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Μόνιμο URI για αυτήν τη συλλογήhttps://dspace.library.tuc.gr/handle/123456789/121

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Channel coding and detection for increased range bistatic scatter radio
(Technical University of Crete, 2014) Alevizos Panagiotis; Αλεβιζος Παναγιωτης; Bletsas Aggelos; Μπλετσας Αγγελος; Karystinos Georgios; Καρυστινος Γεωργιος; Deligiannakis Antonios; Δεληγιαννακης Αντωνιος
Scatter radio, i.e communication by means of reflection, has emerged as a potential key-enabling technology for ultra low-cost, large-scale, ubiquitous sensor networking. This work jointly studies noncoherent detection and channel coding for scatter radio networks, with the ultimate goal to further extend communication range, compared to prior art. Specifically, this work focuses on frequency shift keying modulation (FSK) in bistatic scatter radio architectures, where carrier emitter is dislocated from the software defined radio receiver (SDR). FSK is ideal for the power limited regime and allows for simple, frequency division multiple access (FDMA) of simultaneously operating receiver-less sensors. A novel composite hypothesis testing decoding rule is derived for noncoherent channel-encoded FSK, in bistatic scatter radio architectures. Such decoding rule is evaluated with short block length channel codes; the latter offer ultra-low encoding complexity, and thus, they are appropriate for resource-constraint scatter radio sensors. Reed-Muller and BCH codes are studied, due to their strong algebraic structure. It is shown that the proposed decoding scheme achieves high diversity order through interleaving. Extensive simulations under Rician fading scenarios include the impact of carrier frequency offset estimation errors, channel coherence time and interleaving depth. Closed-form performance analysis is also provided. Theoretical analysis for maximum likelihood coherent detection and decoding in on-off keying modulation (OOK) is also presented. Furthermore, experimental measurements are conducted outdoors, with a commodity SDR reader and custom scatter radio sensor. Sensor-to-reader ranges up to 134 meters are experimentally demonstrated with omnidirectional antennas and 13 dBm (20 milliWatt) transmission power. Coded setup offered 10 additional meters range extension compared to the state-of-the-art uncoded noncoherent detection. As a result, this thesis provided a simple solution that could further leverage the adoption of scatter radio in large-scale, ultra low-cost wireless sensor networks
Coherent detection and channel coding for backscatter sensor networks
(Πολυτεχνείο Κρήτης, 2014) Fasarakis-Chilliarnt Nikos; Φασαρακης-Χιλλιαρντ Νικος; Bletsas Aggelos; Μπλετσας Αγγελος; Karystinos Georgios; Καρυστινος Γεωργιος; Deligiannakis Antonios; Δεληγιαννακης Αντωνιος
Full-rate fifferential M-PSK Alamouti modulation with polunomial-complexity maximum-likelihood noncoherent detection
(Technical University of Crete, 2012) Markopoulos Panagiotis; Μαρκοπουλος Παναγιωτης; Karystinos Georgios; Καρυστινος Γεωργιος; Liavas Athanasios; Λιαβας Αθανασιος; Bletsas Aggelos; Μπλετσας Αγγελος
Grammatical inference for event recognition
(Πολυτεχνείο Κρήτης, 2014) Kofinas Nikolaos; Κοφινας Νικολαος; Lagoudakis Michael; Λαγουδακης Μιχαηλ; Bletsas Aggelos; Μπλετσας Αγγελος; Garofalakis Minos; Γαροφαλακης Μινως
As robot technology finds applications in the real world (search and rescue, daily household tasks, etc.), huge amounts of data are generated during autonomous robot missions. In such applications, it is often desirable to recognize high-level events that may have occurred during a mission either online or offline. Event Recognition in robot missions currently relies on human expertise and time-consuming data annotation. A modern method to recognize events is to employ Probabilistic Context-Free Grammars (PCFGs), which are formal models that can capture complex patterns in discrete sequences and can be used to parse incoming sensor data streams in order to detect patterns that may signal the occurrence of some event of interest. Recent experimentation with such methods on data from Autonomous Underwater Vehicle (AUV) missions indicated that interesting events can be recognized by parsing sequences of sensor data using an intuitive hand-written PCFG. This thesis introduces a generic procedure which can be used to automatically construct PCFGs which encode sensor data sequences that typically appear during normal robot operation using recorded logs from past missions. The resulting PCFGs can be used to recognize abnormal events in new missions evidenced by sensor data sequences which cannot be interpreted as normal. The proposed procedure consists of two parts: (a) the transformation of sensor streams into discrete sequences either to form a training corpus offline or to generate input for online parsing and (b) a Grammatical Inference algorithm in order to learn a compact PCFG consistent with a given training corpus. The learning part relies on a local search method over the space of possible grammars using chunk and merge operations. The search method aims to find a compact grammar that also maximizes its posterior probability, in a Bayesian sense, with respect to a given training corpus. The proposed procedure is evaluated on a variety of domains ranging from data-sets generated by typical context-free grammars to data-sets generated from real robot missions (NAO robot walk and AUV navigation). The results indicate that our approach is capable of producing reliable PCFG-based event recognizers, which may yield some false positive signals, but in general succeed in capturing abnormalities.
Non-coherent receivers for zero-feedback distributed beamforming in connectivity-constrained wireless sensor networks (WSNs)
(Πολυτεχνείο Κρήτης, 2014) Alexandris Konstantinos; Αλεξανδρης Κωνσταντινος; Bletsas Aggelos; Μπλετσας Αγγελος; Karystinos Georgios; Καρυστινος Γεωργιος; Liavas Athanasios; Λιαβας Αθανασιος
Power-constrained wireless sensor networks (WSNs) suffer from network partitioning problems. In many cases, each node among a network subset, cannot reliably communicate with a distant receiver even when transmitting at maximum power. Thus, a collaborative beamforming scheme among the distributed adjacent terminals is needed in terms of power addition. Prior art on distributed beamforming has mainly focused on feedback messages for channel estimation (CSI) or physical layer carrier phase adjustments. In sharp constrast, this thesis assumes commodity radios and studies the low signal to-noise-ratio (SNR) regime, where accurate channel estimation is not feasible and no reliable feedback exists. The main idea is to exploit recently proposed zero-feedback distributed beamforming and design specific non-coherent receivers. Towards that goal, three concrete non-coherent receivers are presented for zero-feedback distributed beamforming (ZF-DBF); one based on energy detection, one based on maximum-likelihood for a specific condition (i.e., full correlation among the received samples), and finally, one non-coherent receiver for all other cases. A non-coherent receiver for energy harvesting through time division multiple access (TDMA) is also provided for comparison purposes. Analytical and numerical bit-error-rate results are presented. It is shown that the ZF-DBF receiver outperforms the energy harvesting one at the low-SNR regime and overcomes connectivity adversities by exploiting signal alignment from the distributed terminals, at the expense of total (network) power transmission.
Optimal blind detection of APSK in polynomial time
(Technical University of Crete, 2014) Fountzoulas Ioannis; Φουντζουλας Ιωαννης; Karystinos Georgios; Καρυστινος Γεωργιος; Bletsas Aggelos; Μπλετσας Αγγελος
Predictive control for stable dynamic locomotion of real humanoid robots
(Πολυτεχνείο Κρήτης, 2014) Piperakis Stylianos; Πιπερακης Στυλιανος; Lagoudakis Michael; Λαγουδακης Μιχαηλ; Liavas Athanasios; Λιαβας Αθανασιος; Bletsas Aggelos; Μπλετσας Αγγελος
Robust stable omnidirectional locomotion for humanoid robots is a crucial problem and an active research area nowadays. In general, biped locomotion relies on distinct gait phases, during which it must be ensured that the sum of the forces acting on the robot do not result in a loss of balance. To generate stable walking patterns, the need of a stability measure is evident to ensure upright locomotion. State-of-the-art work on this problem uses the Zero Moment Point (ZMP) as a criterion to measure stability. The ZMP approach is a formal representation of the problem, which makes full use of sensor information commonly available on humanoid robots and allows for rigorous solutions to be constructed. This thesis presents a complete formulation of the challenging task of stable humanoid robot omnidirectional walk, based on the Cart and Table model for approximating the robot dynamics. For the control task, two novel approaches are proposed: (i) Preview Control augmented with the inverse system for negotiating strong disturbances and uneven terrain and (ii) Linear Model-Predictive Control (LMPC) approximated by an orthonormal basis for computational efficiency coupled with constraints for improved stability. For the generation of smooth feet trajectory, a new approach based on rigid body interpolation is proposed, enhanced by adaptive step correction. Finally, we present a sensor fusion approach for sensor-based state estimation and an effective solution to sensors' noise, delay, and bias issues, as well as to errors induced by the simplified dynamics and actuation imperfections. The proposed formulation is applied on a real Aldebaran Nao humanoid robot, where it achieves real-time onboard execution and yields smooth and stable gaits.
Revenue and irritation-based call admission control using road maps over wireless cellular networks
(Πολυτεχνείο Κρήτης, 2014) Dimitriou Konstantina; Δημητριου Κωνσταντινα; Koutsakis Polychronis; Κουτσακης Πολυχρονης; Paterakis Michalis; Πατερακης Μιχαλης; Bletsas Aggelos; Μπλετσας Αγγελος
Bandwidth remains the most valuable commodity in wireless networks, even more so today, as new bandwidth-hungry multimedia applications emerge constantly and their users have high Quality of Service (QoS) requirements. Hence, the ability of a wireless network to efficiently allocate its bandwidth resources is crucial. In this thesis, we propose a new mechanism which controls the admission of users moving from cell to cell in a wireless cellular network. The Call Admission Control (CAC) mechanism is defined as a sequence of activities that are realized from the network in order to check if a user’s request, to use a specific service of the network, can be admitted or not. This request will be admitted if the desirable level of QoS can be accomplished without causing violation on the QoS that existing users enjoy. The design and simulation of the CAC mechanism were realized for the simultaneous use of the channel both from voice and e-mail users and video users downloading movies encoded with MPEG-4. The CAC mechanism aims to maximize channel throughput without allowing network congestion which would lead to the violation of the users’ QoS requirements. This is difficult to achieve because of the contradictory nature of the different types of traffic. Our work is one of the first in the relevant literature, to the best of our knowledge, to simultaneously consider both the provider revenue and user irritation in making its admission decisions. Our results show the resource allocation efficiency of the proposed mechanism in two different implementations regarding the degradation/upgrades of video users. Our CAC mechanism is shown to provide voice and video users long term satisfaction with the QoS they receive, even for very high traffic loads, while at the same time allowing the provider to increase its profit.
Scatter radio sensor network with analog frequency modulation principles
(Technical University of Crete, 2014) Kabianakis Eleftherios; Καμπιανακης Ελευθεριος; Bletsas Aggelos; Μπλετσας Αγγελος; Dollas Apostolos; Δολλας Αποστολος; Koutroulis Eftychios; Κουτρουλης Ευτυχιος
Scatter radio communication is implemented with very simple, low-power and low-cost front-ends that only consist of a single radio frequency (RF) switch. This work develops a bistatic scatter radio wireless sensor network (WSN) with analog energy-assisted tags that monitor relative humidity percentage (%RH) and consume less than 1 mWatt power. Particularly, the tags em- ploy a capacitance-to-frequency converter, that is implemented with a 555 timer and modulates the capacitance of the HCH-1000 %RH sensor. The frequency-modulated pulses are routed to the tag’s RF front-end which is designed to increase communication range. In order to convert the out- put frequency of the tags to %RH, a transfer function is estimated using careful polynomial surface fitting calibration and including the ambient tem- perature. Frequency division multiple access (FDMA) networking is im- plemented with the utilization of different passive components on each tag. Moreover the receiver that is implemented on a software defined radio (SDR) platform exploits carefully designed software filters based on histogram and Savitsky-Golay smoothing techniques. The achieved communication range is over 130 meters at an end-to-end root mean squared error (RMSE) of less than 5 %RH. For the network evaluation, a testbed is calibrated and deployed in a tomato greenhouse demonstrating a novel analog bistatic scatter radio WSN. Finally, an over the air programmable (OTAP) testbed was developed, employing nodes that utilize both an active radio front-end and scatter radio front-end in order to facilitate remote monitoring and debugging.
SDR readers for Gen2 RFID and backscatter sensor networks
(Technical University of Crete, 2015) Kargas Nikolaos; Καργας Νικολαος; Bletsas Aggelos; Μπλετσας Αγγελος; Karystinos Georgios; Καρυστινος Γεωργιος; Deligiannakis Antonios; Δεληγιαννακης Αντωνιος
Scatter radio has emerged as a key enabling technology for low-cost and large scale ubiquitous sensing. Radio frequency identification (RFID) tags/sensors utilize scatter radio technology to transfer sensed information to readers, typically employing Gen2, the industrial RFID protocol. This work offers a complete software-defined radio Gen2 reader, based on GNU Radio and USRP2 commodity software defined radio (SDR) platform. In sharp contrast to prior art, a single radio front end card is used with coherent detection and optimal exploitation of the FM0 line coding memory. The reader can act as a research tool to experiment with state-of-the-art signal processing algorithms and RFID devices. The two tag collision problem is studied and problems that arise in a real world system, such as channel estimation and tag symbol synchronization are highlighted. Experimental measurements are conducted and it is shown that the reader can identify a commercial, passive UHF RFID tag up to 6 meters with acceptable reliability. In addition, it is shown that collision recovery algorithms can increase performance of the implemented reader. Furthermore, an implementation of a SDR reader for a wireless backscatter sensor network (BSN) is presented. The developed reader implements noncoherent frequency shift keying (FSK) detection. The reader can decode multiple tags in real time and achieves communication ranges with semi-passive tags/sensors up to 130 meters.
Self-powered plant sensor for scatter radio
(Technical University of Crete, 2015) Konstantopoulos Christos; Κωνσταντοπουλος Χρηστος; Koutroulis Eftychios; Κουτρουλης Ευτυχιος; Bletsas Aggelos; Μπλετσας Αγγελος; Deligiannakis Antonios; Δεληγιαννακης Αντωνιος
In agriculture applications (e.g. greenhouses, vineyards etc.) it is required to automatically gather information about environmental variables such as soil and air humidity, as well as temperature in the vicinity of plants within the same field, with low-cost and high-scalability. Thus, sensor networks that are extending over a broad area and gather environmental data for microclimate monitoring, are indispensable for the application of optimal crop management techniques. The field of plant electro-physiology investigates the correlation of environmental variables with the electrical signals that are produced by diverse types of plants. Existing research in measurement of electrical signals generated by plants has been conducted using high-cost equipment, such as laboratory multi-meters and data-loggers, in order to perform the signal-conditioning and data acquisition operations required. This thesis introduces for first time in the existing research literature a novel low cost and self-powered sensor node that belongs to a large-scale scatter radio network and simultaneously is powered in a parasitic way to the plants, as well as is able to acquire and transmit these types of signals from each plant. Furthermore, in the context of this thesis, several experimental prototypes of the proposed node were developed, as well as used to gather measurements of electrical signals that are generated from multiple Avocado plants. The experimental results demonstrate the successful operation of the proposed WSN node, as well as indicate the correlation of plants signals with solar irradiation and plant irrigation events. Thus, the proposed system can be employed in precision agriculture applications for automated irrigation scheduling, control of the plant ambient conditions etc. based on data derived directly by the plants.
Smart sensors of RF and backscatter signals with localization
(Πολυτεχνείο Κρήτης, 2014) Alimpertis Emmanouil; Αλιμπερτης Εμμανουηλ; Bletsas Aggelos; Μπλετσας Αγγελος; Karystinos Georgios; Καρυστινος Γεωργιος; Lagoudakis Michael; Λαγουδακης Μιχαηλ
Information may be more valuable when the location of its source is known. This thesis develops localization algorithms based on received signal strength (RSS) measurements for unknown radio frequency (RF) sources and bistatic scatter radio tags (sensors). This thesis demonstrates RF source location es- timation utilizing RSS measurements by a community of smartphone users, within 800m (or more) from the source. The location estimation algorithm incorporates careful modeling of the time-varying source transmission power, source antenna directionality (even with a single 4-parameter model) and different path loss exponents among the various source-user links. More im- portantly, a vast number of measurements is collected and exploited through an automated community of smartphones. Location estimation error on the order of 50m is achieved, even when users are within 800m or more from the RF source. Furthermore, multiple input single output RSS localization for bistatic scatter radio is also considered. The RF scatter radio tag is illuminated by multiple low-cost carrier emitters, operating consecutively. Experimental validation of the proposed algorithm reports localization error on the order of 3m for tag and emitters placed at an area of 70m x 70m. Both estimation algorithms on real-world data exploit non-parametric estimation based on particle filtering.

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