Caratterizzazione e generazione di segnali PWM per amplificatori in classe D ad alta efficienza

The convergence of information technology and consumer electronics towards battery powered portable devices has increased the interest in high efficiency, low dissipation amplifiers. Class D amplifiers are the state of the art in low power consumption and high performance amplification. In this thesis we explore the possibility of exploiting nonlinearities introduced by the PWM modulation, by designing an optimized modulation law which scales its carrier frequency adaptively with the input signal's average power while preserving the SNR, thus reducing power consumption. This is achieved by means of a novel analytical model of the PWM output spectrum, which shows how interfering harmonics and their bandwidth affect the spectrum. This allows for frequency scaling with negligible aliasing between the baseband spectrum and its harmonics. We performed low noise power spectrum measurements on PWM modulations generated by comparing variable bandwidth, random test signals with a variable frequency triangular wave carrier. The experimental results show that power-optimized frequency scaling is both feasible and effective. The new analytical model also suggests a new PWM architecture that can be applied to digitally encoded input signals which are predistorted and compared with a cosine carrier, which is accurately synthesized by a digital oscillator. This approach has been simulated in a realistic noisy model and tested in our measurement setup. A zero crossing search on the obtained PWM modulation law proves that this approach yields an equivalent signal quality with respect to traditional PWM schemes, while entailing the use of signals whose bandwidth is remarkably smaller due to the use of a cosine instead of a triangular carrier.

Sistemi riconfigurabili a basso consumo per applicazioni di monitoraggio distribuito

The term Ambient Intelligence (AmI) refers to a vision on the future of the information society where smart, electronic environment are sensitive and responsive to the presence of people and their activities (Context awareness). In an ambient intelligence world, devices work in concert to support people in carrying out their everyday life activities, tasks and rituals in an easy, natural way using information and intelligence that is hidden in the network connecting these devices. This promotes the creation of pervasive environments improving the quality of life of the occupants and enhancing the human experience. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. Ambient intelligent systems are heterogeneous and require an excellent cooperation between several hardware/software technologies and disciplines, including signal processing, networking and protocols, embedded systems, information management, and distributed algorithms. Since a large amount of fixed and mobile sensors embedded is deployed into the environment, the Wireless Sensor Networks is one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes which can be deployed in a target area to sense physical phenomena and communicate with other nodes and base stations. These simple devices typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). WNS promises of revolutionizing the interactions between the real physical worlds and human beings. Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. To fully exploit the potential of distributed sensing approaches, a set of challengesmust be addressed. Sensor nodes are inherently resource-constrained systems with very low power consumption and small size requirements which enables than to reduce the interference on the physical phenomena sensed and to allow easy and low-cost deployment. They have limited processing speed,storage capacity and communication bandwidth that must be efficiently used to increase the degree of local ”understanding” of the observed phenomena. A particular case of sensor nodes are video sensors. This topic holds strong interest for a wide range of contexts such as military, security, robotics and most recently consumer applications. Vision sensors are extremely effective for medium to long-range sensing because vision provides rich information to human operators. However, image sensors generate a huge amount of data, whichmust be heavily processed before it is transmitted due to the scarce bandwidth capability of radio interfaces. In particular, in video-surveillance, it has been shown that source-side compression is mandatory due to limited bandwidth and delay constraints. Moreover, there is an ample opportunity for performing higher-level processing functions, such as object recognition that has the potential to drastically reduce the required bandwidth (e.g. by transmitting compressed images only when something ‘interesting‘ is detected). The energy cost of image processing must however be carefully minimized. Imaging could play and plays an important role in sensing devices for ambient intelligence. Computer vision can for instance be used for recognising persons and objects and recognising behaviour such as illness and rioting. Having a wireless camera as a camera mote opens the way for distributed scene analysis. More eyes see more than one and a camera system that can observe a scene from multiple directions would be able to overcome occlusion problems and could describe objects in their true 3D appearance. In real-time, these approaches are a recently opened field of research. In this thesis we pay attention to the realities of hardware/software technologies and the design needed to realize systems for distributed monitoring, attempting to propose solutions on open issues and filling the gap between AmI scenarios and hardware reality. The physical implementation of an individual wireless node is constrained by three important metrics which are outlined below. Despite that the design of the sensor network and its sensor nodes is strictly application dependent, a number of constraints should almost always be considered. Among them: • Small form factor to reduce nodes intrusiveness. • Low power consumption to reduce battery size and to extend nodes lifetime. • Low cost for a widespread diffusion. These limitations typically result in the adoption of low power, low cost devices such as low powermicrocontrollers with few kilobytes of RAMand tenth of kilobytes of program memory with whomonly simple data processing algorithms can be implemented. However the overall computational power of the WNS can be very large since the network presents a high degree of parallelism that can be exploited through the adoption of ad-hoc techniques. Furthermore through the fusion of information from the dense mesh of sensors even complex phenomena can be monitored. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas:Low Power Video Sensor Node and Video Processing Alghoritm and Multimodal Surveillance . Low Power Video Sensor Nodes and Video Processing Alghoritms In comparison to scalar sensors, such as temperature, pressure, humidity, velocity, and acceleration sensors, vision sensors generate much higher bandwidth data due to the two-dimensional nature of their pixel array. We have tackled all the constraints listed above and have proposed solutions to overcome the current WSNlimits for Video sensor node. We have designed and developed wireless video sensor nodes focusing on the small size and the flexibility of reuse in different applications. The video nodes target a different design point: the portability (on-board power supply, wireless communication), a scanty power budget (500mW),while still providing a prominent level of intelligence, namely sophisticated classification algorithmand high level of reconfigurability. We developed two different video sensor node: The device architecture of the first one is based on a low-cost low-power FPGA+microcontroller system-on-chip. The second one is based on ARM9 processor. Both systems designed within the above mentioned power envelope could operate in a continuous fashion with Li-Polymer battery pack and solar panel. Novel low power low cost video sensor nodes which, in contrast to sensors that just watch the world, are capable of comprehending the perceived information in order to interpret it locally, are presented. Featuring such intelligence, these nodes would be able to cope with such tasks as recognition of unattended bags in airports, persons carrying potentially dangerous objects, etc.,which normally require a human operator. Vision algorithms for object detection, acquisition like human detection with Support Vector Machine (SVM) classification and abandoned/removed object detection are implemented, described and illustrated on real world data. Multimodal surveillance: In several setup the use of wired video cameras may not be possible. For this reason building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. Energy efficiency for wireless smart camera networks is one of the major efforts in distributed monitoring and surveillance community. For this reason, building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. The Pyroelectric Infra-Red (PIR) sensors have been used to extend the lifetime of a solar-powered video sensor node by providing an energy level dependent trigger to the video camera and the wireless module. Such approach has shown to be able to extend node lifetime and possibly result in continuous operation of the node.Being low-cost, passive (thus low-power) and presenting a limited form factor, PIR sensors are well suited for WSN applications. Moreover techniques to have aggressive power management policies are essential for achieving long-termoperating on standalone distributed cameras needed to improve the power consumption. We have used an adaptive controller like Model Predictive Control (MPC) to help the system to improve the performances outperforming naive power management policies.

Progetto di un convertitore di potenza da sorgenti fotovoltaiche in regime di basso irraggiamento

L’obiettivo di questa tesi è il progetto di un convertitore di potenza di tipo low power da applicare a sorgenti fotovoltaiche in regime di basso irraggiamento. Il convertitore implementa un controllo con inseguimento del punto di massima potenza (maximum power point tracking) della caratteristica della sorgente fotovoltaica. Una prima parte è dedicata allo studio delle possibilità esistenti in materia di convertitori e di algoritmi di MPPT. Successivamente, in base alle specifiche di progetto è stata selezionata una combinazione ottimale per l'architettura del convertitore di potenza in grado di bilanciare efficienza dell'algoritmo di controllo e requisiti intrinseci di potenza.

A hybrid technology for parallel recording of single ion channels

Hybrid technologies, thanks to the convergence of integrated microelectronic devices and new class of microfluidic structures could open new perspectives to the way how nanoscale events are discovered, monitored and controlled. The key point of this thesis is to evaluate the impact of such an approach into applications of ion-channel High Throughput Screening (HTS)platforms. This approach offers promising opportunities for the development of new classes of sensitive, reliable and cheap sensors. There are numerous advantages of embedding microelectronic readout structures strictly coupled to sensing elements. On the one hand the signal-to-noise-ratio is increased as a result of scaling. On the other, the readout miniaturization allows organization of sensors into arrays, increasing the capability of the platform in terms of number of acquired data, as required in the HTS approach, to improve sensing accuracy and reliabiity. However, accurate interface design is required to establish efficient communication between ionic-based and electronic-based signals. The work made in this thesis will show a first example of a complete parallel readout system with single ion channel resolution, using a compact and scalable hybrid architecture suitable to be interfaced to large array of sensors, ensuring simultaneous signal recording and smart control of the signal-to-noise ratio and bandwidth trade off. More specifically, an array of microfluidic polymer structures, hosting artificial lipid bilayers blocks where single ion channel pores are embededed, is coupled with an array of ultra-low noise current amplifiers for signal amplification and data processing. As demonstrating working example, the platform was used to acquire ultra small currents derived by single non-covalent molecular binding between alpha-hemolysin pores and beta-cyclodextrin molecules in artificial lipid membranes.

Convertitori di potenza multi-sorgente per applicazioni di energy harvesting

L’obiettivo di questa tesi è stato lo svilippo di un convertitore di potenza per applicazioni di energy harvesting in grado di convogliare l’energia estratta da diversi tipi di trasduttori di grandezze ambientali in un unico dispositivo di storage, ad es. un condensatore, utilizzabile per alimentare circuiti a basso consumo. L’idea di base è stata quella di ottimizzare il trasferimento di energia, attraverso una rete logica in grado di gestire le priorità di conversione dalle diverse tipologie di sorgenti e grazie ad una implementazione di un algoritmo di Maximum Power Point Tracking. In base alle specifiche di progetto, in una prima fase è stata sviluppata la rete a livello funzionale, poi sono stati scelti i componenti più opportuni ed infine si è verificato il funzionamento attraverso simulazioni circuitali.

Advanced CMOS Interfaces for Bio-Nanosensors

The improvement of devices provided by Nanotechnology has put forward new classes of sensors, called bio-nanosensors, which are very promising for the detection of biochemical molecules in a large variety of applications. Their use in lab-on-a-chip could gives rise to new opportunities in many fields, from health-care and bio-warfare to environmental and high-throughput screening for pharmaceutical industry. Bio-nanosensors have great advantages in terms of cost, performance, and parallelization. Indeed, they require very low quantities of reagents and improve the overall signal-to-noise-ratio due to increase of binding signal variations vs. area and reduction of stray capacitances. Additionally, they give rise to new challenges, such as the need to design high-performance low-noise integrated electronic interfaces. This thesis is related to the design of high-performance advanced CMOS interfaces for electrochemical bio-nanosensors. The main focus of the thesis is: 1) critical analysis of noise in sensing interfaces, 2) devising new techniques for noise reduction in discrete-time approaches, 3) developing new architectures for low-noise, low-power sensing interfaces. The manuscript reports a multi-project activity focusing on low-noise design and presents two developed integrated circuits (ICs) as examples of advanced CMOS interfaces for bio-nanosensors. The first project concerns low-noise current-sensing interface for DC and transient measurements of electrophysiological signals. The focus of this research activity is on the noise optimization of the electronic interface. A new noise reduction technique has been developed so as to realize an integrated CMOS interfaces with performance comparable with state-of-the-art instrumentations. The second project intends to realize a stand-alone, high-accuracy electrochemical impedance spectroscopy interface. The system is tailored for conductivity-temperature-depth sensors in environmental applications, as well as for bio-nanosensors. It is based on a band-pass delta-sigma technique and combines low-noise performance with low-power requirements.

Analysis of charge-transport properties in GST materials for next generation phase-change memory devices

The quest for universal memory is driving the rapid development of memories with superior all-round capabilities in non-volatility, high speed, high endurance and low power. The memory subsystem accounts for a significant cost and power budget of a computer system. Current DRAM-based main memory systems are starting to hit the power and cost limit. To resolve this issue the industry is improving existing technologies such as Flash and exploring new ones. Among those new technologies is the Phase Change Memory (PCM), which overcomes some of the shortcomings of the Flash such as durability and scalability. This alternative non-volatile memory technology, which uses resistance contrast in phase-change materials, offers more density relative to DRAM, and can help to increase main memory capacity of future systems while remaining within the cost and power constraints. Chalcogenide materials can suitably be exploited for manufacturing phase-change memory devices. Charge transport in amorphous chalcogenide-GST used for memory devices is modeled using two contributions: hopping of trapped electrons and motion of band electrons in extended states. Crystalline GST exhibits an almost Ohmic I(V) curve. In contrast amorphous GST shows a high resistance at low biases while, above a threshold voltage, a transition takes place from a highly resistive to a conductive state, characterized by a negative differential-resistance behavior. A clear and complete understanding of the threshold behavior of the amorphous phase is fundamental for exploiting such materials in the fabrication of innovative nonvolatile memories. The type of feedback that produces the snapback phenomenon is described as a filamentation in energy that is controlled by electron–electron interactions between trapped electrons and band electrons. The model thus derived is implemented within a state-of-the-art simulator. An analytical version of the model is also derived and is useful for discussing the snapback behavior and the scaling properties of the device.

Sparse Signal Representation of Ultrasonic Signals for Structural Health Monitoring Applications

Assessment of the integrity of structural components is of great importance for aerospace systems, land and marine transportation, civil infrastructures and other biological and mechanical applications. Guided waves (GWs) based inspections are an attractive mean for structural health monitoring. In this thesis, the study and development of techniques for GW ultrasound signal analysis and compression in the context of non-destructive testing of structures will be presented. In guided wave inspections, it is necessary to address the problem of the dispersion compensation. A signal processing approach based on frequency warping was adopted. Such operator maps the frequencies axis through a function derived by the group velocity of the test material and it is used to remove the dependence on the travelled distance from the acquired signals. Such processing strategy was fruitfully applied for impact location and damage localization tasks in composite and aluminum panels. It has been shown that, basing on this processing tool, low power embedded system for GW structural monitoring can be implemented. Finally, a new procedure based on Compressive Sensing has been developed and applied for data reduction. Such procedure has also a beneficial effect in enhancing the accuracy of structural defects localization. This algorithm uses the convolutive model of the propagation of ultrasonic guided waves which takes advantage of a sparse signal representation in the warped frequency domain. The recovery from the compressed samples is based on an alternating minimization procedure which achieves both an accurate reconstruction of the ultrasonic signal and a precise estimation of waves time of flight. Such information is used to feed hyperbolic or elliptic localization procedures, for accurate impact or damage localization.

Giunzione mediante laser di materiali difficili, ibridi ed a struttura cellulare

Lo studio presentato in questa sede concerne applicazioni di saldatura LASER caratterizzate da aspetti di non-convenzionalità ed è costituito da tre filoni principali. Nel primo ambito di intervento è stata valutata la possibilità di effettuare saldature per fusione, con LASER ad emissione continua, su pannelli Aluminum Foam Sandwich e su tubi riempiti in schiuma di alluminio. Lo studio ha messo in evidenza numerose linee operative riguardanti le problematiche relative alla saldatura delle pelli esterne dei componenti ed ha dimostrato la fattibilità relativa ad un approccio di giunzione LASER integrato (saldatura seguita da un post trattamento termico) per la realizzazione della giunzione completa di particolari tubolari riempiti in schiuma con ripristino della struttura cellulare all’interfaccia di giunzione. Il secondo ambito di intervento è caratterizzato dall’applicazione di una sorgente LASER di bassissima potenza, operante in regime ad impulsi corti, nella saldatura di acciaio ad elevato contenuto di carbonio. Lo studio ha messo in evidenza come questo tipo di sorgente, solitamente applicata per lavorazioni di ablazione e marcatura, possa essere applicata anche alla saldatura di spessori sub-millimetrici. In questa fase è stato messo in evidenza il ruolo dei parametri di lavoro sulla conformazione del giunto ed è stata definita l’area di fattibilità del processo. Lo studio è stato completato investigando la possibilità di applicare un trattamento LASER dopo saldatura per addolcire le eventuali zone indurite. In merito all’ultimo ambito di intervento l’attività di studio si è focalizzata sull’utilizzo di sorgenti ad elevata densità di potenza (60 MW/cm^2) nella saldatura a profonda penetrazione di acciai da costruzione. L’attività sperimentale e di analisi dei risultati è stata condotta mediante tecniche di Design of Experiment per la valutazione del ruolo preciso di tutti i parametri di processo e numerose considerazioni relative alla formazione di cricche a caldo sono state suggerite.

Self-Assembled Monolayers (SAMs) in Organic Field-Effect Transistors

Organic printed electronics is attracting an ever-growing interest in the last decades because of its impressive breakthroughs concerning the chemical design of π-conjugated materials and their processing. This has an impact on novel applications, such as flexible-large-area displays, low- cost printable circuits, plastic solar cells and lab-on-a-chip devices. The organic field-effect transistor (OFET) relies on a thin film of organic semiconductor that bridges source and drain electrodes. Since its first discovery in the 80s, intensive research activities were deployed in order to control the chemico-physical properties of these electronic devices and consequently their charge. Self-assembled monolayers (SAMs) are a versatile tool for tuning the properties of metallic, semi-conducting, and insulating surfaces. Within this context, OFETs represent reliable instruments for measuring the electrical properties of the SAMs in a Metal/SAM/OS junction. Our experimental approach, named Charge Injection Organic-Gauge (CIOG), uses OTFT in a charge-injection controlled regime. The CIOG sensitivity has been extensively demonstrated on different homologous self-assembling molecules that differ in either chain length or in anchor/terminal group. One of the latest applications of organic electronics is the so-called “bio-electronics” that makes use of electronic devices to encompass interests of the medical science, such as biosensors, biotransducers etc… As a result, thee second part of this thesis deals with the realization of an electronic transducer based on an Organic Field-Effect Transistor operating in aqueous media. Here, the conventional bottom gate/bottom contact configuration is replaced by top gate architecture with the electrolyte that ensures electrical contact between the top gold electrode and the semiconductor layer. This configuration is named Electrolyte-Gated Field-Effect Transistor (EGOFET). The functionalization of the top electrode is the sensing core of the device allowing the detection of dopamine as well as of protein biomarkers with ultra-low sensitivity.

Implementazione di un circuito estrattore di carica quasi-sincrono da trasduttori piezoelettrici

La tecnologia odierna, orientata sempre di più verso il “low-power”, ha permesso di poter sviluppare sistemi elettronici in grado di autoalimentarsi senza alcun bisogno di sorgenti di energia tradizionali. Questo è possibile, ad esempio, utilizzando trasduttori piezoelettrici, in grado di trasformare l’energia meccanica, provocata ad esempio da una vibrazione, in un’altra forma di energia che, in tal caso, risulta essere una grandezza elettrica. Il settore principale in cui viene impiegato questo componente è quello dell’Energy Harvesting, ovvero un campo dell’elettronica in cui si cerca di estrarre dall'ambiente circostante bassissime quantità di energia mediante tecniche opportune, cercando di ridurre i consumi dei circuiti di controllo annessi e renderli, in maggior parte, il più possibile autosufficienti. L’obiettivo è quello di implementare alcune tecniche di recupero dell’energia mediante circuiti gestiti a microcontrollore e valutare se tali metodiche portino a risultati accettabili in grado di soddisfare quelli che sono i requisiti che il mondo dell’Energy Harvesting richiede.

Scene Reconstruction And Understanding By RGB-D Sensors

This thesis investigates interactive scene reconstruction and understanding using RGB-D data only. Indeed, we believe that depth cameras will still be in the near future a cheap and low-power 3D sensing alternative suitable for mobile devices too. Therefore, our contributions build on top of state-of-the-art approaches to achieve advances in three main challenging scenarios, namely mobile mapping, large scale surface reconstruction and semantic modeling. First, we will describe an effective approach dealing with Simultaneous Localization And Mapping (SLAM) on platforms with limited resources, such as a tablet device. Unlike previous methods, dense reconstruction is achieved by reprojection of RGB-D frames, while local consistency is maintained by deploying relative bundle adjustment principles. We will show quantitative results comparing our technique to the state-of-the-art as well as detailed reconstruction of various environments ranging from rooms to small apartments. Then, we will address large scale surface modeling from depth maps exploiting parallel GPU computing. We will develop a real-time camera tracking method based on the popular KinectFusion system and an online surface alignment technique capable of counteracting drift errors and closing small loops. We will show very high quality meshes outperforming existing methods on publicly available datasets as well as on data recorded with our RGB-D camera even in complete darkness. Finally, we will move to our Semantic Bundle Adjustment framework to effectively combine object detection and SLAM in a unified system. Though the mathematical framework we will describe does not restrict to a particular sensing technology, in the experimental section we will refer, again, only to RGB-D sensing. We will discuss successful implementations of our algorithm showing the benefit of a joint object detection, camera tracking and environment mapping.

Microfluidic microbial fuel cell fabrication and rapid screening of electrochemically microbes

The demand for novel renewable energy sources, together with the new findings on bacterial electron transport mechanisms and the progress in microbial fuel cell design, have raised a noticeable interest in microbial power generation. Microbial fuel cell (MFC) is an electrochemical device that converts organic substrates into electricity via catalytic conversion by microorganism. It has represented a continuously growing research field during the past few years. The great advantage of this device is the direct conversion of the substrate into electricity and in the future, MFC may be linked to municipal waste streams or sources of agricultural and animal waste, providing a sustainable system for waste treatment and energy production. However, these novel green technologies have not yet been used for practical applications due to their low power outputs and challenges associated with scale-up, so in-depth studies are highly necessary to significantly improve and optimize the device working conditions. For the time being, the micro-scale MFCs show great potential in the rapid screening of electrochemically active microbes. This thesis presents how it will be possible to optimize the properties and design of the micro-size microbial fuel cell for maximum efficiency by understanding the MFC system. So it will involve designing, building and testing a miniature microbial fuel cell using a new species of microorganisms that promises high efficiency and long lifetime. The new device offer unique advantages of fast start-up, high sensitivity and superior microfluidic control over the measured microenvironment, which makes them good candidates for rapid screening of electrode materials, bacterial strains and growth media. It will be made in the Centre of Hybrid Biodevices (Faculty of Physical Sciences and Engineering, University of Southampton) from polymer materials like PDMS. The eventual aim is to develop a system with the optimum combination of microorganism, ion exchange membrane and growth medium. After fabricating the cell, different bacteria and plankton species will be grown in the device and the microbial fuel cell characterized for open circuit voltage and power. It will also use photo-sensitive organisms and characterize the power produced by the device in response to optical illumination.

Energy-efficient Communication and Estimation in Wireless Sensor Networks

This thesis focuses on the energy efficiency in wireless networks under the transmission and information diffusion points of view. In particular, on one hand, the communication efficiency is investigated, attempting to reduce the consumption during transmissions, while on the other hand the energy efficiency of the procedures required to distribute the information among wireless nodes in complex networks is taken into account. For what concerns energy efficient communications, an innovative transmission scheme reusing source of opportunity signals is introduced. This kind of signals has never been previously studied in literature for communication purposes. The scope is to provide a way for transmitting information with energy consumption close to zero. On the theoretical side, starting from a general communication channel model subject to a limited input amplitude, the theme of low power transmission signals is tackled under the perspective of stating sufficient conditions for the capacity achieving input distribution to be discrete. Finally, the focus is shifted towards the design of energy efficient algorithms for the diffusion of information. In particular, the endeavours are aimed at solving an estimation problem distributed over a wireless sensor network. The proposed solutions are deeply analyzed both to ensure their energy efficiency and to guarantee their robustness against losses during the diffusion of information (against information diffusion truncation more in general).

Mac protocols for linear wireless (sensor) networks

Wireless sensor networks (WSNs) consist of a large number of sensor nodes, characterized by low power constraint, limited transmission range and limited computational capabilities [1][2].The cost of these devices is constantly decreasing, making it possible to use a large number of sensor devices in a wide array of commercial, environmental, military, and healthcare fields. Some of these applications involve placing the sensors evenly spaced on a straight line for example in roads, bridges, tunnels, water catchments and water pipelines, city drainages, oil and gas pipelines etc., making a special class of these networks which we define as a Linear Wireless Network (LWN). In LWNs, data transmission happens hop by hop from the source to the destination, through a route composed of multiple relays. The peculiarity of the topology of LWNs, motivates the design of specialized protocols, taking advantage of the linearity of such networks, in order to increase reliability, communication efficiency, energy savings, network lifetime and to minimize the end-to-end delay [3]. In this thesis a novel contention based Medium Access Control (MAC) protocol called L-CSMA, specifically devised for LWNs is presented. The basic idea of L-CSMA is to assign different priorities to nodes based on their position along the line. The priority is assigned in terms of sensing duration, whereby nodes closer to the destination are assigned shorter sensing time compared to the rest of the nodes and hence higher priority. This mechanism speeds up the transmission of packets which are already in the path, making transmission flow more efficient. Using NS-3 simulator, the performance of L-CSMA in terms of packets success rate, that is, the percentage of packets that reach destination, and throughput are compared with that of IEEE 802.15.4 MAC protocol, de-facto standard for wireless sensor networks. In general, L-CSMA outperforms the IEEE 802.15.4 MAC protocol.