Alamouti Coding Scheme Implementation

Main function Alamouti(Nr, max_snr, max_err_symbol, symbol_per_frame) implements the Alamouti space-time coding scheme with the following components: QpskMapping(psudo_bit_sequence) - converts binary data to QPSK modulated symbols; RayleighCH(Nr, Nt) - simulates Rayleigh fading channel characteristics. Example usage: Alamouti(1, 12, 20, 24). Key parameters: 2 transmit antennas and 1 receive antenna configuration, SNR range from 0dB to 12dB, simulation stops when symbol errors exceed 20 at each SNR point, with 24 QPSK symbols per frame.

Converting LaTeX Symbols to Images in MATLAB

Transforming LaTeX symbols into images within MATLAB and displaying them on current figures. This functionality provides exceptional convenience for handling images containing extensive LaTeX symbols in MATLAB workflows, offering automated rendering through built-in functions.

Comparison of System Configurations Achieving 3 Bits per Symbol in Spatial Modulation (SM) Systems

When achieving 3 bits per symbol (i.e., 3 bit/s/Hz spectral efficiency) in Spatial Modulation (SM) systems, we compare two configurations: 4 transmit antennas with BPSK modulation versus 2 transmit antennas with 4-QAM modulation. This analysis includes implementation considerations such as antenna indexing, constellation mapping, and spectral efficiency calculations.

Soft Decision Decoding vs. Hard Decision Decoding with Viterbi Algorithm

This study compares the performance of soft decision decoding (SDD) and hard decision decoding (HDD) when symbols propagate through an AWGN channel. The frame error rate (FER) decreases logarithmically as error frames reduce, demonstrating SDD's superiority over HDD which yields higher penalties. The implementation employs Viterbi decoding algorithm with branch metric calculations adapted for both hard and soft quantization schemes.