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

Modeling of wide-band MIMO radio channels based on NLoS indoor measurements

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Multiuser MIMO-OFDM for Next-Generation Wireless Systems

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems

A Novel Millimeter-Wave Channel Simulator and Applications for 5G Wireless Communications

This paper presents details and applications of a novel channel simulation software named NYUSIM, which can be used to generate realistic temporal and spatial channel responses to support realistic physical- and link-layer simulations and design for fifth-generation (5G) cellular communications. NYUSIM is built upon the statistical spatial channel model for broadband millimeter-wave (mmWave) wireless communication systems developed by researchers at New York University (NYU). The simulator is applicable for a wide range of carrier frequencies (500 MHz to 100 GHz), radio frequency (RF) bandwidths (0 to 800 MHz), antenna beamwidths (7 to 360 degrees for azimuth and 7 to 45 degrees for elevation), and operating scenarios (urban microcell, urban macrocell, and rural macrocell), and also incorporates multiple-input multiple-output (MIMO) antenna arrays at the transmitter and receiver. This paper also provides examples to demonstrate how to use NYUSIM for analyzing MIMO channel conditions and spectral efficiencies, which show that NYUSIM is an alternative and more realistic channel model compared to the 3rd Generation Partnership Project (3GPP) and other channel models for mmWave bands.Comment: 7 pages, 8 figures, in 2017 IEEE International Conference on Communications (ICC), Paris, May 201

Performance of multiple-input multiple-output wireless communications systems using distributed antennas

In this contribution we propose and investigate a multiple-input multiple-output (MIMO) wireless communications system, where multiple receive antennas are distributed in the area covered by a cellular cell and connected with the base-station (BS). We first analyze the total received power by the BS through the distributed antennas, when assuming that the mobile's signal is transmitted over lognormal shadowed Rayleigh fading channels. Then, the outage probability of the distributed antenna MIMO systems is investigated, when considering various antenna distribution patterns. Furthermore, space-time coding at the mobile transmitter is considered for enhancing the outage performance of the distributed antenna MIMO system. Our study and simulation results show that the outage performance of a distributed antenna MIMO system can be significantly improved, when either increasing the number of distributed receive antennas or increasing the number of mobile transmit antennas

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