Design of Analog-to-Digital Converters with Embedded Mixing for Ultra-Low-Power Radio Receivers

In the field of radio receivers, down-conversion methods usually rely on one (or more) explicit mixing stage(s) before the analog-to-digital converter (ADC). These stages not only contribute to the overall power consumption but also have an impact on area and can compromise the receiver’s performance in terms of noise and linearity. On the other hand, most ADCs require some sort of reference signal in order to properly digitize an analog input signal. The implementation of this reference signal usually relies on bandgap circuits and reference buffers to generate a constant, stable, dc signal. Disregarding this conventional approach, the work developed in this thesis aims to explore the viability behind the usage of a variable reference signal. Moreover, it demonstrates that not only can an input signal be properly digitized, but also shifted up and down in frequency, effectively embedding the mixing operation in an ADC. As a result, ADCs in receiver chains can perform double-duty as both a quantizer and a mixing stage. The lesser known charge-sharing (CS) topology, within the successive approximation register (SAR) ADCs, is used for a practical implementation, due to its feature of “pre-charging” the reference signal prior to the conversion. Simulation results from an 8-bit CS-SAR ADC designed in a 0.13 μm CMOS technology validate the proposed technique

Timing Signals and Radio Frequency Distribution Using Ethernet Networks for High Energy Physics Applications

Timing networks are used around the world in various applications from telecommunications systems to industrial processes, and from radio astronomy to high energy physics. Most timing networks are implemented using proprietary technologies at high operation and maintenance costs. This thesis presents a novel timing network capable of distributed timing with subnanosecond accuracy. The network, developed at CERN and codenamed “White- Rabbit”, uses a non-dedicated Ethernet link to distribute timing and data packets without infringing the sub-nanosecond timing accuracy required for high energy physics applications. The first part of this thesis proposes a new digital circuit capable of measuring time differences between two digital clock signals with sub-picosecond time resolution. The proposed digital circuit measures and compensates for the phase variations between the transmitted and received network clocks required to achieve the sub-nanosecond timing accuracy. Circuit design, implementation and performance verification are reported. The second part of this thesis investigates and proposes a new method to distribute radio frequency (RF) signals over Ethernet networks. The main goal of existing distributed RF schemes, such as Radio-Over-Fibre or Digitised Radio-Over-Fibre, is to increase the bandwidth capacity taking advantage of the higher performance of digital optical links. These schemes tend to employ dedicated and costly technologies, deemed unnecessary for applications with lower bandwidth requirements. This work proposes the distribution of RF signals over the “White-Rabbit” network, to convey phase and frequency information from a reference base node to a large numbers of remote nodes, thus achieving high performance and cost reduction of the timing network. Hence, this thesis reports the design and implementation of a new distributed RF system architecture; analysed and tested using a purpose-built simulation environment, with results used to optimise a new bespoke FPGA implementation. The performance is evaluated through phase-noise spectra, the Allan-Variance, and signalto- noise ratio measurements of the distributed signals

Fully-photonic digital radio over fibre for future super-broadband access network applications

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityIn this thesis a Fully-Photonic DRoF (FP-DRoF) system is proposed for deploying of future super-broadband access networks. Digital Radio over Fibre (DRoF) is more independent of the fibre network impairments and the length of fibre than the ARoF link. In order for fully optical deployment of the signal conversion techniques in the FP-DRoF architecture, two key components an Analogue-to-Digital Converter (ADC) and a Digital-to-Analogue Converter (DAC)) for data conversion are designed and their performance are investigated whereas the physical functionality is evaluated. The system simulation results of the proposed pipelined Photonic ADC (PADC) show that the PADC has 10 GHz bandwidth around 60 GHz of sampling rate. Furthermore, by changing the bandwidth of the optical bandpass filter, switching to another band of sampling frequency provides optimised performance condition of the PADC. The PADC has low changes on the Effective Number of Bit (ENOB) response versus analogue RF input from 1 GHz up to 22 GHz for 60 GHz sampling frequency. The proposed 8-Bit pipelined PADC performance in terms of ENOB is evaluated at 60 Gigasample/s which is about 4.1. Recently, different methods have been reported by researchers to implement Photonic DACs (PDACs), but their aim was to convert digital electrical signals to the corresponding analogue signal by assisting the optical techniques. In this thesis, a Binary Weighted PDAC (BW-PDAC) is proposed. In this BW-PDAC, optical digital signals are fully optically converted to an analogue signal. The spurious free dynamic range at the output of the PDAC in a back-to-back deployment of the PADC and the PDAC was 26.6 dBc. For further improvement in the system performance, a 3R (Retiming, Reshaping and Reamplifying) regeneration system is proposed in this thesis. Simulation results show that for an ultrashort RZ pulse with a 5% duty cycle at 65 Gbit/s using the proposed 3R regeneration system on a link reduces rms timing jitter by 90% while the regenerated pulse eye opening height is improved by 65%. Finally, in this thesis the proposed FP-DRoF functionality is evaluated whereas its performance is investigated through a dedicated and shared fibre links. The simulation results show (in the case of low level signal to noise ratio, in comparison with ARoF through a dedicated fibre link) that the FP-DRoF has better BER performance than the ARoF in the order of 10-20. Furthermore, in order to realize a BER about 10-25 for the ARoF, the power penalty is about 4 dBm higher than the FP-DRoF link. The simulation results demonstrate that by considering 0.2 dB/km attenuation of a standard single mode fibre, the dedicated fibre length for the FP-DRoF link can be increased to about 20 km more than the ARoF link. Moreover, for performance assessment of the proposed FP-DRoF in a shared fibre link, the BER of the FP-DRoF link is about 10-10 magnitude less than the ARoF link for -19 dBm launched power into the fibre and the power penalty of the ARoF system is 10 dBm more than the FP-DRoF link. It is significant to increase the fibre link’s length of the FP-DRoF access network using common infrastructure. In addition, the simulation results are demonstrated that the FP-DRoF with non-uniform Wavelength Division Multiplexing (WDM) is more robust against four wave mixing impairment than the conventional WDM technique with uniform wavelength allocation and has better performance in terms of BER. It is clearly verified that the lunched power penalty at CS for DRoF link with uniform WDM techniques is about 2 dB higher than non-uniform WDM technique. Furthermore, uniform WDM method requires more bandwidth than non-uniform scheme which depends on the total number of channels and channels spacing

System-on-chip Computing and Interconnection Architectures for Telecommunications and Signal Processing

This dissertation proposes novel architectures and design techniques targeting SoC building blocks for telecommunications and signal processing applications. Hardware implementation of Low-Density Parity-Check decoders is approached at both the algorithmic and the architecture level. Low-Density Parity-Check codes are a promising coding scheme for future communication standards due to their outstanding error correction performance. This work proposes a methodology for analyzing effects of finite precision arithmetic on error correction performance and hardware complexity. The methodology is throughout employed for co-designing the decoder. First, a low-complexity check node based on the P-output decoding principle is designed and characterized on a CMOS standard-cells library. Results demonstrate implementation loss below 0.2 dB down to BER of 10^{-8} and a saving in complexity up to 59% with respect to other works in recent literature. High-throughput and low-latency issues are addressed with modified single-phase decoding schedules. A new "memory-aware" schedule is proposed requiring down to 20% of memory with respect to the traditional two-phase flooding decoding. Additionally, throughput is doubled and logic complexity reduced of 12%. These advantages are traded-off with error correction performance, thus making the solution attractive only for long codes, as those adopted in the DVB-S2 standard. The "layered decoding" principle is extended to those codes not specifically conceived for this technique. Proposed architectures exhibit complexity savings in the order of 40% for both area and power consumption figures, while implementation loss is smaller than 0.05 dB. Most modern communication standards employ Orthogonal Frequency Division Multiplexing as part of their physical layer. The core of OFDM is the Fast Fourier Transform and its inverse in charge of symbols (de)modulation. Requirements on throughput and energy efficiency call for FFT hardware implementation, while ubiquity of FFT suggests the design of parametric, re-configurable and re-usable IP hardware macrocells. In this context, this thesis describes an FFT/IFFT core compiler particularly suited for implementation of OFDM communication systems. The tool employs an accuracy-driven configuration engine which automatically profiles the internal arithmetic and generates a core with minimum operands bit-width and thus minimum circuit complexity. The engine performs a closed-loop optimization over three different internal arithmetic models (fixed-point, block floating-point and convergent block floating-point) using the numerical accuracy budget given by the user as a reference point. The flexibility and re-usability of the proposed macrocell are illustrated through several case studies which encompass all current state-of-the-art OFDM communications standards (WLAN, WMAN, xDSL, DVB-T/H, DAB and UWB). Implementations results are presented for two deep sub-micron standard-cells libraries (65 and 90 nm) and commercially available FPGA devices. Compared with other FFT core compilers, the proposed environment produces macrocells with lower circuit complexity and same system level performance (throughput, transform size and numerical accuracy). The final part of this dissertation focuses on the Network-on-Chip design paradigm whose goal is building scalable communication infrastructures connecting hundreds of core. A low-complexity link architecture for mesochronous on-chip communication is discussed. The link enables skew constraint looseness in the clock tree synthesis, frequency speed-up, power consumption reduction and faster back-end turnarounds. The proposed architecture reaches a maximum clock frequency of 1 GHz on 65 nm low-leakage CMOS standard-cells library. In a complex test case with a full-blown NoC infrastructure, the link overhead is only 3% of chip area and 0.5% of leakage power consumption. Finally, a new methodology, named metacoding, is proposed. Metacoding generates correct-by-construction technology independent RTL codebases for NoC building blocks. The RTL coding phase is abstracted and modeled with an Object Oriented framework, integrated within a commercial tool for IP packaging (Synopsys CoreTools suite). Compared with traditional coding styles based on pre-processor directives, metacoding produces 65% smaller codebases and reduces the configurations to verify up to three orders of magnitude

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

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