Beamforming management and beam training in 5G system

Massive multiple-input-multiple-output (MIMO) antenna system with beamforming technique is an integral part of upcoming 5G new radio (NR) system. For the upcoming deployment of 5G NR system in both stand-alone (SA) and non-stand-alone (NSA) structure, beamforming plays an important role to achieve its key features and meet the estimated requirement. To be employed with massive MIMO antenna structure, beamforming will allow 5G system to serve several users at a time with better throughput and spectral usage. Beamforming will also minimize the path loss due to high susceptibility of millimetre wave and provide beamforming gain. For a wide range of benefit scheme, beamforming is currently a hot topic regarding the deployment of 5G. With the advantage of both analog and digital beamforming, hybrid beamforming structure can provide better system benchmark performance in terms of cost and flexibility. Switched beam training and adaptive beam training approaches and algorithms are developed in order to reduce training time, signalling overhead and misdetection probability. Some of the approaches and algorithm are addressed in this thesis. Beamforming management ensures the initiation and sustainability of the established link between transmitter and receiver through different processes. Beam tracking helps to keep track of the receiver devices during mobility. As beamforming is related to antenna configuration, near-field spherical wave front incident problem was ignored, and all the references and examples presented in this topic was obtained with a far-field propagation perspective. To avoid mutual coupling between antenna elements and grating lobe problems in antenna radiation pattern, each element is separated by half of the wavelength. This thesis paper aims to provide a broader view into beamforming scenario, starting from the basics of beamforming to training the beams and management aspects in the hardware part of 5G structure. Another goal is to present the necessity of beamforming in a 5G system by stating different benefits scheme such as spatial diversity, interference suppression, energy efficiency, spectral efficiency and so on. These benefits are justified by evaluating various research paper and MATLAB simulations

Localization, Mapping and SLAM in Marine and Underwater Environments

The use of robots in marine and underwater applications is growing rapidly. These applications share the common requirement of modeling the environment and estimating the robots’ pose. Although there are several mapping, SLAM, target detection and localization methods, marine and underwater environments have several challenging characteristics, such as poor visibility, water currents, communication issues, sonar inaccuracies or unstructured environments, that have to be considered. The purpose of this Special Issue is to present the current research trends in the topics of underwater localization, mapping, SLAM, and target detection and localization. To this end, we have collected seven articles from leading researchers in the field, and present the different approaches and methods currently being investigated to improve the performance of underwater robots

MIMO-aided near-capacity turbo transceivers: taxonomy and performance versus complexity

In this treatise, we firstly review the associated Multiple-Input Multiple-Output (MIMO) system theory and review the family of hard-decision and soft-decision based detection algorithms in the context of Spatial Division Multiplexing (SDM) systems. Our discussions culminate in the introduction of a range of powerful novel MIMO detectors, such as for example Markov Chain assisted Minimum Bit-Error Rate (MC-MBER) detectors, which are capable of reliably operating in the challenging high-importance rank-deficient scenarios, where there are more transmitters than receivers and hence the resultant channel-matrix becomes non-invertible. As a result, conventional detectors would exhibit a high residual error floor. We then invoke the Soft-Input Soft-Output (SISO) MIMO detectors for creating turbo-detected two- or three-stage concatenated SDM schemes and investigate their attainable performance in the light of their computational complexity. Finally, we introduce the powerful design tools of EXtrinsic Information Transfer (EXIT)-charts and characterize the achievable performance of the diverse near- capacity SISO detectors with the aid of EXIT charts

Array Pattern Synthesis Using a Digital Position Shift Method

Considering all possible steering directions for beam scanning, a digital position shift method (DPSM) is presented to minimize the Peak Sidelobe Level (PSL) by searching the best position solution for every sensor and calculating the pattern with position offset factor. For the truly minimum PSL, digital position shift with optimal amplitude (DPSOA) is considered simultaneously for beam scanning. For searching the best solution to the two methods, constrained conditions for position shift range and amplitude range are described. The method of feedback particle swarm optimization (FPSO) is presented to obtain a large searching space and fast convergence in local space with refined solution. Numerical examples show that the optimized results by DPSM and DPSOA in all steering directions can be used in beam scanning for its digital realization. When compared with the other techniques published in the literature, especially the steering direction close to endfire direction, this method has lower PSL when the main beam width is maintained

Reconfigurable Antenna Systems: Platform implementation and low-power matters

Antennas are a necessary and often critical component of all wireless systems, of which they share the ever-increasing complexity and the challenges of present and emerging trends. 5G, massive low-orbit satellite architectures (e.g. OneWeb), industry 4.0, Internet of Things (IoT), satcom on-the-move, Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles, all call for highly flexible systems, and antenna reconfigurability is an enabling part of these advances. The terminal segment is particularly crucial in this sense, encompassing both very compact antennas or low-profile antennas, all with various adaptability/reconfigurability requirements. This thesis work has dealt with hardware implementation issues of Radio Frequency (RF) antenna reconfigurability, and in particular with low-power General Purpose Platforms (GPP); the work has encompassed Software Defined Radio (SDR) implementation, as well as embedded low-power platforms (in particular on STM32 Nucleo family of micro-controller). The hardware-software platform work has been complemented with design and fabrication of reconfigurable antennas in standard technology, and the resulting systems tested. The selected antenna technology was antenna array with continuously steerable beam, controlled by voltage-driven phase shifting circuits. Applications included notably Wireless Sensor Network (WSN) deployed in the Italian scientific mission in Antarctica, in a traffic-monitoring case study (EU H2020 project), and into an innovative Global Navigation Satellite Systems (GNSS) antenna concept (patent application submitted). The SDR implementation focused on a low-cost and low-power Software-defined radio open-source platform with IEEE 802.11 a/g/p wireless communication capability. In a second embodiment, the flexibility of the SDR paradigm has been traded off to avoid the power consumption associated to the relevant operating system. Application field of reconfigurable antenna is, however, not limited to a better management of the energy consumption. The analysis has also been extended to satellites positioning application. A novel beamforming method has presented demonstrating improvements in the quality of signals received from satellites. Regarding those who deal with positioning algorithms, this advancement help improving precision on the estimated position

Signal Subspace Processing in the Beam Space of a True Time Delay Beamformer Bank

A number of techniques for Radio Frequency (RF) source location for wide bandwidth signals have been described that utilize coherent signal subspace processing, but often suffer from limitations such as the requirement for preliminary source location estimation, the need to apply the technique iteratively, computational expense or others. This dissertation examines a method that performs subspace processing of the data from a bank of true time delay beamformers. The spatial diversity of the beamformer bank alleviates the need for a preliminary estimate while simultaneously reducing the dimensionality of subsequent signal subspace processing resulting in computational efficiency. The pointing direction of the true time delay beams is independent of frequency, which results in a mapping from element space to beam space that is wide bandwidth in nature. This dissertation reviews previous methods, introduces the present method, presents simulation results that demonstrate the assertions, discusses an analysis of performance in relation to the Cramer-Rao Lower Bound (CRLB) with various levels of noise in the system, and discusses computational efficiency. One limitation of the method is that in practice it may be appropriate for systems that can tolerate a limited field of view. The application of Electronic Intelligence is one such application. This application is discussed as one that is appropriate for a method exhibiting high resolution of very wide bandwidth closely spaced sources and often does not require a wide field of view. In relation to system applications, this dissertation also discusses practical employment of the novel method in terms of antenna elements, arrays, platforms, engagement geometries, and other parameters. The true time delay beam space method is shown through modeling and simulation to be capable of resolving closely spaced very wideband sources over a relevant field of view in a single algorithmic pass, requiring no course preliminary estimation, and exhibiting low computational expense superior to many previous wideband coherent integration techniques

Signal Subspace Processing in the Beam Space of a True Time Delay Beamformer Bank

A number of techniques for Radio Frequency (RF) source location for wide bandwidth signals have been described that utilize coherent signal subspace processing, but often suffer from limitations such as the requirement for preliminary source location estimation, the need to apply the technique iteratively, computational expense or others. This dissertation examines a method that performs subspace processing of the data from a bank of true time delay beamformers. The spatial diversity of the beamformer bank alleviates the need for a preliminary estimate while simultaneously reducing the dimensionality of subsequent signal subspace processing resulting in computational efficiency. The pointing direction of the true time delay beams is independent of frequency, which results in a mapping from element space to beam space that is wide bandwidth in nature. This dissertation reviews previous methods, introduces the present method, presents simulation results that demonstrate the assertions, discusses an analysis of performance in relation to the Cramer-Rao Lower Bound (CRLB) with various levels of noise in the system, and discusses computational efficiency. One limitation of the method is that in practice it may be appropriate for systems that can tolerate a limited field of view. The application of Electronic Intelligence is one such application. This application is discussed as one that is appropriate for a method exhibiting high resolution of very wide bandwidth closely spaced sources and often does not require a wide field of view. In relation to system applications, this dissertation also discusses practical employment of the novel method in terms of antenna elements, arrays, platforms, engagement geometries, and other parameters. The true time delay beam space method is shown through modeling and simulation to be capable of resolving closely spaced very wideband sources over a relevant field of view in a single algorithmic pass, requiring no course preliminary estimation, and exhibiting low computational expense superior to many previous wideband coherent integration techniques