QR factorization equalisation scheme for mode devision multiplexing transmission in fibre optics

Optical communication systems play a major role in handling worldwide Internet traffic. Internet traffic has been increasing at a dramatic rate and the current optical network infrastructure may not be able to support the traffic growth in a few decades. Mode division multiplexing is introduced as a new emerging technique to improve the optical network capacity by the use of the light modes as individual channels. One of the main issues in MDM is mode coupling which is a physical phenomenon when light modes exchange their energy between each other during propagation through optical fiber resulting in inter-symbol interference (ISI). Many studies based on Least Mean Square (LMS) and Recursive Least Square (RLS) have taken place to mitigate the mode coupling effect. Still, most approaches have high computational complexity and hinders high-speed communication systems. Blind equalisation approach does not need training signals, thus, will reduce the overhead payload. On the other hand, QR factorization shows low computational complexity in the previous research in the radio domain. The combination of these two concepts shows significant results, as the use of low complexity algorithms reduces the processing needed to be done by the communication equipment, resulting in more cost effective and smaller equipment, while having no training signal saves the bandwidth and enhances the overall system performance. To the best knowledge of the researcher, blind equalisation based on QR factorization technique has been not used in MDM equalisation to date. The research goes through the four stages of the design research methodology (DRM) to achieve the purpose of the study. The implementation stage is taken two different simulators has been used, the first one which is the optical simulator is used to collect the initial optical data then, MATLAB is used to develop the equalisation scheme. The development starts with the derivation of the system’s transfer function (H) to be used as the input to the developed equalizer. Blind equalisation based on QR factorization is chosen as a way to introduce an efficient equalization to mitigate ISI by narrowing the pulse width. The development stages include a stage where the channel estimation is taken place. Statistical properties based on the standard deviation (STD) of the powers of the input and output signals has been used for the blind equalisation’s channel estimation part. The proposed channel estimation way has the ability in estimating the channel with an overall mean square error (MSE) of 0.176588301 from the initial transmitted signal. It is found that the worst channel has an MSE of 0.771365 from the transmitted signal, while the best channel has and MSE of 0.000185 from the transmitted signal. This is done by trying to avoid the issues accompanied with the development of the previous algorithms that have been utilized for the same goal. The algorithm mentioned in the study reduces the computational complexity problem which is one of the main issues that accompany currently used tap filter algorithms, such as (LMS) and (RLS). The results from this study show that the developed equalisation scheme has a complexity of O(N) compared with O(N2) for RLS and at the same time, it is faster than LMS as its calculation CPU time is equal to 0.005242 seconds compared with 0.0077814 seconds of LMS. The results are only valid for invertible and square channel matrices

Implementation and Analysis of Spectral Subtraction and Signal Separation in Deterministic Wide-Band Anti-Jamming Scenarios

With the increasing volume of wireless traffic that military operations require, the likelihood of transmissions interfering with each other is steadily growing to the point that new techniques need to be employed. Furthermore, to combat remotely operated improvised explosive devices, many ground convoys transmit high-power broadband jamming signals, which block both hostile as well as friendly communications. These wide-band jamming fields pose a serious technical challenge to existing anti-jamming solutions that are currently employed by the Navy and Marine Corps. This thesis examines the feasibility of removing such deterministic jammers from the spectral environment, enabling friendly communications. Anti-jamming solutions in self-jamming environments are rarely considered in the literature, principally due to the non-traditional nature of such jamming techniques. As a result, a combination of approaches are examined which include: Antenna Subset Selection, Spectral Subtraction, and Source Separation. These are combined to reduce environmental interference for reliable transmissions. Specific operational conditions are considered and evaluated, primarily to define the limitations and utility of such a system. A final prototype was constructed using a collection of USRP software defined radios, providing solid conclusions of the overall system performance

Channel Estimation Architectures for Mobile Reception in Emerging DVB Standards

Throughout this work, channel estimation techniques have been analyzed and proposed for moderate and very high mobility DVB (digital video broadcasting) receivers, focusing on the DVB-T2 (Digital Video Broadcasting - Terrestrial 2) framework and the forthcoming DVB-NGH (Digital Video Broadcasting - Next Generation Handheld) standard. Mobility support is one of the key features of these DVB specifications, which try to deal with the challenge of enabling HDTV (high definition television) delivery at high vehicular speed. In high-mobility scenarios, the channel response varies within an OFDM (orthogonal frequency-division multiplexing) block and the subcarriers are no longer orthogonal, which leads to the so-called ICI (inter-carrier interference), making the system performance drop severely. Therefore, in order to successfully decode the transmitted data, ICI-aware detectors are necessary and accurate CSI (channel state information), including the ICI terms, is required at the receiver. With the aim of reducing the number of parameters required for such channel estimation while ensuring accurate CSI, BEM (basis expansion model) techniques have been analyzed and proposed for the high-mobility DVB-T2 scenario. A suitable clustered pilot structure has been proposed and its performance has been compared to the pilot patterns proposed in the standard. Different reception schemes that effectively cancel ICI in combination with BEM channel estimation have been proposed, including a Turbo scheme that includes a BP (belief propagation) based ICI canceler, a soft-input decision-directed BEM channel estimator and the LDPC (low-density parity check) decoder. Numerical results have been presented for the most common channel models, showing that the proposed receiver schemes allow good reception, even in receivers with extremely high mobility (up to 0.5 of normalized Doppler frequency).Doktoretza tesi honetan, hainbat kanal estimazio teknika ezberdin aztertu eta proposatu dira mugikortasun ertain eta handiko DVB (Digital Video Broadcasting) hartzaileentzat, bigarren belaunaldiko Lurreko Telebista Digitalean DVB-T2 (Digital Video Broadcasting - Terrestrial 2 ) eta hurrengo DVB-NGH (Digital Video Broadcasting - Next Generation Handheld) estandarretan oinarrututa. Mugikortasuna bigarren belaunaldiko telebista estandarrean funtsezko ezaugarri bat da, HDTV (high definition television) zerbitzuak abiadura handiko hartzaileetan ahalbidetzeko erronkari aurre egiteko nahian. Baldintza horietan, kanala OFDM (ortogonalak maiztasun-zatiketa multiplexing ) sinbolo baten barruan aldatzen da, eta subportadorak jada ez dira ortogonalak, ICI-a (inter-carrier interference) sortuz, eta sistemaren errendimendua hondatuz. Beraz, transmititutako datuak behar bezala deskodeatzeko, ICI-a ekiditeko gai diren detektagailuak eta CSI-a (channel state information) zehatza, ICI osagaiak barne, ezinbestekoak egiten dira hartzailean. Kanalaren estimazio horretarako beharrezkoak diren parametro kopurua murrizteko eta aldi berean CSI zehatza bermatzeko, BEM (basis expansion model) teknika aztertu eta proposatu da ICI kanala identifikatzeko mugikortasun handiko DVB-T2 eszenatokitan. Horrez gain, pilotu egitura egokia proposatu da, estandarrean proposatutako pilotu ereduekin alderatuz BEM estimazioan oinarritua. ICI-a baliogabetzen duten hartzaile sistema ezberdin proposatu dira, Turbo sistema barne, non BP (belief propagation) detektagailua, soft BEM estimazioa eta LDPC (low-density parity check ) deskodetzailea uztartzen diren. Ohiko kanal ereduak erabilita, simulazio emaitzak aurkeztu dira, proposatutako hartzaile sistemak mugikortasun handiko kasuetan harrera ona dutela erakutsiz, 0.5 Doppler maiztasun normalizaturaino.Esta tesis doctoral analiza y propone diferentes técnicas de estimación de canal para receptores DVB (Digital Video Broadcasting) con movilidad moderada y alta, centrándose en el estándar de segunda generación DVB-T2 (Digital Video Broadcasting - Terrestrial 2 ) y en el próximó estándar DVB-NGH (Digital Video Broadcasting - Next Generation Handheld ). La movilidad es una de las principales claves de estas especificaciones, que tratan de lidiar con el reto de permitir la recepción de señal HDTV (high definition television) en receptores móviles. En escenarios de alta movilidad, la respuesta del canal varía dentro de un símbolo OFDM (orthogonal frequency-division multiplexing ) y las subportadoras ya no son ortogonales, lo que genera la llamada ICI (inter-carrier interference), deteriorando el rendimiento de los receptores severamente. Por lo tanto, con el fin de decodificar correctamente los datos transmitidos, detectores capaces de suprimir la ICI y una precisa CSI (channel state information), incluyendo los términos de ICI, son necesarios en el receptor. Con el objetivo de reducir el número de parámetros necesarios para dicha estimación de canal, y al mismo tiempo garantizar una CSI precisa, la técnica de estimación BEM (basis expansion model) ha sido analizada y propuesta para identificar el canal con ICI en receptores DVB-T2 de alta movilidad. Además se ha propuesto una estructura de pilotos basada en clústers, comparando su rendimiento con los patrones de pilotos establecidos en el estándar. Se han propuesto diferentes sistemas de recepción que cancelan ICI en combinación con la estimación BEM, incluyendo un esquema Turbo que incluye un detector BP (belief propagation), un estimador BEM soft y un decodificador LDPC (low-density parity check). Se han presentado resultados numéricos para los modelos de canal más comunes, demostrando que los sistemas de recepción propuestos permiten la decodificación correcta de la señal incluso en receptores con movilidad muy alta (hasta 0,5 de frecuencia de Doppler normalizada)

Cyclic Prefix-Free MC-CDMA Arrayed MIMO Communication Systems

The objective of this thesis is to investigate MC-CDMA MIMO systems where the antenna array geometry is taken into consideration. In most MC-CDMA systems, cyclic pre xes, which reduce the spectral e¢ ciency, are used. In order to improve the spectral efficiency, this research study is focused on cyclic pre x- free MC-CDMA MIMO architectures. Initially, space-time wireless channel models are developed by considering the spatio-temporal mechanisms of the radio channel, such as multipath propaga- tion. The spatio-temporal channel models are based on the concept of the array manifold vector, which enables the parametric modelling of the channel. The array manifold vector is extended to the multi-carrier space-time array (MC-STAR) manifold matrix which enables the use of spatio-temporal signal processing techniques. Based on the modelling, a new cyclic pre x-free MC- CDMA arrayed MIMO communication system is proposed and its performance is compared with a representative existing system. Furthermore, a MUSIC-type algorithm is then developed for the estimation of the channel parameters of the received signal. This proposed cyclic pre x-free MC-CDMA arrayed MIMO system is then extended to consider the effects of spatial diffusion in the wireless channel. Spatial diffusion is an important channel impairment which is often ignored and the failure to consider such effects leads to less than satisfactory performance. A subspace-based approach is proposed for the estimation of the channel parameters and spatial spread and reception of the desired signal. Finally, the problem of joint optimization of the transmit and receive beam- forming weights in the downlink of a cyclic pre x-free MC-CDMA arrayed MIMO communication system is investigated. A subcarrier-cooperative approach is used for the transmit beamforming so that there is greater flexibility in the allocation of channel symbols. The resulting optimization problem, with a per-antenna transmit power constraint, is solved by the Lagrange multiplier method and an iterative algorithm is proposed

System Identification with Applications in Speech Enhancement

As the increasing popularity of integrating hands-free telephony on mobile portable devices and the rapid development of voice over internet protocol, identification of acoustic systems has become desirable for compensating distortions introduced to speech signals during transmission, and hence enhancing the speech quality. The objective of this research is to develop system identification algorithms for speech enhancement applications including network echo cancellation and speech dereverberation. A supervised adaptive algorithm for sparse system identification is developed for network echo cancellation. Based on the framework of selective-tap updating scheme on the normalized least mean squares algorithm, the MMax and sparse partial update tap-selection strategies are exploited in the frequency domain to achieve fast convergence performance with low computational complexity. Through demonstrating how the sparseness of the network impulse response varies in the transformed domain, the multidelay filtering structure is incorporated to reduce the algorithmic delay. Blind identification of SIMO acoustic systems for speech dereverberation in the presence of common zeros is then investigated. First, the problem of common zeros is defined and extended to include the presence of near-common zeros. Two clustering algorithms are developed to quantify the number of these zeros so as to facilitate the study of their effect on blind system identification and speech dereverberation. To mitigate such effect, two algorithms are developed where the two-stage algorithm based on channel decomposition identifies common and non-common zeros sequentially; and the forced spectral diversity approach combines spectral shaping filters and channel undermodelling for deriving a modified system that leads to an improved dereverberation performance. Additionally, a solution to the scale factor ambiguity problem in subband-based blind system identification is developed, which motivates further research on subbandbased dereverberation techniques. Comprehensive simulations and discussions demonstrate the effectiveness of the aforementioned algorithms. A discussion on possible directions of prospective research on system identification techniques concludes this thesis

Orthogonal Frequency Division Multiplexing modulation and inter-carrier interference cancellation

The Orthogonal Frequency Division Multiplexing (OFDM) technique, wireless channel models, and a pair of new intercarrier interference self-cancellation methods are investigated in this thesis. The first chapter addresses the history of OFDM, along with its principles and applications. Chapter two consists of three parts: the principal, the modern OFDM models, and the Peak to Average Power Ratio (PAPR) problem. Chapter two also summarizes possible PAPR solutions. Chapter three discusses a series of well-known wireless channel models, as well as the general formula for wireless channels. In Chapter four, ICI problem has been discussed, along with its existing solutions. Chapter five focuses on two new ICI self-cancellation schemes, namely the clustering method and the multi-codebook method. These two new methods show promising results through the simulations. A summary of this thesis and the discussion of future research are also provided in Chapter five

A Survey of Blind Modulation Classification Techniques for OFDM Signals

Blind modulation classification (MC) is an integral part of designing an adaptive or intelligent transceiver for future wireless communications. Blind MC has several applications in the adaptive and automated systems of sixth generation (6G) communications to improve spectral efficiency and power efficiency, and reduce latency. It will become a integral part of intelligent software-defined radios (SDR) for future communication. In this paper, we provide various MC techniques for orthogonal frequency division multiplexing (OFDM) signals in a systematic way. We focus on the most widely used statistical and machine learning (ML) models and emphasize their advantages and limitations. The statistical-based blind MC includes likelihood-based (LB), maximum a posteriori (MAP) and feature-based methods (FB). The ML-based automated MC includes k-nearest neighbors (KNN), support vector machine (SVM), decision trees (DTs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) based MC methods. This survey will help the reader to understand the main characteristics of each technique, their advantages and disadvantages. We have also simulated some primary methods, i.e., statistical- and ML-based algorithms, under various constraints, which allows a fair comparison among different methodologies. The overall system performance in terms bit error rate (BER) in the presence of MC is also provided. We also provide a survey of some practical experiment works carried out through National Instrument hardware over an indoor propagation environment. In the end, open problems and possible directions for blind MC research are briefly discussed