An M-QAM Signal Modulation Recognition Algorithm in AWGN Channel

Computing the distinct features from input data, before the classification, is a part of complexity to the methods of Automatic Modulation Classification (AMC) which deals with modulation classification was a pattern recognition problem. Although the algorithms that focus on MultiLevel Quadrature Amplitude Modulation (M-QAM) which underneath different channel scenarios was well detailed. A search of the literature revealed indicates that few studies were done on the classification of high order M-QAM modulation schemes like128-QAM, 256-QAM, 512-QAM and1024-QAM. This work is focusing on the investigation of the powerful capability of the natural logarithmic properties and the possibility of extracting Higher-Order Cumulant's (HOC) features from input data received raw. The HOC signals were extracted under Additive White Gaussian Noise (AWGN) channel with four effective parameters which were defined to distinguished the types of modulation from the set; 4-QAM~1024-QAM. This approach makes the recognizer more intelligent and improves the success rate of classification. From simulation results, which was achieved under statistical models for noisy channels, manifest that recognized algorithm executes was recognizing in M-QAM, furthermore, most results were promising and showed that the logarithmic classifier works well over both AWGN and different fading channels, as well as it can achieve a reliable recognition rate even at a lower signal-to-noise ratio (less than zero), it can be considered as an Integrated Automatic Modulation Classification (AMC) system in order to identify high order of M-QAM signals that applied a unique logarithmic classifier, to represents higher versatility, hence it has a superior performance via all previous works in automatic modulation identification systemComment: 18 page

Solutions for New Terrestrial Broadcasting Systems Offering Simultaneously Stationary and Mobile Services

221 p.[EN]Since the first broadcasted TV signal was transmitted in the early decades of the past century, the television broadcasting industry has experienced a series of dramatic changes. Most recently, following the evolution from analogue to digital systems, the digital dividend has become one of the main concerns of the broadcasting industry. In fact, there are many international spectrum authorities reclaiming part of the broadcasting spectrum to satisfy the growing demand of other services, such as broadband wireless services, arguing that the TV services are not very spectrum-efficient. Apart from that, it must be taken into account that, even if up to now the mobile broadcasting has not been considered a major requirement, this will probably change in the near future. In fact, it is expected that the global mobile data traffic will increase 11-fold between 2014 and 2018, and what is more, over two thirds of the data traffic will be video stream by the end of that period. Therefore, the capability to receive HD services anywhere with a mobile device is going to be a mandatory requirement for any new generation broadcasting system. The main objective of this work is to present several technical solutions that answer to these challenges. In particular, the main questions to be solved are the spectrum efficiency issue and the increasing user expectations of receiving high quality mobile services. In other words, the main objective is to provide technical solutions for an efficient and flexible usage of the terrestrial broadcasting spectrum for both stationary and mobile services. The first contributions of this scientific work are closely related to the study of the mobile broadcast reception. Firstly, a comprehensive mathematical analysis of the OFDM signal behaviour over time-varying channels is presented. In order to maximize the channel capacity in mobile environments, channel estimation and equalization are studied in depth. First, the most implemented equalization solutions in time-varying scenarios are analyzed, and then, based on these existing techniques, a new equalization algorithm is proposed for enhancing the receivers’ performance. An alternative solution for improving the efficiency under mobile channel conditions is treating the Inter Carrier Interference as another noise source. Specifically, after analyzing the ICI impact and the existing solutions for reducing the ICI penalty, a new approach based on the robustness of FEC codes is presented. This new approach employs one dimensional algorithms at the receiver and entrusts the ICI removing task to the robust forward error correction codes. Finally, another major contribution of this work is the presentation of the Layer Division Multiplexing (LDM) as a spectrum-efficient and flexible solution for offering stationary and mobile services simultaneously. The comprehensive theoretical study developed here verifies the improved spectrum efficiency, whereas the included practical validation confirms the feasibility of the system and presents it as a very promising multiplexing technique, which will surely be a strong candidate for the next generation broadcasting services.[ES]Desde el comienzo de la transmisión de las primeras señales de televisión a principios del siglo pasado, la radiodifusión digital ha evolucionado gracias a una serie de cambios relevantes. Recientemente, como consecuencia directa de la digitalización del servicio, el dividendo digital se ha convertido en uno de los caballos de batalla de la industria de la radiodifusión. De hecho, no son pocos los consorcios internacionales que abogan por asignar parte del espectro de radiodifusión a otros servicios como, por ejemplo, la telefonía móvil, argumentado la poca eficiencia espectral de la tecnología de radiodifusión actual. Asimismo, se debe tener en cuenta que a pesar de que los servicios móviles no se han considerado fundamentales en el pasado, esta tendencia probablemente variará en el futuro cercano. De hecho, se espera que el tráfico derivado de servicios móviles se multiplique por once entre los años 2014 y 2018; y lo que es más importante, se pronostica que dos tercios del tráfico móvil sea video streaming para finales de ese periodo. Por lo tanto, la posibilidad de ofrecer servicios de alta definición en dispositivos móviles es un requisito fundamental para los sistemas de radiodifusión de nueva generación. El principal objetivo de este trabajo es presentar soluciones técnicas que den respuesta a los retos planteados anteriormente. En particular, las principales cuestiones a resolver son la ineficiencia espectral y el incremento de usuarios que demandan mayor calidad en los contenidos para dispositivos móviles. En pocas palabras, el principal objetivo de este trabajo se basa en ofrecer una solución más eficiente y flexible para la transmisión simultánea de servicios fijos y móviles. La primera contribución relevante de este trabajo está relacionada con la recepción de la señal de televisión en movimiento. En primer lugar, se presenta un completo análisis matemático del comportamiento de la señal OFDM en canales variantes con el tiempo. A continuación, con la intención de maximizar la capacidad del canal, se estudian en profundidad los algoritmos de estimación y ecualización. Posteriormente, se analizan los algoritmos de ecualización más implementados, y por último, basándose en estas técnicas, se propone un nuevo algoritmo de ecualización para aumentar el rendimiento de los receptores en tales condiciones. Del mismo modo, se plantea un nuevo enfoque para mejorar la eficiencia de los servicios móviles basado en tratar la interferencia entre portadoras como una fuente de ruido. Concretamente, tras analizar el impacto del ICI en los receptores actuales, se sugiere delegar el trabajo de corrección de dichas distorsiones en códigos FEC muy robustos. Finalmente, la última contribución importante de este trabajo es la presentación de la tecnología LDM como una manera más eficiente y flexible para la transmisión simultánea de servicios fijos y móviles. El análisis teórico presentado confirma el incremento en la eficiencia espectral, mientras que el estudio práctico valida la posible implementación del sistema y presenta la tecnología LDM c

Error resilient H.264 coded video transmission over wireless channels

The H.264/AVC recommendation was first published in 2003 and builds on the concepts of earlier standards such as MPEG-2 and MPEG-4. The H.264 recommendation represents an evolution of the existing video coding standards and was developed in response to the growing need for higher compression. Even though H.264 provides for greater compression, H.264 compressed video streams are very prone to channel errors in mobile wireless fading channels such as 3G due to high error rates experienced. Common video compression techniques include motion compensation, prediction methods, transformation, quantization and entropy coding, which are the common elements of a hybrid video codecs. The ITU-T recommendation H.264 introduces several new error resilience tools, as well as several new features such as Intra Prediction and Deblocking Filter. The channel model used for the testing was the Rayleigh Fading channel with the noise component simulated as Additive White Gaussian Noise (AWGN) using QPSK as the modulation technique. The channel was used over several Eb/N0 values to provide similar bit error rates as those found in the literature. Though further research needs to be conducted, results have shown that when using the H.264 error resilience tools in protecting encoded bitstreams to minor channel errors improvement in the decoded video quality can be observed. The tools did not perform as well with mild and severe channel errors significant as the resultant bitstream was too corrupted. From this, further research in channel coding techniques is needed to determine if the bitstream can be protected from these sorts of error rate

Automatic classification of digital communication signal modulations

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityAutomatic modulation classification detects the modulation type of received communication signals. It has important applications in military scenarios to facilitate jamming, intelligence, surveillance, and threat analysis. The renewed interest from civilian scenes has been fuelled by the development of intelligent communications systems such as cognitive radio and software defined radio. More specifically, it is complementary to adaptive modulation and coding where a modulation can be deployed from a set of candidates according to the channel condition and system specification for improved spectrum efficiency and link reliability. In this research, we started by improving some existing methods for higher classification accuracy but lower complexity. Machine learning techniques such as k-nearest neighbour and support vector machine have been adopted for simplified decision making using known features. Logistic regression, genetic algorithm and genetic programming have been incorporated for improved classification performance through feature selection and combination. We have also developed a new distribution test based classifier which is tailored for modulation classification with the inspiration from Kolmogorov-Smirnov test. The proposed classifier is shown to have improved accuracy and robustness over the standard distribution test. For blind classification in imperfect channels, we developed the combination of minimum distance centroid estimator and non-parametric likelihood function for blind modulation classification without the prior knowledge on channel noise. The centroid estimator provides joint estimation of channel gain and carrier phase o set where both can be compensated in the following nonparametric likelihood function. The non-parametric likelihood function, in the meantime, provide likelihood evaluation without a specifically assumed noise model. The combination has shown to have higher robustness when different noise types are considered. To push modulation classification techniques into a more timely setting, we also developed the principle for blind classification in MIMO systems. The classification is achieved through expectation maximization channel estimation and likelihood based classification. Early results have shown bright prospect for the method while more work is needed to further optimize the method and to provide a more thorough validation.School of Engineering and Design Brunel University London, the Faculty of Engineering University of Liverpool, and the University of Liverpool Graduate Association (Hong Kong)

Wavelet based image compression integrating error protection via arithmetic coding with forbidden symbol and map metric sequential decoding with ARQ retransmission

The phenomenal growth of digital multimedia applications has forced the communication

Optimising lower layers of the protocol stack to improve communication performance in a wireless temperature sensor network

The function of wireless sensor networks is to monitor events or gather information and report the information to a sink node, a central location or a base station. It is a requirement that the information is transmitted through the network efficiently. Wireless communication is the main activity that consumes energy in wireless sensor networks through idle listening, overhearing, interference and collision. It becomes essential to limit energy usage while maintaining communication between the sensor nodes and the sink node as the nodes die after the battery has been exhausted. Thus, conserving energy in a wireless sensor network is of utmost importance. Numerous methods to decrease energy expenditure and extend the lifetime of the network have been proposed. Researchers have devised methods to efficiently utilise the limited energy available for wireless sensor networks by optimising the design parameters and protocols. Cross-layer optimisation is an approach that has been employed to improve wireless communication. The essence of cross-layer scheme is to optimise the exchange and control of data between two or more layers to improve efficiency. The number of transmissions is therefore a vital element in evaluating overall energy usage. In this dissertation, a Markov Chain model was employed to analyse the tuning of two layers of the protocol stack, namely the Physical Layer (PHY) and Media Access Control layer (MAC), to find possible energy gains. The study was conducted utilising the IEEE 802.11 channel, SensorMAC (SMAC) and Slotted-Aloha (S-Aloha) medium access protocols in a star topology Wireless Temperature Sensor Network (WTSN). The research explored the prospective energy gains that could be realised through optimizing the Forward Error Correction (FEC) rate. Different Reed Solomon codes were analysed to explore the effect of protocol tuning on energy efficiency, namely transmission power, modulation method, and channel access. The case where no FEC code was used and analysed as the control condition. A MATLAB simulation model was used to identify the statistics of collisions, overall packets transmitted, as well as the total number of slots used during the transmission phase. The bit error probability results computed analytically were utilised in the simulation model to measure the probability of successful transmitting data in the physical layer. The analytical values and the simulation results were compared to corroborate the correctness of the models. The results indicate that energy gains can be accomplished by the suggested layer tuning approach.Electrical and Mining EngineeringM. Tech. (Electrical Engineering

Communications for smart grid substation monitoring using WIMAX protocol

The SMARTGRID is a general term for a series of infrastructural changes applied to the electric transmission and distribution systems. By using the latest communication and computing technology, additional options such as Condition Monitoring can now be implemented to further improve and optimise complex electricity supply grid operation. Lifecycle optimisation of high voltage assets and other system components in the utility provide a case in point. Today Utility experts agree that application of scheduled maintenance is not the effective use of resources. To reduce maintenance expenses and unnecessary outages and repairs of equipment due to scheduled maintenance, utilities are adopting condition based approaches. Real time online monitoring of substation parameters can be achieved by retrofitting the existing substation with SMARTGRID technology. The IEC 61850 is a common protocol meant for Substation Automation Systems, designed for the purpose of establishing interoperability, one that all manufacturers of all different assets must comply with. This thesis advocates the estimation of bandwidth required for monitoring a substation after retrofitting the existing substation with smart communication technologies. This includes establishing a latest wireless communication infrastructure from the substation to the control centre and evaluating the performance modelling and simulating the physical layer of communication technologies such as WIMAX (IEEE802.16) and MICROWAVE point to point using MATLAB SIMULINK and RADIO mobile online simulation software. Also, link budget of the satellite communication for the same application is calculated. Satellite communication in this case is considered as a redundant or back up technology to ensure that the communication between entities is continuous. On performing the simulation on different environments the results prove that the selected protocols are best suited for condition monitoring. The measured Latency could be the best approximated value which complies with the current objective. However the white noise that exists in the substation has significant hazard with respect to the security of the wireless network. To compensate this constraint whole substation is hard wired by means of plastic fibre optics and the data sent to the base station located near the substation

Network Coding for Multihop Wireless Networks: Joint Random Linear Network Coding and Forward Error Correction with Interleaving for Multihop Wireless Networks

Optimising the throughput performance for wireless networks is one of the challenging tasks in the objectives of communication engineering, since wireless channels are prone to errors due to path losses, random noise, and fading phenomena. The transmission errors will be worse in a multihop scenario due to its accumulative effects. Network Coding (NC) is an elegant technique to improve the throughput performance of a communication network. There is the fact that the bit error rates over one modulation symbol of 16- and higher order- Quadrature Amplitude Modulation (QAM) scheme follow a certain pattern. The Scattered Random Network Coding (SRNC) system was proposed in the literature to exploit the error pattern of 16-QAM by using bit-scattering to improve the throughput of multihop network to which is being applied the Random Linear Network Coding (RLNC). This thesis aims to improve further the SRNC system by using Forward Error Correction (FEC) code; the proposed system is called Joint RLNC and FEC with interleaving. The first proposed system (System-I) uses Convolutional Code (CC) FEC. The performances analysis of System-I with various CC rates of 1/2, 1/3, 1/4, 1/6, and 1/8 was carried out using the developed simulation tools in MATLAB and compared to two benchmark systems: SRNC system (System-II) and RLNC system (System- III). The second proposed system (System-IV) uses Reed-Solomon (RS) FEC code. Performance evaluation of System IV was carried out and compared to three systems; System-I with 1/2 CC rate, System-II, and System-III. All simulations were carried out over three possible channel environments: 1) AWGN channel, 2) a Rayleigh fading channel, and 3) a Rician fading channel, where both fading channels are in series with the AWGN channel. The simulation results show that the proposed system improves the SRNC system. How much improvement gain can be achieved depends on the FEC type used and the channel environment.Indonesian Government and the University of Bradfor

A channel model and coding for vehicle to vehicle communication based on a developed V-SCME

Over the recent years, VANET communication has attracted a lot of attention due to its potential in facilitating the implementation of 'Intelligent Transport System'. Vehicular applications need to be completely tested before deploying them in the real world. In this context, VANET simulations would be preferred in order to evaluate and validate the proposed model, these simulations are considered inexpensive compared to the real world (hardware) tests. The development of a more realistic simulation environment for VANET is critical in ensuring high performance. Any environment required for simulating VANET, needs to be more realistic and include a precise representation of vehicle movements, as well as passing signals among different vehicles. In order to achieve efficient results that reflect the reality, a high computational power during the simulation is needed which consumes a lot of time. The existing simulation tools could not simulate the exact physical conditions of the real world, so results can be viewed as unsatisfactory when compared with real world experiments. This thesis describes two approaches to improve such vehicle to vehicle communication. The first one is based on the development of an already existing approach, the Spatial Channel Model Extended (SCME) for cellular communication which is a verified, validated and well-established communication channel model. The new developed model, is called Vehicular - Spatial Channel Model Extended (V-SCME) and can be utilised for Vehicle to Vehicle communication. V-SCME is a statistical channel model which was specifically developed and configured to satisfy the requirements of the highly dynamic network topology such as vehicle to vehicle communication. V-SCME provides a precise channel coefficients library for vehicle to vehicle communication for use by the research community, so as to reduce the overall simulation time. The second approach is to apply V-BLAST (MIMO) coding which can be implemented with vehicle to vehicle communication and improve its performance over the V-SCME. The V- SCME channel model with V-BLAST coding system was used to improve vehicle to vehicle physical layer performance, which is a novel contribution. Based on analysis and simulations, it was found that the developed channel model V-SCME is a good solution to satisfy the requirements of vehicle to vehicle communication, where it has considered a lot of parameters in order to obtain more realistic results compared with the real world tests. In addition, V-BLAST (MIMO) coding with the V-SCME has shown an improvement in the bit error rate. The obtained results were intensively compared with other types of MIMO coding