Configurable circuits and their impact on multi-standard RF front-end architectures

This thesis studies configurable circuits and their impact on multi-standard RF front-end architectures. In particular, low-voltage low-power linear LNA and mixer topologies suitable for implementation in multi-standard front-ends are subject of the investigation. With respect to frequency and bandwidth, multi-standard front-ends can be implemented using either tunable or wideband LNA and mixer topologies. Based on the type of the LNA and mixer(s), multi-standard receiver RF front-ends can be divided into three groups. They can be (tunable) narrow-band, wide-band or combined. The advantages and disadvantages of the different multi-standard receiver RF front-ends have been discussed in detail. The partitioning between off-chip selectivity, on-chip selectivity provided by the LNA and mixer, linearity, power consumption and occupied chip area in each multi-standard RF front-end group are thoroughly investigated. A Figure of Merit (FOM) for the multi-standard receiver RF front-end has been introduced. Based on this FOM the most suitable multi-standard RF front-end group in terms of cost-effectiveness can be selected. In order to determine which multi-standard RF front-end group is the most cost-effective for a practical application, a GSM850/E-GSM/DCS/PCS/Bluetooth/WLANa/b/g multi-standard receiver RF front-end is chosen as a demonstrator. These standards are the most frequently used standards in wireless communication, and this combination of standards allows to users almost "anytime-anywhere" voice and data transfer. In order to verify these results, three demonstrators have been defined, designed and implemented, two wideband RF front-end circuits in 90nm CMOS and 65nm CMOS, and one combined multi-standard RF front-end circuit in 65nm CMOS. The proposed multi-standard demonstrators have been compared with the state-of the art narrow-band, wide-band and combined multi-standard RF front-ends. On the proposed multi-standard RF front-ends and the state-of the art multi-standard RF front-ends the proposed FOM have been applied. The comparison shows that the combined multi-standard RF front-end group is the most cost effective multi-standard group for this application

Designing Flexible, Energy Efficient and Secure Wireless Solutions for the Internet of Things

The Internet of Things (IoT) is an emerging concept where ubiquitous physical objects (things) consisting of sensor, transceiver, processing hardware and software are interconnected via the Internet. The information collected by individual IoT nodes is shared among other often heterogeneous devices and over the Internet. This dissertation presents flexible, energy efficient and secure wireless solutions in the IoT application domain. System design and architecture designs are discussed envisioning a near-future world where wireless communication among heterogeneous IoT devices are seamlessly enabled. Firstly, an energy-autonomous wireless communication system for ultra-small, ultra-low power IoT platforms is presented. To achieve orders of magnitude energy efficiency improvement, a comprehensive system-level framework that jointly optimizes various system parameters is developed. A new synchronization protocol and modulation schemes are specified for energy-scarce ultra-small IoT nodes. The dynamic link adaptation is proposed to guarantee the ultra-small node to always operate in the most energy efficiency mode, given an operating scenario. The outcome is a truly energy-optimized wireless communication system to enable various new applications such as implanted smart-dust devices. Secondly, a configurable Software Defined Radio (SDR) baseband processor is designed and shown to be an efficient platform on which to execute several IoT wireless standards. It is a custom SIMD execution model coupled with a scalar unit and several architectural optimizations: streaming registers, variable bitwidth, dedicated ALUs, and an optimized reduction network. Voltage scaling and clock gating are employed to further reduce the power, with a more than a 100% time margin reserved for reliable operation in the near-threshold region. Two upper bound systems are evaluated. A comprehensive power/area estimation indicates that the overhead of realizing SDR flexibility is insignificant. The benefit of baseband SDR is quantified and evaluated. To further augment the benefits of a flexible baseband solution and to address the security issue of IoT connectivity, a light-weight Galois Field (GF) processor is proposed. This processor enables both energy-efficient block coding and symmetric/asymmetric cryptography kernel processing for a wide range of GF sizes (2^m, m = 2, 3, ..., 233) and arbitrary irreducible polynomials. Program directed connections among primitive GF arithmetic units enable dynamically configured parallelism to efficiently perform either four-way SIMD GF operations, including multiplicative inverse, or a long bit-width GF product in a single cycle. This demonstrates the feasibility of a unified architecture to enable error correction coding flexibility and secure wireless communication in the low power IoT domain.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137164/1/yajchen_1.pd

Fully Integrated High-Performance MEMS Lumped Element Filters for Reconfigurable Radios.

In this research, we present RF MEMS filters which address the most challenging performance requirements of modern RF front-end systems, namely multi-band processing capability, low energy consumption, and small size. These filters not only provide a wide tuning range for multiple-band selection, but also offer low loss, high power handling capability, fast tuning speed, and temperature stability. Two different technologies are considered for tunable lumped element filter targeting UHF range. The first technology is a tunable RF MEMS platform based on surface micromachining, enabling fabrication of continuously tuned capacitors, capacitive and ohmic switches, as well as high-Q inductors, all on a single chip. The filter is in a third-order coupled resonator configuration. Continuous electrostatic tuning is achieved using three tunable capacitor banks each consisting of one continuously tunable capacitor and three switched capacitors with pull-in voltage of less than 40V. The center frequency of the filter is tuned from 1GHz to 600MHz while maintaining a 3dB-bandwidth of 13 to 14% and insertion loss of 2%. The filter occupies a small size (1.5 cm x 1.0 cm). This filter shows the best published performance yet in terms of insertion loss, out-of-band rejection, temperature stability, and tuning range. The second technology is based on a new tuning mechanism utilizing phase-change (PC) materials. PC technology has been investigated and adopted in memory industry due to its fast transition time in nano second range, small size, and high resistance change ratio. Although PC materials offer several benefits, they have not been considered for RF applications because of their limited power handling capability and relatively higher on-resistance in their current form. In this work, germanium tellurium (GeTe) is considered as it offers a low on-resistivity and pronounced resistance change ratio of up to 106. To characterize RF properties of GeTe, different types of RF switches have been fabricated and compared. Such PC switches can be monolithically integrated with other micromachined components to implement reconfigurable front-end modules, potentially offering high tuning speed, low loss, high linearity, and small size.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/98038/1/yhshim_1.pd

Compressive Sampling as an Enabling Solution for Energy-Efficient and Rapid Wideband RF Spectrum Sensing in Emerging Cognitive Radio Systems

Wireless systems have become an essential part of every sector of the national and global economy. In addition to existing commercial systems including GPS, mobile cellular, and WiFi communications, emerging systems like video over wireless, the Internet of Things, and machine-to-machine communications are expected to increase mobile wireless data traffic by several orders of magnitude over the coming decades, while natural resources like energy and radio spectrum remain scarce. The projected growth of the number of connected nodes into the trillions in the near term and increasing user demand for instantaneous, over-the-air access to large volumes of content will require a 1000-fold increase in network wireless data capacity by 2020. Spectrum is the lifeblood of these future wireless networks and the ’data storm’ driven by emerging technologies will lead to a pressing ’artificial’ spectrum scarcity. Cognitive radio is a paradigm proposed to overcome the existing challenge of underutilized spectrum. Emerging cognitive radio systems employing multi-tiered, shared-spectrum access are expected to deliver superior spectrum efficiency over existing scheduled-access systems; they have several device categories (3 or more tiers) with different access privileges. We focus on lower tiered ’smart’ devices that evaluate the spectrum dynamically and opportunistically use the underutilized spectrum. These ’smart’ devices require spectrum sensing for incumbent detection and interferer avoidance. Incumbent detection will rely on database lookup or narrowband high-sensitivity sensing. Integrated interferer detectors, on the other hand, need to be fast, wideband, and energy efficient, while requiring only moderate sensitivity. These future 'smart' devices operating in small cell environments will need to rapidly (in 10s of μs) detect a few (e.g. 3 to 6) strong interferers within roughly a 1GHz span and accordingly reconfigure their hardware resources or request adjustments to their wireless connection consisting of primary and secondary links in licensed and unlicensed spectrum. Compressive sampling (CS), an evolutionary sensing/sampling paradigm that changes the perception of sampling, has been extensively used for image reconstruction. It has been shown that a single pixel camera that exploits CS has the ability to obtain an image with a single detection element, while measuring the image fewer times than the number of pixels with the prior assumption of sparsity. We exploited CS in the presented works to take a ’snapshot’ of the spectrum with low energy consumption and high frequency resolutions. Compressive sampling is applied to break the fixed trade-off between scan time, resolution bandwidth, hardware complexity, and energy consumption. This contrasts with traditional spectrum scanning solutions, which have constant energy consumption in all architectures to first order and a fixed trade-off between scan time and resolution bandwidth. Compressive sampling enables energy-efficient, rapid, and wideband spectrum sensing with high frequency resolutions at the expense of degraded instantaneous dynamic range due to the noise folding. We have developed a quadrature analog-to-information converter (QAIC), a novel CS rapid spectrum sensing technique for band-pass signals. Our first wideband, energy-efficient, and rapid interferer detector end-to-end system with a QAIC senses a wideband 1GHz span with a 20MHz resolution bandwidth and successfully detects up to 3 interferers in 4.4μs. The QAIC offers 50x faster scan time compared to traditional sweeping spectrum scanners and 6.3x the compressed aggregate sampling rate of traditional concurrent Nyquist-rate approaches. The QAIC is estimated to be two orders of magnitude more energy efficient than traditional spectrum scanners/sensors and one order of magnitude more energy efficient than existing low-pass CS spectrum sensors. We implemented a CS time-segmented quadrature analog-to-information converter (TS-QAIC) that extends the physical hardware through time segmentation (e.g. 8 physical I/Q branches to 16 I/Q through time segmentation) and employs adaptive thresholding to react to the signal conditions without additional silicon cost and complexity. The TS-QAIC rapidly detects up to 6 interferers in the PCAST spectrum between 2.7 and 3.7GHz with a 10.4μs sensing time for a 20MHz RBW with only 8 physical I/Q branches while consuming 81.2mW from a 1.2V supply. The presented rapid sensing approaches enable system scaling in multiple dimensions such as ADC bits, the number of samples, and the number of branches to meet user performance goals (e.g. the number of detectable interferers, energy consumption, sensitivity and scan time). We envision that compressive sampling opens promising avenues towards energy-efficient and rapid sensing architectures for future cognitive radio systems utilizing multi-tiered, shared spectrum access