Localization Of Sensors In Presence Of Fading And Mobility

The objective of this dissertation is to estimate the location of a sensor through analysis of signal strengths of messages received from a collection of mobile anchors. In particular, a sensor node determines its location from distance measurements to mobile anchors of known locations. We take into account the uncertainty and fluctuation of the RSS as a result of fading and take into account the decay of the RSS which is proportional to the transmitter-receiver distance power raised to the PLE. The objective is to characterize the channel in order to derive accurate distance estimates from RSS measurements and then utilize the distance estimates in locating the sensors. To characterize the channel, two techniques are presented for the mobile anchors to periodically estimate the channel\u27s PLE and fading parameter. Both techniques estimate the PLE by solving an equation via successive approximations. The formula in the first is stated directly from MLE analysis whereas in the second is derived from a simple probability analysis. Then two distance estimates are proposed, one based on a derived formula and the other based on the MLE analysis. Then a location technique is proposed where two anchors are sufficient to uniquely locate a sensor. That is, the sensor narrows down its possible locations to two when collects RSS measurements transmitted by a mobile anchor, then uniquely determines its location when given a distance to the second anchor. Analysis shows the PLE has no effect on the accuracy of the channel characterization, the normalized error in the distance estimation is invariant to the estimated distance, and accurate location estimates can be achieved from a moderate sample of RSS measurements

Spatial Modulation for Multiple-Antenna Wireless Systems : A Survey

International audienceMultiple-antenna techniques constitute a key technology for modern wireless communications, which trade-off superior error performance and higher data rates for increased system complexity and cost. Among the many transmission principles that exploit multiple-antenna at either the transmitter, the receiver, or both, Spatial Modulation (SM) is a novel and recently proposed multiple- uniqueness and randomness properties of the wireless channel for communication. This is achieved by adopting a simple but effective coding mechanism that establishes a one-to-one mapping between blocks of information bits to be transmitted and the spatial positions of the transmit-antenna in the antenna-array. In this article, we summarize the latest research achievements and outline some relevant open research issues of this recently proposed transmission technique

Analysis of Multipath Mitigation Techniques with Land Mobile Satellite Channel Model

Multipath is undesirable for Global Navigation Satellite System (GNSS) receivers, since the reception of multipath can create a significant distortion to the shape of the correlation function leading to an error in the receivers’ position estimate. Many multipath mitigation techniques exist in the literature to deal with the multipath propagation problem in the context of GNSS. The multipath studies in the literature are often based on optimistic assumptions, for example, assuming a static two-path channel or a fading channel with a Rayleigh or a Nakagami distribution. But, in reality, there are a lot of channel modeling issues, for example, satellite-to-user geometry, variable number of paths, variable path delays and gains, Non Line-Of-Sight (NLOS) path condition, receiver movements, etc. that are kept out of consideration when analyzing the performance of these techniques. Therefore, this is of utmost importance to analyze the performance of different multipath mitigation techniques in some realistic measurement-based channel models, for example, the Land Multipath is undesirable for Global Navigation Satellite System (GNSS) receivers, since the reception of multipath can create a significant distortion to the shape of the correlation function leading to an error in the receivers’ position estimate. Many multipath mitigation techniques exist in the literature to deal with the multipath propagation problem in the context of GNSS. The multipath studies in the literature are often based on optimistic assumptions, for example, assuming a static two-path channel or a fading channel with a Rayleigh or a Nakagami distribution. But, in reality, there are a lot of channel modeling issues, for example, satellite-to-user geometry, variable number of paths, variable path delays and gains, Non Line-Of-Sight (NLOS) path condition, receiver movements, etc. that are kept out of consideration when analyzing the performance of these techniques. Therefore, this is of utmost importance to analyze the performance of different multipath mitigation techniques in some realistic measurement-based channel models, for example, the Land Mobile Satellite (LMS) channel model [1]-[4], developed at the German Aerospace Center (DLR). The DLR LMS channel model is widely used for simulating the positioning accuracy of mobile satellite navigation receivers in urban outdoor scenarios. The main objective of this paper is to present a comprehensive analysis of some of the most promising techniques with the DLR LMS channel model in varying multipath scenarios. Four multipath mitigation techniques are chosen herein for performance comparison, namely, the narrow Early-Minus-Late (nEML), the High Resolution Correlator, the C/N0-based two stage delay tracking technique, and the Reduced Search Space Maximum Likelihood (RSSML) delay estimator. The first two techniques are the most popular and traditional ones used in nowadays GNSS receivers, whereas the later two techniques are comparatively new and are advanced techniques, recently proposed by the authors. In addition, the implementation of the RSSML is optimized here for a narrow-bandwidth receiver configuration in the sense that it now requires a significantly less number of correlators and memory than its original implementation. The simulation results show that the reduced-complexity RSSML achieves the best multipath mitigation performance in moderate-to-good carrier-to-noise density ratio with the DLR LMS channel model in varying multipath scenarios

Full-duplex MU-MIMO systems under the effects of non-ideal transceivers: performance analysis and power allocation optimization

Modern Technologies, particularly connectivity, increasingly support many facets of everyday life. The next generation of wireless communication systems aims to provide new advanced services and support new demands. These services are required to serve a massive number of devices and achieve higher spectral and energy efficiency, ultra-low latency, and reliable communication. The research community around the globe is still working on finding novel technologies to meet these requirements. Full duplex (FD) communications have been recognized as one of the promising wireless transmission candidates and gamechangers for the future of wireless communication and networking technologies, thanks to their ability to greatly improve spectral efficiency (SE) and dramatically enhance energy efficiency (EE). In this thesis, first, the influence of hardware impairment (HWI) on singleinput single-output (SISO) FD access point (AP) is studied. More precisely, the SE and EE when the system’s terminals have impaired transceivers are analyzed. Optimization problem for EE maximization is formulated to fulfill quality of service (QoS) and power budget constraints. An algorithm to solve the optimization problem by using the fractional programming theory and Karush–Kuhn–Tucker (KKT) conditions technique is proposed. [...

Multi-RIS-aided Wireless Systems: Statistical Characterization and Performance Analysis

In this paper, we study the statistical characterization and modeling of distributed multi-reconfigurable intelligent surface (RIS)-aided wireless systems. Specifically, we consider a practical system model where the RISs with different geometric sizes are distributively deployed, and wireless channels associated to different RISs are assumed to be independent but not identically distributed (i.n.i.d.). We propose two purpose-oriented multi-RIS-aided schemes, namely, the exhaustive RIS-aided (ERA) and opportunistic RIS-aided (ORA) schemes. In the ERA scheme, all RISs participate in assisting the communication of a pair of transceivers, whereas in the ORA scheme, only the most appropriate RIS participates and the remaining RISs are utilized for other purposes. A mathematical framework, which relies on the method of moments, is proposed to statistically characterize the end-to-end (e2e) channels of these schemes. It is shown that either a Gamma distribution or a LogNormal distribution can be used to approximate the distribution of the magnitude of the e2e channel coefficients in both schemes. With these findings, we evaluate the performance of the two schemes in terms of outage probability (OP) and ergodic capacity (EC), where tight approximate closed-form expressions for the OP and EC are derived. Representative results show that the ERA scheme outperforms the ORA scheme in terms of OP and EC. Nevertheless, the ORA scheme gives a better energy efficiency (EE) in a specific range of the target spectral efficiency (SE). In addition, under i.n.i.d. fading channels, the reflecting element setting and location setting of RISs have a significant impact on the overall system performance of both the ERA or ORA schemes. A centralized large-RIS-aided scheme might achieve higher EC than the distributed ERA scheme when the large-RIS is located near a transmitter or a receiver, and vise-versa

Situational Awareness Enhancement for Connected and Automated Vehicle Systems

Recent developments in the area of Connected and Automated Vehicles (CAVs) have boosted the interest in Intelligent Transportation Systems (ITSs). While ITS is intended to resolve and mitigate serious traffic issues such as passenger and pedestrian fatalities, accidents, and traffic congestion; these goals are only achievable by vehicles that are fully aware of their situation and surroundings in real-time. Therefore, connected and automated vehicle systems heavily rely on communication technologies to create a real-time map of their surrounding environment and extend their range of situational awareness. In this dissertation, we propose novel approaches to enhance situational awareness, its applications, and effective sharing of information among vehicles.;The communication technology for CAVs is known as vehicle-to-everything (V2x) communication, in which vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) have been targeted for the first round of deployment based on dedicated short-range communication (DSRC) devices for vehicles and road-side transportation infrastructures. Wireless communication among these entities creates self-organizing networks, known as Vehicular Ad-hoc Networks (VANETs). Due to the mobile, rapidly changing, and intrinsically error-prone nature of VANETs, traditional network architectures are generally unsatisfactory to address VANETs fundamental performance requirements. Therefore, we first investigate imperfections of the vehicular communication channel and propose a new modeling scheme for large-scale and small-scale components of the communication channel in dense vehicular networks. Subsequently, we introduce an innovative method for a joint modeling of the situational awareness and networking components of CAVs in a single framework. Based on these two models, we propose a novel network-aware broadcast protocol for fast broadcasting of information over multiple hops to extend the range of situational awareness. Afterward, motivated by the most common and injury-prone pedestrian crash scenarios, we extend our work by proposing an end-to-end Vehicle-to-Pedestrian (V2P) framework to provide situational awareness and hazard detection for vulnerable road users. Finally, as humans are the most spontaneous and influential entity for transportation systems, we design a learning-based driver behavior model and integrate it into our situational awareness component. Consequently, higher accuracy of situational awareness and overall system performance are achieved by exchange of more useful information

Recent Advances in RF Propagation Modeling for 5G Systems

Stefanovic, M.; Panic, SR.; De Souza, RAA.; Reig, J. (2017). Recent Advances in RF Propagation Modeling for 5G Systems. International Journal of Antennas and Propagation (Online). 2017(4701208):1-5. doi:10.1155/2017/4701208S152017470120