Statistical Modeling and Estimation of Censored Pathloss Data

Pathloss is typically modeled using a log-distance power law with a large-scale fading term that is log-normal. However, the received signal is affected by the dynamic range and noise floor of the measurement system used to sound the channel, which can cause measurement samples to be truncated or censored. If the information about the censored samples are not included in the estimation method, as in ordinary least squares estimation, it can result in biased estimation of both the pathloss exponent and the large scale fading. This can be solved by applying a Tobit maximum-likelihood estimator, which provides consistent estimates for the pathloss parameters. This letter provides information about the Tobit maximum-likelihood estimator and its asymptotic variance under certain conditions.Comment: 4 pages, 3 figures. Published in IEEE Wireless Communication Letter

Tobit Maximum-likelihood estimation of Censored Pathloss Data

Pathloss is typically modeled using a log-distance power law with a large-scale fading term that is log-normal. However, the received signal is affected by the dynamic range and noise floor of the measurement system used to sound the channel, which can cause measurement samples to be truncated or censored. If the information about the censored samples are not included in the estimation method, as in ordinary least squares estimation, it can result in biased estimation of both the pathloss exponent and the large scale fading. This is solved by applying a Tobit maximum-likelihood estimator, which provides consistent estimates for the pathloss parameters. This technical report provides information about the Tobit maximum-likelihood estimator estimator and its asymptotic variance under certain conditions

Measurement Based Vehicle-to-Vehicle Multi-link Channel Modeling and Relaying Performance

There has been intense research in vehicular communication in order to provide reliable low-latency vehicular communication links for developing intelligent transportation system (ITS). As one of the important properties, vehicle-to-vehicle (V2V) communication is learned to be inherently non-stationary due to the high mobility of both transmitter (TX) and receiver (RX). Therefore, the V2V system behavior is essentially different from previous mobile communication studies and needs to be understood. For V2V wireless communication systems, it is crucial to model the vehicular channel accurately to evaluate the quality of the system level applications. Among all channel properties in a V2V system, the shadow fading (i.e. large scale fading, LSF) from other vehicles has a significant adverse impact on the system performance. One promising approach to overcome this issue is by implementing multi-hop technology on the vehicular ad hoc network (VANETs). One goal of this thesis report is to implement relaying schemes on simulated Rician channel based on measurements to evaluate the performance of multi-hop technology in V2V systems. Two relaying schemes, Amplify-and-Forward (AF) and Decode-and-Forward (DF), are employed in the bit level simulation. The results of packet error rate (PER) are evaluated together with non-relaying situation for convoy and overtaking scenarios, respectively. Furthermore, a statistic model is created to model the measured highway environment. Pathloss parameters and shadowing loss together with correlation coefficients are derived. Line-of-sight (LOS) and obstructed line-of-sight (OLOS) conditions are manually separated through on-board video. Each scenario has its own parameter set. Maximum likelihood estimation (MLE) is utilized on the pathloss model to compensate the biasing from the measurement hardware. Also the shadowing is modeled as correlated Gaussian and we derived the decorrelation distance from the auto-correlation function (ACF). The model is also validated against the measurements. For an ad hoc network, the diversity schemes would be strongly affected by the multilink correlation. Only a few joint correlation studies for mobile ad hoc network have been made, but rarely for VANETs. The last goal of this report is to study the joint correlation on VANETs based on measurements for four-dimensional position joint correlation model where shadowing is affected by the vehicle distance. To be precise, we focus on the joint correlation of large scale fading affected by the distances between the two receiver vehicles under the same car obstruction. Finally, a stochastic model based on the sum of sinusoids approach is implemented.The fifth generation wireless systems denotes the next major phase of mobile telecommunications standards and is expected to meet consumer demands by 2020. One of the major approach is the vehicular ad hoc networks, which is a spontaneous creation of a wireless network for data exchange to the domain of vehicles. As a key component of the intelligent transportation systems, it is extremely importance to model the vehicular propagation channel in order to meet the requirement of low latency and high reliability. There are many parameters that could describe the channel characteristics. Among them all, the vehicular shadowing has a significant advise impact on the system performance which describes the signal fluctuation affected by an obstruction vehicle. In order to study it, a measurement was designed and took place in Sweden, road Rv 40. Four Volvo cars were forming convoy and overtaking scenarios with equipped signal-transmit-receive devices. Three major works are done in this thesis project based on this measured highway scenario: Firstly, a simulation is designed based on the multi-hop technology. A scenario is simulated where a source car sends packets to a destination car with the help of a relay car. All the packets are randomly generated with each containing proper coding and modulation to enhance the transmission quality as well as to check the success or failure of the transmission. The power properties of the wireless channels between each car-link are captured from the the measurements. They are simulated with a vehicular-based distribution while each byte of the signal would experiences a vehicular channel more close to practice. Two relaying schemes are implemented in the simulation with a different reaction at the relay car after receiving the signal from the source. The destination then combines the two signals from the source and relay. It decodes the signal and records the decoding results. For each observation, the ratio of successfully transmission number and total transmission number is recorded as packet error rate. Eventually, the packet error rate performances of different schemes are compared and evaluated. Secondly, based on whether the link between antennas are obstructed, two scenarios are separated manually by watching the on-board videos. After that, the signal penetration based on transmission distance and the signal fluctuation affected by large obstructions are modeled based on the individual scenario. An advanced estimation method is employed during the modeling of the signal penetration to efficiently include the lost packet information. As for the modeling of the signal fluctuation, an extended distribution is used to describe the facts that, when a transmission link is obstructed by another vehicle, it normally remains obstructed for a certain amount of time. Eventually, channel power can be regenerated based on the model containing the measured channel properties. At last, a model is created to describe the joint effects on the signal fluctuation based on the vehicles' movement and the distances between two receive cars whose signals are obstructed by the same vehicle. The vehicular shadowing following a certain distribution is approximately represented by the sum of many sinusoid waves with random phases and chosen frequencies. The frequencies are generated based on the power and joint correlation properties of the measured channel based on the two effects

60 GHz Wireless Propagation Channels: Characterization, Modeling and Evaluation

To be able to connect wirelessly to the internet is nowadays a part of everyday life and the number of wireless devices accessing wireless networks worldwide are increasing rapidly. However, with the increasing number of wireless devices and applications and the amount available bandwidth, spectrum shortage is an issue. A promising way to increase the amount of available spectrum is to utilize frequency bands in the mm-wave range of 30-300 GHz that previously have not been used for typical consumer applications. The 60 GHz band has been pointed out as a good candidate for short range, high data rate communications, as the amount of available bandwidth is at least 5 GHz worldwide, with most countries having 7 GHz of bandwidth available in this band. This large bandwidth is expected to allow for wireless communication with bit rates up to 7 Gbit/s, which can be compared to the typical WLAN systems of today that typically provide bit rates up to 0.6 Gbit/s. However, the performance of any wireless system is highly dependent on the properties and characteristics of the wireless propagation channel. This thesis focuses on indoor short range wireless propagation channels in the 60 GHz band and contains a collection of papers that characterizes, models and evaluates different aspects that are directly related to the propagation channel properties. Paper I investigates the directional properties of the indoor 60 GHz wireless radio channel based on a set of indoor measurements in a conference room. In the paper, the signal pathways and propagation mechanisms for the strongest paths are identified. The results show that first and second order interactions account for the major contribution of the received power. The results also show that finer structures, such as ceiling lamps, can be significant interacting objects. Paper II presents a cluster-based double-directional channel model for 60 GHz indoor multiple-input multiple-output (MIMO) systems. This paper is a direct continuation of the results in paper I. The model supports arbitrary antenna elements and array configurations and is validated against measurement data. The validation shows that the channel model is able to efficiently reproduce the statistical properties of the measured channels. The presented channel model is also compared with the 60 GHz channel models developed for the industry standards IEEE802.15.3c and IEEE802.11ad. Paper III characterizes the effect of shadowing due to humans and other objects. Measurements of the shadowing gain for human legs, metallic sheets, as well as metallic and plastic cylinders are presented. It is shown that the shadowing gain of these objects are fairly similar and that the shadowing due to the metal cylinder can be determined based on the geometrical theory of diffraction. Next, the shadowing due to a water-filled human body phantom is compared with the shadowing due to real humans. The results show that the water-filled phantom has shadowing properties similar to those of humans and is therefore suitable for use in 60 GHz human body shadowing measurements. Paper IV presents a novel way of estimating the cluster decay and fading. Previously, the cluster decay has usually been determined by performing a simple linear regression, without considering the effects of the noise floor and cluster fading. The paper presents an estimation method which takes these effects into account and jointly estimates both the cluster decay and cluster fading. It is shown that this estimation method can greatly improve the estimated parameters. Paper V evaluates the capacity improvement capability of spatial multiplexing and beamforming techniques for 60 GHz systems in an indoor environment. In this paper, beamforming refers to conventional gain focusing in the direction of the strongest propagation path. The paper uses a capacity metric that only depends on the multi-path richness of the propagation channel and the antenna aperture size. In the paper, it is shown that, when the link budget is limited due to electrically small antennas and long Tx-Rx separation distances, beamforming approximates the capacity of spatial multiplexing. However, spatial multiplexing is a worthwhile option when Rx SNR is favorable and a higher peak data rate is required. Paper VI describes different methods for the clustering of wireless multi-path components. In the literature, the clustering method that is predominantly used is the K-means algorithm, or a power-weighted version of K-means, called K-power means. In this paper, we point out that K-means is a special case of a Gaussian mixture model (GMM). The paper presents a clustering method based on a GMM. This method is able to handle arbitrary cluster spreads in the different dimensions better than the K-means algorithm. A power-weighted version of the GMM is also presented. In addition to this, a mixture model based on asymmetric Laplace distributions is also presented, with and without power-weighting. Paper VII is based on channel measurements in a small and a large room, where the Tx and Rx arrays have dual polarized elements. Using these measurements, the cross-polarization ratio (XPR) of the multi-path components are characterized. This gives valuable information on how the MPCs are affected by the propagation channel. A statistical description of the XPR is also needed for the development of a propagation channel model that supports polarization. The paper also investigates the eigenvalue spreads for single and dual polarized elements. Furthermore, the measurements include LOS and NLOS measurement, where the NLOS scenarios include water-filled human presented in paper III. The results show that the capacity can be greatly improved if dual-polarized elements are used, and that the XPR values are in general higher compared to lower frequencies

AMPLE: An Adaptive Multiple Path Loss Exponent Radio Propagation Model Considering Environmental Factors

We present AMPLE -- a novel multiple path loss exponent (PLE) radio propagation model that can adapt to different environmental factors. The proposed model aims at accurately predicting path loss with low computational complexity considering environmental factors. In the proposed model, the scenario under consideration is classified into regions from a raster map, and each type of region is assigned with a PLE. The path loss is then computed based on a direct path between the transmitter (Tx) and receiver (Rx), which records the intersected regions and the weighted region path loss. To regress the model, the parameters, including PLEs, are extracted via measurement and the region map. We also verify the model in a suburban area. To the best of our knowledge, this is the first time that a multi-slope model precisely maps PLEs and region types. Besides, this model can be integrated into map systems by creating a new path loss attribute for digital maps.Comment: This paper has been submitted to IEEE Transactions for possible publication

Experimental Performance of Blind Position Estimation Using Deep Learning

Accurate indoor positioning for wireless communication systems represents an important step towards enhanced reliability and security, which are crucial aspects for realizing Industry 4.0. In this context, this paper presents an investigation on the real-world indoor positioning performance that can be obtained using a deep learning (DL)-based technique. For obtaining experimental data, we collect power measurements associated with reference positions using a wireless sensor network in an indoor scenario. The DL-based positioning scheme is modeled as a supervised learning problem, where the function that describes the relation between measured signal power values and their corresponding transmitter coordinates is approximated. We compare the DL approach to two different schemes with varying degrees of online computational complexity. Namely, maximum likelihood estimation and proximity. Furthermore, we provide a performance comparison of DL positioning trained with data generated exclusively based on a statistical path loss model and tested with experimental data.Comment: Published in: GLOBECOM 2022 - 2022 IEEE Global Communications Conferenc

Characterization of Single- and Multi-antenna Wireless Channels

The wireless propagation channel significantly influences the received signal, so that it needs to be modeled effectively. Extensive measurements and analysis are required for investigating the validity of theoretical models and postulating new models based on measurements. Such measurements, analysis, and modeling are the topic of this thesis. The focus of the included contributions are Multiple-Input Multiple-Output (MIMO) propagation channels and radio channels for sensor network applications. Paper I presents results from one of the first MIMO measurements for a double-directional characterization of the outdoor-to-indoor wireless propagation channel. Such channels are of interest for both cellular and wireless LAN applications. We discuss physical aspects of building penetration, and also provide statistics of angle and delay spreads in the channel. The paper also investigates the coupling between DOD and DOA and the two spectra are found to have non-negligible dependence. We test the applicability of three analytical channel models that make different assumptions on the coupling between DODs and DOAs. Our results indicate that analytical models, that impose fewer restrictions on the DOD to DOA coupling, should be used preferrably over models such as the Kronecker model that have more restrictive assumptions. Paper II presents a cluster-based analysis of the outdoor-to-indoor MIMO measurements analyzed in Paper I. A subset of parameters of the COST 273 channel model, a generic model for MIMO propagation channels, are characterized for the outdoor-to-indoor scenario. MPC parameters are extracted at each measured location using a high-resolution algorithm and clusters of MPCs are identified with an automated clustering approach. In particular, the adopted clustering approach requires that all MPC parameters must be similar in order for the MPCs to form a cluster. A statistical analysis of the identified clusters is performed for both the intra- and inter-cluster properties. Paper III analyzes the spatial fading distribution for a range of canonical sensor deployment scenarios. The presented results are relevant to communicating within, and between, clusters of nodes. Contrary to the widely accepted assumption in published literature that the channel is AWGN at a small-enough distance, our measurements indicate that values of the Rice factor do not, in general, increase monotonically as the Tx-Rx distance is reduced. A probability mixture model is presented, with distance dependent parameters, to account for the distance dependent variations of the Rice factor. A simulation model that includes small- and large-scale fading effects is presented. According to the modeling approach, a sensor node placed anywhere within the spatial extent of a small-scale region will experience the channel statistics applicable to that region. Paper IV presents results characterizing a radio channel for outdoor short-range sensor networks. A number of antennas are placed on the ground in an open area and time-variation of the channel is induced by a person moving in the vicinity of the nodes. The channel statistics of both the LOS path and the overall narrowband signal are non-stationary. We investigate the stationarity interval length to be used for small-scale analysis. Our analysis of the various measured links shows that the Rx signal strength is significantly influenced by a moving person only when the person blocks the LOS path. We present a generic approach for modeling the LOS blockage, and also model the time-variant Doppler spectrum of the channel's scattered components