Scientific publications—2021

Year: 2021

Abstract: Automatic modulation classification (AMC) has been intriguing many researchers as it has many civil and military applications. Recently, cooperative AMC (CAMC) using a dynamic or ad hoc sensor network becomes appealing and challenging. As the unmanned aerial vehicles (UAVs) can facilitate three-dimensional communication/sensor network, we propose a novel CAMC approach based on a dynamic (ad hoc) UAV network. In our proposed new CAMC approach, the local classification decisions, which are made by spatially distributed nodes (UAVs) using our previously proposed graph-based modulation classifier, are gathered to reach an overall decision by a new weighted voting mechanism pertinent to individual received signal qualities. Note that the fusion center does not have to be a fixed UAV and it can be dynamically reassigned to any UAV within the same network in each sensing interval. The corresponding weights to individual UAVs are to be determined according to their cumulative states and the temporal discount factor. As a result, our proposed new CAMC approach can be fully distributed as no control center (or hub) is necessary. Besides, our new CAMC scheme can accommodate realistic ad hoc network variations to allow the existing UAVs to depart and/or the new UAVs to join in any sensing interval. Monte Carlo simulation results demonstrate that our proposed new CAMC scheme is quite robust and outperforms the existing CAMC method. © 2001-2012 IEEE.

Source title: IEEE Sensors Journal

DOI : 10.1109/JSEN.2021.3123048

Series Number: Volume 21, issue 24

Link: Novel Cooperative Automatic Modulation Classification Using Unmanned Aerial Vehicles

Year: 2021

Abstract:

Indoor air quality is a major issue for public health, particularly in northern communities. In this extreme environment, adequate ventilation is crucial to provide a healthier indoor environment, especially in airtight dwellings. The main objective of the study is to assess the impact of ventilation systems and their optimization on microbial communities in bioaerosols and dust in 54 dwellings in Nunavik. Dwellings with three ventilation strategies (without mechanical ventilators, with heat recovery ventilators, and with energy recovery ventilators) were investigated before and after optimization of the ventilation systems. Indoor environmental conditions (temperature, relative humidity) and microbiological parameters (total bacteria, Aspergillus/Penicillium, endotoxin, and microbial biodiversity) were measured. Dust samples were collected in closed face cassettes with a polycarbonate filter using a micro-vacuum while a volume of 20 m³ of bioaerosols were collected on filters using a SASS3100 (airflow of 300 L/min). In bioaerosols, the median number of copies was 4.01 × 10³ copies/m³ of air for total bacteria and 1.45 × 10¹ copies/m³ for Aspergillus/Penicillium. Median concentrations were 5.13 × 10⁴ copies/mg of dust, 5.07 × 10¹ copies/mg, 9.98 EU/mg for total bacteria, Aspergillus/Penicillium and endotoxin concentrations, respectively. The main microorganisms were associated with human occupancy such as skin-related bacteria or yeasts, regardless of the type of ventilation.

Source title: Indoor Air

DOI: 10.1111/ina.12857

Series Number: Volume 31, issue 6

Link: Indoor air quality assessment in dwellings with different ventilation strategies in Nunavik and impacts on bacterial and fungal microbiota

Year: 2021

Abstract: A novel method for confining the undesired radiation of the feed transition of a low-profile leaky-wave antenna (LWA) is demonstrated in this paper. The proposed design method uses novel tapered CPW transitions resulting in variation of the parasitic capacitance and electrical length of the feed. This leads to the reduction of the side-lobe level (SLL), which is dictated by the feed and the slotted sections of the antenna. The undesired radiation from the feed becomes crucial in the low-profile antenna in which the surface-mounted connector along feed transition is the only practical feeding mechanism. The key novelty of the proposed approach is the reduction of SLL by exclusively modifying the feed structure rather than the slotted radiation section. To validate the proposed approach, a modified compact feeding mechanism for LWA is designed. The antenna is realized based on the substrate integrated waveguide (SIW). The antenna's length, width, and height are 110 mm, 31 mm, and 0.5 mm, respectively. The operating frequency band was chosen as 26 to 30 GHz, covering an allocated 5G band. The measured peak realized gain and SLL are 6.1 dBi and  11.4 dB, respectively. An improvement of 5.7 dB in SLL compared to the conventional LWA was observed. The simple fabrication process and efficiency of the proposed method make it a viable approach for reducing the SLL of the low-profile antennas. Compactness, low SLL, and proper gain of the reported antenna make it a suitable candidate for 5G vehicle to everything (V2X) communications and mm-wave navigation systems. © 2021 Wiley Periodicals LLC

Source title: International Journal of RF and Microwave Computer-Aided Engineering

DOI : 10.1002/mmce.22607

Series Number: Vol. 31, issue 5

Link: A tapered CPW fed leaky-wave antenna based on substrate integrated waveguide with reduced side-lobe level

Year: 2021

Abstract: Nonpharmaceutical interventions remain the primary means of controlling severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) until vaccination coverage is sufficient to achieve herd immunity. We used anonymized smartphone mobility measures to quantify the mobility level needed to control SARS-CoV-2 (i.e., mobility threshold), and the difference relative to the observed mobility level (i.e., mobility gap). METHODS: We conducted a time-series study of the weekly incidence of SARSCoV-2 in Canada from Mar. 15, 2020, to Mar. 6, 2021. The outcome was weekly growth rate, defined as the ratio of cases in a given week versus the previous week. We evaluated the effects of average time spent outside the home in the previous 3 weeks using a log-normal regression model, accounting for province, week and mean temperature. We calculated the SARS-CoV-2 mobility threshold and gap. RESULTS: Across the 51-week study period, a total of 888 751 people were infected with SARS-CoV-2. Each 10% increase in the mobility gap was associated with a 25% increase in the SARS-CoV-2 weekly case growth rate (ratio 1.25, 95% confidence interval 1.20-1.29). Compared to the prepandemic baseline mobility of 100%, the mobility threshold was highest in the summer (69%; interquartile range [IQR] 67%-70%), and dropped to 54% in winter 2021 (IQR 52%-55%); a mobility gap was present in Canada from July 2020 until the last week of December 2020. INTERPRETATION: Mobility strongly and consistently predicts weekly case growth, and low levels of mobility are needed to control SARS-CoV-2 through spring 2021. Mobility measures from anonymized smartphone data can be used to guide provincial and regional loosening and tightening of physical distancing measures. © 2021 CMA Joule Inc. or its licensors

Source title: CMAJ

DOI : 10.1503/cmaj.210132

Series Number: Vol. 193, issue17

Link: The mobility gap: Estimating mobility thresholds required to control SARS-CoV-2 in Canada

Year: 2021

Abstract: To improve spectrum efficiency without interfering with licensed users, reliable prediction of spectrum occupancy plays a pivotal role in a dynamic spectrum allocation (DSA) system. A reliable machine learning method capable of exploring the long-term correlation in the data is using a neural network with long short-term memory (LSTM). However, in the situation that there are multiple sensors in the network, how to effectively exploit the spatial correlation among these sensors' data for accurate spectrum prediction remains an open issue. Directly applying LSTM to multiple series may even reduce the prediction accuracy if some series are uncorrelated. In this article, we propose a method of clustering to aid in predicting multi-dimensional received power based on the hierarchical agglomerative clustering (HAC) model, which clusters the correlated series with high spearman's rank correlation coefficient (SRCC). Similar series are grouped into clusters and trained to predict independently using HAC. By ensuring uncorrelated series do not influence each other, the LSTM prediction accuracy is improved. A low-pass filter is used to remove high-frequency noise components and further reduce the prediction error. Experimental results show that our method significantly increases the prediction accuracy in all cases. © 2021 IEEE.

Source title: 2021 IEEE 18th Annual Consumer Communications and Networking Conference, CCNC 2021

DOI : 10.1109/CCNC49032.2021.9369631

Series Number:

Link: Hierarchical agglomerative clustering and LSTM-based load prediction for dynamic spectrum allocation

Year: 2021

Abstract: An approach for improving the gain of the leaky-wave antenna (LWA) is presented in this paper. Embedding cavities in the structure leads to gain improvement. To validate the proposed method, it was implemented on a half-mode substrate integrated waveguide (HMSIW) LWA. The proposed HMSIW LWA was realized on a low temperature co-fired ceramic (LTCC) structure to achieve a compact structure. The key novelty of the proposed antenna is the gain improvement by using embedded cavities without increasing the antenna size. Applying the novel design method results in a measured peak realized gain of 7.6 dBi. Tapering the aperture leads to about 6 dB reduction of sidelobe level (SLL) in the upper hemisphere as well. The impedance matching frequency bandwidth of the antenna ranges from 28.3 to 29 GHz that falls within the 5G mm-wave frequency bands. The length, width, and thickness of the antenna are 40 mm, 16 mm, and 1 mm, respectively. The compactness, medium gain, and low loss of the proposed antenna make it a suitable candidate for 5G wireless devices. A good agreement between the measured and simulated results is observed. © 2013 IEEE.

Source title: IEEE Access

DOI : 10.1109/ACCESS.2021.3057303

Series Number: Vol. 9

Link: A Compact Cavity-Based Leaky-Wave Antenna in a Low Temperature Co-Fired Ceramic Process with Improved Performance

Year: 2021

Abstract: A new reconfigurable slotted antenna is presented in this manuscript. The proposed antenna is realized on a half-mode substrate integrated waveguide (HMSIW). The beam-steering is achieved using embedded varactor diodes in circular cells. Sweeping the bias voltage causes variations of the phase constant, which leads to the fixed frequency beam-scanning. Each reconfigurable cell includes a circular slot at the top plate and varactor switch, DC block, and RF block at the backside of the structure. The operating frequency is chosen as 28.5 GHz in the support of the upcoming 5G mm-wave communications systems. The proposed antenna beam scans 29° of space by switching among different states at 28.5 GHz. The length, width, and height of the antenna are 67 mm, 48 mm, and 0.32 mm, respectively. The proposed antenna's main novelties are compactness and electronic beam-scanning capability using a single switch per cell. The measured peak realized gain and sidelobe level (SLL) at 28.5 GHz are 8.2 ± 0.6 dBi and 5 dB, respectively. While the impedance bandwidth of the proposed antenna is 1.5 GHz. A good agreement between measured and simulated results is observed. The discrepancies are investigated through a sensitivity analysis. Fixed frequency beam-scanning capability, compactness, simplicity of the assembly, backward radiation, and slight gain variation of the proposed antenna make it a suitable candidate for blind-spot monitoring and 5G vehicle to everything (V2X) communications. © 2013 IEEE.

Source title: IEEE Access

DOI : 10.1109/ACCESS.2021.3070195

Series Number: Vol. 9

Link: Fixed Frequency Beam-Scanning HMSIW-Based Leaky-Wave Antenna Composed of Circular Slots in V-Shape Configuration

Year: 2021

Abstract: In this paper, we investigate the capability of generative adversarial networks, including conditional and conditional convolutional generative adversarial networks, in generating electromagnetic engineered surfaces (EES). Generative models such as generative adversarial networks and their conditional variants can be used to generate different categories of designs based on the current dataset. k-means clustering algorithm is used to obtain the desirable categories of EES designs, including an initial two main categories, followed by six and eight subcategories. Conditional and conditional convolutional generative adversarial networks are proposed and trained on designs with different image dimensions conditioned on different sets of categories. The trained conditional convolutional generative adversarial network models have comparable accuracy with conditional generative adversarial network in low-dimensional designs over two categories. Conditional convolutional generative adversarial networks generate more unique designs for six and eight categories for smaller image dimensions (e.g., 9 × 9 designs) and for two main categories over larger designs. Both generative adversarial network structures are suitable for generating a wide variety of low- and high-pass EES designs. The creation of new datasets can benefit from conditional convolutional generative adversarial networks to provide greater variety in designs. © 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd. part of Springer Nature.

Source title: Neural Computing and Applications

DOI : 10.1007/s00521-020-05656-2

Series Number:

Link: Designing mm-wave electromagnetic engineered surfaces using generative adversarial networks

Year: 2021

Abstract: A new modulation scheme using multiwavelets for downlink non-orthogonal multiple-access (NOMA) transceivers is presented in this work. Multiwavelets leading to remarkable spectral diversity are exploited to modulate/demodulate the superimposed multi-user signals in downlink NOMA systems, where the discrete multiwavelet transform and the inverse discrete multiwavelet transform are invoked in the new demodulator of the user equipment and the new modulator of the base station, respectively. The performance evaluation and the computational-complexity analysis of our proposed new NOMA scheme are also conducted. Simulation results demonstrate that the proposed new scheme can significantly increase the system capacity while dramatically suppressing the peak-to-average-power ratio (PAPR) compared to the conventional OFDM-based NOMA approach. Meanwhile, our new scheme can achieve the same system capacity as the scalar-wavelet-based NOMA approach but with a lower PAPR at little extra cost of computational-complexity. All of these three aforementioned NOMA schemes can result in the identical bit-error-rate under the same signal-to-noise ratio condition. IEEE

Source title: IEEE Wireless Communications Letters

DOI : 10.1109/LWC.2021.3063122

Series Number: Volume 10, issue 6

Link: Novel Efficient Multiwavelet-Based Modulation for Downlink NOMA Systems

Year: 2021

Abstract: The new ways to consume and deliver media content in a wireless environment have led to a significant increase in the demand for spectrum resources. In addition, the arrival of next-generation wireless communication technologies has encouraged the creating of new verticals targeting novel applications, such as industry IoT, e-health, distance learning, smart city, smart-metering. All these new use cases are centred on an IP-based infrastructure. A promising alternative to satisfy the demand for resources is to incorporate a new delivery mechanism that can alleviate the congestion of classical cell-based point-to-point broadband wireless infrastructures. The best-positioned candidate is the next-generation Digital Terrestrial Television system, which offers a very spectrum efficient one-to-many PHY, and for the first time, native IP support. In ATSC 3.0, the whole system was designed with an IP-centric view, whereas DVB has created standards to deliver services to generic IP devices (DVB-I). Nevertheless, there is still a last missing piece to bring the broadcast infrastructure to the IP-connected world: a Broadcast Core Network (BCN). In this paper, the basics of a BCN are presented with new use cases that are attractive to Broadcast Network Operator (BNO). A possible roadmap towards implementation is described, and a service-based architecture for a BCN is presented and discussed. © 1963-12012 IEEE.

Source title: IEEE Transactions on Broadcasting

DOI : 10.1109/TBC.2021.3105026

Series Number:  Volume 67, issue 3

Link: Broadcast Core-Network: Converging Broadcasting with the Connected World

Year: 2021

Abstract: This paper describes systems, devices, and methods to implement a bi-directional integrated inter-tower wireless communications network (IITWCN). The described technology can be implemented in combination with the Broadcast Core Network (BCN) in next generation broadcast eco-system and, therefore, support new business cases for broadcast operators such as the delivery of flexible datacasting services or support broadcast or point-to-point Internet services. The introduced bi-directional inter-tower communications network (ITCN) extends the previous unidirectional in-band distribution links (IDL) and adopts the on-channel repeater (OCR) as a simplified backhaul solution in single frequency networks (SFN). The concept of the coordinated ITCN is also presented, aiming at future broadcast Internet services. The ITCN provides a scalable and configurable network solution embedded in a broadcast system, which becomes independent from any non-broadcasting telecommunication infrastructure. The described technology partially relies on the infrastructure of the underlying broadcast/multicast network, using the allocated service channels without requiring additional frequency bands or a separate frequency band. The bi-directional inter-transmitter communication links are therefore referred to as integrated transmission links and the corresponding network as an integrated network. © 1963-12012 IEEE.

Source title: IEEE Transactions on Broadcasting

DOI: 10.1109/TBC.2021.3081861

Series Number: Volume 67, issue 3

Link: Integrated Inter-Tower Wireless Communications Network for Terrestrial Broadcasting and Multicasting Systems

Year: 2021

Abstract: We have developed a hardware-accelerated Monte Carlo path tracing tool based upon a novel mmWave propagation prediction model. Much faster than conventional tools, it is designed to meet the needs of large-scale coverage and interference studies. The results of initial validation against conventional ray- tracing simulations and measurements in an indoor office environment at 60 GHz demonstrate the merit of the approach. Overall, prediction accuracy was comparable between the two approaches in this scenario, while Monte Carlo path tracing was more than an order of magnitude faster. With further validation and suitable building and terrain data, this method should also be suitable for outdoor and mixed environments. © 2021 IEEE.

Source title: 2021 IEEE 19th International Symposium on Antenna Technology and Applied Electromagnetics, ANTEM 2021

DOI: 10.1109/ANTEM51107.2021.9518408

Series Number:

Link: mmWave Propagation Prediction using Hardware-Accelerated Monte Carlo Path Tracing

Year: 2021

Abstract: The rapid uptake of wireless technologies over the past decade has resulted in an increasing pressure on the limited radio spectrum resources. To improve the efficiency of the current spectrum allocation, dynamic spectrum sharing is being considered by regulators in several jurisdictions. The success, however, of an efficient dynamic wireless environment depends on the ability to characterize spectrum usage patterns. Since traditional methods prove unable to scale to a wide range of channels, we propose DeepAir, a robust and scalable model that is capable of learning and predicting complex temporal and spectral patterns in multivariate spectrum data. Specifically, we design a Sequence-to-Sequence model that employs an encoder-decoder architecture with two Deep Temporal Convolutional Networks.Using a test set consisting of approximately 900 channels in the Land Mobile Radio frequency bands, we obtain a median RMSE and median MAE of approximately 6.51 and 5.15, respectively, for a one-week forecast horizon. Moreover, we apply transfer learning to demonstrate the effectiveness of this model in forecasting patterns from any sensor, regardless of the band, the sensitivity, and the geographical location. Finally, our proposed approach demonstrates no significant performance degradation when predicting usage almost three years after training. © 2021 IEEE.

Source title: 2021 IEEE International Conference on Communications Workshops, ICC Workshops 2021 - Proceedings

DOI: 10.1109/ICCWorkshops50388.2021.9473745

Series Number:  

Link: DeepAir: Predicting Radio Spectrum Usage at Scale with Deep Temporal Convolutional Networks

Year: 2021

Abstract: Spectrum monitoring is a key element of spectrum management process, in which spectrum sensors are considered the most crucial component. In this paper, we discuss the problem of optimal sensor deployment for spectrum monitoring applications. Optimal sensor deployment can significantly reduce the cost of sensor deployment and improve spectrum monitoring performance and efficiency. An optimal sensor deployment technique is developed, which provides the minimized number of sensors required, as well as their locations of deployment, for monitoring transmissions by desired stations in an area of interest. The problem of optimal sensor deployment is formulated using binary linear integer programming that is solved using efficient numerical optimization algorithms. The technique is scalable in the sense that it considers the effects of pre-installed or existing spectrum sensors in the area. Finally, we apply the technique to an Ottawa area for deploying sensor to monitor all down-link transmissions in the 800 MHz Land Mobile Radio (LMR) band to demonstrate its effectiveness and performance. © 2021 IEEE.

Source title: 2021 IEEE International Conference on Communications Workshops, ICC Workshops 2021 - Proceedings

DOI: 10.1109/ICCWorkshops50388.2021.9473884

Series Number:  

Link: An Optimal Sensor Deployment Technique for Spectrum Monitoring Applications

Year: 2021

Abstract: In this communication, we introduce a novel design for mitigating the side-lobe level (SLL) of the half-mode substrate integrated waveguide (HMSIW)-based leaky-wave antenna (LWA). Applying a novel approach through modification of the side aperture of HMSIW, we achieved an SLL of -13.8 and -11.2 dB in the upper hemisphere and full space, respectively. The key novelty of this communication is the reduction of SLL in full space while the state-of-the-art antennas only mitigated the SLL in the upper hemisphere. Furthermore, tapering the open side aperture in a thin trapezoid shape led to a significant reduction of beam squint. The operating frequency band of the antenna matches the allocated 5G wireless network millimeter-wave bands from 26 to 30 GHz. The measured peak realized gain of the antenna is 10.6 dBi at 28.5 GHz. The length, width, and height of the HMSIW antenna are 70, 15, and 0.5 mm, respectively. The antenna was fabricated on a Rogers RT/Duroid 5880 substrate. Excellent agreement between the measurements and simulated results was observed. The discrepancies between the measured and simulated results were analyzed by a complete and thorough sensitivity analysis that included the effects of the fabrication tolerances, connectors' misalignment, and bending due to the mechanical stress. High gain, low SLL, and compactness are among the advantages of the proposed antenna making it a suitable candidate for the miniaturization of 5G communication systems. © 1963-2012 IEEE.

Source title: IEEE Transactions on Antennas and Propagation

DOI: 10.1109/TAP.2020.3037806

Series Number: Volume 69, issue 6

Link: Side-Lobe Level Reduction of Half-Mode Substrate Integrated Waveguide Leaky-Wave Antenna