fast processing on IoT nodes. The proposed schemes are primarily evaluated theoretically, followed by implementing them on a USRP software-defined radio (SDR)-based hardware testbed. The evaluation results demonstrate high accuracy in the real-time detection of different wireless technologies for seamless IoT applications.