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AdvDCSM Key Capabilities and Features

      

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•T1 VERSION 1 Key Capabilities and Features

•T1 VERSION 2 (PROFESSIONAL) Key Capabilities and Features

AdvDCSMT1DCSS (T1) Version 1 OUTLINE

The PC Computer-Based software system tool AdvDCSM Digital Communication System Simulator [AdvDCSMT1DCSS (T1)] provides key Digital Communication (Comm) System and Subsystem models and algorithms that can be used to study, evaluate or possibly design Convolutional Channel Codes and Viterbi Algorithm Channel Decoders.

Also, models and algorithms for certain Linear Block Channel Codes and Likelihood (& Syndrome) Channel Decoders are included in T1 for study, evaluation, and design of Block Codes and associated Channel Decoders.

Thus, T1 can be used by a Coding or Information Theorist to focus on developing implementable/practical Coder-Decoder devices that might improve the Reliability of a Digital Comm System, a reduction in the Information Bit Error Rate (BER) of the system.

•T1 has Five Operational Modes

•T1 Capabilities for Operational Modes 1 & 3

•T1 Capabilities for Operational Modes 2 & 4

•T1 Capabilities for Operational Mode 5

•T1's Features/Components/Models

•T1 Supporting Features

T1 has Five Operational Modes:

1) Channel Coded Signaling over a Memoryless or Memory Single Channel or a Parallel MultiChannel;

2) Convolutional Code Finite-State Machine Definition (Code Vectors Generation);

3) UnCoded Signaling over a Memoryless or Memory Single Channel or a Parallel MultiChannel;

4) Markov Source-Convolutional Code Trellis States Generation; and

5) Past Results Review.

T1 Capabilities for Operational Modes 1 and 3 (System Model & Simulate)

T1 is capable of operating in the Channel Coded Signaling Mode (1) that can exist in one of six possible cases. These six cases are as follows:

1) Binary Information Source, Convolutional Coding & Memoryless Channel;

2) Binary Information Source, Convolutional Coding & Memory Channel;

3) Binary Information Source, Convolutional Coding & Parallel MultiChannel;

4) Binary Information Source, Block Coding & Memoryless Channel;

5) Binary Information Source, Block Coding & Memory Channel; and

6) Binary Information Source, Block Coding & Parallel MultiChannel.

Cases 1, 2 and 3 are further partitioned into two possible Configurations that are predicated/based upon the characteristics of the Convolutional Code (CC) and the complexity of the Viterbi Algorithm Channel Decoder. They are as follows:

1) default: b <= 3 CC, Independent and Identically Distributed Source and b <= 2 CC, Markov Source; and

2) alternate: b = 1 CC for both types of Sources.

For the Block Coding Cases (4, 5 and 6) T1 has only one configuration.

Also, T1 is capable of operating in the UnCoded Signaling Mode (3). This Mode can exist in one of three possible cases that are as follows:

1) Binary Information Source & Memoryless Channel;

2) Binary Information Source & Memory Channel; and

3) Binary Information Source & Parallel MultiChannel;

T1 Capabilities for Operational Modes 2 and 4 (SubSystem Model & Analyze)

T1 is capable of operating in the Convolutional Code (CC) Finite-State Machine (FSM) Definition Mode (2) that can exist in one of two possible cases. These cases are as follows:

1) Non-Orthogonal Non-Recursive CC & AWGN Memoryless Channel (Modulator: Signal Vector Space); and

2) Orthogonal Non-Recursive CC.

Case 1 and 2 can exist in the same configurations as in Operational Mode 1.

A CC FSM Plot can be created for 2, 4, 8, or 16 States (& 32 States for Non-Orthogonal, b = 1) cases, saved as a User named output file (.PLT-CCFSM), and accessed via the File 'Open' choice;

T1 is capable of operating in the Markov Source-Convolutional Code Trellis States Generation Mode (4) that can exist in one of two possible configurations. These configurations are as follows:

1) b = 2 CC for Binary Symmetric or 4-States Markov Source; and

2) b = 1 CC for Binary Symmetric or 4-States Markov Source;

T1 Capabilities for Operational Mode 5 (Past Results Review)

T1 is capable of retrieving and displaying a past Results and Statistics Output File so that the User can access easily one of the User's MOST RECENT generated such files (222 Maximum). Note: Older such files are accessible using the File Menu 'Open' item.


T1 provides the following Features/Components/Models:

i) Simulated System Manager:

Digital Communication System Model Visual Builder:

Information (Info) Source, Channel Code, and Binary Coding Channel Category Selection;

Digital Communication System Simulation Progress and Elapsed Time Displayer governed by the Simulated System Clock Display Interval (SS Clk D I) parameter:

User-specified with AutoScale if required to display the progress of the simulated transmission of a sequence of Information Source Bits (e.g. for 1,000,000 Info Bits, set SS Clk D I to 10,000);

User-Specified file name for a simulation's Results and Statistics output file (.txt):

File name can consist of up to & including fifty one (51) characters;

ii) Binary Information Sources:

Independent and Identically Distributed (i.i.d.): Equiprobable and Unequiprobable (User can specify the probability of a '1');

Markov: Binary Symmetric and 4-States (User can Specify State Transition Probabilities);

User-Specified Number of Information Bits: 1,000,000,000 MAX (Initial), with AutoScale increase if required by Matching Channel Code and/or Signaling Channel Throughput Requirements.

iii) Channel Codes:

Non-Recursive Convolutional Codes (b <= 3, bK = 15 MAX Classes; b = 1, bK = 13 MAX Class) including Rate = 1/2, 1/3 Odenwalder Codes;

Best/Optimal Convolutional Codes:

Rate = 1/2 (K = 3,..,13), 1/3 (K = 3,..,13), 1/4 (K = 3,..,8), 1/5 (K = 3,..,8), 1/6 (K = 3,..,8) and

High Rate = 2/3 ({K} = 2,2;..;5,5), 3/4 ({K} = 2,2,2;..;4,4,4) as specified by their Column Vector (CVR) and Binary Tap Weights Representations;

Trellis-Coded Modulation (TCM) Trellis Codes (Parallel Branches) (b = 2 and b = 3) including Rate = 2/4 (K = [2,1]) and Rate = 2/3 (K = [2,1]) examples as specified by their CVR and Binary Tap Weights Representations;

Orthogonal Non-Recursive Convolutional Codes (b = 1, bK = 5) that can only used for Parallel MultiChannel Signaling Systems;

Linear Block Codes (N,L):

Systematic Parity-Check Codes (N = 14 MAX) (Gallager's code structure) including (5,2); (6,3); (7,3), (7,4); (8,4), (8,5); (9,3), (9,4), (9,5); (10,4), (10,5); (11,4), (11,5) codes as specified by the Parity Array of their Generator Matrices in Column Vector Representation (CVR); and

Orthogonal Non-Systematic Parity-Check Codes, L = 6 MAX for Single Channel or L = 5 MAX for Parallel MultiChannel;

Block Code Minimum Distance (dmin) Determination;

Custom Convolutional Code and Systematic Parity-Check Block Code Visual Constructors;

iv) Memoryless Single Channels:

Noiseless, Binary Symmetric Channel (BSC) and Baseband Additive White Gaussian Noise (AWGN) Vector;

Channel Attenuation Model;

Channel Synchronization, Phase Coherency Model:

Coherent and Non-Coherent Signaling and Demodulation;

Actual Coherent Signaling and Demodulation (Phase-Lock Loop Based);

Baseband AWGN 1-D, 2-D or Multi-Dimensional Discrete-Time (DT) Waveform Channels using DT Matched Filter-Based Demodulators;

Linear Filter DT Waveform Channels: 1st-Order or 2nd-Order Polynomial-Based examples, User-Specified 1st-Order, 2nd-Order and 3nd-Order Polynomial-Based Models and Impulse (Unit-Sample Sequence);

Custom Linear Filter Channel Visual Builder/Mapper;

v) Additive White Gaussian Noise (AWGN) Signal Vector Spaces:

Linear Modulations Schemes:

Binary PSK, M-PSK (Phase Shift Keying) M = 4 (QPSK), 8, 16, 32, 64;

2-PAM, M-PAM (Pulse Amplitude Modulation) M = 4, 8, 16, 32, 64;

4-QAM, 16-QAM, 64-QAM (Quadrature Amplitude Modulation): Square Constellation;

Baseband Received or Transmitted Signal-to-Noise Ratio (SNR, dB);

Gray Code Bit-to-M-ary Channel Symbol Converter and User-Specified Bit-to-M-ary Channel Symbol Converter;

Custom Bit-to-M-ary Channel Symbol Converter Visual Builder/Mapper;

Non-Linear Modulation Schemes:

Binary FSK, M-FSK (Frequency Shift Keying) M = 4, 8, 16, 32, 64;

Baseband Received or Transmitted Signal-to-Noise Ratio(SNR, dB);

vi) Memory Channels:

Classic Bursty Channel and Block Interleaver-DeInterleaver;

Vector and DT Waveform Channels:

Gilbert-Elliot Burst Channel with AWGN and Symbol Interleaver-DeInterleaver;

Rayleigh, Rician and Frequency-Selective Fading with AWGN and Diversity-Combiner and Symbol Interleaver-DeInterleaver;

Frequency-Selective Fading Channel Parameter Visual Builder/Mapper;

Real-valued (PAM) and Complex-valued (QAM) AWGN Channel with InterSymbol Interference (ISI) with AWGN: modeled as an Equivalent DT White Noise Transversal Filter;

ISI Channel Models include PAM ISI Transversal Filter examples and User-Specified PAM or QAM DT Transversal Filter models (ISI Length: 1,...,10);

Custom PAM and QAM ISI Channel Visual Builder/Mapper;

Real-valued (PAM) and Complex-valued (QAM) Linear Equalization Filters:

Tap Weights (Coefficients) Optimization is based on Mean-Square-Error Criterion using Analytic, Recursive, and Recursive-Adaptive (Training) Algorithms; and

Linear Equalizer Coefficients' Decision-Directed Tracking Mode Update;

vii) Parallel MultiChannels:

Additive White Gaussian Noise (AWGN) and Crosstalk (XTalk) Parallel MultiChannels with AWGN;

Discrete MultiTone (DMT) Modulation MultiCarrier/MultiChannel (FFT-Based Orthogonal frequency-division multiplexing) with AWGN;

Parallel K-MultiChannel (SubChannel) Types:

Distinct or Identical (Small K); or

Identical (Large K);

K-MultiChannel-Channel Input Symbol Bits Partition Visual Builder/Mappers (Coded Signaling);

K-MultiChannel Signal Vector-to-SubChannel Visual Builder/Mappers (Coded Signaling);

K-MultiChannel Signal Vector Type Mix Visual Builder/Mappers (UnCoded Signaling);

Bit and Power Allocation MultiChannel Parameters: Effective/Average Channel Input Bits per Subchannel Use and "Water Filling" Parameter-to-Noise Ratio VNR, Ev/No;

The MultiChannel can have a flat or Non-flat Frequency Response. The MultiChannel Linear Filter models are the same as in the Single Channel case.

For AWGN MultiChannels, the subchannels can exist as a Set of Linear Filters with Identical Impulse Responses or as a Set of Linear Filters constructed from a Single Linear Filter;

For XTalk MultiChannels, the subchannels can exist as a Set of Linear Filters with Identical Impulse Responses;

For DMT MultiChannels, the MultiChannel can exists as a Single Linear Filter;

Custom Signal Vector-to-SubChannel Impulse Response Visual Builder/Mapper;

Crosstalk Coefficients Visual Builder/Mapper for Distinct or Identical SubChannels;

For XTalk MultiChannels, a fraction of each Subchannel's Transmitter Info Bit Baseband SNR is propagated completely (transmitter to receiver). Each subchannel's fraction is dependent on the amount of crosstalk derived from that subchannel;

Convolutional Coded DMT Systems: combination of Convolutional Code, DMT MultiCarrier/MultiChannel Signaling and Viterbi Algorithm Decoder;

Block Coded DMT Systems: combination of Block Code, DMT MultiCarrier/MultiChannels Signaling and Block Decoder;

viii) ML (Maximum Likelihood) Viterbi Algorithm (VA) Channel Decoders &

MAP (Maximum A Posteriori Probability) Viterbi Algorithm (VA) Channel Decoders;

ix) ML (Maximum Likelihood) Block Code Likelihood Channel Decoders;

MAP (Maximum A Posteriori Probability) Block Code Likelihood Channel Decoders;

ML (Maximum Likelihood) Syndrome Channel Decoders;

x) Destination:

Decoded Information Bit Stream Receiver for Coded Signaling or Demodulated Information Bit Stream Receiver for UnCoded Signaling;

Bit Error Rate (BER)/Bit Error Probability (Pb) Estimate for Coded or UnCoding Signaling.

T1 Supporting Features:

1) Channel Code Capabilities/Configuration:

This feature allows the User to choose one of two possible CC classes (b <= 3; b = 1) or allows the User to observe the Block Codes configuration;

2) Channel Code Construction:

This feature allows the User to add a CC or Block Code to his/her Custom CC or Block Code List. This code will then become available for a Convolutional Code or Block Code Input selection, respectively;

3) Channel Decoder Validation:

This feature allows the User to verify the correct operation of the Viterbi Algorithm Channel Decoder for an Equiprobable i.i.d. Binary Information Source, a Rate = 1/2, K = 3 Odenwalder Convolutional Code (Tap Weights CVR of [3,2,3]) and a given Binary Symmetric Channel (BSC) Output Vector Y Sequence. The 'Resultsvadecodervalidation.txt' file is created to contain the output validity data. This output file is accessible via the File 'Open' choice. A User named plot output file (.PLT-TRELLIS) is accessible via the File 'Open' choice;

4) Simulated System Randomness Processes Validation:

This feature allows the User to observe the Randomness of the Uniform Distributed Random Number Generation or the Gaussian Distributed Random Number Generation via a Serial Correlation Test as shown by a 2-Dimensional Plot. A User named plot output file (.PLT-RN) is accessible via the File 'Open' choice;

5) M-ary Modulation Scheme Validation:

This feature allows the User to verify the Peak Baseband Channel Symbol SNR for an Information Bit Baseband SNR, Eb/N0 and its derived Average Channel Symbol Baseband SNR, Es/N0 for a selected M-QAM (Quadrature Amplitude Modulation) Scheme for a UnCoded Signaling System. The Gray Code Penalty and Peak Gray Penalty is also determined for this selected M-QAM scheme and its associated Bit-Symbol Mapping. A User-named '.txt' file is created to contain the output validity data. This output file is accessible via the File 'Open' choice. A User-named plot output file (.PLT-MQAMSV) is accessible via the File 'Open' choice; and

6) Bit Error Rate (BER)/Bit Error Probability (Pb) Plot Generation:

This feature allows the User to generate a Bit Error Rate (BER) or Bit Error Probability (Pb) versus Information Bit Baseband SNR, Eb/N0 in dB Plot. A BER plot can consist of one (1) to six (6) curves where a curve can consist of three (3) to sixteen (16) data points. These data point SNR dB values are taken from the set of possible SNR dB values [0.0, 60.0] = {s element of Real Numbers | 0.0 <= s <= 60.0}. These data point BER/Pb values are taken from the set of possible BER/Pb values (1.e-10, 1.0) = {p element of Real Numbers | 1.e-10 < p < 1.0}. The User can assign a color to each plot's BER curve from a set of colors (Red, Green, Blue, Yellow, Magenta, & Cyan).

Also, this feature allows the User to add a BER Plot Data to the User's Custom BER Plot Data List. This list, a set of BER Plot Data Files, is indexed via a BER Plot Data MOST RECENT generated File Names (FN) List, 222 File Names Maximum, via a Query. Older BER Plot Data files can be indexed via the same BER Plot FN Query. This BER Plot Data will then become available (via a Data File) for a BER Plot Input selection for BER Plot Edit for generating a revised BER Plot.

The User can create a plot output file (.PLT-BER) for the generated BER Plot. A User-name plot output file (.PLT-BER) is accessible via the File 'Open' choice. If an 'Unexpected file format' error or failure to open, the User can use the BER PLOT EDIT option and appropriate BER Plot Data File to redo the creation of its BER Plot and corresponding .PLT-BER file.

Consult HELP Menu: Bit Error Rate (BER) Plot Generation Guide for BER Plot Generation information.

VIEW a BER PLOT GENERATION EXAMPLE and LEARN more about this feature.

T1 is NOW AVAILABLE as a TRIAL VERSION that will allow you to use T1, a Digital Communication (Information-Theoretic) System Modeling and Simulation software tool, for a Limited Period without Charge and to learn about the valuable utility of T1 in the study, evaluation, and possibly design of certain Complex Digital Communication Systems first hand before purchase. 

      

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