Optimisation of Bluetooth wireless personal area networks

In recent years there has been a marked growth in the use of wireless cellular telephones, PCs and the Internet. This proliferation of information technology has hastened the advent of wireless networks which aim to increase the accessibility and reach of communications devices. Ambient Intelligence (Ami) is a vision of the future of computing in which all kinds of everyday objects will contain intelligence. To be effective, Ami requires Ubiquitous Computing and Communication, the latter being enabled by wireless networking. The IEEE's 802.11 task group has developed a series of radio based replacements for the familiar wired ethernet LAN. At the same time another IEEE standards task group, 802.15, together with a number of industry consortia, has introduced a new level of wireless networking based upon short range, ad-hoc connections. Currently, the most significant of these new Wireless Personal Area Network (WPAN) standards is Bluetooth, one of the first of the enabling technologies of Ami to be commercially available. Bluetooth operates in the internationally unlicensed Industrial, Scientific and Medical (ISM) band at 2.4 GHz. unfortunately, this spectrum is particularly crowded. It is also used by: WiFi (IEEE 802.11); a new WPAN standard called Zig- Bee; many types of simple devices such as garage door openers; and is polluted by unintentional radiators. The success of a radio specification for ubiquitous wireless communications is, therefore, dependant upon a robust tolerance to high levels of electromagnetic noise. This thesis addresses the optimisation of low power WPANs in this context, with particular reference to the physical layer radio specification of the Bluetooth system

Performance enhancement for LTE and beyond systems

A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of PhilosophyWireless communication systems have undergone fast development in recent years. Based on GSM/EDGE and UMTS/HSPA, the 3rd Generation Partnership Project (3GPP) specified the Long Term Evolution (LTE) standard to cope with rapidly increasing demands, including capacity, coverage, and data rate. To achieve this goal, several key techniques have been adopted by LTE, such as Multiple-Input and Multiple-Output (MIMO), Orthogonal Frequency-Division Multiplexing (OFDM), and heterogeneous network (HetNet). However, there are some inherent drawbacks regarding these techniques. Direct conversion architecture is adopted to provide a simple, low cost transmitter solution. The problem of I/Q imbalance arises due to the imperfection of circuit components; the orthogonality of OFDM is vulnerable to carrier frequency offset (CFO) and sampling frequency offset (SFO). The doubly selective channel can also severely deteriorate the receiver performance. In addition, the deployment of Heterogeneous Network (HetNet), which permits the co-existence of macro and pico cells, incurs inter-cell interference for cell edge users. The impact of these factors then results in significant degradation in relation to system performance. This dissertation aims to investigate the key techniques which can be used to mitigate the above problems. First, I/Q imbalance for the wideband transmitter is studied and a self-IQ-demodulation based compensation scheme for frequencydependent (FD) I/Q imbalance is proposed. This combats the FD I/Q imbalance by using the internal diode of the transmitter and a specially designed test signal without any external calibration instruments or internal low-IF feedback path. The instrument test results show that the proposed scheme can enhance signal quality by 10 dB in terms of image rejection ratio (IRR). In addition to the I/Q imbalance, the system suffers from CFO, SFO and frequency-time selective channel. To mitigate this, a hybrid optimum OFDM receiver with decision feedback equalizer (DFE) to cope with the CFO, SFO and doubly selective channel. The algorithm firstly estimates the CFO and channel frequency response (CFR) in the coarse estimation, with the help of hybrid classical timing and frequency synchronization algorithms. Afterwards, a pilot-aided polynomial interpolation channel estimation, combined with a low complexity DFE scheme, based on minimum mean squared error (MMSE) criteria, is developed to alleviate the impact of the residual SFO, CFO, and Doppler effect. A subspace-based signal-to-noise ratio (SNR) estimation algorithm is proposed to estimate the SNR in the doubly selective channel. This provides prior knowledge for MMSE-DFE and automatic modulation and coding (AMC). Simulation results show that this proposed estimation algorithm significantly improves the system performance. In order to speed up algorithm verification process, an FPGA based co-simulation is developed. Inter-cell interference caused by the co-existence of macro and pico cells has a big impact on system performance. Although an almost blank subframe (ABS) is proposed to mitigate this problem, the residual control signal in the ABS still inevitably causes interference. Hence, a cell-specific reference signal (CRS) interference cancellation algorithm, utilizing the information in the ABS, is proposed. First, the timing and carrier frequency offset of the interference signal is compensated by utilizing the cross-correlation properties of the synchronization signal. Afterwards, the reference signal is generated locally and channel response is estimated by making use of channel statistics. Then, the interference signal is reconstructed based on the previous estimate of the channel, timing and carrier frequency offset. The interference is mitigated by subtracting the estimation of the interference signal and LLR puncturing. The block error rate (BLER) performance of the signal is notably improved by this algorithm, according to the simulation results of different channel scenarios. The proposed techniques provide low cost, low complexity solutions for LTE and beyond systems. The simulation and measurements show good overall system performance can be achieved

Energy-Detecting Receivers for Wake-Up Radio Applications

In the energy-limited wireless sensor node applications, wake-up radios are required to reduce the average power consumption of the node. Energy-detecting receivers are the best fit for such low power operations. This thesis presents the energy-detecting receiver design; challenges; techniques to enhance sensitivity, selectivity; and multi-access operation. Self-mixers instead of the conventional envelope detectors are proposed and proved to be optimal for signal detection. A fully integrated wake-up receiver uses the self-mixer and time-encoded baseband signal processing to provide a sensitivity of -79.1dBm at 434MHz with 420pW of power, providing an 8dB better sensitivity at 10dB lower power consumption compared to the SoA. A novel approach using narrowband interferers as local oscillators will be presented to further enhance sensitivity and selectivity, effectively operating the energy-detector receiver as a direct down-conversion receiver. Additionally, a clockless continuous-time analog correlator will be introduced to enhance the selectivity to wide-band AM interferers. The architecture uses pulse-position-encoded analog signal processing with VCOs as integrators and pulse-controlled relaxation delays; it operates as a code-domain matched filter to de-spread asynchronous wake-up codes. This code-domain matched filtering also provides code-division multiple access (CDMA) for simultaneous wakeups. Additional enhancement in the link can be achieved using directional antennas, providing spatial gain and selectivity. Certain applications can leverage a nearby reflector similar to a Yagi antenna to enhance the directivity. A low power directional backscatter tag is proposed, it uses multiple antennas acting as a reflectarray by configuring constant phase gradients depending on the direction of arrival (DoA) of the signal. Thus, instead of harvesting energy, the same energy and the surrounding environment can be leveraged to enhance functionality (e.g. interferer as LO, using a backscatter tag on a wall) for low power operation. Innovations spanning both system and circuit architectures that leverage the ambient energy and environment to enable power-efficient solutions for next-generation wake-up radios are presented in this work

A Novel Power-Efficient Wireless Multi-channel Recording System for the Telemonitoring of Electroencephalography (EEG)

This research introduces the development of a novel EEG recording system that is modular, batteryless, and wireless (untethered) with the supporting theoretical foundation in wireless communications and related design elements and circuitry. Its modular construct overcomes the EEG scaling problem and makes it easier for reconfiguring the hardware design in terms of the number and placement of electrodes and type of standard EEG system contemplated for use. In this development, portability, lightweight, and applicability to other clinical applications that rely on EEG data are sought. Due to printer tolerance, the 3D printed cap consists of 61 electrode placements. This recording capacity can however extend from 21 (as in the international 10-20 systems) up to 61 EEG channels at sample rates ranging from 250 to 1000 Hz and the transfer of the raw EEG signal using a standard allocated frequency as a data carrier. The main objectives of this dissertation are to (1) eliminate the need for heavy mounted batteries, (2) overcome the requirement for bulky power systems, and (3) avoid the use of data cables to untether the EEG system from the subject for a more practical and less restrictive setting. Unpredictability and temporal variations of the EEG input make developing a battery-free and cable-free EEG reading device challenging. Professional high-quality and high-resolution analog front ends are required to capture non-stationary EEG signals at microvolt levels. The primary components of the proposed setup are the wireless power transmission unit, which consists of a power amplifier, highly efficient resonant-inductive link, rectification, regulation, and power management units, as well as the analog front end, which consists of an analog to digital converter, pre-amplification unit, filtering unit, host microprocessor, and the wireless communication unit. These must all be compatible with the rest of the system and must use the least amount of power possible while minimizing the presence of noise and the attenuation of the recorded signal A highly efficient resonant-inductive coupling link is developed to decrease power transmission dissipation. Magnetized materials were utilized to steer electromagnetic flux and decrease route and medium loss while transmitting the required energy with low dissipation. Signal pre-amplification is handled by the front-end active electrodes. Standard bio-amplifier design approaches are combined to accomplish this purpose, and a thorough investigation of the optimum ADC, microcontroller, and transceiver units has been carried out. We can minimize overall system weight and power consumption by employing battery-less and cable-free EEG readout system designs, consequently giving patients more comfort and freedom of movement. Similarly, the solutions are designed to match the performance of medical-grade equipment. The captured electrical impulses using the proposed setup can be stored for various uses, including classification, prediction, 3D source localization, and for monitoring and diagnosing different brain disorders. All the proposed designs and supporting mathematical derivations were validated through empirical and software-simulated experiments. Many of the proposed designs, including the 3D head cap, the wireless power transmission unit, and the pre-amplification unit, are already fabricated, and the schematic circuits and simulation results were based on Spice, Altium, and high-frequency structure simulator (HFSS) software. The fully integrated head cap to be fabricated would require embedding the active electrodes into the 3D headset and applying current technological advances to miniaturize some of the design elements developed in this dissertation

Generalised sensor linearisation and calibration

The aim of this work was to conduct a survey of current sensor measurement technologies and investigate sensor linearisation, cahbration and compensation methods m order to determine the methods most suitable for generic embedded sensor implementation. The thesis contains a comprehensive survey of sensor technologies and their interfacing requirements as a prerequisite for determining modules required by the generic embedded sensor interface. Different linearisation and calibration techmques are investigated and the most promising techniques, curve fitting and progressive polynomial calibration method, are then examined in greater detail and simulations performed to compare their performance. The fundamental limitations and trade offs in design and implementation on the microprocessor of these methods are studied. The design of the compensation module is also presented and its implementation on the microprocessor m the form of the C code is described. All methods are tested and implemented on a PIC microcontroller as a part of linearisation, cahbration and compensation module of the generic embedded sensor interface

Advanced Interfaces for HMI in Hand Gesture Recognition

The present thesis investigates techniques and technologies for high quality Human Machine Interfaces (HMI) in biomedical applications. Starting from a literature review and considering market SoA in this field, the thesis explores advanced sensor interfaces, wearable computing and machine learning techniques for embedded resource-constrained systems. The research starts from the design and implementation of a real-time control system for a multifinger hand prosthesis based on pattern recognition algorithms. This system is capable to control an artificial hand using a natural gesture interface, considering the challenges related to the trade-off between responsiveness, accuracy and light computation. Furthermore, the thesis addresses the challenges related to the design of a scalable and versatile system for gesture recognition with the integration of a novel sensor interface for wearable medical and consumer application

Radio-Communications Architectures

Wireless communications, i.e. radio-communications, are widely used for our different daily needs. Examples are numerous and standard names like BLUETOOTH, WiFI, WiMAX, UMTS, GSM and, more recently, LTE are well-known [Baudoin et al. 2007]. General applications in the RFID or UWB contexts are the subject of many papers. This chapter presents radio-frequency (RF) communication systems architecture for mobile, wireless local area networks (WLAN) and connectivity terminals. An important aspect of today's applications is the data rate increase, especially in connectivity standards like WiFI and WiMAX, because the user demands high Quality of Service (QoS). To increase the data rate we tend to use wideband or multi-standard architecture. The concept of software radio includes a self-reconfigurable radio link and is described here on its RF aspects. The term multi-radio is preferred. This chapter focuses on the transmitter, yet some considerations about the receiver are given. An important aspect of the architecture is that a transceiver is built with respect to the radio-communications signals. We classify them in section 2 by differentiating Continuous Wave (CW) and Impulse Radio (IR) systems. Section 3 is the technical background one has to consider for actual applications. Section 4 summarizes state-of-the-art high data rate architectures and the latest research in multi-radio systems. In section 5, IR architectures for Ultra Wide Band (UWB) systems complete this overview; we will also underline the coexistence and compatibility challenges between CW and IR systems

Development and Experimental Analysis of Wireless High Accuracy Ultra-Wideband Localization Systems for Indoor Medical Applications

This dissertation addresses several interesting and relevant problems in the field of wireless technologies applied to medical applications and specifically problems related to ultra-wideband high accuracy localization for use in the operating room. This research is cross disciplinary in nature and fundamentally builds upon microwave engineering, software engineering, systems engineering, and biomedical engineering. A good portion of this work has been published in peer reviewed microwave engineering and biomedical engineering conferences and journals. Wireless technologies in medicine are discussed with focus on ultra-wideband positioning in orthopedic surgical navigation. Characterization of the operating room as a medium for ultra-wideband signal transmission helps define system design requirements. A discussion of the first generation positioning system provides a context for understanding the overall system architecture of the second generation ultra-wideband positioning system outlined in this dissertation. A system-level simulation framework provides a method for rapid prototyping of ultra-wideband positioning systems which takes into account all facets of the system (analog, digital, channel, experimental setup). This provides a robust framework for optimizing overall system design in realistic propagation environments. A practical approach is taken to outline the development of the second generation ultra-wideband positioning system which includes an integrated tag design and real-time dynamic tracking of multiple tags. The tag and receiver designs are outlined as well as receiver-side digital signal processing, system-level design support for multi-tag tracking, and potential error sources observed in dynamic experiments including phase center error, clock jitter and drift, and geometric position dilution of precision. An experimental analysis of the multi-tag positioning system provides insight into overall system performance including the main sources of error. A five base station experiment shows the potential of redundant base stations in improving overall dynamic accuracy. Finally, the system performance in low signal-to-noise ratio and non-line-of-sight environments is analyzed by focusing on receiver-side digitally-implemented ranging algorithms including leading-edge detection and peak detection. These technologies are aimed at use in next-generation medical systems with many applications including surgical navigation, wireless telemetry, medical asset tracking, and in vivo wireless sensors