Technical Field
The present invention relates to apparatus for detecting interference in wireless signals
Related Art
Signal interference is the inevitable result of the proliferation of wireless systems. Home networking, Bluetooth enabled devices, broadcast digital television, or even a microwave oven, can all contribute potential interference. Regulatory and environmental restrictions further compound these problems by limiting the distribution of new transmitter sites, forcing base station transceivers to share towers.
There are several apparatus on the market today designed to detect interference which may affect the quality of wireless signals. These apparatus include, for example, the Anritsu MT8222A Base Station Analyzer and the MS272xB line of Spectrum Analyzers, all available from Anritsu Company, Morgan Hill, Calif. These apparatus, among others, implement several methods of measuring and analyzing interference including measuring signal strength, received signal strength indication (RSSI), spectrograms, real-time scanning, and Error Vector Spectrum (EVS). However, when interference is weak enough to be buried under the spectrum of the desired signal and when the desired signal is present during the entire period of time that interference is present, current apparatus' ability to detect interference is weakened.
Thus, it is desirable to provide an apparatus for detecting interference in wireless signals.
According to embodiments of the present invention, an apparatus is provided to detect interference in a received signal by modifying the received signal to remove sequentially deterministic components.
In one embodiment of the present invention, an apparatus can be configured to receive any wireless communication signal that includes sequentially deterministic components and to modify those wireless communication signals to detect interference that would otherwise be undetected. The sequentially deterministic components include portions of the signal that are made of predefined sequences. Examples of sequentially deterministic components include Pilot sequences in Code Division Multiple Access-based (CDMA-based) wireless technologies and Preambles in Worldwide Interoperability for Microwave Access (WiMAX). Because these components are predefined, they can be removed using ideal reference waveforms. The ideal reference waveforms are the ideal versions of the sequentially deterministic components for a given signal type of interest.
The received signal can be cross-correlated with the ideal reference waveforms to identify a dominant waveform and its characteristics in the received signal. The characteristics may include frequency, phase, and time offset and power. Using this information, the ideal reference waveform corresponding to the dominant waveform can be adjusted and subtracted from the received signal. This process can be repeated until no more dominant waveforms can be identified or until all reference waveforms have been subtracted. The resulting signal will be left with the interference that was previously undetectable. This can be analyzed using a spectrum analysis procedure to view the residual spectrum and identify possible sources of interference.
Further details of the present invention are explained with the help of the attached drawings in which:
Apparatus of the present invention implement a method that removes the sequentially deterministic components of wireless communication signals to isolate weaker, interfering signals that would otherwise be hidden below the spectrum of the dominant signal(s). In one embodiment, a set of ideal reference waveforms are used to remove the sequentially deterministic components from the received signal.
Using the set of ideal reference waveforms constructed as shown in
Returning to
At block 712, the adjusted reference waveform, Padj(k), is subtracted from the received signal, Rx(t), to create a modified received signal, Rx′(t). At block 714, steps 704-712 are repeated, recursively substituting the modified received signal, Rx′(t), for the received signal, Rx(t), until no more dominant waveforms can be identified or until all available reference waveforms have been subtracted. The resulting Rx′(t) is as shown at 206 in
In one embodiment, a noise floor is estimated based on the cross-correlation of the sampled signal and the ideal reference waveforms. Some signal standards limit the total pool of waveforms that can be present in a signal at any time, therefore the noise floor can be estimated from the power of any waveforms detected in addition to the standard-set limit. Additionally, under signal standards where there is no set limit, physical limitations (such as geography) make the presence of a large number of waveforms unlikely. Therefore, the noise floor can be estimated based on the power of the weakest waveforms detected. Thus, if no waveform is detected with a peak-magnitude above the estimated noise floor, then no dominant waveform remains in the sampled signal.
In one embodiment, an apparatus can display each dominant waveform identified in block 706, along with its characteristics measured in block 708, providing a very sensitive reading of the waveforms present in the received signal. Thus, secondary signals, those waveforms identified as dominant after the first dominant waveform has been removed, may be detected with greater sensitivity in apparatus of the present invention than in conventional Base Station Analyzers.
In another embodiment, the results of the method can be used for spectrum analysis. As each dominant waveform is removed from the received signal, the spectrum analyzer can perform a Fourier transform on each resulting Rx′(t). Each spectrum, including the Residual Spectrum (i.e., the spectrum of the remaining signal after all dominant waveforms have been removed) can be displayed on the spectrum analyzer. Analysis can then be performed on the spectra to identify the source of the interference.
In one embodiment, the device may be configured to display the spectrum 912 of the signal that remains after the dominant waveforms have been removed, this is referred to as the Residual Spectrum. Additionally, a conventional spectrum analysis result (the original spectrum before any signal component is removed) may be superimposed in a different color on top of this Residual Spectrum trace for comparison purposes. An apparatus in accordance with an embodiment can use the Residual Spectrum to identify the source and signal type of the interfering signal.
Although the present invention has been described above with particularity, this was merely to teach one of ordinary skill in the art how to make and use the invention. Many modifications will fall within the scope of the invention, as that scope is defined by the following claims.
This application is continuation of U.S. Pat. No. 9,571,142 entitled “APPARATUS TO DETECT INTERFERENCE IN WIRELESS SIGNALS”, by Kee-dyi Huang, Bhaskar Thiaqaraian, Randy L. Lundquist, and Vaidyanathan Venuqopal.
Number | Name | Date | Kind |
---|---|---|---|
5144642 | Weinberg | Sep 1992 | A |
5151919 | Dent | Sep 1992 | A |
5648765 | Cresap | Jul 1997 | A |
5835489 | Moriya | Nov 1998 | A |
6275543 | Petrus | Aug 2001 | B1 |
6571089 | Richards | May 2003 | B1 |
6609008 | Whang | Aug 2003 | B1 |
7379724 | Nilsson | May 2008 | B2 |
7424268 | Diener | Sep 2008 | B2 |
7460837 | Diener | Dec 2008 | B2 |
7606335 | Kloper | Oct 2009 | B2 |
7961777 | Nakanishi | Jun 2011 | B2 |
9571142 | Huang | Feb 2017 | B2 |
20020037737 | Learned | Mar 2002 | A1 |
20020094785 | Deats | Jul 2002 | A1 |
20020126778 | Ojard | Sep 2002 | A1 |
20030040277 | Deats | Feb 2003 | A1 |
20030219069 | Chen | Nov 2003 | A1 |
20050037724 | Walley | Feb 2005 | A1 |
20050047493 | Underbrink | Mar 2005 | A1 |
20060217080 | Nguyen | Sep 2006 | A1 |
20070091720 | Woo | Apr 2007 | A1 |
20080049600 | Liu | Feb 2008 | A1 |
Entry |
---|
Agilent AN 1314: Testing and Troubleshooting Digital RF Communications Receiver Designs: Application Note, Agilent Technologies, May 2000, 38 pages. |
Agilent E7476A W-CDMA (UMTS) Drive Test System with E6455C IMT2000 Digital Receiver: Data Sheet, Agilent Technologies, Aug. 2001, 16 pages. |
Xi UMTS/HSDPA, X-Tel Communications, Inc., Trend Test Communications, Inc., 2008, 2 pages, http://www.trendtestsystems.com/Trendweb/test/trendtestsystems.nsf/vlPageLookup/English%5E%5EProducts%5E%5EX-TEL+-+-Xi+UMTS-HSDPA+(TTS). |
“Datasheet—Wireless Field Test,” RF Scout Interference Hunter, Tektronix, 8 pages. |
“Symphony Prizm Data Sheet,” Symphony Scanning Receiver System, Comarco Wireless Test Solutions 2007, Revision B, 4 pages. |
Wilson, K., “Audio-Video Array Source Separation for Perceptual User Interfaces,” Workshops on Perceptual/Perceptive User Interfaces, Orlando, FL, Nov. 15-16, 2001, 7 pages. |
Reyes-Gomez, M., “Audio: Model Based Source Separation,” 2006, 3 pages, http://research.microsoft.com/˜manuelrg/Audio_MBSS.html. |
WCDMA/GSM (SeeGull® LX) Technical Specifications, Wireless Test Solutions, PCTEL: RF Solutions Group, Dec. 2006, Revision M, 2 pages. |
R&S TSMQ Radio Network Analyzer, Rohde and Schwarz, Version 1.00, Feb. 2007, 8 pages. |
SA2600: Field Spectrum Management: Application Note, Tektronix Communications, Jul. 2008,12 pages. |
“Drive Test: What causes unexpectedly high Ec values?” FAQ, Agilent Technologies, 2000-2008, 1 page, http://www.home.agilent.com/agilent/faqDetail.jspx?cc=US&Ic=eng&ckey=1000003427:epsg:faq&nid=-11143.0.00&id=1000003427:epsg:faq. |
SA2600 Handheld Real-Time Spectrum Analyzer: Product Video, Tektronix Communications, http://www2.tek.com/WMNoReg/applications/sa2600/SA2600_HI_BW.wmv, Screenshot of source URL: http://www.tek.com/products/spectrum_analyzers/sa2600/, 1 page. |
Akmal, M. et al., “An Enhanced Modulated Waveform Measurement System for the Robust Characterization of Microwave Devices under Modulated Excitation”, Proceedings of the 6th European Microwave Integrated Circuits Conference, © 2011, Oct. 2011, Manchester, UK, pp. 180-183. |
Cunha, Telmo R. et al., “Characterizing Power Amplifier Static AM/PM with Spectrum Analyzer Measurements”, IEEE © 2014, 4 pages. |
Fager, Christian et al., “Prediction of Smart Antenna Transmitter Characteristics Using a New Behavioral Modeling Approach” IEEE® 2014, 4 pages. |
Fager, Christian et al., “Analysis of Nonlinear Distortion in Phased Array Transmitters” 2017 International Workshop on Integrated Nonlinear Microwave and Millmetre-Wave Circuits (INMMiC), Apr. 20-21, 2017, Graz, Austria, 4 pages. |
Martens, J. et al., “Towards Faster, Swept, Time-Coherent Transient Network Analyzer Measurements” 86th ARFTG Conf. Dig., Dec. 2015, 4 pages. |
Martens, J., “Match correction and linearity effects on wide-bandwidth modulated AM-AM and AM-PM measurements” 2016 EuMW Conf. Dig., Oct. 2016, 4 pages. |
Nopchinda, Dhecha et al., “Emulation of Array Coupling Influence on RF Power Amplifiers in a Measurement Setup”, IEEE © 2016, 4 pages. |
Pedro, Jose Carlos et al., “On the Use of Multitone Techniques for Assessing RF Components' Intermodulation Distortion”, IEEE Transactions on Microwave Theory and Techniques, vol. 47, No. 12, Dec. 1999, pp. 2393-2402. |
Ribeiro, Diogo C. et al., “D-Parameters: A Novel Framework for Characterization and Behavorial Modeling of Mixed-Signal Systems”, IEEE Transactions on Microwave Theory and Techniques, vol. 63, No. 10, Oct. 2015, pp. 3277-3287. |
Roblin, Patrick, “Nonlinear RF Circuits and Nonlinear Vector Network Analyzers; Interactive Measurement and Design Techniques”, The Cambridge RF and Microwave Engineering Series, Cambridge University Press © 2011, entire book. |
Rusek, Fredrik et al., “Scaling Up MIMO; Opportunities and challenges with very large arrays”, IEEE Signal Processing Magazine, Jan. 2013, pp. 40-60. |
Senic, Damir et al., “Estimating and Reducing Uncertainty in Reverberation-Chamber Characterization at Millimeter-Wave Frequencies”, IEEE Transactions on Antennas and Propagation, vol. 64, No. 7, Jul. 2016, pp. 3130-3140. |
Senic, Damir et al., “Radiated Power Based on Wave Parameters at Millimeter-wave Frequencies for Integrated Wireless Devices”, IEEE © 2016, 4 pages. |
Number | Date | Country | |
---|---|---|---|
20170222675 A1 | Aug 2017 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 12258172 | Oct 2008 | US |
Child | 15431671 | US |