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Link-Level Simulation

Link-level communications systems simulation and analysis examples

Simulate link-level models of communications systems. Use bit error rate simulations to analyze system response to the noise and interference inherent in communication channels, explore hypothetical scenarios, and evaluate the tradeoffs between competing system architectures and parameters. The physical layer (PHY) processing chain prepares data received from the higher layers for transmission and recovers transmitted data before passing it to the higher layers.

Examples presented in this section demonstrate signal transmission, signal impairment signal by the radio and propagation channel, signal reception, data recovery, and analysis of link performance.

Featured Examples

Indoor MIMO-OFDM Communication Link Using Ray Tracing

Perform ray tracing in an indoor environment and use the results to build a channel model for a link level simulation with the MIMO-OFDM technique.

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RF Satellite Link

Simulate a satellite link that models amplifier impairments by using a Memoryless Nonlinearity block.

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BER Simulations with Parallel Computing Toolbox

Improve the execution speed of communication systems involving BER simulations. To improve the performance of these systems, one of the available options is to parallelize the simulations. This example introduces the usage of the Parallel Computing Toolbox™ in BER simulations. It presents two possible ways of parallelizing BER simulations and recommends the better method.

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QPSK Transmitter and Receiver

Simulate a QPSK transmitter and receiver.

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QPSK Transmitter and Receiver in Simulink

Model a QPSK transmitter and receiver in Simulink^®.

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End-to-End QAM Simulation with RF Impairments and Corrections

Visualization capabilities that show the effects of RF impairments and corrections in a satellite downlink.

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Introduction to MIMO Systems

Model Multiple-Input-Multiple-Output (MIMO) systems that use multiple antennas at the transmitter and receiver ends of a wireless communication system.

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DVB-S.2 Link, Including LDPC Coding in Simulink

The state-of-the-art channel coding scheme used in the second generation Digital Video Broadcasting standard (DVB-S.2), which is deployed by DIRECTV in the United States. The coding scheme is based on concatenation of LDPC (Low-Density Parity-Check) and BCH codes. LDPC codes, invented by Gallager in his seminal doctoral thesis in 1960, can achieve extremely low error rates near channel capacity by using a low-complexity iterative decoding algorithm. The outer BCH codes are used to correct sporadic errors made by the LDPC decoder.

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Estimate BER of QPSK in AWGN with Reed-Solomon Coding

Transmit Reed-Solomon encoded data using QPSK over an AWGN channel. Demodulate and decode the received signal and collect error statistics. Compute the theoretical bit error rate (BER) for coded and noncoded data. Plot the BER results to compare performance.

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Apply OFDM in MIMO Simulation

OFDM in 2-by-2 MIMO simulation.

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Parallel Concatenated Convolutional Coding: Turbo Codes

Characterize the performance of turbo codes over a noisy channel.

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End to End System Simulation Acceleration Using GPUs

A comparison of four techniques which can be used to accelerate bit error rate (BER) simulations using System objects in the MATLAB® Communications Toolbox™ software. A small system, based on convolutional coding, illustrates the effect of code generation using the MATLAB® Coder™ product, parallel loop execution using parfor in the Parallel Computing Toolbox™ product, a combination of code generation and parfor, and GPU-based System objects.

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802.11ac Multiuser MIMO Precoding with WINNER II Channel Model

Transmit and receive processing for a IEEE^® 802.11ac™ multiuser downlink transmission over a WINNER II fading channel.

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OFDM Transmitter and Receiver

Simulate an end-to-end OFDM transmission system for a single-input, single-output (SISO) channel.

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