pre6GLayerMap

R2026b

Pre-6G layer mapping

Since R2026b

Syntax

mapped = pre6GLayerMap(ch,sym)

Description

Add-On Required: This feature requires the 6G Exploration Library for 5G Toolbox add-on.

mapped = pre6GLayerMap(ch,sym) maps modulated symbols to transmission layers for 6G research and prototyping. The function distributes symbols across the number of layers specified by ch.

Examples

Map Pre-6G Symbols to Layers

Create a physical channel configuration object with two layers.

ch = pre6GPhysicalChannelConfig(Modulation="QPSK",NumLayers=2);

Generate random bits and modulated symbols for them.

bits = randi([0 1],480,3,"int8");
sym = pre6GSymbolModulate(ch,bits);

Map symbols to layers.

mapped = pre6GLayerMap(ch,sym);

Verify the output dimensions.

size(mapped)

ans = 1×3

    120    2    3

Input Arguments

ch — Physical channel configuration parameters

pre6GPhysicalChannelConfig object

Physical channel configuration parameters, specified as a pre6GPhysicalChannelConfig object. This function uses only the NumLayers property of the pre6GPhysicalChannelConfig object.

sym — Modulated symbols

complex matrix | dlarray object

Modulated symbols, specified as a numeric matrix of size N-by-B or a dlarray object. N is the total number of symbols and B is the batch size. N must be a multiple of NumLayers.

Data Types: single | double
Complex Number Support: Yes

Output Arguments

mapped — Layer-mapped symbols

complex 3-D array | dlarray object

Layer-mapped symbols, returned as a complex 3-D array of size (N / ν)-by-ν-by-B, or, if sym is a dlarray, as a dlarray object. N is the total number of input symbols, ν is NumLayers, and B is the batch size. Each column corresponds to one transmission layer.

Data Types: single | double
Complex Number Support: Yes

More About

dlarray Support

The pre6GLayerMap object supports an input signal represented in a dlarray (Deep Learning Toolbox). When you specify the input sym as a dlarray object, the function returns the output mapped as a dlarray object.

Extended Capabilities

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

The pre6GLayerMap function fully supports GPU arrays. To run the function on a GPU, specify the input data as a gpuArray (Parallel Computing Toolbox). For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

Version History

Introduced in R2026b