Channel Prediction for Mobile MIMO Wireless Communication Systems

Temporal variation and frequency selectivity of wireless channels constitute a major drawback to the attainment of high gains in capacity and reliability offered by multiple antennas at the transmitter and receiver of a mobile communication system. Limited feedback and adaptive transmission schemes such as adaptive modulation and coding, antenna selection, power allocation and scheduling have the potential to provide the platform of attaining the high transmission rate, capacity and QoS requirements in current and future wireless communication systems. Theses schemes require both the transmitter and receiver to have accurate knowledge of Channel State Information (CSI). In Time Division Duplex (TDD) systems, CSI at the transmitter can be obtained using channel reciprocity. In Frequency Division Duplex (FDD) systems, however, CSI is typically estimated at the receiver and fed back to the transmitter via a low-rate feedback link. Due to the inherent time delays in estimation, processing and feedback, the CSI obtained from the receiver may become outdated before its actual usage at the transmitter. This results in significant performance loss, especially in high mobility environments. There is therefore a need to extrapolate the varying channel into the future, far enough to account for the delay and mitigate the performance degradation. The research in this thesis investigates parametric modeling and prediction of mobile MIMO channels for both narrowband and wideband systems. The focus is on schemes that utilize the additional spatial information offered by multiple sampling of the wave-field in multi-antenna systems to aid channel prediction. The research has led to the development of several algorithms which can be used for long range extrapolation of time-varyingchannels. Based on spatial channel modeling approaches, simple and efficient methods for the extrapolation of narrowband MIMO channels are proposed. Various extensions were also developed. These include methods for wideband channels, transmission using polarized antenna arrays, and mobile-to-mobile systems. Performance bounds on the estimation and prediction error are vital when evaluating channel estimation and prediction schemes. For this purpose, analytical expressions for bound on the estimation and prediction of polarized and non-polarized MIMO channels are derived. Using the vector formulation of the Cramer Rao bound for function of parameters, readily interpretable closed-form expressions for the prediction error bounds were found for cases with Uniform Linear Array (ULA) and Uniform Planar Array (UPA). The derived performance bounds are very simple and so provide insight into system design. The performance of the proposed algorithms was evaluated using standardized channel models. The effects of the temporal variation of multipath parameters on prediction is studied and methods for jointly tracking the channel parameters are developed. The algorithms presented can be utilized to enhance the performance of limited feedback and adaptive MIMO transmission schemes

Exploiting the spatio-temporal channel properties of multiple antenna systems

The spatio-temporal channel properties of multiple antenna systems are exploited to obtain new approaches to localization and channel prediction. It is shown that a mobile station can be localized in multipath environments under the explicit consideration of scatterers. Thus, unlike conventional localization systems, the scatterers are used as an aid in localization. Moreover, it is shown that channel prediction in multiple antenna systems can be performed using linear prediction filters. This result is used to propose optimal and computationally inexpensive suboptimal channel predictors

Characterisation of MIMO radio propagation channels

Due to the incessant requirement for higher performance radio systems, wireless designers have been constantly seeking ways to improve spectrum efficiency, link reliability, service quality, and radio network coverage. During the past few years, space-time technology which employs multiple antennas along with suitable signalling schemes and receiver architectures has been seen as a powerful tool for the implementation of the aforementioned requirements. In particular, the concept of communications via Multiple-Input Multiple-Output (MIMO) links has emerged as one of the major contending ideas for next generation ad-hoc and cellular systems. This is inherently due to the capacities expected when multiple antennas are employed at both ends of the radio link. Such a mobile radio propagation channel constitutes a MIMO system. Multiple antenna technologies and in particular MIMO signalling are envisaged for a number of standards such as the next generation of Wireless Local Area Network (WLAN) technology known as 802.1 ln and the development of the Worldwide Interoperability for Microwave Access (WiMAX) project, such as the 802.16e. For the efficient design, performance evaluation and deployment of such multiple antenna (space-time) systems, it becomes increasingly important to understand the characteristics of the spatial radio channel. This criterion has led to the development of new sounding systems, which can measure both spatial and temporal channel information. In this thesis, a novel semi-sequential wideband MIMO sounder is presented, which is suitable for high-resolution radio channel measurements. The sounder produces a frequency modulated continuous wave (FMCW) or chirp signal with variable bandwidth, centre frequency and waveform repetition rate. It has programmable bandwidth up to 300 MHz and waveform repetition rates up to 300 Hz, and could be used to measure conventional high- resolution delay/Doppler information as well as spatial channel information such as Direction of Arrival (DOA) and Direction of Departure (DOD). Notably the knowledge of the angular information at the link ends could be used to properly design and develop systems such as smart antennas. This thesis examines the theory of multiple antenna propagation channels, the sounding architecture required for the measurement of such spatial channel information and the signal processing which is used to quantify and analyse such measurement data. Over 700 measurement files were collected corresponding to over 175,000 impulse responses with different sounder and antenna array configurations. These included measurements in the Universal Mobile Telecommunication Systems Frequency Division Duplex (UMTS-FDD) uplink band, the 2.25 GHz and 5.8 GHz bands allocated for studio broadcast MIMO video links, and the 2.4 GHz and 5.8 GHz ISM bands allocated for Wireless Local Area Network (WLAN) activity as well as for a wide range of future systems defined in the WiMAX project. The measurements were collected predominantly for indoor and some outdoor multiple antenna channels using sounding signals with 60 MHz, 96 MHz and 240 MHz bandwidth. A wide range of different MIMO antenna array configurations are examined in this thesis with varying space, time and frequency resolutions. Measurements can be generally subdivided into three main categories, namely measurements at different locations in the environment (static), measurements while moving at regular intervals step by step (spatial), and measurements while the receiver (or transmitter) is on the move (dynamic). High-scattering as well as time-varying MIMO channels are examined for different antenna array structures

On geometry-base statistical channel models for MIMO wireles communications

El uso de sistemas de comunicación de banda ancha de múltiple entradamúltiple salida (Multiple Input Multiple Output MIMO) es actualmente objeto de un interés considerable. Una razón para esto es el reciente desarrollo de sistemas de comunicación móvil de tercera generación (3G) y superiores, tales como la tecnología de banda ancha Wideband Code Division Multiple Access (WCDMA, por sus siglas en inglés), la cual proporciona canales de radio de 5 MHz de ancho de banda. Para el diseño y la simulación de estos sistemas de radio móviles que usan propagación inalámbrica MIMO (como Wideband-CDMA por ejemplo), necesitamos modelos de canal que provean la requerida información espacial y temporal necesaria para el estudio de tales sistemas, esto es, los parámetros básicos de modelado en los dominios del espacio y el tiempo. Como ejemplo podemos mencionar, el valor cuadrático medio de la dispersión del retardo (Delay spread DS) el cual está directamente relacionado a la capacidad de un sistema de comunicación específico y nos da una idea aproximada de la complejidad del receptor. En esta tesis, se propone un modelo basado en geometría con enfoque en grupos (clusters) y es utilizado para el análisis en los dominios del espacio y el tiempo para condiciones estacionarias, y para representar los perfiles de potencia-angulo-retardo (Power Delay Angle Profiles PDAPs) de los componentes multi-trayectoria en ambientes urbanos. Además, se han derivado soluciones en formas cerradas para las expresiones en el dominio del ángulo (espacial) y del tiempo. La investigación previa sobre el modelado de canales cubre una amplia variedad de aspectos en varios niveles de detalle, incluyendo análisis para condiciones no estacionarias. Sin embargo el trabajo presentado en la literatura no incluye las relaciones entre los grupos (cluster) físicos y los PDAPs. El modelo propuesto basado en grupos (clusters) puede ser usado para mejorar aún más el desempeño en condiciones estacionarias de los sistemas de comunicaciones móviles actuales y futuros tales como los sistemas de comunicación MIMO de banda ancha. En la tesis también se presenta un análisis en el dominio del ángulo (espacial) y del tiempo respectivamente, a través de las funciones densidad de probabilidad (PDF) de la dirección de llegada (Direction of Arrival DOA) y el tiempo de llegada (Time of Arrival TOA) para el modelo basado en grupos. A fin de evaluar las funciones de probabilidad teóricas derivadas, éstas han sido comparadas con resultados experimentales publicados en la literatura. La comparación con estos resultados experimentales muestran una buena concordancia, no obstante la técnica de modelado presentada en esta tesis se encuentra limitada a condiciones estacionarias del canal. La condición de no estacionariedad se ubica más allá del alcance de esta tesis, es decir, el modelo propuesto no incorpora el efecto Doppler en los análisis

Space time transceiver design over multipath fading channels

Imperial Users onl

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

A Tutorial on Environment-Aware Communications via Channel Knowledge Map for 6G

Sixth-generation (6G) mobile communication networks are expected to have dense infrastructures, large-dimensional channels, cost-effective hardware, diversified positioning methods, and enhanced intelligence. Such trends bring both new challenges and opportunities for the practical design of 6G. On one hand, acquiring channel state information (CSI) in real time for all wireless links becomes quite challenging in 6G. On the other hand, there would be numerous data sources in 6G containing high-quality location-tagged channel data, making it possible to better learn the local wireless environment. By exploiting such new opportunities and for tackling the CSI acquisition challenge, there is a promising paradigm shift from the conventional environment-unaware communications to the new environment-aware communications based on the novel approach of channel knowledge map (CKM). This article aims to provide a comprehensive tutorial overview on environment-aware communications enabled by CKM to fully harness its benefits for 6G. First, the basic concept of CKM is presented, and a comparison of CKM with various existing channel inference techniques is discussed. Next, the main techniques for CKM construction are discussed, including both the model-free and model-assisted approaches. Furthermore, a general framework is presented for the utilization of CKM to achieve environment-aware communications, followed by some typical CKM-aided communication scenarios. Finally, important open problems in CKM research are highlighted and potential solutions are discussed to inspire future work