In the world of wireless communication, keeping up with users’ demands for high data rates and spectral efficiency is crucial. Combining multiple input-multiple output (MIMO) technology with orthogonal frequency division multiplexing (OFDM) has emerged as a promising solution. However, OFDM suffers from a significant drawback of high peak-to-average power ratio (PAPR). To tackle this challenge, the commonly used partial transmit sequence (PTS) method is employed, though it is notorious for its computational complexity. In our research, we’ve taken a unique approach by fine-tuning PTS with spider monkey optimization (SMO), which is developed from spider monkey’s social behavior and is a population-based algorithm. This adjustment significantly reduces computational complexity. By further integrating polar coding (PC) with SMO-PTS, we’ve enhanced the efficiency of the MIMO-OFDM system. This powerful combination not only minimizes PAPR but also reduces the bit error rate (BER). Our findings clearly demonstrate that our proposed approach substantially decreases search complexity, PAPR, and bit error rate, ensuring a more seamless and efficient wireless communication experience for users.