Symmetric complex-valued RBF receiver for multiple-antenna aided wireless systems

A nonlinear beamforming assisted detector is proposed for multiple-antenna-aided wireless systems employing complex-valued quadrature phase shift-keying modulation. By exploiting the inherent symmetry of the optimal Bayesian detection solution, a novel complex-valued symmetric radial basis function (SRBF)-network-based detector is developed, which is capable of approaching the optimal Bayesian performance using channel-impaired training data. In the uplink case, adaptive nonlinear beamforming can be efficiently implemented by estimating the system’s channel matrix based on the least squares channel estimate. Adaptive implementation of nonlinear beamforming in the downlink case by contrast is much more challenging, and we adopt a cluster-variationenhanced clustering algorithm to directly identify the SRBF center vectors required for realizing the optimal Bayesian detector. A simulation example is included to demonstrate the achievable performance improvement by the proposed adaptive nonlinear beamforming solution over the theoretical linear minimum bit error rate beamforming benchmark

Symmetric RBF classifier for nonlinear detection in multiple-antenna aided systems

In this paper, we propose a powerful symmetric radial basis function (RBF) classifier for nonlinear detection in the so-called “overloaded” multiple-antenna-aided communication systems. By exploiting the inherent symmetry property of the optimal Bayesian detector, the proposed symmetric RBF classifier is capable of approaching the optimal classification performance using noisy training data. The classifier construction process is robust to the choice of the RBF width and is computationally efficient. The proposed solution is capable of providing a signal-to-noise ratio (SNR) gain in excess of 8 dB against the powerful linear minimum bit error rate (BER) benchmark, when supporting four users with the aid of two receive antennas or seven users with four receive antenna elements. Index Terms—Classification, multiple-antenna system, orthogonal forward selection, radial basis function (RBF), symmetry

Signal Processing for Wireless Power and Information Transfer

The rapid development of the Internet of Things (IoT) and wireless sensor network (WSN) technologies enable easy access and control of a variety forms of information and data from numerous number of smart devices, and give rise to many novel applications and research areas such as smart home, machine type communications, etc. However due to the small sizes, sophisticated environment, and large number of devices in network, it is hard to directly power the devices from grid. Hence the power connectivity remains one of the major issues that needs to be addressed for related IoT applications. Wireless power transfer (WPT) and backscatter communications are provisioned to be prominent solutions to overcome the power connectivity challenge, but they suer strong efficiency limitation which becomes the barrier to universally popularize such technologies. On the other hand, network optimization is also a research focus of such applications which significantly affects the performance of the system due to the high volume of connected devices and different features. In this thesis we propose advanced techniques to overcome the challenges on the low efficiency and network design of the wireless information and power transfer systems. The thesis consists of two parts. In the first part we focus on the power transmitter design which addresses the low efficiency issue associated with backscatter communication and WPT. In Chapter 2, we consider a backscatter RFID system with the multi-antenna reader and propose a blind transmit and receive adaptive beamforming algorithm. The interrogation range and data transmission performance are both investigated under such configuration. In Chapter 3 we study wireless power transfer by the beamspace large-scale MIMO system with lens antenna arrays. We first present the WPT model for the beamspace MIMO which is derived from the spatial MIMO model. By constraining on the number of RF chains in the transmitter, we formulate two WPT optimization problems: the sum power transfer problem and the max-min power transfer problem. For both problems we consider two different transmission schemes, the multi-stream and uni-stream transmissions, and we propose different algorithms to solve both problems in both schemes respectively. In the second part we study the network optimization problems in the WPT and backscatter systems. In Chapter 4, we study the resource allocation problem for a RF-powered network, where the objective is to maximize the total data throughput of all sensors. We break the problem into two subproblems: the sensor battery energy utilization problem and the charging power allocation problem of the central node, which is an RF power transmitter that transmits RF power to the sensors. We analyze and show several key properties of both problems, and then propose computationally efficient algorithms to solve both problems optimally. In Chapter 5, we study the time scheduling problem in RF-powered backscatter communication networks, where all transmitters can operates in either backscattering mode or harvest-then-transmit (HTT) mode. The objective is to decide the operating mode of each transmitter and minimize the total transmission time of the network. We also consider both ideal and realistic transmitters based on different internal power consumption models for HTT transmitters. Under both transmitter models we show several key properties, and propose bisection based algorithms which has low computational complexity that solves the problem optimally. The results are then extended to the massive MIMO regime

Multi-layer Utilization of Beamforming in Millimeter Wave MIMO Systems

mmWave frequencies ranging between (30-300GHz) have been considered the perfect solution to the scarcity of bandwidth in the traditional sub-6GHz band and to the ever increasing demand of many emerging applications in today\u27s era. 5G and beyond standards are all considering the mmWave as an essential part of there networks. Beamforming is one of the most important enabling technologies for the mmWave to compensate for the huge propagation lose of these frequencies compared to the sub-6GHz frequencies and to ensure better spatial and spectral utilization of the mmWave channel space. In this work, we tried to develop different techniques to improve the performance of the systems that use mmWave. In the physical layer, we suggested several hybrid beamforming architectures that both are relatively simple and spectrally efficient by achieving fully digital like spectral efficiency (bits/sec/Hz). For the mobility management, we derived the expected degradation that can affect the performance of a special type of beamforming that is called the Random Beamforming (RBF) and optimized the tunable parameters for such systems when working in different environments. Finally, in the networking layer, we first studied the effect of using mmWave frequencies on the routing performance comparing to the performance achieved when using sub-6 GHz frequencies. Then we developed a novel opportunistic routing protocol for Mobile Ad-Hoc Networks (MANET) that uses a modified version of the Random Beamforming (RBF) to achieve better end to end performance and to reduce the overall delay in delivering data from transmitting nodes to the intended receiving nodes. From all these designs and studies, we conclude that mmWave frequencies and their enabling technologies (i.e. Beamforming, massive MIMO, ...etc.) are indeed the future of wireless communicatons in a high demanding world of Internet of Things (IoT), Augmented Reality (AR), Virtual Reality (VR), and self driving cars

Підвищення пропускної спроможності мережі за допомогою MIMO-формування діаграми спрямованості

The performance of transmission Multi Input Multi Output (MIMO) beamforming for the multi subscriber in large cell with effective channel throughput has been investigated. The work procedure was based on singular value decomposition (SVD) using Single User (SU) in 3GPP Long Term Evolution (LTE). In LTE Single User – Multiple Input Multiple Output (SU-MIMO) operation mode, the data of a single user is transmitted simultaneously on several parallel data streams, using the available transmission resources, both in time and frequency dimensions. The simulation comparisons with beamforming and without beamforming have been studied for transmission in MIMO modulations. Despite the protection of information in LTE networks have their vulnerabilities. Planned for a more comprehensive analysis of statistical data and based on them to accurately determine the feasibility of using various protective mechanisms 4G networks for different user groups.Была исследована пропускная способность системы с множеством входов и множеством выходов (MIMO) при формировании диаграммы направленности в крупной сети с эффективной пропускной способностью канала. Работа была основана на сингулярном разложения (SVD), используя Single User (SU) в 3GPP Long Term Evolution (LTE). В LTE Single User - Multiple Input Multiple Output (SU-MIMO) - режим работы, при котором данные от одного пользователя передаются одновременно несколькими параллельными потоками данных, используя доступные ресурсы сети как по времени так и по частоте. Для сравнения пропускной способности проведено моделирования с формированием диаграммы направленности и без нее для двух типов модуляции передачи потока. Несмотря на имеющиеся средства защиты информации в сетях LTE они имеют свои уязвимости. Планируется провести более детальный анализ статистических данных и на их основе точно определить целесообразность использования различных защитных механизмов сетей 4G для различных групп пользователей.Була досліджена пропускна спроможність системи з великою кількістю входів та виходів ( MIMO ) при формування діаграми спрямованості у великій мережі з ефективною пропускною здатністю каналу. Робота була заснована на сингулярному розкладанні ( SVD ), використовуючи Single User ( SU) в 3GPP Long Term Evolution (LTE ). У LTE Single User - Multiple Input Multiple Output (SU- MIMO) - режим роботи, при якому дані від одного користувача передаються одночасно кількома паралельними потоками даних, використовуючи доступні ресурси мережі як за часом так і за частотою. Для порівняння пропускної здатності проведено моделювання з формуванням діаграми спрямованості і без нього для двох типів модуляції передачі потоку. Незважаючи на наявні засоби захисту інформації в мережах LTE вони мають свої уразливості. Планується провести більш детальний аналіз статистичних даних і на їх основі точно визначити доцільність використання різних захисних механізмів мереж 4G для різних груп користувачів

Maximum-rate Transmission with Improved Diversity Gain for Interference Networks

Interference alignment (IA) was shown effective for interference management to improve transmission rate in terms of the degree of freedom (DoF) gain. On the other hand, orthogonal space-time block codes (STBCs) were widely used in point-to-point multi-antenna channels to enhance transmission reliability in terms of the diversity gain. In this paper, we connect these two ideas, i.e., IA and space-time block coding, to improve the designs of alignment precoders for multi-user networks. Specifically, we consider the use of Alamouti codes for IA because of its rate-one transmission and achievability of full diversity in point-to-point systems. The Alamouti codes protect the desired link by introducing orthogonality between the two symbols in one Alamouti codeword, and create alignment at the interfering receiver. We show that the proposed alignment methods can maintain the maximum DoF gain and improve the ergodic mutual information in the long-term regime, while increasing the diversity gain to 2 in the short-term regime. The presented examples of interference networks have two antennas at each node and include the two-user X channel, the interferring multi-access channel (IMAC), and the interferring broadcast channel (IBC).Comment: submitted to IEEE Transactions on Information Theor