A fully integrated SRAM-based CMOS arbitrary waveform generator for analog signal processing

This dissertation focuses on design and implementation of a fully-integrated SRAM-based arbitrary waveform generator for analog signal processing applications in a CMOS technology. The dissertation consists of two parts: Firstly, a fully-integrated arbitrary waveform generator for a multi-resolution spectrum sensing of a cognitive radio applications, and an analog matched-filter for a radar application and secondly, low-power techniques for an arbitrary waveform generator. The fully-integrated low-power AWG is implemented and measured in a 0.18-¥ìm CMOS technology. Theoretical analysis is performed, and the perspective implementation issues are mentioned comparing the measurement results. Moreover, the low-power techniques of SRAM are addressed for the analog signal processing: Self-deactivated data-transition bit scheme, diode-connected low-swing signaling scheme with a short-current reduction buffer, and charge-recycling with a push-pull level converter for power reduction of asynchronous design. Especially, the robust latch-type sense amplifier using an adaptive-latch resistance and fully-gated ground 10T-SRAM bitcell in a 45-nm SOI technology would be used as a technique to overcome the challenges in the upcoming deep-submicron technologies.Ph.D.Committee Chair: Kim, Jongman; Committee Member: Kang, Sung Ha; Committee Member: Lee, Chang-Ho; Committee Member: Mukhopadhyay, Saibal; Committee Member: Tentzeris, Emmanouil

Design of Cognitive Radios

Cognitive radios are expected to perform spectrum sensing and communication in the frequency range of tens of megahertz to about 10 GHz. As such, they pose tough architecture and circuit design problems. This paper deals with issues such as broadband, low-noise amplification, multidecade carrier frequency synthesis, and spectrum sensing. The paper also describes the effect of nonlinearity and local oscillator harmonics, demonstrating that cognitive radios entail more difficult challenges than do software-defined radios. Multi-decade synthesis techniques and RF-assisted sensing methods are also presented

WN: COGNET: Cognitive radio networks based on OFDM

Issued as final reportNational Science Foundation (U.S.

A CMOS spectrum analyzer frontend for cognitive radio achieving +25dBm IIP3 and −169 dBm/Hz DANL

A dual RF-receiver preceded by discrete-step attenuators is implemented in 65nm CMOS and operates from 0.3– 1.0 GHz. The noise of the receivers is reduced by cross-correlating the two receiver outputs in the digital baseband, allowing attenuation of the RF input signal to increase linearity. With this technique a displayed average noise level below -169 dBm/Hz is obtained with +25 dBm IIP3, giving a spurious-free dynamic range of 89 dB in 1 MHz resolution bandwidth

Analysis Framework for Opportunistic Spectrum OFDMA and its Application to the IEEE 802.22 Standard

We present an analytical model that enables throughput evaluation of Opportunistic Spectrum Orthogonal Frequency Division Multiple Access (OS-OFDMA) networks. The core feature of the model, based on a discrete time Markov chain, is the consideration of different channel and subchannel allocation strategies under different Primary and Secondary user types, traffic and priority levels. The analytical model also assesses the impact of different spectrum sensing strategies on the throughput of OS-OFDMA network. The analysis applies to the IEEE 802.22 standard, to evaluate the impact of two-stage spectrum sensing strategy and varying temporal activity of wireless microphones on the IEEE 802.22 throughput. Our study suggests that OS-OFDMA with subchannel notching and channel bonding could provide almost ten times higher throughput compared with the design without those options, when the activity and density of wireless microphones is very high. Furthermore, we confirm that OS-OFDMA implementation without subchannel notching, used in the IEEE 802.22, is able to support real-time and non-real-time quality of service classes, provided that wireless microphones temporal activity is moderate (with approximately one wireless microphone per 3,000 inhabitants with light urban population density and short duty cycles). Finally, two-stage spectrum sensing option improves OS-OFDMA throughput, provided that the length of spectrum sensing at every stage is optimized using our model

Spectrum measurement, sensing, analysis and simulation in the context of cognitive radio

The radio frequency (RF) spectrum is a scarce natural resource, currently regulated locally by national agencies. Spectrum has been assigned to different services and it is very difficult for emerging wireless technologies to gain access due to rigid spectmm policy and heavy opportunity cost. Current spectrum management by licensing causes artificial spectrum scarcity. Spectrum monitoring shows that many frequencies and times are unused. Dynamic spectrum access (DSA) is a potential solution to low spectrum efficiency. In DSA, an unlicensed user opportunistically uses vacant licensed spectrum with the help of cognitive radio. Cognitive radio is a key enabling technology for DSA. In a cognitive radio system, an unlicensed Secondary User (SU) identifies vacant licensed spectrum allocated to a Primary User (PU) and uses it without harmful interference to the PU. Cognitive radio increases spectrum usage efficiency while protecting legacy-licensed systems. The purpose of this thesis is to bring together a group of CR concepts and explore how we can make the transition from conventional radio to cognitive radio. Specific goals of the thesis are firstly the measurement of the radio spectrum to understand the current spectrum usage in the Humber region, UK in the context of cognitive radio. Secondly, to characterise the performance of cyclostationary feature detectors through theoretical analysis, hardware implementation, and real-time performance measurements. Thirdly, to mitigate the effect of degradation due to multipath fading and shadowing, the use of -wideband cooperative sensing techniques using adaptive sensing technique and multi-bit soft decision is proposed, which it is believed will introduce more spectral opportunities over wider frequency ranges and achieve higher opportunistic aggregate throughput.Understanding spectrum usage is the first step toward the future deployment of cognitive radio systems. Several spectrum usage measurement campaigns have been performed, mainly in the USA and Europe. These studies show locality and time dependence. In the first part of this thesis a spectrum usage measurement campaign in the Humber region, is reported. Spectrum usage patterns are identified and noise is characterised. A significant amount of spectrum was shown to be underutilized and available for the secondary use. The second part addresses the question: how can you tell if a spectrum channel is being used? Two spectrum sensing techniques are evaluated: Energy Detection and Cyclostationary Feature Detection. The performance of these techniques is compared using the measurements performed in the second part of the thesis. Cyclostationary feature detection is shown to be more robust to noise. The final part of the thesis considers the identification of vacant channels by combining spectrum measurements from multiple locations, known as cooperative sensing. Wideband cooperative sensing is proposed using multi resolution spectrum sensing (MRSS) with a multi-bit decision technique. Next, a two-stage adaptive system with cooperative wideband sensing is proposed based on the combination of energy detection and cyclostationary feature detection. Simulations using the system above indicate that the two-stage adaptive sensing cooperative wideband outperforms single site detection in terms of detection success and mean detection time in the context of wideband cooperative sensing

Novel Method for Broadband On-Chip Noise Characterization

A novel method for on-chip noise characterization of mm-wave circuits is presented. Different available methods for noise measurements and requirements for on-chip noise mea-surements are studied. The Y-factor method is chosen to be the more suitable method for in-situ applications since it does not require absolute measurements. A state of the art CMOS noise source is implemented in 32nm SOI CMOS technology to enable the in-situ noise measurements of a 20-35 GHz reconfigurable low noise amplifier. Measurement results show that the ENR of the noise source is repeatable enough so that the calibration of the noise source is only required for one integrated circuit. Using different scenarios for the noise figure response of the LNA, the performance of the noise source is evaluated. To the authors’ knowledge, this is the first time that an on-chip CMOS noise source is used for in-situ noise characterization of mm-wave frequency circuits

On The Dynamic Spectrum Access For Next Generation Wireless Communication Systems

Ph.DDOCTOR OF PHILOSOPH

A Flexible RFIC Architecture for High-Sensitivity Reception and Compressed-Sampling Wideband Detection

Compressed sensing (CS) is a new signal processing approach that has disrupted the Shannon-Nyquist limit based design methodology and has opened promising avenues for building energy-efficient radio frequency integrated circuits (RFICs) for detecting and estimating particular classes (i.e. sparse) of signals. Whether in application domains where naturally occurring signals are sparse or where representations of signals subject to the fidelity limits or configuration settings of the radio equipment are often found to be sparse, the emergence of CS has forced us to re-imagine the radio receiver. While realizing some of the potential benefits promised by theory, CS-RFIC architectures proposed in earlier research were not particularly suitable for mass-market applications. This thesis demonstrates how to take a new signal processing technique all the way to the hardware level. So far, the main focus in literature has been how CS offers a significant advantage for signal processing. This work will show how CS techniques drive novel architectures down to the integrated circuit level. This requires close collaboration between communication system developers, integrated circuit designers and signal processing experts. The trans-disciplinary approach presented here has led to the unification of CS-inspired architectures for wideband signal detection with robust, legacy architectures for high-sensitivity signal reception. The result is a functionally flexible and rapidly reconfigurable CMOS RFIC compactly implemented on silicon with the potential to achieve the cost, size and power targets in mass-market applications. While the focus of this thesis is RF signal finding and reception in frequency, the CS-based RFIC design approach presented here is applicable to a wide range of other applications like direction-of-arrival and range finding. We begin by developing a signal-model driven approach for optimizing the performance of CS RF frontends (RFFEs). We consider sparse multiband signals with supports contained within a frequency span extending from fMIN to fMAX. The resulting quadrature analog-to-information converter (QAIC) is a flexible-bandwidth, blind sub-Nyquist sampling architecture optimized for energy consumption and sensitivity performance. The QAIC addresses key drawbacks of earlier CS RFFE architectures like the modulated wideband converter (MWC) that implement frequency spans extending from 0 to fMAX. While these earlier architectures, a direct implementation of CS signal processing theory, have several beneficial properties, the true cost of their proposed analog frontend significantly diminishes the sensitivity performance and energy savings that CS methods have the potential to deliver. They use periodic pseudo-random bit sequence (PRBS) generators where the clock frequency fPRBS scales up with the maximum signal frequency fMAX. In contrast, fPRBS in the QAIC RFFE scales up with the instantaneous bandwidth IBW, where IBW = ( fMAX − fMIN ). This results in significant performance advantages in terms of energy consumption and sensitivity performance. The QAIC uncouples fPRBS from fMAX by performing wideband quadrature downconversion ahead of analog mixing with PRBSs at an intermediate frequency (IF). However, the dual heterodyne architecture of the QAIC suffers from spurious responses at IF caused by gain and phase imbalance in its wideband downconverter. We then show how the direct RF-to-information converter (DRF2IC) compactly adds CS wideband detection to a direct conversion frequency-translational noise-cancelling (FTNC) receiver by introducing pseudo-random modulation of the local oscillator (LO) signals and by consolidating multiple CS measurements into one hardware branch. The DRF2IC inherits benefits of the FTNC receiver in signal reception mode. In CS wideband detection mode, the DRF2IC inherits key advantages from both the earlier lowpass CS architectures and the QAIC while avoiding the drawbacks of both. It uncouples fPRBS from fMAX in contrast with the MWC. In contrast with the QAIC, the DRF2IC employs a direct conversion RF chain with narrow bandwidth analog components at baseband thereby avoiding frequency-dependent gain and phase imbalance. The DRF2IC chip occupies 0.56mm2 area in 65nm CMOS. In reception mode, it consumes 46.5mW from 1.15V and delivers 40MHz RF bandwidth, 41.5dB conversion gain, 3.6dB noise figure (NF) and -2dBm blocker 1dB compression point (B1dB). In CS wideband detection mode, 66dB operational dynamic range, 40dB instantaneous dynamic range and 1.43GHz instantaneous bandwidth are demonstrated and 6 interferers each 10MHz wide scattered over a 1.27GHz span are detected in 1.2us consuming 58.5mW