In modern communication systems, the rapid advancement of technology has introduced new methods for data transmission and modulation. However, two fundamental challenges continue to affect signal quality: noise and inter-symbol interference (ISI). ISI occurs when a signal travels through multiple paths with varying delays, causing interference at the receiver. This issue is exacerbated by dynamic factors, such as moving communication carriers and surrounding objects, which introduce time-varying environmental changes that complicate ISI due to multi-path effects. To address these challenges, a range of adaptive algorithms has been developed. These include differential evolution (DE), particle swarm optimization (PSO), and least mean square (LMS), each with its own strengths in improving signal quality. DE and PSO are popular for their ability to optimize complex systems, while LMS is widely used due to its simplicity and effectiveness in minimizing error. Among these, the variable step size LMS (VSSLMS) algorithm stands out as a particularly efficient method for adjusting equalizer coefficients in the presence of ISI. The VSSLMS algorithm enhances stability and speeds up adaptation compared to traditional algorithms like PSO and DE. Its variable step size feature allows it to adjust more rapidly to changing conditions, making it less prone to errors. Moreover, the VSSLMS algorithm is easier to implement, reducing the complexity and computational burden typically associated with adaptive algorithms. This makes it a valuable tool in the realm of adaptive channel equalization, where maintaining signal quality is critical. Overall, the VSSLMS algorithm’s combination of stability, speed, and simplicity makes it an ideal choice for addressing the challenges of ISI in modern communication systems.