pre6GSymbolDemodulate

R2026b

Pre-6G symbol demodulation

Since R2026b

Syntax

cw = pre6GSymbolDemodulate(ch,sym,nVar)

Description

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

cw = pre6GSymbolDemodulate(ch,sym,nVar) demodulates complex symbols to soft bits (log-likelihood ratios) for 6G research and prototyping. The function uses the modulation scheme specified by ch and the noise variance nVar.

Examples

Demodulate Pre-6G Symbols

Create a physical channel configuration object with QPSK modulation.

ch = pre6GPhysicalChannelConfig(Modulation="QPSK");

Generate random QPSK symbols for a batch size of three and add noise.

txBits = randi([0 1],200,3,"int8");
sym = pre6GSymbolModulate(ch,txBits);
[rxSym,nVar] = awgn(sym,5);

Demodulate to soft bits. Verify the output length and calculate the bit error rate.

cw = pre6GSymbolDemodulate(ch,rxSym,nVar);
isequal(length(cw),length(txBits))

ans = logical
   1

hardBits = cw < 0;
ber = sum(hardBits ~= txBits)/length(txBits)

ber = 1×3

    0.0300    0.0400    0.0200

Input Arguments

ch — Physical channel configuration parameters

pre6GPhysicalChannelConfig object

Physical channel configuration parameters, specified as a pre6GPhysicalChannelConfig object. This function uses only the Modulation, Constellation, and Qm properties of the pre6GPhysicalChannelConfig object.

sym — Received symbols to demodulate

complex matrix

Received symbols to demodulate, specified as a complex matrix of size N_sym-by-B, where N_sym is the number of symbols and B is the batch size.

Data Types: single | double
Complex Number Support: Yes

nVar — Noise variance

nonnegative scalar | nonnegative real matrix

Noise variance, specified as a nonnegative scalar or a nonnegative real matrix of the same size as symbols. This value scales the soft-bit output. When specified as a scalar, the same noise variance applies to all symbols.

Data Types: single | double

Output Arguments

cw — Demodulated soft bits

real matrix

Demodulated soft bits, returned as a real matrix of size (N_sym × Q_m)-by-B, where N_sym is the number of input symbols, Q_m is the modulation order, and B is the batch size. Values are log-likelihood ratios (LLRs).

Data Types: single | double

Extended Capabilities

GPU Arrays

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

The pre6GSymbolDemodulate 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