MIMO Transmission with Residual Transmit-RF Impairments

Physical transceiver implementations for multiple-input multiple-output (MIMO) wireless communication systems suffer from transmit-RF (Tx-RF) impairments. In this paper, we study the effect on channel capacity and error-rate performance of residual Tx-RF impairments that defy proper compensation. In particular, we demonstrate that such residual distortions severely degrade the performance of (near-)optimum MIMO detection algorithms. To mitigate this performance loss, we propose an efficient algorithm, which is based on an i.i.d. Gaussian model for the distortion caused by these impairments. In order to validate this model, we provide measurement results based on a 4-stream Tx-RF chain implementation for MIMO orthogonal frequency-division multiplexing (OFDM).Comment: to be presented at the International ITG Workshop on Smart Antennas - WSA 201

Concepts for Short Range Millimeter-wave Miniaturized Radar Systems with Built-in Self-Test

This work explores short-range millimeter wave radar systems, with emphasis on miniaturization and overall system cost reduction. The designing and implementation processes, starting from the system level design considerations and characterization of the individual components to final implementation of the proposed architecture are described briefly. Several D-band radar systems are developed and their functionality and performances are demonstrated

Low-Overhead Built-In Self-Test for Advanced RF Transceiver Architectures

abstract: Due to high level of integration in RF System on Chip (SOC), the test access points are limited to the baseband and RF inputs/outputs of the system. This limited access poses a big challenge particularly for advanced RF architectures where calibration of internal parameters is necessary and ensure proper operation. Therefore low-overhead built-in Self-Test (BIST) solution for advanced RF transceiver is proposed. In this dissertation. Firstly, comprehensive BIST solution for RF polar transceivers using on-chip resources is presented. In the receiver, phase and gain mismatches degrade sensitivity and error vector magnitude (EVM). In the transmitter, delay skew between the envelope and phase signals and the finite envelope bandwidth can create intermodulation distortion (IMD) that leads to violation of spectral mask requirements. Characterization and calibration of these parameters with analytical model would reduce the test time and cost considerably. Hence, a technique to measure and calibrate impairments of the polar transceiver in the loop-back mode is proposed. Secondly, robust amplitude measurement technique for RF BIST application and BIST circuits for loop-back connection are discussed. Test techniques using analytical model are explained and BIST circuits are introduced. Next, a self-compensating built-in self-test solution for RF Phased Array Mismatch is proposed. In the proposed method, a sinusoidal test signal with unknown amplitude is applied to the inputs of two adjacent phased array elements and measure the baseband output signal after down-conversion. Mathematical modeling of the circuit impairments and phased array behavior indicates that by using two distinct input amplitudes, both of which can remain unknown, it is possible to measure the important parameters of the phased array, such as gain and phase mismatch. In addition, proposed BIST system is designed and fabricated using IBM 180nm process and a prototype four-element phased-array PCB is also designed and fabricated for verifying the proposed method. Finally, process independent gain measurement via BIST/DUT co-design is explained. Design methodology how to reduce performance impact significantly is discussed. Simulation and hardware measurements results for the proposed techniques show that the proposed technique can characterize the targeted impairments accurately.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

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

Design of 28 GHz 4x4 RF Beamforming Array for 5G Radio Front-Ends

Current state of wireless infrastructure sees mass migration to higher frequencies as much of the already used spectrum is insufficient in supporting the influx of numerous users and various data intensive mobile applications. Data rates are projected to increase by an order of magnitude and harnessing the necessary bandwidth below 6 GHz is not feasible. A move to higher frequencies sees not only increased fractional bandwidth, but also significantly enhanced antenna apertures as a result of beamforming capabilities. Due to device level complications with frequencies nearing the unit gain frequency of transistor technology, high output power is seldom found, and in conjunction with severe path loss, communication links cannot be established without the usage of antenna arrays. Phased array systems offer significant upside to the traditional array implementation as it permits reconfigurable directive communication. However, Ka-Band phased arrays still struggle to arrive at a reasonable tradeoff between design complexity, cost and performance. With a divide between both organic and printed circuit board (PCB) based approaches to the development of an antenna-in-package (AiP), this thesis sides with the latter. An antenna-on-PCB variant of the AiP is developed, which implements both commercially available RF laminates and RFIC front end modules to produce a 28 GHz 4x4 RF beamforming phased array that is found to exhibit extremely low loss (-0.66 dB), adequate scan volume (+/- 45 degrees, in E and H planes) and large bandwidth (3 GHz) for a single layer, non-isolated patch antenna design. Unit cell, infinite array analysis is emphasized and lattice resizing is leveraged to obtain desired scan performance, while significantly reducing design complexity via the absence of intricate isolation enhancement techniques. In an effort to aid in application based design, the AiP is extended to application of linearization where it is found that the inclusion of dummy elements along the perimeter of the package not only serve as element pattern enhancement, but also provide reliable means of output signal capture. Negating the traditional transmitter observation receiver (TOR) architecture, the AiP design as a TOR for millimeter-wave communication proves optimistic in the quest for maximum system efficiency