第二章. 基本通信原理实验内容



Principles of Communications

M-sequence Source & AWGN Channel

Aim of the Project

1. Generate AWGN channel and add them to the digital communication simulation system to observe the impact of SNR change on bit error rate.

2. Generate M-sequence as the source of the digital communication system.

Requirement of the Project

1. This project requires two students to work as a team. In case a team cannot be formed, one student working alone is also acceptable.

2. You must submit the electronic copy of lab report. The report should consist of answer to all the questions, simulation results, analysis and discussion.

3. Send the final project report to the TA’s email address with the subject “Lab x” .

Contents of the Project

Summary

In this part of the lab, you will build two basic components, that is the M-sequence as the source of the digital communication system and AWGN channel, of the SDR that you will be designing throughout the labs. And program to verify the properties of n-order m-sequence.

3. AWGN Channel

Communication channel provides connection between transmitter and receiver. One common problem of signal transmission through any channel is additive noise, so the basic channel model established during channel simulation is AWGN channel model. The complex gaussian white noise signal can be generated according to gaussian white noise power (dB) with related VI called in LabVIEW library.

Replace the channel.vi module in tranmitter_apply_channel.vi with the generated channel model.

Table 1 Channel.vi

|Channel.vi - |

|Inputs |modulation parameters in |cluster | |

| |Channel model parameters |cluster | |

| |input complex waveform |IQ waveform cluster |From make_MT_wave.vi in |

| | | |tranmitter_apply_channel.vi，3 |

| | | |components：Y(1D array of CDB), |

| | | |dt(DBL), t0(DBL) |

|Outputs |output complex waveform |IQ waveform cluster | |

| |actual delay(sec) |DBL |Channel delay |

4. Random Numbers (Sequences)

In computer algorithms, pseudo-random numbers (sequences) are usually used to replace (true) random numbers for ease of implementation. Pseudo-random sequence is a numerical sequence with periodicity. When the period N is relatively large, the statistical property approximates the random sequence to some extent, so the effect is similar to (true) random number. In the following sections of the course, there is no strict distinction between pseudo random numbers (sequences) and true random numbers (sequences)..

High-level programming languages have ready-made functions for generating uniformly distributed RANDOM Numbers, such as C language containing RANDOM (N) function, which is used to generate a uniformly distributed pseudo-random number (sequence) that meets the statistical requirements between 0 and n-1. And the "random number (0-1) function" in the library of LabVIEW language can produce uniformly distributed double-precision floating-point numbers between 0-1. In this experiment, we can use this method to obtain a uniformly distributed random sequence.

5. M-sequence and its characteristics

Pseudo-random sequences have some statistical characteristics of random sequences, but they are easy to generate and process repeatedly. To date, the most widely known binary pseudo-random sequence is the maximum length shift register sequence, or M- sequence. Its cycle length is [pic]. It can be generated by n-stage linear feedback shift register. In LabVIEW, the MT Generate Bits VI module in its additional communication toolkit can be used to generate pseudo-random sequences of different generation modes. In this experiment, we can use this VI to obtain pseudo-random sequence.

M-sequence has several interesting properties and statistical properties.

1) The period of m sequence with n order is [pic]

2) In a cycle, "0" appears [pic] and "1" appears [pic]

3) In a cycle, there are [pic] runs.

There are [pic] of length k, one ”0“ run of length n-1, and one “1” run of length n.

4) The normalized autocorrelation function is

[pic]

The period of [pic] is P.

You are required to generate n order (n=3~8) m-sequences. Analyze and verify the properities.

6. Source generator

Generate 9-order m-sequence using LabVIEW library function to replace the source.vi module in the simulation system.

Table 2 Source.vi

|Source.vi – generates 9-order m-sequence |

|Input |modulation parameters in |cluster | |

|Outputs |output bitstream |Array of U8 (unsigned byetes) |random bit sequence |

| | | |(array of |

| | | |unsigned bytes taking |

| | | |value 0 |

| | | |or 1) |

| |modulation parameters out |cluster | |

Turn In

Submit your implementation of all the VIs. Remember, you will be penalized if you do not wire the error cluster inputs and outputs in your code.

Note: If you need to generate additional subVIs for this or any future labs, please submit these subVIs along with your other VIs.

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