Hybrid MIMO Architectures for Millimeter Wave Communications: Phase Shifters or Switches?

Hybrid analog/digital MIMO architectures were recently proposed as an alternative for fully-digitalprecoding in millimeter wave (mmWave) wireless communication systems. This is motivated by the possible reduction in the number of RF chains and analog-to-digital converters. In these architectures, the analog processing network is usually based on variable phase shifters. In this paper, we propose hybrid architectures based on switching networks to reduce the complexity and the power consumption of the structures based on phase shifters. We define a power consumption model and use it to evaluate the energy efficiency of both structures. To estimate the complete MIMO channel, we propose an open loop compressive channel estimation technique which is independent of the hardware used in the analog processing stage. We analyze the performance of the new estimation algorithm for hybrid architectures based on phase shifters and switches. Using the estimated, we develop two algorithms for the design of the hybrid combiner based on switches and analyze the achieved spectral efficiency. Finally, we study the trade-offs between power consumption, hardware complexity, and spectral efficiency for hybrid architectures based on phase shifting networks and switching networks. Numerical results show that architectures based on switches obtain equal or better channel estimation performance to that obtained using phase shifters, while reducing hardware complexity and power consumption. For equal power consumption, all the hybrid architectures provide similar spectral efficiencies.Comment: Submitted to IEEE Acces

Space shuttle electromagnetic environment experiment. Phase A: Definition study

Methods for carrying out measurements of earth electromagnetic environment using the space shuttle as a measurement system platform are herein reported. The goal is to provide means for mapping intentional and nonintentional emitters on earth in the frequency range 0.4 to 40 GHz. A survey was made of known emitters using available data from national and international regulatory agencies, and from industry sources. The spatial distribution of sources, power levels, frequencies, degree of frequency re-use, etc., found in the survey, are here presented. A concept is developed for scanning the earth using a directive antenna whose beam is made to rotate at a fixed angle relative to the nadir; the illuminated area swept by the beam is of the form of cycloidal annulus over a sphere. During the beam's sojourn over a point, the receiver sweeps in frequency over ranges in the order of octave width using sweeping filter bandwidths sufficient to give stable readings

Automated tracking of the Florida manatee (Trichechus manatus)

The electronic, physical, biological and environmental factors involved in the automated remote tracking of the Florida manatee (Trichechus manatus) are identified. The current status of the manatee as an endangered species is provided. Brief descriptions of existing tracking and position locating systems are presented to identify the state of the art in these fields. An analysis of energy media is conducted to identify those with the highest probability of success for this application. Logistic questions such as the means of attachment and position of any equipment to be placed on the manatee are also investigated. Power sources and manateeborne electronics encapsulation techniques are studied and the results of a compter generated DF network analysis are summarized

Circuits and Systems for On-Chip RF Chemical Sensors and RF FDD Duplexers

Integrating RF bio-chemical sensors and RF duplexers helps to reduce cost and area in the current applications. Furthermore, new applications can exist based on the large scale integration of these crucial blocks. This dissertation addresses the integration of RF bio-chemical sensors and RF duplexers by proposing these initiatives. A low power integrated LC-oscillator-based broadband dielectric spectroscopy (BDS) system is presented. The real relative permittivity ε’r is measured as a shift in the oscillator frequency using an on-chip frequency-to-digital converter (FDC). The imaginary relative permittivity ε”r increases the losses of the oscillator tank which mandates a higher dc biasing current to preserve the same oscillation amplitude. An amplitude-locked loop (ALL) is used to fix the amplitude and linearize the relation between the oscillator bias current and ε”r. The proposed BDS system employs a sensing oscillator and a reference oscillator where correlated double sampling (CDS) is used to mitigate the impact of flicker noise, temperature variations and frequency drifts. A prototype is implemented in 0.18 µm CMOS process with total chip area of 6.24 mm^2 to operate in 1-6 GHz range using three dual bands LC oscillators. The achieved standard deviation in the air is 2.1 ppm for frequency reading and 110 ppm for current reading. A tunable integrated electrical balanced duplexer (EBD) is presented as a compact alternative to multiple bulky SAW and BAW duplexers in 3G/4G cellular transceivers. A balancing network creates a replica of the transmitter signal for cancellation at the input of a single-ended low noise amplifier (LNA) to isolate the receive path from the transmitter. The proposed passive EBD is based on a cross-connected transformer topology without the need of any extra balun at the antenna side. The duplexer achieves around 50 dB TX-RX isolation within 1.6-2.2 GHz range up to 22 dBm. The cascaded noise figure of the duplexer and LNA is 6.5 dB, and TX insertion loss (TXIL) of the duplexer is about 3.2 dB. The duplexer and LNA are implemented in 0.18 µm CMOS process and occupy an active area of 0.35 mm^2

Array Architectures and Physical Layer Design for Millimeter-Wave Communications Beyond 5G

Ever increasing demands in mobile data rates have resulted in exploration of millimeter-wave (mmW) frequencies for the next generation (5G) wireless networks. Communications at mmW frequencies is presented with two keys challenges. Firstly, high propagation loss requires base stations (BSs) and user equipment (UEs) to use a large number of antennas and narrow beams to close the link with sufficient received signal power. Consequently, communications using narrow beams create a new challenge in channel estimation and link establishment based on fine angular probing. Current mmW system use analog phased arrays that can probe only one angle at the time which results in high latency during link establishment and channel tracking. It is desirable to design low latency beam training by exploring both physical layer designs and array architectures that could replace current 5G approaches and pave the way to the communications for frequency bands in higher mmW band and sub-THz region where larger antenna arrays and communications bandwidth can be exploited. To this end, we propose a novel signal processing techniques exploiting unique properties of mmW channel, and show both theoretically, in simulation and experiments its advantages over conventional approaches. Secondly, we explore different array architecture design and analyze their trade-offs between spectral efficiency and power consumption and area. For comprehensive comparison, we have developed a methodology for optimal design of system parameters for different array architecture candidates based on the spectral efficiency target, and use these parameters to estimate the array area and power consumption based on the circuits reported in the literature. We show that the hybrid analog and digital architectures have severe scalability concerns in radio frequency signal distribution with increased array size and spatial multiplexing levels, while the fully-digital array architectures have the best performance and power/area trade-offs.The developed approaches are based on a cross-disciplinary research that combines innovation in model based signal processing, machine learning, and radio hardware. This work is the first to apply compressive sensing (CS), a signal processing tool that exploits sparsity of mmW channel model, to accelerate beam training of mmW cellular system. The algorithm is designed to address practical issues including the requirement of cell discovery and synchronization that involves estimation of angular channel together with carrier frequency offset and timing offsets. We have analyzed the algorithm performance in the 5G compliant simulation and showed that an order of magnitude saving is achieved in initial access latency for the desired channel estimation accuracy. Moreover, we are the first to develop and implement a neural network assisted compressive beam alignment to deal with hardware impairments in mmW radios. We have used 60GHz mmW testbed to perform experiments and show that neural networks approach enhances alignment rate compared to CS. To further accelerate beam training, we proposed a novel frequency selective probing beams using the true-time-delay (TTD) analog array architecture. Our approach utilizes different subcarriers to scan different directions, and achieves a single-shot beam alignment, the fastest approach reported to date. Our comprehensive analysis of different array architectures and exploration of emerging architectures enabled us to develop an order of magnitude faster and energy efficient approaches for initial access and channel estimation in mmW systems