Performance analysis and comparison of a novel Steiner-Quadrature Space Shift Keying (S-QSSK) scheme in massive MIMO systems.

This paper introduces Steiner-quadrature space shift keying (QSSK) (S-QSSK), an innovative modulation scheme tailored for multiple–input multiple–output (MIMO) systems. The study compares S-QSSK with existing modulation schemes (S-space shift keying (SSK)(S-SSK), QSSK, generalized quadrature space shift keying (GQSSK)) across various performance metrics, considering diverse channel conditions, transmit antenna numbers, and spectral efficiencies. Theoretical average bit error rate (ABER) analysis, validated by Monte Carlo simulations, establishes a close agreement between analytical and practical results, especially at realistic signal-to-noise-ratio (SNR) values. Additionally, capacity and mutual information formulas shed light on the system's information transmission capabilities. The research delves into the outage probability, power consumption, and computational complexity of S-QSSK MIMO systems. It unveils a promising trade-off, demonstrating that S-QSSK achieves competitive performance in ABER, capacity, and mutual information, positioning it as a practical modulation technique. Importantly, S-QSSK exhibits about a 1 dB ABER performance decrease compared to S-SSK and QSSK, while offering a noteworthy 2 dB improvement over GQSSK. Despite requiring slightly more transmit antennas than GQSSK, S-QSSK demands significantly fewer than both S-SSK and traditional QSSK, particularly when targeting high spectral efficiencies. Moreover, the analysis underscores the advantageous power consumption and favorable computational complexity of S-QSSK relative to other modulation schemes. The proposed S-QSSK MIMO system thus presents itself as an efficient solution, enabling high data rates with fewer transmit antennas, resulting in substantial reductions in power consumption and computational complexity without a significant sacrifice in ABER and mutual information. These attributes make it a compelling choice for various applications, including those requiring efficient massive multiple–input multiple–output (mMIMO) operations. [ABSTRACT FROM AUTHOR]