Methods, devices and systems for receiving and decoding a signal in the presence of noise using slices and warping

Abstract

A method may comprise receiving and sampling a signal. The signal may encode a data packet. A slice may be generated and stored comprising a pair of values for each of a selected number of samples of the signal representing a correlation of the signal to reference functions in the receiver. The presence of the data packet may then be detected and the detected packet decoded from the stored slices. The generating and storing slices may be carried out as the received signal is sampled. The sampled values of the signal may be discarded as the slices are generated and stored. The slice representation of the signal can be manipulated to generate filters with flexible bandwidth and center frequency.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS[0001]This application claims the benefit under 35 USC §119(e) of U.S. Provisional Application No. 61 / 880,786 titled “Methods, Devices and Systems for Receiving and Decoding a Signal in the Presence of Noise Using Slices and Warping,” filed Sep. 20, 2013, the disclosure of which application is herein incorporated by reference.INTRODUCTION[0002]Ingestible sensors may comprise a low power communicator whose transmissions are received by a receiver that may be worn outside of the body. Conventional ‘body communication systems’ should be capable of processing high-speed raw data in a predetermined amount of time, with considerations to available power consumption and memory size. In a conventional receiver, the incoming signal passes through an ‘analog front-end’ circuit comprising analog filters and analog electronic amplifiers. The analog filter typically has a wide bandwidth, to allow for the detection of all possible transmitted frequencies, as...

AI Technical Summary

Benefits of technology

[0008]Embodiments address the problems inherent in capturing and storing a great many high-speed samples, which strains both computational capability and memory size. Embodiments solve both problems by capturing “slices”. The slice data representation, according to one embodiment, contains sufficient information to efficiently and compactly represent the incoming signal and to implement filters of most any bandwidth. According to one embodiment, slices may be subject to a warping operation, by which sets of slices are transformed in useful ways to complete the detection process. Indeed, slices may be combined, according to one embodiment, to create filters having selectably wide or narrow pass-bands. According to embodiments, the warping operation may be configured to transform slices captured at one frequency to slices at another nearby frequency. This warping operation may be carried out by an algorithm configured to find an incoming carrier frequency and to find evidence of data packets in a noisy environment. The slice representation of signal data, coupled with the warping function, according to embodiments, represent a novel and highly efficient way to perform sophisticated detection algorithms with modest hardware and memory resources.

Problems solved by technology

The filtering provided in the analog front-end is modest, and allows a significant amount of noise to get through along with the desired signal.

In cases in which the receiver's estimate of the carrier frequency has a significant amount of uncertainty, the receiver is required to start with a wider-bandwidth digital filter and to, therefore, admit a greater amount of noise.

The greater amount of noise means that a weak signal may be missed entirely.

But, if the narrow filter is centered on the incorrect carrier frequency, the incoming signal may be missed entirely.

This process of searching for the carrier with a narrow bandwidth filter is both time consuming and power intensive.

This process not only requires significant memory resources (especially using high resolution ADCs) but also expends a significant amount of device battery life merely to identify the carrier frequency of the incoming signal.

Embodiments address the problems inherent in capturing and storing a great many high-speed samples, which strains both computational capability and memory size.

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