Geometric Capacity Studies for DTV Transmitter Identification By Using Kasami Sequences

The transmitter identification of the DTV systems becomes crucial nowadays. Transmitter identification (TxID, or transmitter fingerprinting) technique is used to detect, diagnose and classify the operating status of any radio transmitter of interest. A pseudo random sequence was proposed to be embedded into the DTV signal before transmission. Thus, the transmitter identification can be realized by invoking the cross-correlation functions between the received signal and the possible candidates of the pseudo random sequences. Gold sequences and Kasami sequences are two excellent candidates for the transmitter ID sequences as they provide a large family of nearly-orthogonal codes. In order to investigate the sensitivity of the transmitter identification in different topologies and Kasami sequences with different length, we present the analysis here for four different geometric layouts, namely circular distribution, doubly concentric and circular distribution, square array and hexagonal tessellation. The covered area and the lowest received signal-to-interference ratio are considered as two essential parameters for the multiple-transmitter identification. It turns out to be that the larger the Kasami sequence length, the larger the received signal-to-interference ratio. Our new analysis can be used to determine the required Kasami sequence length for a specific broadcasting coverage

Orthogonal Pseudo-Random Sequence Enabled Cognitive and Emergency Communications

With the ever-increasing demands for the broadband mobile communications, it is becoming more and more difficult to accommodate all existing and emerging wireless services and applications due to the limited communication resources particularly radio spectrum. In addition, system parameters of wireless communications often need to be adapted due to the variation of channel characteristics and user demands. Cognitive communication is emerged as an effective technique, particularly to improve the utilization rate of limited communication resources adaptively according to the change in its operating conditions and requirements. To handle these challenges efficiently and reliably in cognitive radio scenario, cyclic prefix (CP) of the OFDM system is precoded in this thesis using pseudo-random sequence. This signaling link can effectively carry transmission parameters and system adaptation information. In first part of the thesis, mutual interference minimization and transmission power adaptation enabled by the additional signaling link are also investigated. In order to make use of this precoded cyclic prefix (PCP) signaling link, an efficient demodulation scheme is needed to reduce the implementation complexity. Therefore, a low complexity signaling demodulator along with a multipath combining technique to further improve the performance in real communication scenario like in multipath channel is proposed in the thesis. The final aspect of this thesis is the investigation of a robust communication system using digital television (DTV) transmitter identification watermark signal which is also a modulated pseudo-random sequence. The previous study on PCP signaling is thus extended to an emergency communication system using DTV watermark. It is found that watermark based communication system is more robust than the DTV broadcasting and can reach a much wider coverage with significantly increased network reliability, which is suitable for national emergency situations

Physical Layer Watermarking of Binary Phase-shift Keyed Signals Using Standard Gnu Radio Blocks

This thesis discussed the development, implementation, simulation, and testing of a physical layer watermarking method. The method was to use pre-existing GNU Radio building blocks. The main goal of the project was to implement a watermarking method using GNU Radio with the USRP software radios which could also be implemented using standard communications hardware so implementation on SDR systems as well as pre-existing communications systems was possible. Simulations of the physical layer watermarking system were created using a Monte Carlo method. The generation of a probability distribution of phase difference error was appropriate to analyze the expected performance of the DPSK watermarking system developed. Testing was performed in a realistic office environment where interference in the tested frequency band was common. A stationary receiver gathered data from a transmitter at various locations and power levels. The bit error rate of the gathered data was determined to analyze performance. While the testing in a real world environment had a limited range of valid analysis due to limited sampling time and interference, the results were comparable with the simulations. Testing and simulations showed the proposed physical layer watermarking method has the potential to compete with the performance of other authentication focused watermarking methods. In addition, the proposed method could be used to provide a separate, possible secretive, data channel under certain circumstances. An important benefit of the proposed watermarking method is its ability to be implemented in many SDR or traditional communication systems with no hardware modifications.School of Electrical & Computer Engineerin

Analysis and Modeling of a MIMO Ultrasonic Sensorial Structure based on M-CSS and correlation techniques.

[EN] This paper describes the analysis and modeling of an ultrasonic sensorial structure based on processing algorithm that uses a set of macro-sequences and correlation techniques for obtaining the impulse response of transmission channels simultaneously is proposed. The sensory structure is formed by multiple ultrasonic transducers that transmitting and receiving environment information simultaneously. This processing algorithm employs a pseudorandom macro-sequence obtained from a complementary set of M sequences (M- CSS) which, by auto-correlation and cross-correlation functions, the impulse responses from environment are obtained. The transmission in the ultrasonic system is represented by frequency selective MIMO model, which is analyzed every instant in the process of reflection-transmission-reception of the signals generated. Once the system model of ultrasonic transmission MIMO is developed and correlation algorithms are implemented for the detection of macro-sequences; the mathematical model, the results obtained in the simulation as well as experimental evidence are presented in this paper. These validate the use of the methodology applied to the channel modeling as well as the estimation of the impulse response of the transmission channels to process the received echoes corresponding to an object in front of the sensor system. The model implemented allows it on can develop algorithms and processing techniques, before they are physically implemented, in order to reduce application development time. In all such cases, is possible to obtain the impulse responses produced in the environment due to the reflectors located opposite the sensor system using correlation techniques. [ES] En este artículo se propone el análisis y modelado de una estructura sensorial ultrasónica empleando un algoritmo de procesamiento que utiliza un conjunto de macro-secuencias y técnicas de correlación para obtener respuestas impulsivas de canales de transmisión de forma simultánea. La estructura sensorial está formada por múltiples transductores ultrasónicos que transmiten y reciben información del entorno simultáneamente. Este algoritmo de procesamiento emplea una macro-secuencia pseudo-aleatoria obtenida a partir un conjunto complementario de M secuencias (M-CSS) con las cuales, mediante funciones de auto-correlación y correlación cruzada, se generan las respuestas impulsivas del entorno. Para modelar el sistema de transmisión ultrasónico se emplea el modelo MIMO de frecuencia selectiva, con el cual se logra analizar cada instante del proceso de emisión-reflexión-recepción de las señales generadas. Una vez que el modelo del sistema de transmisión ultrasónico MIMO es desarrollado y los algoritmos de correlación son implementados para la detección de las macro-secuencias, se presenta en este documento el modelo matemático y los resultados obtenidos en las simulaciones así como en las pruebas experimentales. Estos validan la utilización de la metodología del modelado de canal aplicado, como de la estimación de las respuestas impulsivas de los canales de transmisión al procesar los ecos recibidos correspondientes a un objeto frente al sistema sensor. El modelo implementado permite desarrollar sobre de él, algoritmos y técnicas de procesamiento, antes de que estos sean implementados físicamente, con el fin de reducir el tiempo de desarrollo de aplicaciones. En cada uno de los casos considerados, se logró obtener las respuestas impulsivas considerando que está presente un objeto frente a la estructura sensorial.Este trabajo ha sido posible gracias a el ministerio de educación y ciencia español (PROYECTO RESELAI: TIN2006- 14986-CO2-01); al Ministerio de Fomento (Proyecto VIATOR: ref 70025-T05); y al Fondo Ramón Álvarez-Buylla de Aldana (ADCESUDRU FRABA715/10).Ochoa, A.; Ureña, J.; Hernández, Á.; González, A.; Mata, W.; Félix, RA. (2015). Análisis y modelado de una estructura sensorial ultrasónica MIMO basado en M-CSS y técnicas de correlación. Revista Iberoamericana de Automática e Informática industrial. 12(3):270-281. https://doi.org/10.1016/j.riai.2015.04.002OJS270281123Álvarez, F.J.; Ureña, J.; Mazo, M.; Hernandez, A.; Garcia J.J.; Jiménez, J.A. “Efficient Generator and Pulse Compressor for Complementary Set of Four Sequences”, IEE Electronics Letters, Vol. 40, No. 11, pp. 703-704, May 2004.Álvarez, F.J.; Hernández, A.; Urena, J.; Jimenez, A.; Pérez, M.C.; García, J.J.; Gude, I.; De Marziani, C. Encoding ultrasonic signals with kasami sequences to perform spectrum-based localization. In proceedings of IEEE International Symposium on Intelligent Signal Processing (WISP 2009), Budapest, Hungary, 26-28 August 2009, pp. 49-53.Araújo, A., Portugal, D., Couceiro, M., Sales, J., Rocha, P., 2014. Desarrollo de un robot móvil compacto integrado en el middleware ros. Revista Iberoamericana de Automática e Informática Industrial {RIAI}, 11 (3) (2014), pp. 315-326.Bolcskei, H.; Gesbert, D.; Paulraj, A.J. On the capacity of OFDM-based spatial multiplexing systems. IEEE Transactions on Communications 2002, 50(2), 225-234.De Marziani, C.; Urena, J.; Hernandez, A.; Mazo, M.; Garcia, J.J.; Jimenez, A.; Villadangos, J.M.; Perez, M.C.; Ochoa, A.; Alvarez, F. Inter-Symbol Interference Reduction on Macro-Sequences Generated from Complementary Set of Sequences. In proceedings of 32nd Annual Conference on IEEE Industrial Electronics (IECON 2006), Paris, France, 6-10 November 2006, pp. 3367-3372.De Marziani, C.; Ureña, J.; Hernández, A.; Mazo, M.; Álvarez, F.; García, J.; Donato, P. Modular Architecture for Efficient Generation and Correlation of Complementary Set of Sequences. IEEE Transactions on Signal Processing 2007, 55, 2323-2337.De Marziani, C.; Urena, J.; Hernandez, A.; Garcia, J.J.; Álvarez, F.J.; Jimenez, A.; Perez, M.C.; Carrizo, J.M.V.; Aparicio, J.; Alcoleas, R. Simultaneous Round-Trip Time-of-Flight Measurements With Encoded Acoustic Signals. IEEE Sensors Journal 2012, 12, 2931-2940.Data Acquisition Solutions Acquitek. http://www.acquitek.com/(13/02/2014).Docmac, D., Silva, E., González, A., 2013. Evaluación de algoritmos para la estimación del Round-Trip Delay Time y una propuesta de mejora, Revista Iberoamericana de Automática e Informática Industrial RIAI, Vol. 10, No. 1, January–March 2013, Pages 62-72.Hernandez, A.; Urena, J.; Garcia, J.J.; Mazo, M.; Hernanz, D.; Derutin, J.-P.; Serot, J. Ultrasonic ranging sensor using simultaneous emissions from different transducers. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control 2004, 51(12), 1660-1670.Jimenez, J.A.; Mazo, M.; Urena, J.; Hernandez, A.; Alvarez, F.; García, J.J.; Santiso, E. Using PCA in time-of-flight vectors for reflector recognition and 3-D localization. IEEE Transactions on Robotics 2005, 21, 909-924.Kafle, P.L.; Intarapanich, A.; Sesay, A.B.; McRory, J.; Davies, R.J. Spatial correlation and capacity measurements for wideband MIMO channels in indoor office environment. IEEE Transactions on Wireless Communications 2008, 7(5), 1560-1571.Larsson, E.; Stoica, P. Space-Time Block Coding for Wireless Communications, 1st ed.; Cambridge University Press: The Edinburg Building, Cambridge CB2 8RU, UK, 2003; Volume 3, pp. 8-21.Matin, M.A.; Ozaki, K.; Numata, Y.; Akai, D.; Sawada, K.; Ishida, M., “Quantifying modal shapes in smart piezoelectric ultrasonic transducer array: Modeling and experiment,” SENSORS, 2013 IEEE , vol., no., pp.1,4, 3-6 Nov. 2013.Pitarokoilis, A.; Mohammed, S.; Larsson, E.G., “Uplink Performance of Time-Reversal MRC in Massive MIMO Systems Subject to Phase Noise,” IEEE Transactions on Wireless Communications, no.99, pp. 1,1. DOI: 10.1109/TWC.2014.2359018. 2014.Ochoa, A.; Urena, J.; Hernandez, A.; Mazo, M.; Jimenez, J.A.; Perez, M.C. Ultrasonic Multitransducer System for Classification and 3-D Location of Reflectors Based on PCA. IEEE Transactions on Instrumentation and Measurement. 2009, 58, 3031-3041.Ochoa, A.; Urena, J.; Hernández, A.; Mazo, M.; De Marziani, C.; Pérez, M.C. Processing Algorithm for obtaining the Impulse Response in a MIMO Ultrasonic System. In Proceedings of The IEEE Conference on Emerging Technologies and Factory Automation (ETFA’06), Prague, Czech Republic, 20-22 September 2006; pp. 977-980.Ruiz, D.; Garcia, E.; Urena, J.; Villadangos, J.M.; Garcia, J.J.; De Marziani, C., “Performance comparison of correlation-based receive filters in an ultrasonic Indoor Positioning System,” 2014 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, pp.1548,1551, 12-15 May 2014.Sarma, K.K.; Mitra, A., “Multiple-input–multiple-output channel modelling using multi-layer perceptron with finite impulse response and infinite impulse response synapses,” Communications, IET , vol.7, no.14, pp.1540,1549, September 24 2013.Satchidanandan, B.; Kuchi, K.; Koilpillai, R.D., “Generalized Reduced-State Vector Sequence Detection,” Communications Letters, IEEE , vol.18, no.10, pp.1691,1694, Oct. 2014.SensComp Global Components. http://www.senscomp.com/products/(13/02/2014).Siyau, M.F.; Nobles, P.; Ormondroyd, R.F. Channel estimation for layered space-time systems. In Proceedings of 4th IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2003),Rome, Italy, 15-18 June 2003; pp.482-486.Vía, J., Santamaría, I., Pérez, J. and Vielva, L. (2010), A new subspace method for blind estimation of selective MIMO-STBC channels. Wirel. Commun. Mob. Comput., 10: 1478-1492.Xianbin Wang; Yiyan Wu; Caron B. Transmitter identification using embedded pseudo random sequences. IEEE Transactions on Broadcasting 2004, 50, 244 – 252