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In this thesis, we present a space-time coded system which achieves high through- put and good performance with low processing delay using low-complexity detection and decoding. Initially, Hamming codes are used in a simple interleaved bit-mapped coded modulation structure (BMCM). This is concatenated with Alamouti's or- thogonal space-time block codes. The good performance achieved by this system indicates that higher throughput is possible while maintaining performance. An analytical bound for the performance of this system is presented. We also develop a class of low density parity check codes which allows flexible "throughput versus performance" tradeoffs. We then focus on a Rate 2 quasi-orthogonal space-time block code structure which enables us to achieve an overall throughput of 5.6 bits/symbol period with good performance and relatively simple decoding using iterative parallel interference cancellation. We show that this can be achieved through the use of a bit-mapped coded modulation structure using parallel short low density parity check codes. The absence of interleavers here reduces processing delay significantly. The proposed system is shown to perform well on flat Rayleigh fading channels with a wide range of normalized fade rates, and to be robust to channel estimation errors. A comparison with bit-interleaved coded modulation is also provided (BICM).

A wireless relay network consists of multiple source nodes, multiple destination nodes, and possibly many relay nodes in between to facilitate its transmission. It is clear that the performance of such networks highly depends on information for- warding strategies adopted at the relay nodes. This dissertation studies a particular information forwarding strategy called compute-and-forward. Compute-and-forward is a novel paradigm that tries to incorporate the idea of network coding within the physical layer and hence is often referred to as physical layer network coding. The main idea is to exploit the superposition nature of the wireless medium to directly compute or decode functions of transmitted signals at intermediate relays in a net- work. Thus, the coding performed at the physical layer serves the purpose of error correction as well as permits recovery of functions of transmitted signals. For the bidirectional relaying problem with Gaussian channels, it has been shown by Wilson et al. and Nam et al. that the compute-and-forward paradigm is asymptotically optimal and achieves the capacity region to within 1 bit; however, similar results beyond the memoryless case are still lacking. This is mainly because channels with memory would destroy the lattice structure that is most crucial for the compute-and-forward paradigm. Hence, how to extend compute-and-forward to such channels has been a challenging issue. This motivates this study of the extension of compute-and-forward to channels with memory, such as inter-symbol interference. The bidirectional relaying problem with parallel Gaussian channels is also studied, which is a relevant model for the Gaussian bidirectional channel with inter-symbol interference and that with multiple-input multiple-output channels. Motivated by the recent success of linear finite-field deterministic model, we first investigate the corresponding deterministic parallel bidirectional relay channel and fully characterize its capacity region. Two compute-and-forward schemes are then proposed for the Gaussian model and the capacity region is approximately characterized to within a constant gap. The design of coding schemes for the compute-and-forward paradigm with low decoding complexity is then considered. Based on the separation-based framework proposed previously by Tunali et al., this study proposes a family of constellations that are suitable for the compute-and-forward paradigm. Moreover, by using Chinese remainder theorem, it is shown that the proposed constellations are isomorphic to product fields and therefore can be put into a multilevel coding framework. This study then proposes multilevel coding for the proposed constellations and uses multistage decoding to further reduce decoding complexity.

The main topic of this thesis is based on multiple-input multiple-output (MIMO) wireless communications, which is a novel technology that has attracted great interest in the last twenty years. Conventional MIMO systems using up to eight antennas play a vital role in the urban cellular network, where the deployment of multiple antennas have significantly enhanced the throughput without taking extra spectrum or power resources. The massive MIMO systems “scales” up the benefits that offered by the conventional MIMO systems. Using sixty four or more antennas at the BS not only improves the spectrum efficiency significantly, but also provides additional link robustness. It is considered as a key technology in the fifth generation of mobile communication technology standards network, and the design of new algorithms for these two systems is the basis of the research in this thesis. Firstly, at the receiver side of the conventional MIMO systems, a general framework of bit error rate (BER) approximation for the detection algorithms is proposed, which aims to support an adaptive modulation scheme. The main idea is to utilize a simplified BER approximation scheme, which is based on the union bound of the maximum-likelihood detector (MLD), whereby the bit error rate (BER) performance of the detector for the varying channel qualities can be efficiently predicted. The K-best detector is utilized in the thesis because its quasi- MLD performance and the parallel computational structure. The simulation results have clearly shown the adaptive K-best algorithm, by applying the simplified approximation method, has much reduced computational complexity while still maintaining a promising BER performance. Secondly, in terms of the uplink channel estimation for the massive MIMO systems with the time-division-duplex operation, the performance of the Grassmannian line packing (GLP) based uplink pilot codebook design is investigated. It aims to eliminate the pilot contamination effect in order to increase the downlink achievable rate. In the case of a limited channel coherence interval, the uplink codebook design can be treated as a line packing problem in a Grassmannian manifold. The closed-form analytical expressions of downlink achievable rate for both the single-cell and multi-cell systems are proposed, which are intended for performance analysis and optimization. The numerical results validate the proposed analytical expressions and the rate gains by using the GLP-based uplink codebook design. Finally, the study is extended to the energy efficiency (EE) of the massive MIMO system, as the reduction carbon emissions from the information and communication technology is a long-term target for the researchers. An effective framework of maximizing the EE for the massive MIMO systems is proposed in this thesis. The optimization starts from the maximization of the minimum user rate, which is aiming to increase the quality-of-service and provide a feasible constraint for the EE maximization problem. Secondly, the EE problem is a non-concave problem and can not be solved directly, so the combination of fractional programming and the successive concave approximation based algorithm are proposed to find a good suboptimal solution. It has been shown that the proposed optimization algorithm provides a significant EE improvement compared to a baseline case.

Les systèmes de communication à intensité optique en espace libre (FSOI) sont largement utilisés dans les communications à courte portée, telles que les communications infrarouges entre des dispositifs électroniques portables. L’émetteur de ces systèmes module sur l’intensité des signaux optiques émis par des diodes électroluminescentes (LEDs) ou des diodes laser (LDs), et le récepteur mesure les intensités optiques entrantes au moyen de photodétecteurs. Les entrées ne sont pas négatives car elles représentent des intensités. En outre, ils sont généralement soumis à des contraintes de puissance de pointe et moyenne, la contrainte de puissance de pointe étant principalement dû aux limitations techniques des composants utilisés, alors que la contrainte de puissance moyenne est imposée par des limitations de batterie et des considérations de sécurité. En première approximation, le bruit dans de tels systèmes peut être supposé être gaussien et indépendant du signal transmis. Cette thèse porte sur les limites fondamentales des systèmes de communication FSOI, plus précisément sur leur capacité. L’objectif principal de notre travail est d’étudier la capacité d’un canal FSOI général à entrées multiples et sorties multiples (MIMO) avec une contrainte de puissance de crête par entrée et une contrainte de puissance moyenne totale sur toutes les antennes d’entrée. Nous présentons plusieurs résultats de capacité sur le scénario quand il y a plus d’antennes d’émission que d’antennes de réception, c’est à-dire, nT > nR > 1. Dans ce scénario, différents vecteurs d’entrée peuvent donner des distributions identiques à la sortie, lorsqu’ils aboutissent au même vecteur d’image multiplié par la matrice de canal. Nous déterminons d’abord les vecteurs d’entrée d’énergie minimale permettant d’atteindre chacun de ces vecteurs d’image. Il définit à chaque instant dans le temps un sous-ensemble de nT − nR antennes à zéro ou à pleine puissance et utilise uniquement les nR antennes restantes pour la signalisation. Sur cette base, nous obtenons une expression de capacité équivalente en termes de vecteur d’image, ce qui permet de décomposer le canal d’origine en un ensemble de canaux presque parallèles. Chacun des canaux parallèles est un canal MIMO nR x nR à contrainte d’amplitude, avec une contrainte de puissance linéaire, pour laquelle des limites de capacité sont connues. Avec cette décomposition, nous établissons de nouvelles limites supérieures en utilisant une technique de limite supérieure basée sur la dualité, et des limites inférieures en utilisant l’inégalité de puissance d’entropie (EPI). Les limites supérieure et inférieure dérivées correspondent lorsque le rapport signal sur bruit (SNR) tend vers l’infini, établissant la capacité asymptotique à haut SNR. À faible SNR, il est connu que la pente de capacité est déterminée par la trace maximale de la matrice de covariance du vecteur image. Nous avons trouvé une caractérisation de cette trace maximale qui est plus facile à évaluer en calcul que les formes précédentes. / Free-space optical intensity (FSOI) communication systems are widely used in short-range communication such as the infrared communication between electronic handheld devices. The transmitter in these systems modulates on the intensity of optical signals emitted by light emitting diodes (LEDs) or laser diodes (LDs), and the receiver measures incoming optical intensities by means of photodetectors. Inputs are nonnegative because they represent intensities. Moreover, they are typically subject to both peak- and average-power constraints, where the peak-power constraint is mainly due to technical limitations of the used components, whereas the average-power constraint is imposed by battery limitations and safety considerations. As a first approximation, the noise in such systems can be assumed to be Gaussian and independent of the transmitted signal. This thesis focuses on the fundamental limits of FSOI communication systems, more precisely on their capacity. The major aim of our work is to study the capacity of a general multiple-input multiple-output (MIMO) FSOI channel under a per-input-antenna peak-power constraint and a total average-power constraint over all input antennas. We present several capacity results on the scenario when there are more transmit than receive antennas, i.e., nT > nR > 1. In this scenario, different input vectors can yield identical distributions at the output, when they result in the same image vector under multiplication by the channel matrix. We first determine the minimum-energy input vectors that attain each of these image vectors. It sets at each instant in time a subset of nT − nR antennas to zero or to full power, and uses only the remaining nR antennas for signaling. Based on this, we derive an equivalent capacity expression in terms of the image vector, which helps to decompose the original channel into a set of almost parallel channels. Each of the parallel channels is an amplitude-constrained nR⇥nR MIMO channel, with a linear power constraint, for which bounds on the capacity are known. With this decomposition, we establish new upper bounds by using a duality-based upper-bounding technique, and lower bounds by using the Entropy Power Inequality (EPI). The derived upper and lower bounds match when the signal-to-noise ratio (SNR) tends to infinity, establishing the high-SNR asymptotic capacity. At low SNR, it is known that the capacity slope is determined by the maximum trace of of the covariance matrix of the image vector. We found a characterization to this maximum trace that is computationally easier to evaluate than previous forms.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第20031号 / 情博第626号 / 新制||情||109(附属図書館) / 33127 / 京都大学大学院情報学研究科通信情報システム専攻 / (主査)教授 守倉 正博, 教授 原田 博司, 教授 梅野 健 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DGAM

Multi-antenna communication systems are attracting research interest as a means to increase the information capacity, reliability, and spectral efficiency of wireless information transfer. Ray-tracing methods predict the behavior of wireless channels using a model of the propagation environment and are a low-cost alternative to direct measurements. We use ray tracing simulations to validate the statistical time and angle of arrival characteristics of an indoor multipath channel and compare model parameter estimates with estimates derived from channel sounding measurements. Ray tracing predicts the time and angle clustering of multipaths observed in the measurements and provides model parameter estimates which are closely correlated with measured estimates. The ray tracing parameters relating to power characteristics show more deviation from measurements than the time and angle related parameters. Our results also indicate that the description of reflective scatterers in the propagation environment is more important to the quality of the predicted statistical behavior than the description of bulk materials. We use a ray synthesis model to investigate means of efficiently representing the channel for feedback information to the transmitter as a means to increase the information capacity. Several methods of selecting the ray-model feedback information are demonstrated with results from simulated and measured channels. These results indicate that an ESPRIT algorithm coupled with ad hoc transmit/receive pairing can yield better than 90% of the ideal waterfilling capacity when adequate training-based channel estimates are available. Additionally, we investigate a covariance feedback method for providing channel feedback for increased capacity. Both the ray-based and covariance-based feedback methods yield their highest capacity improvements when the signal to noise ratio is low. This results because of the larger benefit of focusing transmit power into the most advantageous eigenmodes of the channel when fewer eigenmodes have power allocated to them by the waterfilling capacity solution. In higher signal to noise ratio cases, more eigenmodes of the channel receive power when waterfilling, and the capacity improvement from feedback information decreases relative to a uniform power allocation. In general, ray model feedback methods are preferable because the covariance feedback quickly requires higher computational effort as the array sizes increase and typically results in lower capacity for a given amount of feedback information.

Yes / The paper presents the general requirements and an exemplary design of the RF front-end system that in today's handset is a key consumer of power. The design is required to minimize the carbon footprint in mobile handsets devices, whilst facilitating cooperation, and providing the energy-efficient operation of multi-standards for 5G communications. It provides the basis of hardware solutions for RF front-end integration challenges and offers design features covering energy efficiency for power amplifiers (PAs), Internet of Things (IoT) controlled tunable filters and compact highly isolated multiple-input and multiple-output (MIMO) antennas. An optimum design requires synergetic collaboration between academic institutions and industry in order to satisfy the key requirements of sub-6 GHz energy-efficient 5G transceivers, incorporating energy efficiency, good linearity and the potential for low-cost manufacturing. A highly integrated RF transceiver was designed and implemented to transmit and receive a picture using compact MIMO antennas integrated with efficient tunable filters and high linearity PAs. The proposed system has achieved a bit error rate (BER) of less than 10-10 at a data rate of 600 Mb/s with a wireless communication distance of more than 1 meter and power dissipation of 18-20 mW using hybrid beamforming technology and 64-QAM modulation. / 10.13039/100010665-H2020 Marie Skodowska Curie

This thesis explores the practical application of Physical Layer Security (PLS) inMultiple-Input Multiple-Output (MIMO) systems, particularly focusing on ShortPacket Communication (SPC). The aim is to enhance the security of wireless com-munications against eavesdropping threats. By employing advanced techniques suchas Maximum Ratio Transmission (MRT) and Maximum Ratio Combining (MRC),along with Beamforming, the study demonstrates how these methods can signifi-cantly strengthen the signal integrity in MIMO systems.In developing a comprehensive system model that integrates PLS into MIMO,the research provides a dual approach of evaluation. Rigorous theoretical analy-sis coupled with MATLAB simulations are utilized to validate the effectiveness ofthe proposed model. These methods not only underscore the feasibility of PLSin real-world applications but also highlight the potential improvements in wirelesscommunication security, offering a valuable contribution to the field.

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