Taylor-Based Least Square Estimation in MIMO-OFDM Systems for Multimedia Applications

Recent mobile telecommunication systems are using multiple-input multiple-output system (MIMO) collective with the orthogonal frequency division multiplexing (OFDM), which is well-known as MIMO-OFDM, to offer robustness and higher spectrum efficiency. The most important challenge in this scenario is to achieve an accurate channel estimation to identify the information symbols once the receiver must have the channel state information to balance and process the received signal. Hence, an effective technique is introduced by proposing the Taylor-least square error algorithm (TLSE) to improve the performance of the MIMO-OFDM system in multimedia applications. In addition, the user admission control is done in multi user-MIMO (MU-MIMO) system using the priority-based scheduling based on Dolphin-rider optimization (DRO) algorithm that is integrated within the space–time block code (STBC) STBC-MIMO-OFDM system for efficient power allocation to ensure the energy efficiency. The DRO is the integration of rider optimization algorithm (ROA) and Dolphin Echolocation (DE). Here, channel estimation is done using the novel optimization algorithm, termed TLSE, which is designed by modifying LSE with the Taylor series. Moreover, the fitness parameters, such as power, priority, throughput, and Proportionally Fair, are computed. The experimentation is conducted in different fading environments with three modulation schemes, binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), and quadrature amplitude modulation (QAM) with the performance metrics, namely bit error rate (BER) and throughput. The developed TLSE + DRO (QAM) outperformed other methods with minimal BER of 0.0001 based on channel-2 and maximal throughput of 0.9965 with respect to channel-1.