5G wireless networks accommodate a variety of traffic types generated by applications on different devices. These include traditional data traffic from protocols like HTTP, FTP, and video streaming, as well as Human-Type Communication (HTC) and Machine-Type Communication (MTC). MTC uses sensors, actuators, and other devices that produce data in a periodic or event-driven manner, adding variability to traffic patterns ( VijaylakshmiChetlapalli., et al.: Modelling time-dependent aggregate traffic in 5G Networks. Telecommunication Systems 73(5), 557–575 (2020)). This study investigates how MTC traffic loads impact Transmission Control Protocol (TCP) performance within a 5G network, focusing on periodic MTC traffic. Traffic control at the base station is achieved through a Random Early Detection (RED) router to manage congestion. Building on previous research ( VijaylakshmiChetlapalli., et al.: Modelling time-dependent aggregate traffic in 5G Networks. Telecommunication Systems 73(5), 557–575 (2020)), the study analyzes TCP sender window dynamics, Round-Trip Time (RTT) delays, queue behavior, and packet loss rates in various MTC traffic scenarios. Python is used for visual and statistical analysis, aiming to enhance network performance and maintain Quality of Service (QoS) through efficient resource allocation.