A low-cost time-hopping impulse radio system for high data rate transmission

We present an efficient, low-cost implementation of time-hopping impulse radio that fulfills the spectral mask mandated by the FCC and is suitable for high-data-rate, short-range communications. Key features are: (i) all-baseband implementation that obviates the need for passband components, (ii) symbol-rate (not chip rate) sampling, A/D conversion, and digital signal processing, (iii) fast acquisition due to novel search algorithms, (iv) spectral shaping that can be adapted to accommodate different spectrum regulations and interference environments. Computer simulations show that this system can provide 110Mbit/s at 7-10m distance, as well as higher data rates at shorter distances under FCC emissions limits. Due to the spreading concept of time-hopping impulse radio, the system can sustain multiple simultaneous users, and can suppress narrowband interference effectively.Comment: To appear in EURASIP Journal on Applied Signal Processing (Special Issue on UWB - State of the Art

DQLEL: Deep Q-Learning for Energy-Optimized LoS/NLoS UWB Node Selection

Recent advancements in Internet of Things (IoTs) have brought about a surge of interest in indoor positioning for the purpose of providing reliable, accurate, and energy-efficient indoor navigation/localization systems. Ultra Wide Band (UWB) technology has been emerged as a potential candidate to satisfy the aforementioned requirements. Although UWB technology can enhance the accuracy of indoor positioning due to the use of a wide-frequency spectrum, there are key challenges ahead for its efficient implementation. On the one hand, achieving high precision in positioning relies on the identification/mitigation Non Line of Sight (NLoS) links, leading to a significant increase in the complexity of the localization framework. On the other hand, UWB beacons have a limited battery life, which is especially problematic in practical circumstances with certain beacons located in strategic positions. To address these challenges, we introduce an efficient node selection framework to enhance the location accuracy without using complex NLoS mitigation methods, while maintaining a balance between the remaining battery life of UWB beacons. Referred to as the Deep Q-Learning Energy-optimized LoS/NLoS (DQLEL) UWB node selection framework, the mobile user is autonomously trained to determine the optimal set of UWB beacons to be localized based on the 2-D Time Difference of Arrival (TDoA) framework. The effectiveness of the proposed DQLEL framework is evaluated in terms of the link condition, the deviation of the remaining battery life of UWB beacons, location error, and cumulative rewards. Based on the simulation results, the proposed DQLEL framework significantly outperformed its counterparts across the aforementioned aspects

Stochastic Modeling and Estimation of Wireless Channels with Application to Ultra Wide Band Systems

This thesis is concerned with modeling of both space and time variations of Ultra Wide Band (UWB) indoor channels. The most common empirically determined amplitude distribution in many UWB environments is Nakagami distribution. The latter is generalized to stochastic diffusion processes which capture the dynamics of UWB channels. In contrast with the traditional models, the statistics of the proposed models are shown to be time varying, but converge in steady state to their static counterparts. System identification algorithms are used to extract various channel parameters using received signal measurement data, which are usually available at the receiver. The expectation maximization (EM) algorithm and the Kalman filter (KF) are employed in estimating channel parameters as well as the inphase and quadrature components, respectively. The proposed algorithms are recursive and therefore can be implemented in real time. Further, sufficient conditions for the convergence of the EM algorithm are provided. Comparison with recursive Least-square (LS) algorithms is carried out using experimental measurements. Distributed stochastic power control algorithms based on the fixed point theorem and stochastic approximations are used to solve for the optimal transmit power problem and numerical results are also presented. A framework which can capture the statistics of the overall received signal and a methodology to estimate parameters of the counting process based on the received signal is developed. Furthermore, second moment statistics and characteristic functions are computed explicitly and considered as an extension of Rice’s shot noise analysis. Another two important components, input design and model selection are also considered. Gel’fand n-widths and Time n-widths are used to represent the inherent error introduced by input design. Kolmogorov n-width is used to characterize the representation error introduced by model selection. In particular, it is shown that the optimal model for reducing the representation error is a finite impulse response (FIR) model and the optimal input is an impulse at the start of the observation interval

Cognitive routing models

This paper investigates the effect of introducing cognitive mechanisms in the routing module of a wireless network. A routing cost function that incorporates measurements of both internal network status and instantaneous behavior of external world is described. The proposed cost function is analyzed by simulation in the framework of IEEE 802.1.5.4a-like low data rate and low cost networks for mixed indoor/outdoor communications. The analysis focuses on the impact of MUI modeling on network performance. Results indicate that MUI-awareness, as provided by the proposed cognitive cost function, may improve network performance in terms of network lifetime. Based on this analysis, a mechanism for learning from previous routing decisions and adapting the routing cost function to MUI conditions is introduced

A Review on suboptimal power allocation schemes for WSN localization

This paper considers a review of two proposed power allocation algorithms for increasing accuracy in localization scenarios, a deeper theoretical analysis and a detailed performance comparison. Appropriate power allocation (PA) among beacons is an effective tool to implement localization with improved precision. At first, a brief review on existing optimal PA strategies is presented. Subsequently, the first PA algorithm is discussed: a function called uncertainty area is defined according to the interaction of beacons in a pair-wise selection procedure. A general selection strategy among allocated transmission powers for each beacon completes the algorithm structure. In the literature, on one hand the commonly made assumption about ranging measures is that their ideal values are equal to their corresponding Cramer-Rao bounds but, on the other hand, at high signal-to-noise ratios, real ranging estimators are characterized by different lower limits on their performance, mainly as a result of maximum sampling rates and computational load available in the sensors. The second PA algorithm develops a type of adaptive PA (APA) directly based on measured SNRs and, consequently, much simpler than other techniques

Code-Multiplexing-Based One-Way Detect-and-Forward Relaying Schemes for Multiuser UWB MIMO Systems

In this paper, we consider decode-and-forward (DF) one-way relaying schemes for multiuser impulse-radio ultrawideband (UWB) communications. We assume low-complexity terminals with limited processing capabilities and a central transceiver unit (i.e., the relay) with a higher computational capacity. All nodes have a single antenna differently from the relay in which multiple antennas may be installed. In order to keep the complexity as low as possible, we concentrate on noncoherent transceiver architectures based on multiuser code-multiplexing transmitted-reference schemes. We propose various relaying systems with different computational complexity and different levels of required channel knowledge. The proposed schemes largely outperform systems without relay in terms of both bit error rate (BER) performance and coverage

Relaying Techniques for Multi Hop Differential Transmitted Reference IR-UWB Systems

This thesis develops novel relaying techniques to overcome the limited coverage of Impulse Radio Ultra Wideband (IR-UWB) systems based on Differential Transmitted Reference (DTR). Firstly, we describe a cooperative approach for two hop Amplify-and-Forward (A&F) relaying that exploits both the signal forwarded by the relay and the one directly transmitted by the source. After deriving the log-likelihood ratio based decision rule, we propose a semi-analytical power allocation strategy by evaluating a closed form expression for the effective Signal to Noise Ratio (SNR) at the destination, which is maximized by exhaustive search. Successively, we present a Joint Power Allocation and Path Selection (JPAPS) method for multi hop Decode-and-Forward (D&F) relaying. Starting from the heuristic consideration that the overall Bit Error Rate (BER) of the system is essentially driven by the quality of the path with the best performance, the proposed technique associates to each possible route a metric given by an approximation of the minimum BER which can be achieved as the power allocation coefficients vary and then takes into account only the path minimizing that metric. Specifically, we employ an equal SNR power allocation strategy that yields a closed form expression for the power allocation coefficients and we describe a path selection algorithm with polynomial complexity. Simulation results show the remarkable SNR gains obtained by the proposed schemes with respect to direct transmission and existing relaying techniques. Lo scopo di questa tesi è elaborare nuove tecniche di relaying per risolvere il problema della copertura limitata in sistemi radio ad impulsi a banda ultra larga (Impulse-Radio Ultra-Wideband, IR-UWB) basati su Differential Transmitted Reference (DTR). Innanzi tutto, si descrive un approccio cooperativo per singolo relay Amplify-and-Forward (A&F) che sfrutta sia il segnale inoltrato dal relay sia quello trasmesso direttamente dalla sorgente. Dopo aver introdotto una regola di decisione basata sul logaritmo del rapporto di verosimiglianza, si propone una strategia di allocazione di potenza semi-analitica valutando un'espressione in forma chiusa per il rapporto segnale rumore (SNR) effettivo al nodo destinazione, che viene massimizzato per mezzo di una ricerca esaustiva. Successivamente, si presenta un metodo congiunto di allocazione di potenza e scelta del cammino ottimo (Joint Power Allocation and Path Selection, JPAPS) per relay Decode-and-Forward (D&F) multipli. Partendo dalla considerazione euristica che la probabilità d'errore complessiva del sistema dipende essenzialmente dalla qualità del cammino migliore, la tecnica proposta associa ad ogni possibile percorso una metrica data da un'approssimazione della minima probabilità d'errore ottenibile al variare dei coefficienti di allocazione di potenza e poi prende in considerazione soltanto il cammino che minimizza tale metrica. Specificatamente, si adopera una strategia di allocazione di potenza in cui si impone l'uguaglianza degli SNR dei singoli link (equal SNR power allocation strategy), ottenendo un'espressione in forma chiusa per i coefficienti di allocazione di potenza. Inoltre, si descrive un algoritmo di scelta del cammino ottimo con complessità polinomiale. I risultati delle simulazioni mostrano i notevoli guadagni in termini di SNR ottenuti dagli schemi proposti rispetto alla trasmissione diretta e alle altre tecniche di relaying esistenti