Performance analysis of reconfigurable intelligent surface assisted wireless communications

The advent of the smart radio environment has challenged traditional wireless communication systems, and reconfigurable intelligent surfaces (RIS) have emerged as a promising solution to enhance the performance limits of wireless communications. This thesis aims to study RIS technology in future networks by examining the performance of four typical RIS-assisted communication systems, each featuring unique models and practical RIS characteristics. The research begins with the performance analysis of RIS-assisted wireless communication systems with phase errors in both line-of-sight (LoS) and Rayleigh fading scenarios. It investigates the impact of different types of phase errors and other system parameters on system performance. Next, the impact of channel correlations on RIS-assisted communication systems is examined by deriving closed-form expressions of outage probability and average achievable rates for both correlated Rayleigh fading and correlated Nakagami-m fading models. The relationship between RIS size and performance degradation caused by channel correlations is explored. The study further investigates the application of RIS technology in more intricate wireless communication systems, specifically focusing on two spectrum efficiency techniques: non-orthogonal multiple access (NOMA) and full-duplex (FD) communications. For RIS-assisted NOMA, the research derives closed-form expressions for the outage probability of users with strong and weak channel conditions, while for RIS-assisted FD systems, the research proposes a setup where an FD transceiver serves uplink and downlink users simultaneously with two dedicated RISs and examines the impact of residual self-interference (SI). Finally, the performance of a RIS-assisted largescale network is examined through stochastic geometry, assessing coverage probability and average achievable rate. The research discusses two association strategies: nearest and fixed association, and investigates the effects of increasing transmitter (TX) density and RIS association probability on system performance. This thesis provides valuable analytical resources on RIS-assisted wireless communications performance, laying a foundation for future research and application of RIS technology

Advanced Trends in Wireless Communications

Physical limitations on wireless communication channels impose huge challenges to reliable communication. Bandwidth limitations, propagation loss, noise and interference make the wireless channel a narrow pipe that does not readily accommodate rapid flow of data. Thus, researches aim to design systems that are suitable to operate in such channels, in order to have high performance quality of service. Also, the mobility of the communication systems requires further investigations to reduce the complexity and the power consumption of the receiver. This book aims to provide highlights of the current research in the field of wireless communications. The subjects discussed are very valuable to communication researchers rather than researchers in the wireless related areas. The book chapters cover a wide range of wireless communication topics

Enhancing Signal Detection in 6G Networks through LSTM-based MIMO Technology

Artificial intelligence (AI) transforms the multiple input multiple output (MIMO) technology into a promising candidate for beyond-fifth-generation (B5G) and upcoming sixth-generation (6G) networks. However, due to the large number of antennas in the MIMO systems, the detection process becomes very complex and also shows high computational complexity. To address this issue, this paper introduces an optimized AI-based signal detection method based on Long short-term memory (LSTM) called LSTM-based signal detection for MIMO systems. The proposed model works more efficiently in signal detection as compared to the conventional signal detection methods in terms of symbol error rate (SER) at different signal-to-noise ratios (SNR). The optimized simple LSTM architecture provides significant advantages in detecting patterns from input data. This paper goes through the various aspects of signal detection using LSTM, such as system architecture design, data preparation and training process of the neural network, performance evaluation, and future scope. Overall, this paper provides a comprehensive resource for the deployment of an LSTM neural network for signal detection in the upcoming 6G wireless networks.</p

Multiple-Input Multiple-Output Communications Systems Using Reconfigurable Antennas

RÉSUMÉ Depuis les années 1990, l'utilisation des systèmes de communications sans-fil à entrées multiples-sorties multiples (MIMO) a été introduit pour fournir des transmissions fiables à grande vitesse. Cette thèse porte sur l'application et l’étude des systèmes MIMO avec des antennes reconfigurables, qui sont ajustable électroniquement pour produire différents diagrammes de rayonnement d'un seul élément d'antenne et ainsi offrir une diversité de diagrammes de rayonnement. En particulier, nous étudions le comportement de la capacité de canal des systèmes MIMO à sélection de diagrammes de rayonnement (PS-MIMO), et nous proposons aussi des algorithmes de sélection du diagramme de rayonnement atteignant la capacité maximale. Tout d'abord, nous étudions l'application des antennes reconfigurables dans l'estimation des statistiques spatiales à long terme de canaux spatiaux avec grappes de multi-trajets (cluster). Nous proposons un estimateur de spectre de type Capon et une technique d'adaptation de la covariance (COMET) pour estimer conjointement l'angle moyen et l’étalement angulaire de la grappe spatiale avec des antennes reconfigurables. En second lieu, sur la base des statistiques à long terme du canal MIMO, nous proposons des algorithmes de sélection de diagramme de rayonnement MIMO (SPS-MIMO) pour atteindre la capacité maximale de canal ergodique. L'analyse de la maximisation de la capacité ergodique du système SPS-MIMO indique que le modèle statistique de sélection fournit des gains supplémentaires en améliorant la puissance du signal reçu et en décorrélant les signaux reçus avec différents diagrammes de rayonnement directionnels. Troisièmement, nous nous concentrons sur le modèle de sélection instantanée des diagrammes de rayonnement MIMO (IPS-MIMO) basé sur des informations instantanées d'état de canal (CSI) afin de maximiser la capacité instantanée pour chaque réalisation de canal. Nous démontrons que l’ordre de diversité des systèmes MIMO peut être multipliée par le nombre de diagrammes de rayonnement avec sélection de diagramme instantanée. Afin d'évaluer la capacité moyenne de l'IPS-MIMO, nous proposons un nouvel algorithme qui permet d’approximer étroitement la moyenne de la valeur maximale de la capacité du canal MIMO avec des trajets arbitrairement corrélés. Nous proposons également un algorithme pour sélectionner instantanément les diagrammes de rayonnement pour atteindre la capacité moyenne. En outre, sur la base d'une simple expression en forme fermée de la capacité coefficient de corrélation, nous sommes en mesure de proposer un algorithme de sélection de sous-ensemble de diagrammes qui offre un compromis entre performances et la complexité de l’algorithme de sélection. En conclusion, des gains de performance importants peuvent être obtenus grâce à la combinaison de l'utilisation d’antennes reconfigurables et de systèmes MIMO avec soit des algorithmes de sélection de diagramme de rayonnement statistique ou instantanée. La capacité des systèmes PS-MIMO à améliorer les performances du système, y compris la capacité et de l'ordre de la diversité, est démontrée par l'analyse théorique et des simulations numériques.----------ABSTRACT Since the 1990s, the use of multiple-input multiple-output (MIMO) systems has been introduced to modern wireless communications to provide reliable transmission at high data rates. This thesis focuses on the application of MIMO systems with reconfigurable antennas, which are electronically tunable to produce a number of radiation patterns at a single antenna element and provide pattern diversity. In particular, we investigate the capacity performance of the pattern selection MIMO (PS-MIMO) systems, and we also present maximum capacity achieving algorithms for radiation pattern selection. First, we investigate the application of reconfigurable antennas in estimating long term spatial statistics of spatial clustered channels. We propose a Capon-like spectrum estimator and a covariance matching technique (COMET) to jointly estimate the mean angle and the angular spread of the spatial cluster with reconfigurable antennas. Second, based on the long term statistics of the MIMO channel, we propose statistical pattern selection MIMO (SPS-MIMO) algorithms to achieve maximum ergodic channel capacity. Analysis of the ergodic capacity maximization of the SPS-MIMO indicates that the statistical pattern selection provides additional gains by enhancing received signal power and decorrelating received signals with different directional radiation patterns. Third, we focus on the instantaneous pattern selection MIMO (IPS-MIMO) based on instantaneous channel state information (CSI) in order to maximize the instantaneous capacity for every channel realization. We prove that the diversity order of MIMO systems can be multiplied by the number of radiation patterns with instantaneous pattern selection. In order to evaluate the mean capacity of the IPS-MIMO, we propose a novel algorithm which closely approximates the mean of the maximum of the channel capacity of arbitrarily correlated MIMO channels. We also propose an algorithm for instantaneously selecting radiation patterns to achieve the mean capacity. In addition, based on a simple closed-form approximation to the capacity correlation coefficient, we are able to propose a subset pattern selection algorithm which enables the trade-off between performances and complexity. In conclusion, important extra gains can be obtained as a result of combining the use of reconfigurable antennas and MIMO systems with either statistical or instantaneous radiation pattern selection. The capability of the PS-MIMO to improve system performances, including capacity and diversity order, is demonstrated through theoretical analysis and numerical simulations

Performance analysis of cooperative diversity in land mobile satellite systems.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2013.Land Mobile Satellite Systems (LMSS) generally differ from other terrestrial wireless systems. The LMSS exhibit unique characteristics with regard to the physical layer, interference scenarios, channel impairements, propagation delay, link characteristics, service coverage, user and satellite mobility etc. Terrestrial wireless systems have employed the spatial diversity or MIMO (Multiple Input Multiple Output) technique in addressing the problem of providing uninterrupted service delivery to all mobile users especially in places where non-Line-of-Sight (NLoS) condition is prevalent (e.g. urban and suburban environments). For the LMSS, cooperative diversity has been proposed as a valuable alternative to the spatial diversity technique since it does not require the deployment of additional antennas in order to mitigate the fading effects. The basis of cooperative diversity is to have a group of mobile terminals sharing their antennas in order to generate a “virtual” multiple antenna, thus obtaining the same effects as the conventional MIMO system. However, the available cooperative diversity schemes as employed are based on outdated channel quality information (CQI) which is impracticable for LMSS due to its peculiar characteristics and its particularly long propagation delay. The key objective of this work is therefore to develop a cooperative diversity technology model which is most appropriate for LMSS and also adequately mitigates the outdated CQI challenge. To achieve the objective, the feasibility of cooperative diversity for LMSS was first analyzed by employing an appropriate LMSS channel model. Then, a novel Predictive Relay Selection (PRS) cooperative diversity scheme for LMSS was developed which adequately captured the LMSS architecture. The PRS cooperative scheme developed employed prediction algorithms, namely linear prediction and pattern-matching prediction algorithms in determining the future CQI of the available relay terminals before choosing the most appropriate relay for cooperation. The performance of the PRS cooperative diversity scheme in terms of average output SNR, outage probability, average channel capacity and bit error probability were simulated, then numerically analyzed. The results of the PRS cooperative diversity model for LMSS developed not only showed the gains resulting from introducing cooperative techniques in satellite communications but also showed improvement over other cooperative techniques that based their relay selection cooperation on channels with outdated quality information (CQI). Finally, a comparison between the results obtained from the various predictive models considered was carried out and the best prediction model was recommended for the PRS cooperation