Low-Complexity Huffman Coding-Based Adaptive Spatial Modulation

Abstract

Adaptive spatial modulation (ASM) is a novel technology in multiple-input-multiple-output (MIMO) systems, which dynamically adjusts the modulation order of the transmit antenna based on the constantly changing channel state information (CSI). The combination of ASM and Huffman coding, using the Huffman method, allows for flexible spatial symbols to provide different activation probabilities for the transmit antenna. However, the exhaustive search conducted by Huffman-ASM requires a large number of candidate combinations to identify the optimal modulation combination. This results in high computational complexity and a heavy feedback burden. To address the challenge, this letter proposes a low-complexity algorithm based on the Huffman-ASM scheme. This scheme does not include all candidate combinations in the calculation but directly selects several optimal candidate combinations based on channel gain sorting; therefore, it reduces system complexity and alleviates the burden on the feedback path. The simulation results indicate that, compared to the conventional scheme, the proposed scheme exhibits only a slight decrease in performance while significantly reducing computational complexity.