Accurate 3D tracking of objects from monocular camera poses challenges due to the loss of depth during projection. Although ranging by RADAR has proven effective in highway environments, people tracking remains beyond the capability of single sensor systems. In this paper, we propose a cooperative RADAR-camera fusion method for people tracking on the ground plane. Using average person height, joint detection likelihood is calculated by back-projecting detections from the camera onto the RADAR Range-Azimuth data. Peaks in the joint likelihood, representing candidate targets, are fed into a Particle Filter tracker. Depending on the association outcome, particles are updated using the associated detections (Tracking by Detection), or by sampling the raw likelihood itself (Tracking Before Detection). Utilizing the raw likelihood data has the advantage that lost targets are continuously tracked even if the camera or RADAR signal is below the detection threshold. We show that in single target, uncluttered environments, the proposed method entirely outperforms camera-only tracking. Experiments in a real-world urban environment also confirm that the cooperative fusion tracker produces significantly better estimates, even in difficult and ambiguous situations.
An accurate step length estimation can provide valuable information to different applications such as indoor positioning systems or it can be helpful when analyzing the gait of a user, which can then be used to detect various gait impairments that lead to a reduced step length (caused by e.g., Parkinson's disease or multiple sclerosis). In this paper, we focus on the estimation of the step length using machine learning techniques that could be used in an indoor positioning system. Previous step length algorithms tried to model the length of a step based on measurements from the accelerometer and some tuneable (user-specific) parameters. Machine-learning-based step length estimation algorithms eliminate these parameters to be tuned. Instead, to adapt these algorithms to different users, it suffices to provide examples of the length of multiple steps for different persons to the machine learning algorithm, so that in the training phase the algorithm can learn to predict the step length for different users. Until now, these machine learning algorithms were trained with features that were chosen intuitively. In this paper, we consider a systematic feature selection algorithm to be able to determine the features from a large collection of features, resulting in the best performance. This resulted in a step length estimator with a mean absolute error of 3.48 cm for a known test person and 4.19 cm for an unknown test person, while current state-of-the-art machine-learning-based step length estimators resulted in a mean absolute error of 4.94 cm and 6.27 cm for respectively a known and unknown test person.
For the extremely high sampling rate and high resolution required for Terahertz (THz) communication, time-interleaved analog-to-digital converters (TI-ADCs) are being considered. However, in practice, mismatches between the parallel sub-ADCs degrade the system performance. In this extended abstract, we provide an overview of the effects of TI-ADC offset, gain and timing mismatches on the bit error rate (BER) of orthogonal frequency division multiplexing (OFDM) system.
Vehicle-to-anything (V2X) is a promising communication technology to support operability in large-scale vehicular networks. The future deployment of V2X necessitates interworking between different access technologies, i.e., Dedicated Short-Range Communications (DSRC) and Cellular networks. However to achieve an efficient V2X interworking, we need to resolve the multi-hop issue, mainly originating from the V2X hybrid architecture. To resolve this issue and consequently to analyze the interconnected system, characterizing the output process of IEEE 802.11p-based DSRC protocol is of a fundamental importance. This paper proposes stochastic Regenerative Model to provide a complete description of IEEE 802.11p output process. The accuracy of the model is verified through extensive simulations. As a case study, the proposed model is compared with the Poisson model in the performance evaluation of V2X interworking. Numerical and simulation results verify the ability of the Regenerative Model to capture the deviations of the actual output process of IEEE 802.11p under different traffic intensity as compared to the Poisson model.
The use of multiple radio access technologies (RATs) is inevitable in future heterogeneous cellular networks. Various RATs can offer different throughputs, and thus RAT selection plays an important role in quality of service provisioning. In this paper, considering a heterogeneous network with two throughput classes, we introduce a new practical probabilistic RAT selection approach. In contrary to the common deterministic approaches, in this scheme, each user performs the RAT selection periodically in a random manner using an association probability determined by a central unit in the network. The user remains connected to the selected RAT for a specific amount of time and then again performs the selection. To find the association probabilities, the network throughput maximization is formulated. Since the resulting problem is not convex, we propose two alternatives, one with sub-optimal solution but lower complexity and one with the use of change of variables with optimal solution. Finally, numerical simulations demonstrate the superior performance of our proposed schemes in comparison to several possible approaches. Also, these numerical investigations indicate that our sub-optimal method works very close to the optimal one.
The Optimized Link State Routing (OLSR) protocol, early designed for Mobile Ad hoc Networks (MANET), has been customized and evaluated for various Vehicular Ad hoc Network (VANET) scenarios. Most of the related work focus on changing OLSR parameters in order to adapt it to the high dynamicity of VANET due to high velocity of its nodes. However, they keep using OLSR with its native clustering scheme, the Multipoint Relaying (MPR). Recently, the chain-branch-leaf (CBL) clustering scheme has been proposed for road traffic configuration. This work presents a comparative analysis of CBL with MPR clustering in OLSR. The results show that CBL reduces significantly the routing traffic overhead in OLSR by reducing the number of relays, without degrading the performance for the application traffic.
In this contribution we consider a communication system consisting of a cascade of a passive optical network (PON) link with on/off keying, and a short twisted pair (TP) link with discrete multitone modulation (DMT). Three coding configurations are investigated. In the first configuration (C1), the PON link and the TP link are protected by a Reed-Solomon (RS) code and trellis-coded modulation (TCM), respectively. In the second configuration (C2), the PON link is the same as with C1, but the TP link is now protected by the concatenation of an outer RS code and inner TCM. We compare these conventional coding configurations C1 and C2 with an alternative configuration (C3), in which an outer RS code protects the cascade of the uncoded PON and the TCM-encoded TP. Whereas the configuration C3 has the same complexity as the configuration C1, we show that the former is able to achieve approximately the same information bitrate as the (more complex) configuration C2, at the expense of a slightly (about 1 dB) higher optical power. Our numerical results for a typical setting indicate that the configurations C2 and C3 can provide information bitrates beyond 10 Gbps, which are about 20-25% larger than for configuration C1.
This paper evaluates the performance of the routing protocols HWMP, Babel and B.A.T.M.A.N. advanced for disaster networks. The evaluation is performed using a virtual environment so that the obtained results are similar to the expectations of a real world testbed. According to the specific requirements in disaster situations, three different scenario categories are implemented. The focus of the scenarios defined in the first category is to evaluate the behavior of the protocols inside a static network. The focus in the second category is to test their performance after dynamic processes. The focus in the last category is to predict the behavior of the routing protocols inside a large network expected after a disaster. The obtained results can be interpreted as follows: in the first category, the results obtained by HWMP and B.A.T.M.A.N. advanced are similar. Both protocols take the variations in the link throughput into consideration for their routing operations. In the second category, the protocol HWMP shows the most promising results concerning dynamic processes inside the network. The results obtained in the last category show that none of the examined protocols is appropriate for large networks, with the exception of Babel, which can be modified to support a large number of clients and routers. Because none of the examined routing protocols can fulfil the requirements in disaster situation, a new network architecture is proposed, which combines the advantages of two routing protocols to address the existing routing challenges.
Radio Frequency (RF) fingerprinting is the problem of identifying and authenticating an electronic device through its radio frequency emissions. These emissions contain intrinsic features of the device itself. RF fingerprinting can be used to enhance the security of wireless networks since the fingerprints provide a form of authentication complementing other measures. RF-based authentication turns out to be of practical use in security applications as long as the RF fingerprinting delivers high identification and verification accuracy, and the whole process is computationally efficient. In this paper, we investigate a novel approach to RF fingerprinting based on the application to time series of the Symbolic Aggregate Approximation algorithm (SAX). This is a compression scheme known to be time efficient and, although it has been applied to many domains, it has so far never been investigated in the problem of RF fingerprinting. We demonstrate that a SAX-based approach provides a very high identification accuracy (over 99%), and turns out to be attractive, as compared to classification without SAX, from both a computational standpoint and its robustness to noise.
The fifth-generation cellular networks aim to provide uniform and very high throughput. Massive MIMO is widely seen as the most promising 5G radio technology as it promises very high throughput to many users while also guaranteeing fairness, thanks to the channel hardening effect limiting the small-scale fading. A key question though is to what extent this achieved throughput is homogeneous among users, and what degrees of freedom exist to improve fairness. A promising option to provide uniform throughput using Massive MIMO would be a proper power control, based on long-term channel statistics. This paper studies the trade-off between throughput and fairness and it compares different power-allocation schemes. Assuming users affected by log-normal large-scale fading, simulations show that the trade-off is critical. as user-dependent differences caused by large-scale fading are causing unfairness in the system and fairness is achieved at the price of throughput reduction. In a limited large-scale fading scenario, throughput or fairness optimization is possible without incurring huge losses on the other dimension. For heavy large-scale fading scenarios the cost of enforcing fairness is very large: more than 50% of throughput reduction is observed. Despite the critical trade-off, Massive MIMO is shown to be less sensitive to throughput losses when enforcing fairness, compared with traditional communication systems.
Many Internet of Things (IoT) applications benefit greatly from low-power long-range connectivity. A promising technology to achieve the low-power and long-range requirements is seen in LoRaWAN, a media access control (MAC) protocol maintained by the LoRa Alliance and leveraging Semtech's patented LoRa radio modulation technology. LoRaWAN provides three different device classes (A, B and C), which provide a tradeoff between performance (i.e., throughput and latency) and energy consumption. This paper offers a theoretical and experimental comparison of these classes. The objective of the quantitative experiment was twofold: to verify the published current levels of different operating modes in a LoRa chip's datasheet and to compare the battery lifetime for the LoRa class A and C modes of operation. We used a high-end current sensing circuit to gather the voltage levels and temporal variation with increasing payload sizes and spreading factors. Using the Ohmic Law, the energy drain can be calculated and compared across the different spreading factors (SF) and classes.
We have seen an ever-expanding set of location-aware services and devices become broadly available over the past years. Despite these promising applications and thorough research, indoor localization remains a very challenging topic and (near) perfect accuracy continues to be an open research challenge. In this paper, we acknowledge the growth and potential of smart home environments and focus on the usage of Bluetooth Low Energy (BLE) for wireless indoor positioning in such cases. This is in contrast with existing work around BLE that more focuses on use-cases in large public areas or buildings. In particular, we compare the applicability of different distance functions for the fingerprinting localization method and propose a dynamic approach of selecting the most suited distance function. Furthermore, we investigate the impact on the quality of the fingerprints by looking at directional fingerprints and search space restrictions. Finally, we discuss the design and usage of a real-life location-aware smart home application, where a user controls the lights in a room through gestures.
The use of UWB for Industrial Internet of Things (IIoT) applications benefits from the following four main properties; 1) scalability due to the inherent short transmissions times of the UWB radio, 2) bandwidth-consuming applications such as condition monitoring with vibration sensing, 3) applications with real-time positioning (RTLS) requirements, and 4) wireless communication in electromagnetically harsh environments with a high level of multipath fading. In this paper, we present a UWB-based 6LoWPAN implementation in the Contiki OS as a step towards incorporating UWB in the industrial IoT domain.
This paper presents a design of fully differential low-noise amplifier (LNA) used for 60 GHz low power wireless communication in 65 nm CMOS technology. The proposed LNA consists of an input stage employing capacitive cross-coupling technique and an gain stage using current-reuse techniques. The simulated amplifier achieves both input and output matching better than -15dB, a forward gain of 15 dB, a noise figure of 4.7 dB, an input IP3 of -14dBm and the power consumption is 5 mW. The author also proposed a simple design method based on "black box" approach, which can be used for low power LNA design.
This work addresses the extra power penalty caused by high-speed visible light communication (VLC) that adopting traditional lighting system, in particular, with OFDM as well as binary modulation such as PAM. In this work, we emphasize the use of switched mode power supply (SMPS) as current source for joint illumination and communication (JIC), although it is initially optimized for efficient lighting. The key components which potentially cause extra power in the transmitter are taken into account, including the SMPS, the field effect transistor (FET) modulator and the LEDs. An approximated model is derived to calculate the extra power in the SMPS. We compare the extra power loss in the modulator that operates in the saturation and linear region, according to the circuit bias point (Q-point) and the root mean square (rms) modulation depth, from a power and communication engineers perspective, respectively. The extra power loss in the LED is modelled by a DC and a non-linear resistance. The main merit of this work is that it presents a theoretical model to quantify the extra power loss that considering the paramount components in the transmitter.
Home automation devices are becoming increasingly popular in the field of consumer electronics. Various appliances like thermostats, smoke detectors, intelligent lighting systems, etc., have appeared on the market to create a smart home. Vendors have the availability over multiple wireless technologies to connect their products to the smart home and communicate with the user. The most adopted technologies are the ones that can interface directly with a mobile device such as a smartphone or tablet, without the need for an additional gateway. Within this context, Wi-Fi and Bluetooth are the dominant technologies. In this paper we look at home automation devices that have chosen to solely support Bluetooth 4.0 as communication interface. We highlight the downsides of this technology in a home setting and try to mitigate this problem by exploiting the Wi-Fi capabilities of other devices, in particular smartphones. The proposed solution realizes a Wi-Fi bridge on the smartphone that is connected to the Bluetooth device. This enables other smartphone users to connect to the Bluetooth device over the Wi-Fi network, alleviating some of the downsides of the Bluetooth technology.
This paper explores a 60 GHz phased array system for ultra-high data rate communication in indoor environments. The channel modeling is addressed and the system link budget is calculated. A 16-element phased array system specifications are presented. This paper also presents the design of one of the key blocks - a 5-bit digitally controlled passive phase shifter. The switch-type phase shifter is implemented in 40 nm CMOS technology, with the maximum phase error of 4.68° and the rms gain error of 1.72 dB.
The performance of multicarrier systems can be considerably degraded because of inter-carrier interference (ICI) caused by a carrier frequency offset (CFO) between the transmitter and the receiver. A recently developed multicarrier modulation technique, referred to as uniform filtered multicarrier (UFMC), improves the robustness against CFO, thereby relaxing the synchronization requirements, consequently providing energy efficient and low latency transmissions. However, the goodput (GP) of the system still rapidly drops with increasing CFO when using the classical adaptive modulation and coding (AMC) schemes based on the SNRs of the subcarriers, because they ignore the presence of the CFO-induced ICI. To tackle this problem, this contribution performs the AMC, also taking into account the ICI caused by the CFO, and thereby achieving a significant increase of the GP.
