Two dimensional signal processing for storage channels

Over the past decade, storage channels have undergone a steady increase in capacity. With the prediction of achieving 10 Tb/in2 areal density for magnetic recording channels in sight, the industry is pushing towards di erent technologies for storage channels. Heat-assisted magnetic recording, bit-patterned media, and twodimensional magnetic recording (TDMR) are cited as viable alternative technologies to meet the increasing market demand. Among these technologies, the twodimensional magnetic recording channel has the advantage of using conventional medium while relying on improvement from signal processing. Capacity approaching codes and detection methods tailored to the magnetic recording channels are the main signal processing tools used in magnetic recording. The promise is that two-dimensional signal processing will play a role in bringing about the theoretical predictions. The main challenges in TDMR media are as follows: i) the small area allocated to each bit on the media, and the sophisticated read and write processes in shingled magnetic recording devices result in signi cant amount of noise, ii) the twodimensional inter-symbol interference is intrinsic to the nature of shingled magnetic recording. Thus, a feasible two-dimensional communication system is needed to combat the errors that arise from aggressive read and write processes. In this dissertation, we present some of the work done on signal processing aspect for storage channels. We discuss i) the nano-scale model of the storage channel, ii) noise characteristics and corresponding detection strategies, iii) two-dimensional signal processing targeted at shingled magnetic recording

Detailed examination of a packet collision model for Bluetooth Low Energy advertising mode

The aim of this paper is to investigate the amount of energy that is required to successfully transmit information inside the Bluetooth Low Energy (BLE) advertising packets. There are applications that require more than one BLE node to simultaneously transmit data. The BLE protocol utilizes a specific communication method termed advertising mode to perform unidirectional broadcasts of data from the advertising devices. However, with an increased number of BLE devices advertising simultaneously, there will be inevitable packet collisions from the advertising devices. This results in a waste of energy, specifically in low-power applications where lower consumption is desirable to minimize the need for battery replacements. This paper examines a packet collision model for the BLE advertising mode with the results validated using experimental data. Our analysis shows that when the throughput of the BLE network starts to fall due to an increase in the number of packet collisions, the energy consumption of the BLE nodes increase exponentially with respect to the number of nodes

A survey on wireless body area networks for eHealthcare systems in residential environments

The progress in wearable and implanted health monitoring technologies has strong potential to alter the future of healthcare services by enabling ubiquitous monitoring of patients. A typical health monitoring system consists of a network of wearable or implanted sensors that constantly monitor physiological parameters. Collected data are relayed using existing wireless communication protocols to the base station for additional processing. This article provides researchers with information to compare the existing low-power communication technologies that can potentially support the rapid development and deployment of WBAN systems, and mainly focuses on remote monitoring of elderly or chronically ill patients in residential environments

Lowering Error Floors by Concatenation of Low-Density Parity-Check and Array Code

Low-density parity-check (LDPC) codes have been shown to deliver capacity approaching performance; however, problematic graphical structures (e.g. trapping sets) in the Tanner graph of some LDPC codes can cause high error floors in bit-error-ratio (BER) performance under conventional sum-product algorithm (SPA). This paper presents a serial concatenation scheme to avoid the trapping sets and to lower the error floors of LDPC code. The outer code in the proposed concatenation is the LDPC, and the inner code is a high rate array code. This approach applies an interactive hybrid process between the BCJR decoding for the array code and the SPA for the LDPC code together with bit-pinning and bit-flipping techniques. Margulis code of size (2640, 1320) has been used for the simulation and it has been shown that the proposed concatenation and decoding scheme can considerably improve the error floor performance with minimal rate loss

Laboratory and field evaluation of three low-cost particulate matter sensors

Low-cost off-the-shelf particulate matter (PM) sensors have the potentiality to be used for evaluating the air quality in outdoor settings. Monitoring of air quality in surface coal mines is an example of such applications. In coal mines, long-term exposure to inhalation of coal dust is harmful and can lead to coal workers' pneumoconiosis, which is a potentially disabling lung disease. Therefore, continual monitoring of air quality in coal mines is a must and vital and can potentially assist in preventing such diseases. Although, using and deploying of the existing low-cost and lightweight sensors can help to improve monitoring resolution in a much cost-effective manner, there are some concerns regarding the reliability of the collected data from these sensors. Therefore, low-cost PM sensors are required to initially be compared with the standard reference instruments and then be calibrated. In this study, three different types of low-cost, light-scattering-based widely available PM sensors (Shinyei PPD42NS, Sharp GP2Y1010AU0F and Laser SEN0177) are evaluated, compared, and calibrated with the reference instruments in a controlled environment as well as in a field experiment (surface coal mineLow-cost off-the-shelf particulate matter (PM) sensors have the potentiality to be used for evaluating the air quality in outdoor settings. Monitoring of air quality in surface coal mines is an example of such applications. In coal mines, long-term exposure to inhalation of coal dust is harmful and can lead to coal workers' pneumoconiosis, which is a potentially disabling lung disease. Therefore, continual monitoring of air quality in coal mines is a must and vital and can potentially assist in preventing such diseases. Although, using and deploying of the existing low-cost and lightweight sensors can help to improve monitoring resolution in a much cost-effective manner, there are some concerns regarding the reliability of the collected data from these sensors. Therefore, low-cost PM sensors are required to initially be compared with the standard reference instruments and then be calibrated. In this study, three different types of low-cost, light-scattering-based widely available PM sensors (Shinyei PPD42NS, Sharp GP2Y1010AU0F and Laser SEN0177) are evaluated, compared, and calibrated with the reference instruments in a controlled environment as well as in a field experiment (surface coal mineAlpha Foundation for the Improvement of Mine Safety and Health. Grant Number: Grant Number AFC417-39Alpha Foundation for the Improvement of Mine Safety and Health. Grant Number: Grant Number AFC417-3