16-ary Modulation based Uncoded Space-Time Labeling Diversity with Four Transmit Antenna for Future Wireless Communication Systems

Uncoded space-time labeling diversity (USTLD) is a recent multi-diversity technique that directly extends the space-time block code (STBC). Existing USTLD schemes either employ two or three transmit antennas. This paper explores the antenna diversity of USTLD systems by using four transmit antennas. By utilizing more transmit antennas, the error performance of USTLD systems is reduced. Artificial intelligence (AI) was recently introduced to produce mapper designs for two transmit USTLD systems. This paper presents an AI approach termed hill climbing (HC) to build the fourth mapper irrespective of constellation shape or size. Analytical expressions for the proposed scheme are derived using the union-bound approach with the trapezoidal approximation. The proposed method exhibits a close fit between analytical and simulation results at high signal to noise (SNR). This work's main research finding shows that the proposed scheme's Monte Carlo simulations exhibit a better error performance than existing USTLD schemes. Finally, the results reveal that in the case of the 16QAM USTLD, the proposed scheme provides diversity gains of approximately 3.5 dB and 2 dB over the two transmit and three transmit USTLD schemes, respectively.