Adaptive implementation of turbo multi-user detection architecture

MULTI-access techniques have been adopted widely for communications in underwater acoustic channels, which present many challenges to the development of reliable and practical systems. In such an environment, the unpredictable and complex ocean conditions cause the acoustic waves to be affected by many factors such as limited bandwidth, large propagation losses, time variations and long latency, which limit the usefulness of such techniques. Additionally, multiple access interference (MAI) signals and poor estimation of the unknown channel parameters in the presence of limited training sequences are two of the major problems that degrade the performance of such technologies. In this thesis, two different single-element multi-access schemes, interleave division multiple access (IDMA) and code division multiple access (CDMA), employing decision feedback equalization (DFE) and soft Rake-based architectures, are proposed for multi-user underwater communication applications. By using either multiplexing pilots or continuous pilots, these adaptive turbo architectures with carrier phase tracking are jointly optimized based on the minimum mean square error (MMSE) criterion and adapted iteratively by exchanging soft information in terms of Log-Likelihood Ratio (LLR) estimates with the single-user’s channel decoders. The soft-Rake receivers utilize developed channel estimation and the detection is implemented using parallel interference cancellation (PIC) to remove MAI effects between users. These architectures are investigated and applied to simulated data and data obtained from realistic underwater communication trials using off-line processing of signals acquired during sea-trials in the North Sea. The results of different scenarios demonstrate the penalty in performance as the fading induces irreducible error rates that increase with channel delay spread and emphasize the benefits of using coherent direct adaptive receivers in such reverberant channels. The convergence behaviour of the detectors is evaluated using EXIT chart analyses and issues such as the adaptation parameters and their effects on the performance are also investigated. However, in some cases the receivers with partial knowledge of the interleavers’ patterns or codes can still achieve performance comparable to those with full knowledge. Furthermore, the thesis describes implementation issues of these algorithms using digital signal processors (DSPs), such as computational complexity and provides valuable guidelines for the design of real time underwater communication systems.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Adaptive implementation of turbo multi-user detection architecture

MULTI-access techniques have been adopted widely for communications in underwater acoustic channels, which present many challenges to the development of reliable and practical systems. In such an environment, the unpredictable and complex ocean conditions cause the acoustic waves to be affected by many factors such as limited bandwidth, large propagation losses, time variations and long latency, which limit the usefulness of such techniques. Additionally, multiple access interference (MAI) signals and poor estimation of the unknown channel parameters in the presence of limited training sequences are two of the major problems that degrade the performance of such technologies. In this thesis, two different single-element multi-access schemes, interleave division multiple access (IDMA) and code division multiple access (CDMA), employing decision feedback equalization (DFE) and soft Rake-based architectures, are proposed for multi-user underwater communication applications. By using either multiplexing pilots or continuous pilots, these adaptive turbo architectures with carrier phase tracking are jointly optimized based on the minimum mean square error (MMSE) criterion and adapted iteratively by exchanging soft information in terms of Log-Likelihood Ratio (LLR) estimates with the single-user’s channel decoders. The soft-Rake receivers utilize developed channel estimation and the detection is implemented using parallel interference cancellation (PIC) to remove MAI effects between users. These architectures are investigated and applied to simulated data and data obtained from realistic underwater communication trials using off-line processing of signals acquired during sea-trials in the North Sea. The results of different scenarios demonstrate the penalty in performance as the fading induces irreducible error rates that increase with channel delay spread and emphasize the benefits of using coherent direct adaptive receivers in such reverberant channels. The convergence behaviour of the detectors is evaluated using EXIT chart analyses and issues such as the adaptation parameters and their effects on the performance are also investigated. However, in some cases the receivers with partial knowledge of the interleavers’ patterns or codes can still achieve performance comparable to those with full knowledge. Furthermore, the thesis describes implementation issues of these algorithms using digital signal processors (DSPs), such as computational complexity and provides valuable guidelines for the design of real time underwater communication systems.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Blind source separation for interference cancellation in CDMA systems

Communication is the science of "reliable" transfer of information between two parties, in the sense that the information reaches the intended party with as few errors as possible. Modern wireless systems have many interfering sources that hinder reliable communication. The performance of receivers severely deteriorates in the presence of unknown or unaccounted interference. The goal of a receiver is then to combat these sources of interference in a robust manner while trying to optimize the trade-off between gain and computational complexity. Conventional methods mitigate these sources of interference by taking into account all available information and at times seeking additional information e.g., channel characteristics, direction of arrival, etc. This usually costs bandwidth. This thesis examines the issue of developing mitigating algorithms that utilize as little as possible or no prior information about the nature of the interference. These methods are either semi-blind, in the former case, or blind in the latter case. Blind source separation (BSS) involves solving a source separation problem with very little prior information. A popular framework for solving the BSS problem is independent component analysis (ICA). This thesis combines techniques of ICA with conventional signal detection to cancel out unaccounted sources of interference. Combining an ICA element to standard techniques enables a robust and computationally efficient structure. This thesis proposes switching techniques based on BSS/ICA effectively to combat interference. Additionally, a structure based on a generalized framework termed as denoising source separation (DSS) is presented. In cases where more information is known about the nature of interference, it is natural to incorporate this knowledge in the separation process, so finally this thesis looks at the issue of using some prior knowledge in these techniques. In the simple case, the advantage of using priors should at least lead to faster algorithms.reviewe

Energy-efficient diversity combining for different access schemes in a multi-path dispersive channel

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e ComputadoresThe forthcoming generation of mobile communications, 5G, will settle a new standard for a larger bandwidth and better Quality of Service (QoS). With the exploding growth rate of user generated data, wireless standards must cope with this growth and at the same time be energy efficient to avoid depleting the batteries of wireless devices. Besides these issues, in a broadband wireless setting QoS can be severely affected from a multipath dispersive channel and therefore be energy demanding. Cross-layered architectures are a good choice to enhance the overall performance of a wireless system. Examples of cross-layered Physical (PHY) - Medium Access Control (MAC) architectures are type-II Diversity Combining (DC) Hybrid-ARQ (H-ARQ) and Multi-user Detection (MUD) schemes. Cross-layered type-II DC H-ARQ schemes reuse failed packet transmissions to enhance data reception on posterior retransmissions; MUD schemes reuse data information from previously collided packets on posterior retransmissions to enhance data reception. For a multipath dispersive channel, a PHY layer analytical model is proposed for Single-Carrier with Frequency Domain Equalization (SC-FDE) that supports DC H-ARQ and MUD. Based on this analytical model, three PHY-MAC protocols are proposed. A crosslayered Time Division Multiple Access (TDMA) scheme that uses DC H-ARQ is modeled and its performance is studied in this document; the performance analysis shows that the scheme performs better with DC and achieves a better energy efficiency at the cost of a higher delay. A novel cross-layered prefix-assisted Direct-Sequence Code Division Multiple Access (DS-CDMA) scheme is proposed and modeled in this document, it uses principles of DC and MUD. This protocol performs better by means of additional retransmissions, achieving better energy efficiency, at the cost of higher redundancy from a code spreading gain. Finally, a novel cross-layered protocol H-ARQ Network Division Multiple Access (H-NDMA) is proposed and modeled, where the combination of DC H-ARQ and MUD is used with the intent of maximizing the system capacity with a lower delay; system results show that the proposed scheme achieves better energy efficiency and a better performance at the cost of a higher number of retransmissions. A comparison of the three cross-layered protocols is made, using the PHY analytical model, under normalized conditions using the same amount of maximum redundancy. Results show that the H-NDMA protocol, in general, obtains the best results, achieving a good performance and a good energy efficiency for a high channel load and low Signal-to-Noise Ratio (SNR). TDMA with DC H-ARQ achieves the best energy efficiency, although presenting the worst delay. Prefix-assisted DS-CDMA in the other hand shows good delay results but presents the worst throughput and energy efficiency

Optimisation of Iterative Multi-user Receivers using Analytical Tools

The objective of this thesis is to develop tools for the analysis and optimization of an iterative receiver. These tools can be applied to most soft-in soft-out (SISO) receiver components. For illustration purposes we consider a multi-user DS-CDMA system with forward error correction that employs iterative multi-user detection based on soft interference cancellation and single user decoding. Optimized power levels combined with adaptive scheduling allows for efficient utilization of receiver resources for heavily loaded systems.¶ Metric transfer analysis has been shown to be an accurate method of predicting the convergence behavior of iterative receivers. EXtrinsic Information (EXIT), fidelity (FT) and variance (VT) transfer analysis are well-known methods, however the relationship between the different approaches has not been explored in detail. We compare the metrics numerically and analytically and derive functions to closely approximate the relationship between them. The result allows for easy translation between EXIT, FT and VT methods. Furthermore, we extend the $J$ function, which describes mutual information as a function of variance, to fidelity and symbol error variance, the Rayleigh fading channel model and a channel estimate. ...

Advanced signal processing concepts for multi-dimensional communication systems

Die weit verbreitete Nutzung von mobilem Internet und intelligenten Anwendungen hat zu einem explosionsartigen Anstieg des mobilen Datenverkehrs geführt. Mit dem Aufstieg von intelligenten Häusern, intelligenten Gebäuden und intelligenten Städten wächst diese Nachfrage ständig, da zukünftige Kommunikationssysteme die Integration mehrerer Netzwerke erfordern, die verschiedene Sektoren, Domänen und Anwendungen bedienen, wie Multimedia, virtuelle oder erweiterte Realität, Machine-to-Machine (M2M) -Kommunikation / Internet of Things (IoT), Automobilanwendungen und vieles mehr. Daher werden die Kommunikationssysteme zukünftig nicht nur eine drahtlose Verbindung über Gbps bereitstellen müssen, sondern auch andere Anforderungen erfüllen müssen, wie z. B. eine niedrige Latenzzeit und eine massive Maschinentyp-Konnektivität, während die Dienstqualität sichergestellt wird. Ohne bedeutende technologische Fortschritte zur Erhöhung der Systemkapazität wird die bestehende Telekommunikationsinfrastruktur diese mehrdimensionalen Anforderungen nicht unterstützen können. Dies stellt eine wichtige Forderung nach geeigneten Wellenformen und Signalverarbeitungslösungen mit verbesserten spektralen Eigenschaften und erhöhter Flexibilität dar. Aus der Spektrumsperspektive werden zukünftige drahtlose Netzwerke erforderlich sein, um mehrere Funkbänder auszunutzen, wie zum Beispiel niedrigere Frequenzbänder (typischerweise mit Frequenzen unter 10 GHz), mm-Wellenbänder (einige hundert GHz höchstens) und THz-Bänder. Viele alternative Technologien wie Optical Wireless Communication (OWC), dynamische Funksysteme und zellulares Radar sollten ebenfalls untersucht werden, um ihr wahres Potenzial abzuschätzen. Insbesondere bietet OWC ein großes, aber noch nicht genutztes optisches Band im sichtbaren Spektrum, das Licht als Mittel zur Informationsübertragung nutzt. Daher können zukünftige Kommunikationssysteme als zusammengesetzte Hybridnetzwerke angesehen werden, die aus einer Anzahl von verschiedenen drahtlosen Netzwerken bestehen, die auf Funk und optischem Zugang basieren. Auf der anderen Seite ist es eine große Herausforderung, fortschrittliche Signalverarbeitungslösungen für mehrere Bereiche von Kommunikationssystemen zu entwickeln. Diese Arbeit trägt zu diesem Ziel bei, indem sie Methoden für die Suche nach effizienten algebraischen Lösungen für verschiedene Anwendungen der digitalen Mehrkanal-Signalverarbeitung demonstriert. Insbesondere tragen wir zu drei verschiedenen Anwendungsgebieten bei, d.h. Wellenformen, optischen drahtlosen Systemen und mehrdimensionaler Signalverarbeitung. Gegenwärtig ist das Cyclic Prefix Orthogonal Frequency Division Multiplexing (CP-OFDM) die weit verbreitete Multitragetechnik für die meisten Kommunikationssysteme. Um jedoch die CP-OFDM-Nachteile in Bezug auf eine schlechte spektrale Eingrenzung, Robustheit in hoch asynchronen Umgebungen und Unflexibilität der Parameterwahl zu überwinden, wurden viele alternative Wellenformen vorgeschlagen. Solche Mehrfachträgerwellenformen umfassen einen Filter bank Multicarrier (FBMC), ein Generalized Frequency Division Multiplexing (GFDM), einen Universal Filter Multicarrier (UFMC) und ein Unique Word Orthogonal Orthogonal Frequency Division Multiplexing (UW-OFDM). Diese neuen Luftschnittstellenschemata verwenden verschiedene Ansätze, um einige der inhärenten Mängel bei CP-OFDM zu überwinden. Einige dieser Wellenformen wurden gut untersucht, während andere sich noch in den Kinderschuhen befinden. Insbesondere die Integration von Multiple-Input-Multiple-Output (MIMO) -Konzepten mit UW-OFDM und UFMC befindet sich noch in einem frühen Forschungsstadium. Daher schlagen wir im ersten Teil dieser Arbeit neuartige lineare und sukzessive Interferenzunterdrückungstechniken für MIMO UW-OFDM-Systeme vor. Das Design dieser Techniken zielt darauf ab, Empfänger mit einer geringen Rechenkomplexität zu erhalten. Ein weiterer Schwerpunkt ist die Anwendbarkeit von Space-Time Block Codes (STBCs) auf UW-OFDM und UFMC-Wellenformen. Zu diesem Zweck stellen wir neue Techniken zusammen mit Detektionsverfahren vor. Wir vergleichen auch die Leistung dieser Wellenformen mit unseren vorgeschlagenen Techniken mit den anderen Wellenformen des Standes der Technik, die in der Literatur vorgeschlagen wurden. Wir zeigen, dass raumzeitblockierte UW-OFDM-Systeme mit den vorgeschlagenen Methoden nicht nur andere Wellenformen signifikant übertreffen, sondern auch zu Empfängern mit geringer Rechnerkomplexität führen. Der zweite Anwendungsbereich umfasst optische Systeme im sichtbaren Band (390-700 nm), die in Plastic Optical Fibers (POFs), Multimode-Fasern oder OWC-Systemen wie der Kommunikation über Visible Light Communication (VLC) verwendet werden können. VLC kann Lösungen für eine Reihe von Anwendungen anbieten, einschließlich drahtloser lokaler, persönlicher und Körperbereichsnetzwerke (WLAN, WPAN und WBANs), Innenlokalisierung und -navigation, Fahrzeugnetze, U-Bahn- und Unterwassernetze und bietet eine Reihe von Datenraten von wenigen Mbps zu 10 Gbps. VLC nutzt voll sichtbare Light Emitting Diodes (LEDs) für den doppelten Zweck der Beleuchtung und Datenkommunikation bei sehr hohen Geschwindigkeiten. Daher verwenden solche Systeme Intensitätsmodulation und Direct Detection (IM / DD), wodurch gefordert wird, dass das Sendesignal reellwertig und positiv sein sollte. Dies impliziert auch, dass die herkömmlichen Wellenformen, die für die Radio Frequency (RF) Kommunikation ausgelegt sind, nicht direkt verwendet werden können. Zum Beispiel muss eine hermetische Symmetrie auf das CP-OFDM angewendet werden, um ein reellwertiges Signal zu erhalten (oft als Discrete Multitone Transmission (DMT) bezeichnet), das im Gegenzug die Bandbreiteneffizienz verringert. Darüber hinaus begrenzt die LED / LED-Treiberkombination die elektrische Bandbreite. Alle diese Faktoren erfordern die Verwendung spektral effizienter Übertragungsverfahren zusammen mit robusten Entzerrungsschemata, um hohe Datenraten zu erzielen. Deshalb schlagen wir im zweiten Teil der Arbeit Übertragungsverfahren vor, die für solche optischen Systeme am besten geeignet sind. Insbesondere demonstrieren wir die Leistung der PAM-Blockübertragung mit Frequenzbereichsausgleich. Wir zeigen, dass dieses Schema nicht nur leistungsstärker ist, sondern auch alle modernen Verfahren wie CP-DMT-Schemata übertrifft. Wir schlagen auch neue UW-DMT-Schemata vor, die vom UW-OFDM-Konzept abgeleitet sind. Diese Schemata zeigen auch ein sehr überlegenes Bitfehlerverhältnis (BER) -Performance gegenüber den herkömmlichen CP-DMT-Schemata. Der dritte Anwendungsbereich konzentriert sich auf mehrdimensionale Signalverarbeitungstechniken. Bei der Verwendung von MIMO, STBCs, Mehrbenutzerverarbeitung und Mehrträgerwellenformen bei der drahtlosen Kommunikation ist das empfangene Signal mehrdimensional und kann eine multilineare Struktur aufweisen. In diesem Zusammenhang können Signalverarbeitungstechniken, die auf einem Tensor-Modell basieren, gleichzeitig von mehreren Formen von Diversität profitieren, um Mehrbenutzer-Signaltrennung / -entzerrung und Kanalschätzung durchzuführen. Dieser Vorteil ist eine direkte Konsequenz der Eigenschaft der wesentlichen Eindeutigkeit, die für matrixbasierte Ansätze nicht verfügbar ist. Tensor-Zerlegung wie die Higher Order Singular Value Decomposition (HOSVD) und die Canonical Polyadic Decomposition (CPD) werden weithin zur Durchführung dieser Aufgaben empfohlen. Die Leistung dieser Techniken wird oft mit zeitraubenden Monte-Carlo-Versuchen bewertet. Im letzten Teil der Arbeit führen wir eine Störungsanalyse erster Ordnung dieser Tensor-Zerlegungsmethoden durch. Insbesondere führen wir eine analytische Performanceanalyse des Semi-algebraischen Frameworks für approximative Canonical polyadic decompositions Simultaneous matrix diagonalizations (SECSI) durch. Das SECSI-Framework ist ein effizientes Werkzeug zur Berechnung der CPD eines rauscharmen Tensor mit niedrigem Rang. Darüber hinaus werden die erhaltenen analytischen Ausdrücke in Bezug auf die Momente zweiter Ordnung des Rauschens formuliert, so dass abgesehen von einem Mittelwert von Null keine Annahmen über die Rauschstatistik erforderlich sind. Wir zeigen, dass die abgeleiteten analytischen Ergebnisse eine ausgezeichnete Übereinstimmung mit den Monte-Carlo-Simulationen zeigen.The widespread use of mobile internet and smart applications has led to an explosive growth in mobile data traffic. With the rise of smart homes, smart buildings, and smart cities, this demand is ever growing since future communication systems will require the integration of multiple networks serving diverse sectors, domains and applications, such as multimedia, virtual or augmented reality, machine-to-machine (M2M) communication / the Internet of things (IoT), automotive applications, and many more. Therefore, in the future, the communication systems will not only be required to provide Gbps wireless connectivity but also fulfil other requirements such as low latency and massive machine type connectivity while ensuring the quality of service. Without significant technological advances to increase the system capacity, the existing telecommunications infrastructure will be unable to support these multi-dimensional requirements. This poses an important demand for suitable waveforms with improved spectral characteristics and signal processing solutions with an increased flexibility. Moreover, future wireless networks will be required to exploit several frequency bands, such as lower frequency bands (typically with frequencies below 10 GHz), mm-wave bands (few hundred GHz at the most), and THz bands. Many alternative technologies such as optical wireless communication (OWC), dynamic radio systems, and cellular radar should also be investigated to assess their true potential. Especially, OWC offers large but yet unexploited optical band in the visible spectrum that uses light as a means to carry information. Therefore, future communication systems can be seen as composite hybrid networks that consist of a number of different wireless networks based on radio and optical access. On the other hand, it poses a significant challenge to come up with advanced signal processing solutions in multiple areas of communication systems. This thesis contributes to this goal by demonstrating methods for finding efficient algebraic solutions to various applications of multi-channel digital signal processing. In particular, we contribute to three different scientific fields, i.e., waveforms, optical wireless systems, and multi-dimensional signal processing. Currently, cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) is the widely adopted multicarrier technique for most of the communication systems. However, to overcome the CP-OFDM demerits in terms of poor spectral containment, poor robustness in highly asynchronous environments, and inflexibility of parameter choice, and many alternative waveforms have been proposed. Such multicarrier waveforms include filter bank multicarrier (FBMC), generalized frequency division multiplexing (GFDM), universal filter multicarrier (UFMC), and unique word orthogonal frequency division multiplexing (UW-OFDM). These new air interface schemes take different approaches to overcome some of the inherent deficiencies in CP-OFDM. Some of these waveforms have been well investigated while others are still in its infancy. Specifically, the integration of multiple-input multiple-output (MIMO) concepts with UW-OFDM and UFMC is still at an early stage of research. Therefore, in the first part of this thesis, we propose novel linear and successive interference cancellation techniques for MIMO UW-OFDM systems. The design of these techniques is aimed to result in receivers with a low computational complexity. Another focus area is the applicability of space-time block codes (STBCs) to UW-OFDM and UFMC waveforms. For this purpose, we present novel techniques along with detection procedures. We also compare the performance of these waveforms with our proposed techniques to the other state-of-the-art waveforms that has been proposed in the literature. We demonstrate that space-time block coded UW-OFDM systems with the proposed methods not only outperform other waveforms significantly but also results in receivers with a low computational complexity. The second application area comprises of optical systems in the visible band (390-700 nm) that can be utilized in plastic optical fibers (POFs), multimode fibers or OWC systems such as visible light communication (VLC). VLC can provide solutions for a number of applications including wireless local, personal, and body area networks (WLAN, WPAN, and WBANs), indoor localization and navigation, vehicular networks, underground and underwater networks, offering a range of data rates from a few Mbps to 10 Gbps. VLC takes full advantage of visible light emitting diodes (LEDs) for the dual purpose of illumination and data communications at very high speeds. Because of the incoherent nature of the LED sources, such systems employ intensity modulation and direct detection (IM/DD), thus demanding that the transmit signal should be real-valued and positive. This also implies that the conventional waveforms designed for the radio frequency (RF) communication cannot be directly used. For example, a Hermitian symmetry has to be applied to the CP-OFDM spectrum to obtain a real-valued signal (often referred to as discrete multitone transmission (DMT)) that in return reduces the bandwidth efficiency. Moreover, the LED/LED driver combination limits the electrical bandwidth. All these factors require the use of spectrally efficient transmission schemes along with robust equalization schemes to achieve high data rates. Therefore, in the second part of the thesis, we propose transmission schemes that are best suited for such optical systems. Specifically, we demonstrate the performance of PAM block transmission with frequency domain equalization. We show that this scheme is not only more power efficient but also outperforms all of the state-of-the-art schemes such as CP-DMT schemes. We also propose novel UW-DMT schemes that are derived from the UW-OFDM concept. These schemes also show a much superior bit error ratio (BER) performance over the conventional CP-DMT schemes. The third application area focuses on multi-dimensional signal processing techniques. With the use of MIMO, STBCs, multi-user processing, and multicarrier waveforms in wireless communications, the received signal is multidimensional in nature and may exhibit a multilinear structure. In this context, signal processing techniques based on a tensor model can simultaneously benefit from multiple forms of diversity to perform multi-user signal separation/equalization and channel estimation. This advantage is a direct consequence of the essential uniqueness property that is not available for matrix based approaches. Tensor decompositions such as the higher order singular value decomposition (HOSVD) and the canonical polyadic decomposition (CPD) are widely recommended for performing these tasks. The performance of these techniques is often evaluated using time consuming Monte-Carlo trials. In the last part of the thesis, we perform a first-order perturbation analysis of the truncated HOSVD and the Semi-algebraic framework for approximate Canonical polyadic decompositions via Simultaneous matrix diagonalizations (SECSI). The SECSI framework is an efficient tool for the computation of the approximate CPD of a low-rank noise corrupted tensor. Especially, the SECSI framework shows a much improved performance and comparatively low-complexity as compared to the conventional algorithms such as alternative least squares (ALS). Moreover, it also facilitates the implementation on a parallel hardware architecture. The obtained analytical expressions for both algorithms are formulated in terms of the second-order moments of the noise, such that apart from a zero-mean, no assumptions on the noise statistics are required. We demonstrate that the derived analytical results exhibit an excellent match to the Monte-Carlo simulations

The Interplay between Computation and Communication

In this thesis, a comprehensive exploration into the integration of communication and learning within the massive Internet of Things (mIoT) is undertaken. Addressing one of the fundamental challenges of mIoT, where traditional channel estimation methods prove inefficient due to high device density and short packets; initially, a novel approach leveraging unsupervised machine learning for joint channel estimation and signal detection is proposed. This technique utilizes the Gaussian mixture model (GMM) clustering of received signals, thereby reducing the necessity for exhaustive channel estimation, decreasing the number of required pilot symbols, and enhancing symbol error rate (SER) performance. Building on this foundation, an innovative method is proposed that eliminates the need for pilot symbols entirely. By coupling GMM clustering with rotational invariant (RI) coding, the model maintains robust performance against the effects of channel rotation, thereby improving the efficiency of mIoT systems. This research delves further into integrating communication and learning in mIoT, specifically focusing on federated learning (FL) convergence under error-prone conditions. It carefully analyzes the impact of factors like block length, coding rate, and signal-to-noise ratio on FL's accuracy and convergence. A novel approach is proposed to address communication error challenges, where the base station (BS) uses memory to cache key parameters. Closing the thesis, an extensive simulation of a real-world mIoT system, integrating previously developed techniques, such as the innovative channel estimation method, RI coding, and the introduced FL model. It notably demonstrates that optimal learning outcomes can be achieved even without stringent communication reliability. Thus, this work not only achieves comparable or superior performance to traditional methods with fewer pilot symbols but also provides valuable insights for optimizing mIoT systems within the FL framework

An Efficient Noisy-ICA Based Approach to Multiuser Detection in IDMA Systems Abstract

Interleaved Division Multiple Access (IDMA) is a new access scheme that has been proposed in the literature to increase the capacity of wireless channels. The performance of such systems depends on the accuracy of the channel state information at the receiver. In this paper, a Noisy-Independent Component Analysis (N-ICA) based IDMA receiver for multiple access communication channels is proposed. The N-ICA component is applied as a post processor. Unlike other IDMA receivers, the proposed scheme detects and separates the transmitted symbols without channel state information tracking. The performance of the proposed technique is presented in terms of raw bit error rate (BER) without channel coding for different signal to noise ratios (SNR). Simulation results demonstrate that N-ICA post processor provides an improvement in performance in BER in loaded systems. When the system is not loaded, the proposed post processor has the same performance as conventional IDMA receiver with less iterations leading to a complexity reduction