ITU-R SM 1600-2-2015 Technical identification of digital signals《数据信号的技术识别》.pdf

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1、 Recommendation ITU-R SM.1600-2 (08/2015) Technical identification of digital signals SM Series Spectrum management ii Rec. ITU-R SM.1600-2 Foreword The role of the Radiocommunication Sector is to ensure the rational, equitable, efficient and economical use of the radio-frequency spectrum by all rad

2、iocommunication services, including satellite services, and carry out studies without limit of frequency range on the basis of which Recommendations are adopted. The regulatory and policy functions of the Radiocommunication Sector are performed by World and Regional Radiocommunication Conferences an

3、d Radiocommunication Assemblies supported by Study Groups. Policy on Intellectual Property Right (IPR) ITU-R policy on IPR is described in the Common Patent Policy for ITU-T/ITU-R/ISO/IEC referenced in Annex 1 of Resolution ITU-R 1. Forms to be used for the submission of patent statements and licens

4、ing declarations by patent holders are available from http:/www.itu.int/ITU-R/go/patents/en where the Guidelines for Implementation of the Common Patent Policy for ITU-T/ITU-R/ISO/IEC and the ITU-R patent information database can also be found. Series of ITU-R Recommendations (Also available online

5、at http:/www.itu.int/publ/R-REC/en) Series Title BO Satellite delivery BR Recording for production, archival and play-out; film for television BS Broadcasting service (sound) BT Broadcasting service (television) F Fixed service M Mobile, radiodetermination, amateur and related satellite services P R

6、adiowave propagation RA Radio astronomy RS Remote sensing systems S Fixed-satellite service SA Space applications and meteorology SF Frequency sharing and coordination between fixed-satellite and fixed service systems SM Spectrum management SNG Satellite news gathering TF Time signals and frequency

7、standards emissions V Vocabulary and related subjects Note: This ITU-R Recommendation was approved in English under the procedure detailed in Resolution ITU-R 1. Electronic Publication Geneva, 2015 ITU 2015 All rights reserved. No part of this publication may be reproduced, by any means whatsoever,

8、without written permission of ITU. Rec. ITU-R SM.1600-2 1 RECOMMENDATION ITU-R SM.1600-2 Technical identification of digital signals (2002-2012-2015) Scope This Recommendation describes process, methods and tools for technical identification of digital signals. It provides comparison of methods and

9、tools and recommends application for different use cases. It does not provide in-depth explanation of the algorithms or design features of the hardware or software tools. It should be noted that the usability of this Recommendation is not limited to signals referred to as examples such as in Fig. 7.

10、 Keywords Signal identification, signal analysis, digital signals Related ITU Reports Report ITU-R SM.2304 NOTE In every case the latest edition of the Report in force should be used. The ITU Radiocommunication Assembly, considering a) that the use of radio grows steadily; b) that digital signals ar

11、e being widely used; c) that an increasingly large number of devices can be used without a licence or certification process, making it difficult for an administration to identify the source of an emission; d) that sharing of the same spectrum by several radiocommunication technologies is an emerging

12、 trend; e) that the interference complaints involving digital emissions are often difficult to resolve; f) that technical identification often is an essential prerequisite to any measurement on digital signals with complex waveforms as used in many digital communication systems; g) that signal datab

13、ases are available which can associate modern digital signals with their respective external and internal parameters; h) that new analysis and identification tools and techniques are available, that can lead to recognition of the nature of an unknown signal or to complete identification of modern di

14、gital standards, recommends 1 that digital signals should be identified in the following order: general identification process based on signal external characteristics; identification based on the signal internal characteristics (modulation type and other internal waveform parameters) when low/parti

15、al a priori knowledge is available about the signal; identification based on correlation with known waveform characteristics when strong a priori knowledge is available about the signal; 2 Rec. ITU-R SM.1600-2 identification confirmed by signal demodulation, decoding and comparison with known wavefo

16、rm characteristics, 2 that the processes described in Annex 1 be followed. Annex 1 Introduction This Annex describes steps designed to be used either stand-alone or together in sequence to identify a digital signal of interest. The information is intended to provide fundamental, practical and logica

17、l advice on the handling of standard modern digital signals. The text addresses the use of external signal parameters, offers advice on the analysis of internal signal parameters to more completely classify the signal; and describes the use of software tools and techniques to positively identify a s

18、tandard modern digital signal. While some modern spectrum analysers have the capability to characterize signals, many do not have the capability of preserving and providing the in-phase and quadrature (I/Q) signal data that are useful for more advanced analysis of signal internals. While the focus o

19、f this Annex is on Vector signal analysers and Monitoring receivers, spectrum analysers possessing signal analysis features may in some cases be used as well. Definitions Standard modern digital signals: These signals typically include the following modulation schemes and multiple access formats: Am

20、plitude, phase and frequency shift keyed (ASK, PSK, FSK) including Minimum shift keyed (MSK). Quadrature amplitude modulation (QAM). Orthogonal frequency division multiplexed (OFDM). Time division multiple access (TDMA). Code division multiple access (CDMA). (Coded) Orthogonal frequency division mul

21、tiplex (Access) (C)OFDM(A). Single carrier frequency division multiple access (SC-FDMA). Single carrier frequency domain equalization (SC-FDE). Signal identification systems and software: This is a class of system or software that can provide positive identification of a modern digital signal by cor

22、relating the signal waveform to a library of known patterns such as pre-amble, mid-amble, guard time, synchronization word, synchronization tones, training sequences, pilot symbols and codes, scrambling codes and by correlating the demodulated or decoded signal to a library of known patterns such as

23、 signalling data in broadcast channels. I/Q signal data: I/Q refers to in-phase and quadrature signal data. The I/Q data resulting from sampling of a signal allows all of the amplitude, frequency and phase information contained in the signal to be preserved. This allows the signal to be accurately a

24、nalysed or demodulated in different ways, and is a common method of detailed signal analysis. Modulation recognition software: This is software that can operate on raw I/Q or audio demodulated recordings and estimate signal characteristics that include: Centre frequency and frequency distance betwee

25、n carriers; Signal bandwidth; Rec. ITU-R SM.1600-2 3 Signal duration and inter-pulse duration (when impulsive); Modulation class: single or multiple carrier, linear or non-linear; Modulation format; Symbol rate; Signal-to-noise ratio (SNR)1; Signal specific patterns (such as synchronization/pilot to

26、nes, guard times, guard intervals, frame structure). Vector signal analysers (VSA) and VSA software: Instrument VSAs combine either super-heterodyne technology or direct conversion hardware with high speed Analogue to Digital converters (ADCs) and Digital signal processing (DSP), Field programmable

27、gate arrays (FPGA) or embedded General programmable processors (GPP) to perform fast, high-resolution spectrum measurements, demodulation, and advanced time-domain and spectrum-time-domain analysis. VSAs are especially useful for characterizing complex signals such as burst, transient or digitally m

28、odulated signals used in communications, video and broadcast. They can provide users with the ability to collect raw I/Q data on signals of interest, modulation recognition capabilities and signal identification capabilities such as defined above. VSA software may or may not control a physical recei

29、ver. But, in all cases, it allows the user to analyse raw I/Q data either from a receiver or from files. Further, VSA software typically provides pre-set configurations or signal templates to demodulate and decode standard digital communications formats (listed in section 6). Users can make use of t

30、hese templates to easily validate the format of signal types being analysed to confirm that they match signal characteristics of the type licensed to a frequency band. Users can also add new or modify existing signal formats. Monitoring receiver: A monitoring receiver selects a radio signal from all

31、 the signals intercepted by the antenna to which it is connected, and reproduces at the receiver output the information transmitted by the radio signal, while providing access to measurement of the detailed characteristics of the signal. This is typically accomplished by either: access to intermedia

32、te steps in the signal chain, or in most modern receivers, by recording or providing as an output, the complete amplitude and phase characteristics (usually by sampling and saving the I/Q data). Error vector magnitude: The error vector is the vector difference at a given time between the ideal refer

33、ence signal and the measured signal. Expressed another way, it is the residual noise and distortion remaining after an ideal version of the signal has been stripped away. EVM is the root-mean-square (RMS) value of the error vector over time at the instants of the symbol (or chip) clock transitions.

34、Steps to identify a digital signal 1 Evaluate signal externals The first step in identifying a digital signal is to use the simplest approach. This involves comparing the signals “external” parameters to the Regulators licensed signal database and frequency plan. External signal parameters include:

35、Centre frequency and frequency distance between carriers; Signal bandwidth; Spectral shape; 1 While this is not a common modulation parameter, it is often provided by modulation recognition software. 4 Rec. ITU-R SM.1600-2 Signal duration (when impulsive or intermittent); Frequency shift. Visual ins

36、pection and matching of the signal of interest to the Regulators license database provides a good start to identifying a digital signal of interest. If the signal matches all of the external parameters, chances are high that a correct identification can be made without further analysis. An example o

37、f a Frequency Allocation Table is shown in Table 1. The table provides a general description of the services licensed to operate in the band, the operational parameters, signal bandwidths and channelization. These can all be used to match external signal parameters and make an initial assessment of

38、the identity of the signal of interest. TABLE 1 Sample Frequency Allocation Table By using a spectrum analyser, vector signal analyser or monitoring receiver, the Regulator can determine the signal centre frequency, frequency distance between adjacent carriers and signal bandwidth. The frequency sho

39、uld be checked against the frequency plan to make sure the signal is centred on one of the allocated channels. Also, the signal bandwidth should be checked for compliance with the standards of channelization for the frequency band of interest. Figure 1 shows how display markers can be used to determ

40、ine centre frequency, signal bandwidth and power measured at the receiver input. Rec. ITU-R SM.1600-2 5 FIGURE 1 Sample spectral display with markers S M .16 00 -01 Table 2 provides a comprehensive set of analysis methods that may be employed by the Regulator to detect signals and estimate signal ex

41、ternal parameters. Many signal analysis software packages have the ability to perform mathematic operations on time or spectral data or a series of spectral data. Such packages can be used to make these kinds of estimations of signal external parameters. 6 Rec. ITU-R SM.1600-2 TABLE 2 Manual methods

42、 to detect signals and extract external parameters Parameters to be measured Analysis tools Modulation type Radio environment Presence of a radio-communication signal Cross-correlation of I-Q signal or of instantaneous amplitude Ai with reference signal Any modulation type but especially for known T

43、DMA, CDMA and DSSS signals Any Power spectral density Any modulation type Medium and high SNR Auto-correlation and cyclic auto-correlation OFDM, SC-FDMA, SC-FDE Any Spectrum correlation analysis Unknown DSSS and weak signals Any PRF or burst length Amplitude time analysis of the signal OOK, radar, I

44、FF, other bursted signal Medium and high SNR Carrier frequency Subcarrier frequencies Power spectral density Any modulation type Medium and high SNR Histogram of instantaneous frequency, Fi FSK Medium and high SNR Average of instantaneous frequency, Fi FSK Medium and high SNR Spectrum of I-Q signal

45、raised to power N (=M(MPSK), 4 (QAM) or 1/h for CPM) PSK, QAM, CPM Positive SNR Spectrum correlation analysis Any linear modulation, and especially ASK, BPSK, QPSK. Any The spectrum of signal module raised to power 2 or 4 with severe filtering Pi/2DBPSK, pi/4DQPSK, SQPSK Positive SNR Any Emission ba

46、ndwidth and channelization Power spectral density compared with mask or limit line function Any modulation type Medium and high SNR Frequency distance between subcarriers (Shift for FSK) Power spectral density. Harmonic search and/or harmonic markers FSK, OFDM, COFDM Medium and high SNR Histogram of

47、 instantaneous frequency, Fi FSK Medium and high SNR Rec. ITU-R SM.1600-2 7 Spectral Shape: Another method of signal identification using signal externals is to evaluate the spectral shape or signature. Most VSA software programs have a demonstration library of standard modern digital signals. These

48、 demonstrations enable the Regulator to view the signal external (and in some cases the internal) parameters including spectral shape, duration and others. Some emissions have a feature that is unique to the type of transmission, for example a pilot tone. Some digital high definition television tran

49、smissions can have a pilot signal located on the low frequency side of the signal. The display shown in Fig. 2 depicts a television transmission (U.S. Channel 60, 749 MHz) using the ATSC system. Notice the lower left-hand trace and the unique shape of the spectrum with the presence of the pilot signal. This shape, combined with the centre frequency and signal bandwidth, provides a strong indication of the type of transmission. FIGURE 2 VSA display illustrating a unique spectral shape S M .16 00 -02 If further information about the