A selective control information detection scheme for OFDM receivers

In wireless communications, both control information and payload (user-data) are concurrently transmitted and required to be successfully recovered. This paper focuses on block-level detection, which is applicable for detecting transmitted control information, particularly when this information is selected or chosen from a finite set of information that are known at both transmitting and receiving devices. Using an orthogonal frequency division multiplexing architecture, this paper investigates and evaluates the performance of a time-domain decision criterion in comparison with a form of Maximum Likelihood (ML) estimation method. Unlike the ML method, the proposed time-domain detection technique requires no channel estimation as it uses the correlation (in the time-domain) that exists between the received and the transmitted selective information as a means of detection. In comparison with the ML method, results show that the proposed method offers improved detection performance, particularly when the control information consists of at least 16. However, the implementation of the proposed method requires a slightly increased number of mathematical computations

A joint OFDM PAPR reduction and data decoding scheme with no SI estimation

The need for side information (SI) estimation poses a major challenge when selected mapping (SLM) is implemented to reduce peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. Recent studies on pilot-assisted SI estimation procedures suggest that it is possible to determine the SI without the need for SI transmission. However, SI estimation adds to computational complexity and implementation challenges of practical SLM-OFDM receivers. To address these technical issues, this paper presents the use of a pilot-assisted cluster-based phase modulation and demodulation procedure called embedded coded modulation (ECM). The ECM technique uses a slightly modified SLM approach to reduce PAPR and to enable data recovery with no SI transmission and no SI estimation. In the presence of some non-linear amplifier distortion, it is shown that the ECM method achieves similar data decoding performance as conventional SLM-OFDM receiver that assumed a perfectly known SI and when the SI is estimated using a frequency-domain correlation approach. However, when the number of OFDM subcarriers is small and due to the clustering in ECM, the modified SLM produces a smaller PAPR reduction gain compared with conventional SLM

A low complexity SI sequence estimator for pilot-aided SLM–OFDM systems

Selected mapping (SLM) is a well-known method for reducing peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. However, as a consequence of implementing SLM, OFDM receivers often require estimation of some side information (SI) in order to achieve successful data recovery. Existing SI estimation schemes have very high computational complexities that put additional constraints on limited resources and increase system complexity. To address this problem, an alternative SLM approach that facilitates estimation of SI in the form of phase detection is presented. Simulations show that this modified SLM approach produces similar PAPR reduction performance when compared to conventional SLM. With no amplifier distortion and in the presence of non-linear power amplifier distortion, the proposed SI estimation approach achieves similar data recovery performance as both standard SLM–OFDM (with perfect SI estimation) and also when SI estimation is implemented through the use of an existing frequency-domain correlation (FDC) decision metric. In addition, the proposed method significantly reduces computational complexity compared with the FDC scheme and an ML estimation scheme

AFM imaging and plasmonic detection of organic thin-films deposited on nanoantenna arrays

In this study, atomic force microscopy (AFM) imaging has been used to reveal the preferential deposition of organic thin-films on patterned nanoantenna array surfaces - identifying the localised formation of both monolayer and multilayer films of octadecanethiol (ODT) molecules, depending on the concentration of the solutions used. Reliable identification of this selective deposition process has been demonstrated for the first time, to our knowledge. Organic thin-films, in particular films of ODT molecules, were deposited on plasmonic resonator surfaces through a chemi-sorption process - using different solution concentrations and immersion times. The nanoantennas based on gold asymmetric-split ring resonator (A-SRR) geometries were fabricated on zinc selenide (ZnSe) substrates using electron-beam lithography and the lift-off technique. Use of the plasmonic resonant-coupling technique has enabled the detection of ODT molecules deposited from a dilute, micromolar (1 M) solution concentration - with attomole sensitivity of deposited material per A-SRR – a value that is three orders of magnitude lower in concentration than previously reported. Additionally, on resonance, the amplitude of the molecular vibrational resonance peaks is typically an order of magnitude larger than that for the non-resonant coupling. Fourier-transform infrared (FTIR) spectroscopy shows molecule specific spectral responses – with magnitudes corresponding to the different film thicknesses deposited on the resonator surfaces. The experimental results are supported by numerical simulation

Deposition of Organic Molecules on Gold Nanoantennas for Sensing

The deposition of organic molecules on gold nanoantennas is reported through chemisorption for sensing in the midinfrared (mid-IR) spectral range. The specific nanostructures are gold asymmetric-split ring resonators (A-SRRs) based on circular-geometry with two different ‘arc’ lengths. The plasmonic resonant coupling technique was used to match the vibrational responses of the targeted molecules for their enhanced detection. Gold nanostructures are functionalised through chemisorption of octadecanethiol (ODT) in ethanol solution. The molecular vibrational responses were measured using a microscope coupled Fourier Transform Infrared (FTIR) spectroscopy. The experimental findings are closely supported using FDTD simulation. The modified nanoantennas surfaces are capable of supporting wide range of organic-sensing applications

Design of a microwave radiometer for monitoring high voltage insulator contamination level

Microwave radiometry is a novel method for monitoring contamination levels on high voltage insulators. The microwave radiometer described measures energy emitted from the contamination layer and could provide a safe, reliable, contactless monitoring method that is effective under dry conditions. The design of the system has focused on optimizing accuracy, stability and sensitivity using a relatively low cost architecture. Experimental results demonstrate that the output from the radiometer is able to clearly distinguish between samples with different contamination levels under dry conditions. This contamination monitoring method could potentially provide advance warning of the future failure of wet insulators in climates where insulators can experience dry conditions for extended periods

Mapping the sensitivity of split ring resonators using a localized analyte

Split ring resonator (SRR) based metamaterials have frequently been demonstrated for use as optical sensors of organic materials. This is made possible by matching the wavelength of the SRR plasmonic resonance with a molecular resonance of a specific analyte, which is usually placed on top of the metal structure. However, systematic studies of SRRs that identify the regions that exhibit a high electric field strength are commonly performed using simulations. In this paper we demonstrate that areas of high electric field strength, termed “hot-spots,” can be found by localizing a small quantity of organic analyte at various positions on or near the structure. Furthermore, the sensitivity of the SRR to the localized analyte can be quantified to determine, experimentally, suitable regions for optical sensing

Computational efficient SLM–OFDM receiver for time-invariant indoor fading channel

This paper addresses receiver related side information (SI) estimation issues when selected mapping is used to reduce peak-to-average power ratio in orthogonal frequency division multiplexing (OFDM) systems. The SI contains critical information and its accurate estimation is required to enable successful recovery of payload data regardless of the channel condition. However, the need for SI estimation poses some practical issues in the form of high computational complexity and implementation challenges. Through simulations, this paper investigates the performance of an alternative data decoding approach called Embedded Coded Modulation (ECM), which requires no SI estimation. Using a form of block-type OFDM frame structure, results show that the ECM technique produces identical data decoding performance as other methods even in the presence of some non-linear amplifier distortions. In addition, it is shown that the ECM method eliminates SI related computational complexity and implementation problems

An investigative study into the sensitivity of different partial discharge φ-q-n pattern resolution sizes on statistical neural network pattern classification

This paper investigates the sensitivity of statistical fingerprints to different phase resolution (PR) and amplitude bins (AB) sizes of partial discharge (PD) φ-q-n (phase-amplitude-number) patterns. In particular, this paper compares the capability of the ensemble neural network (ENN) and the single neural network (SNN) in recognizing and distinguishing different resolution sizes of φ-q-n discharge patterns. The training fingerprints for both the SNN and ENN comprise statistical fingerprints from different φ-q-n measurements. The result shows that there exists statistical distinction for different PR and AB sizes on some of the statistical fingerprints. Additionally, the ENN and SNN outputs change depending on training and testing with different PR and AB sizes. Furthermore, the ENN appears to be more sensitive in recognizing and discriminating the resolution changes when compared with the SNN. Finally, the results are assessed for practical implementation in the power industry and benefits to practitioners in the field are highlighted