WO2010138006A1

WO2010138006A1 - Method and system for training sequence synchronization in a digital communication network

Info

Publication number: WO2010138006A1
Application number: PCT/PL2009/000058
Authority: WO
Inventors: Dariusz J. Lisik; Jacek S. Majerczyk; Mariusz R. Wawrowski
Original assignee: Motorola, Inc
Priority date: 2009-05-29
Filing date: 2009-05-29
Publication date: 2010-12-02
Also published as: GB201120883D0; GB2483189B; GB2483189A

Abstract

A pre-selection technique selects a group of samples (a sub-window) from received modulated signal. An Integral signal is computed from the sampled modulated signal and then used to speed up a Haar signal computation. The computed Haar signal is used to classify the sampled modulated signal for the presence or absence of a training sequence in the sub-window. Additional cascaded classifier stages are applied after positive classification indicating the presence of a training sequence in the sub-window. Once the last pre- classification has been completed, a cross-correlation function is computed on the sub-window. The results of the computed cross-correlation are compared to a cross-correlation threshold. Negative results indicate the lack of a training sequence and a return to select another sub-window. Positive classification indicates an optimum training sequence position to use for synchronization of a receiver.

Description

METHOD AND SYSTEM FOR TRAINING SEQUENCE SYNCHRONIZATION IN A DIGITAL COMMUNICATION NETWORK

FIELD OF THE DISCLOSURE

[0001] The present invention relates generally to digital communication networks, and in particular to synchronization of training sequences for modulated signals being received by a digital communication receiver.

BACKGROUND

[0002] The transmission and reception of communication signals between components of a communication system is of paramount importance in the overall operation of the system in terms of synchronization, information transfer and current drain. When information is transferred over a radio channel, the transmitted signal must be modulated. Modulation is required so that the signal can be transmitted over a radio frequency channel. Ideally, the modulation should enable the largest possible amount of information to be transferred on the narrowest possible frequency band. An example of a modulation method is π/4- DQPSK (π/4-shifted, Differential Quaternary Phase Shift Keying).

[0003] When a signal is received, the received signal has to be demodulated. Demodulation involves the use of a detector to determine the information from the modulated signal. Data detectors used in receivers, such as those used in TErestrial Trunked RAdio (TETRA), Global System for Mobile (GSM), APCO P25, Universal Mobile Telecommunication Service (UMTS), digital TV systems and many others, typically rely on correlating a received signal burst with a known pattern in the received sequence. This known pattern or sequence is often referred to as a Training Sequence (TS) that is embedded within a portion of the burst. [0004] A Digital Signal Processor (DSP), in conjunction with other processing resources, controls the techniques for sampling and detecting the training sequence within the received signal. The type of DSP technology, such as field programmable gate array (FPGA) technology, used in the implementation of the sampling and detection technique impacts the usage of resources (micro- cells). While advances in DSP technology and processing techniques have enabled improvements in training sequence detection and correlating techniques, the use of increasingly complex modulation techniques and communication protocols have dramatically increased processing loads on DSPs/FPGAs and other processing resources. The additional computational capabilities thus come at the cost of battery life and resource usage particularly when working with portable communications equipment.

[0005] As an example, cross-correlation generally refers to an integral of the product of two signals, which indicates how well the signals correspond. Hence, the sampling moment of the received signal producing the maximum cross- correlation value is the ideal sampling moment and synchronization is carried out accordingly in a known manner. For a device operating within the TETRA standard, which uses π/4-DQPSK modulation, cross-correlation can be computed on an up-sampled signal (10 samples per symbol). The burst of 510 bits (2 bits per symbol) have length of M = 10 * (510/2 - 1) = 2540 samples per burst. Synchronization Training Sequence of 38 bits (2 bits per symbol) have length of N= 10 * (38/2 - 1) = 180 samples per training sequence. The cost of searching synchronization sequence in the whole burst using cross-correlation method is T =M*N = 457,200 Multiply and Accumulate (MAC) operations on complex numbers. Thus, the computational cost in terms of time is also of concern.

[0006] Accordingly, it would be desirable to an improved technique for detecting a training sequence in a received signal. BRIEF DESCRIPTION OF THE FIGURES

[0007] The accompanying figures, where like reference numerals refer to identical or functionally similar elements throughout the separate views, together with the detailed description below, are incorporated in and form part of the specification, and serve to further illustrate embodiments of concepts that include the claimed invention, and explain various principles and advantages of those embodiments.

[0008] FIG. 1 is a block diagram depicting an exemplary communications unit and an input signal burst in accordance with some embodiments.

[0009] FIG. 2 is a block diagram depicting components of the exemplary communications unit in accordance with some embodiments.

[0010] FIG. 3 is a flowchart depicting a method for training sequence detection and synchronization in accordance with some embodiments.

[0011] Skilled artisans will appreciate that elements in the figures are illustrated for simplicity and clarity and have not necessarily been drawn to scale. For example, the dimensions of some of the elements in the figures may be exaggerated relative to other elements to help to improve understanding of embodiments of the present invention.

[0012] The apparatus and method components have been represented where appropriate by conventional symbols in the drawings, showing only those specific details that are pertinent to understanding the embodiments of the present invention so as not to obscure the disclosure with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein. DETAILED DESCRIPTION

[0013] Briefly, the present disclosure concerns the reception of signals at a wireless communications device such as a portable handheld radio or mobile vehicular adapted radio, and the like and a method and apparatus for detecting a training sequence to provide improve synchronization of the incoming signal.

[0014] It will be appreciated that detecting a training sequence and otherwise processing the training sequence for improved synchronization may be performed in a dedicated device such as a receiver having a dedicated processor, a processor coupled to an analog processing circuit or receiver analog "front-end" with appropriate software for performing a receiver function, an application specific integrated circuit (ASIC), a digital signal processor (DSP), or the like, or various combinations thereof, as would be appreciated by one of ordinary skill. Memory devices may further be provisioned with routines and algorithms for operating on the training sequence.

[0015] It will further be appreciated that wireless communications units may refer to subscriber devices such as, two-way radios, messaging devices, cellular or mobile phones, personal digital assistants, personal assignment pads, personal computers equipped for wireless operation, a cellular handset or device, or the like, or equivalents thereof provided such units are arranged and constructed for operation in accordance with the various inventive concepts and principles embodied in exemplary receivers, and methods for detecting a training sequence.

[0016] The principles and concepts discussed and described may be particularly applicable to receivers and associated communication units, devices, and systems providing or facilitating voice communications services or data or messaging services over wide area networks (WANs), such as conventional two way systems and devices, various cellular phone systems including analog and digital cellular, CDMA (code division multiple access) and variants thereof, TETRA (TErestrial Trunked RAdio), GSM (Global System for Mobile Communications), GPRS (General Packet Radio System), 2.5 G and 3G systems such as UMTS (Universal Mobile Telecommunication Service) systems, integrated digital enhanced networks and variants or evolutions thereof.

[0017] Principles and concepts described herein may further be applied in devices or systems with short range communications capability normally referred to as W-LAN capabilities, such as IEEE 802.11, Bluetooth, or Hiper-LAN and the like that preferably utilize CDMA, frequency hopping, orthogonal frequency division multiplexing, or TDMA access technologies and one or more of various networking protocols, such as those associated with physical and link layers (e.g. Ethernet), BIOS (Network Basic Input Output System) or other protocol structures.

[0018] Referring to FIG. 1, a simplified and representative diagram of exemplary scenario 100 having communication unit 1 10, signal 120, and wireless channel or air interface 121, are shown. Exemplary signal 120, as noted above, is preferably a TETRA modulated signal transmitted in a burst, and may further include preambles and postambles, or tails 122 at each end thereof, and data section 124, which includes a training sequence known, a priori, to be described in greater detail hereinafter. The burst is a structure which is transmitted in one time division multiple access (TDMA) time slot or sub-time slot. The training sequence is a predetermined bit sequence that is stored in the memory of a receiver such that a training sequence of the received signal can be compared with the stored training sequence. The training sequence is used for synchronizing the reception .

[0019] To provide a better understanding of the operating environment in accordance with various exemplary and alternative exemplary embodiments, a more detailed block diagram of exemplary communication unit 110 is shown in FIG. 2. Therein, communication unit 110 is shown to include a receive section 112 which may be an analog front end or the like, for processing raw incoming baseband signals, for example, from antenna 116, and providing conditioned signals such as digital signals, I and Q or in-phase and quadrature components, real and imaginary components, or the like to other sections or devices by way of interconnection 114 which may be a signal path, bus, or the like. It will further be appreciated that various functions such as analog-to-digital conversion or other conditioning, decoding, or the like, of the incoming signal or samples representative thereof may be allocated in one or several sections within communication unit 110. Further, various inputs and outputs may be generated relevant to a user, which inputs and outputs may be sent and received from user interface 115. Power is provided to the communication unit 110 via a battery 118, the battery 118 being coupled to the device in the portable environment or adapted to the device within the vehicular environment.

[0020] The exemplary receiver shown in FIG. 2, further includes processor 111 having memory 113 associated therewith. It will be appreciated that memory

113 may be an internal memory, an external memory, or the like as would be known by one of ordinary skill and sufficiently matched, for example, to the speed and other performance related characteristics of processor 1 1 1, receive section 112, bus 114 and other devices within communication unit 110 to enable useful storage of and access to programs, data, instructions, or the like associated with receiver operation in accordance with various embodiments.

[0021] In accordance with some embodiments and continuing to refer to FIGs. 1 and 2, a modulated RF signal is received by communication unit 110 at antenna 116 and receive section 112. Controller 111 utilizes a pre-selection technique to sample the received modulated signal and select a group of samples. The group of samples is also referred to as a sub-window. The computation of an Integral Signal (IS) at index "n" equals the sum of all samples of the modulated signal from the beginning of the signal to index n, i.e. IS(n) = S(l)+S(2)+...+S(n), where IS is the Integral Signal and S is the sampled modulated signal. [0022] The Integral Signal is used as an intermediate signal representation to speed up the computation of a Haar signal using a Haar function or other rectangular function. The Haar function H(x) is described by its parameters a, b, c (relative to the beginning of tested sub-window) and following equations: H(x) = 1 for a < x <= b H(x) = -1 for b < x <= c H(x) = 0 otherwise.

The Haar signal HS at index "n" is represented by HS(n). The Haar signal is computed as a sum of products of the modulated signal samples S by Haar function H shifted in the domain by "n", i.e.

HS(n) = Sum[H(x)*S(n+x)] where x is an element of the set of natural numbers.

Using the Integral Signal, the Haar signal can be computed very effectively, e.g.

HS(n) = (IS(n+b) - IS(n+a)) - (IS(n+c) - IS(n+b)) where a, b, and c are parameters of Haar function (described above).

[0023] The computed Haar signal is subjected to a pre-selection classification which classifies based on the presence or absence of a training sequence in the sub-window of the sampled modulated signal. Additional, cascaded classifier stages can be applied only after positive classification indicating the presence of a training sequence in the sub-window.

[0024] Once the last pre-classification has been completed, a cross- correlation function is computed on the sub- window of the sampled modulated signal. The results of the computed cross-correlation are compared to a cross- correlation threshold. Negative results indicate the lack of a training sequence in the sampled modulated signal and a return to await another modulated signal sample. Positive classification from the cross-correlation indicates an optimum training sequence position in the sampled modulated signal to use for synchronization of the receiver section 112.

[0025] The trainings sequence detection provided by communication unit 110 can be applied to various types of modulated signals. For example, when the sampled modulated signal is a differential modulated signal, the classification may be implemented by comparing the modulus of the computed Haar signal with the upper and lower Haar thresholds. Alternatively, when the sampled modulated signal is a non- differential modulated signal, classification may be implemented by comparing the amplitude of the computed Haar signal to upper and lower Haar thresholds.

[0026] An exemplary approach to a training sequence detection technique operating in accordance is shown in FIG. 3. In accordance with various embodiments, technique 300 begins with a set up step 302 in which Haar functions (1 to N) are chosen and Haar thresholds (1 to N) are selected as well as a cross-correlation threshold. At 304 the receiver waits to receive a modulated signal sample from which to select a group of samples (sub-window). Each sub- window thus provides a group of samples selected from the sampled modulated signal to classify for the positive or negative presence of a training sequence.

[0027] An Integral Signal computation is performed at 306 and a first Haar signal computation is performed using the Integral Signal and the first Haar function at the first operation 308. The first computed Haar signal is then subjected to a first pre-selection operation to determine whether positive or negative classification occurs 310. A negative classification represents the absence of a training sequence in the computed Haar signal which results in a return to 304 to await another modulated signal sample. A positive classification indicates the presence of a training sequence in a sub-window of the first computed Haar signal. A positive classification allows the technique to move to the next Haar signal computation at pre-selection operation 312 and the next Haar signal threshold classification 314. The pre-selection operation and pre-selection classification is continued for the number of classifiers (Haar functions and Haar thresholds) selected (1 to N).

[0028] A cascade of classifiers, such as wavelet classifiers or the like can be used to implement the pre-selection classification step. Each classifier tests statistical characteristics of the Haar signal, provided by the Haar function, against a predetermined Haar threshold. The predetermined Haar threshold comprises upper and lower Haar thresholds selected to match characteristics of the training sequence. Hence, classification of the computed Haar signal is made according to the upper and lower Haar thresholds to detect the presence or absence of a training sequence in a sub-window of the sampled modulated signal. Upper and lower Haar thresholds can be selected to optimize a False Acceptance Rate (FAR) while maintaining a predetermined False Rejection Rate (FRR) of the pre-selection technique.

[0029] Once the last pre-selection classification has been made at 314, a cross-correlation is performed at 316 on the sub-window of the sampled modulated signal that passed all the previous classification tests with positive results. The results of the computed cross-correlation are then compared to the cross-correlation threshold at 318 for cross-correlation classification. Negative results mean the lack of a training sequence in the sampled modulated signal and a return to step 304 to await another modulated signal sample. Positive cross- correlation classification indicates the presence of a training sequence within the sampled modulated signal and generates a positive result 320 indicating an optimum training sequence position to use for synchronization of the receiver.

[0030] Accordingly, there has been provided a pre-selection technique which is performed based on Haar functions in conjunction with an Integral Signal to speed up computations. The use of the Integral Signal adds only one additional operation per new sample while highly optimize the computation of the Haar signals. A cascade of classifiers is used for pre-selection classification of sub- windows of the sampled signal to indicate the presence or absence of a training sequence. At each stage of the cascaded classifiers further processing is possible only after positive classification of a sub-window, a positive classification indicating the presence of a training sequence within predetermined thresholds. Each classifier tests statistical characteristics of the signal, provided by the Haar function, against a predetermined Haar threshold. The predetermined Haar threshold comprises upper and lower Haar thresholds selected to match characteristics of the training sequence. Hence, classification of the computed Haar signal is made according to the upper and lower Haar thresholds to detect the presence or absence of a training sequence in a sub-window of the sampled modulated signal.

[0031] The training sequence synchronization technique operating in accordance with the various embodiments provides a means with which to speed up the detection of a training sequence while using substantially fewer signal processing resources than conventional correlation. The use of the Integral signal speeds up computation time. Rectangular functions, such as Walsh functions and/or Haar functions can be used to improve classification rate as well as other square/rectangular shaped functions. Computational cost is particularly important to portable terminals (e.g. TETRA portables, cellular phones), and the reduced computational cost provided by the training and synchronization technique lowers power consumption thereby providing the advantage of extended battery life. The computational and power advantages provided by the training sequence synchronization technique have been achieved without detriment to the quality of synchronization. The training and synchronization technique can be applied to a variety of systems in which training sequences are used for synchronization, including but not limited to, TETRA, Apco P25, GSM, and digital TV.

[0032] In the foregoing specification, specific embodiments have been described. However, one of ordinary skill in the art appreciates that various modifications and changes can be made without departing from the scope of the invention as set forth in the claims below. Accordingly, the specification and figures are to be regarded in an illustrative rather than a restrictive sense, and all such modifications are intended to be included within the scope of the present teachings. The benefits, advantages, solutions to problems, and any element(s) that may cause any benefit, advantage, or solution to occur or become more pronounced are not to be construed as critical, required, or essential features or elements of any or all the claims. The invention is defined solely by the appended claims including any amendments made during the pendency of this application and all equivalents of those claims as issued.

[0033] Moreover in this document, relational terms such as first and second, top and bottom, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. The terms "comprises," "comprising," "has", "having," "includes", "including," "contains", "containing" or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises, has, includes, or contains a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element preceded by "comprises a ...", "has a ...", "includes a ...", or "contains a ..." does not, without more constraints, preclude the existence of additional identical elements in the process, method, article, or apparatus that comprises, has, includes, or contains the element. The terms "a" and "an" are defined as one or more unless explicitly stated otherwise herein. The terms "substantially", "essentially", "approximately", "about" or any other version thereof, are defined as being close to as understood by one of ordinary skill in the art, and in one non-limiting embodiment the term is defined to be within 10%, in another embodiment within 5%, in another embodiment within 1% and in another embodiment within 0.5%. The terms "coupled" or "connected" as used herein define a connection that is not necessarily direct but may be indirect. A device or structure that is "configured" in a certain way is configured in at least that way, but may also be configured in ways that are not listed.

[0034] It will be appreciated that some embodiments may be comprised of one or more generic or specialized processors (or "processing devices") such as microprocessors, digital signal processors, customized processors and field programmable gate arrays (FPGAs) and unique stored program instructions (including both software and firmware) that control the one or more processors to implement, in conjunction with certain non-processor circuits, some, most, or all of the functions of the method and system described herein. Alternatively, some or all functions could be implemented by a state machine that has no stored program instructions, or in one or more application specific integrated circuits (ASICs), in which each function or some combinations of certain of the functions are implemented as custom logic. Of course, a combination of the two approaches could be used.

[0035] Moreover, an embodiment can be implemented as a computer- readable storage medium having computer readable code stored thereon for programming a computer (e.g., comprising a processor) to perform a method as described and claimed herein. Examples of such computer-readable storage mediums include, but are not limited to, a hard disk, a CD-ROM, an optical storage device, a magnetic storage device, a ROM (Read Only Memory), a PROM (Programmable Read Only Memory), an EPROM (Erasable Programmable Read Only Memory), an EEPROM (Electrically Erasable Programmable Read Only Memory) and a Flash memory. Further, it is expected that one of ordinary skill, notwithstanding possibly significant effort and many design choices motivated by, for example, available time, current technology, and economic considerations, when guided by the concepts and principles disclosed herein will be readily capable of generating such software instructions and programs and ICs with minimal experimentation.

[0036] The Abstract of the Disclosure is provided to allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in various embodiments for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separately claimed subject matter.

Claims

We claim:

1. A method for detecting a training sequence in a received signal, comprising: receiving a modulated signal at a receiver; processing the modulated signal by: sampling the received modulated signal; computing an Integral Signal from the sampled modulated signal; computing a Haar signal using the Integral signal and a Haar function; classifying the computed Haar signal according to upper and lower Haar thresholds to detect the presence or absence of a training sequence in a sub- window; and repeating to the step of computing the Haar signal using another Haar function and the step of classifying the computed Haar signal according to other upper and lower Haar thresholds in response to positive classification until a predetermined number of Haar functions have been used.

2. The method of claim 1, further comprising: applying a cross-correlation function to the sub-window of the sampled modulated signal to generate a cross-correlation value; classifying the cross-correlation value based on a correlation threshold to detect the presence or absence of a training sequence within the sub-window of the sampled modulated signal; and synchronizing the receiver using a positively classified training sequence resulting from the cross-correlation.

3. The method of claim 1, wherein prior to the step of receiving a modulated signal, a learning set up is performed comprising: selecting a plurality of Haar functions by a processor; setting upper and lower Haar thresholds for each of the plurality of Haar functions, every Haar function corresponding to one pre-selection classifier; and choosing a Haar function from the plurality of Haar functions.

4. The method of claim 3, wherein the upper and lower Haar thresholds are selected to match characteristics of the training sequence.

5. The method of claim 4, wherein the upper and lower thresholds are selected to optimize a False Acceptance Rate (FAR) while maintaining a False Rejection Rate (FRR).

6. The method of claim 1, wherein a rectangular shaped function is used in conjunction with the Haar function.

7. The method of claim 1, wherein the step of comparing further comprises comparing the modulus of the computed Haar signal with the upper and lower Haar thresholds when the modulated signal is a differential modulated signal.

8. The method of claim 1, wherein the step of comparing further comprises comparing the amplitude of the computed Haar signal with the upper and lower Haar thresholds when the received modulated signal is a non- differential modulated signal.

9. The method of claim 7, wherein a positive classification indicates the presence of a training sequence presence in the sub-window and a negative classication represents the absence of a training sequence in the sub- window, and the upper and lower Haar thresholds are selected to detect the presence or absence of a training sequence in the sub-window.

10. The method of claim 8, wherein a positive classification indicates the presence of a training sequence presence in the sub-window and a negative classification represents the absence of a training sequence in the sub-window, and the upper and lower Haar thresholds are selected to detect the presence or absence of a training sequence in the sub-window.

11. A communication device, comprising: a receiver receiving a modulated signal; and a processor providing a cascade of computational and classifier stages with which to detect and classify samples from the received modulated signal for the presence or absence of a training sequence thereby providing pre-classifϊcation of the sampled modulated signal prior to application of a correlation function and synchronization of the receiver.

12. The communication device of claim 11, wherein the cascade of classifier stages are based on rectangular shaped functions.

13. The communication device of claim 12, wherein the rectangular shaped functions comprise one or more of Haar functions or Walsh functions.

14. A method for selecting a sampled signal to use for synchronizing a receiver, comprising: receiving a modulated signal sample; sampling the modulated signal and selecting a groups of samples (sub- window) of the modulated signal sample; computing an Integral Signal from the sampled modulated signal; applying a pre-determined number of Haar functions to the sub-window of the sampled modulated signal in conjunction with utilizing a cascade of classifiers to indicate the presence or absence of a training sequence, a positive classification indicating the presence of a training sequence, and a negative classification indicating the absence of a training sequence; applying a correlation function to the sub-window of the sampled modulated signal that passes all of the Haar classification thresholds; determining the presence or absence of a training sequence within the sub- window using a cross-correlation classification threshold; and using the sampled modulated signal having a training sequence that passes all the predetermined Haar thresholds and the cross-correlation classification threshold to synchronize the receiver.