Performance Comparison of QoS Aware Power Allocation and Optimization Techniques for the Small-Cell 5G Networks

The deployment of small cells in highly dense areas or buildings, and offices is a key technique in upcoming 5G networks that enhance the signal coverage and capacity. However, the presence of co-channel cells may result in interference among the user stations and degrade the overall system capacity. Hence, resource optimization techniques are required in these scenarios to improve the system capacity and user quality. In this study, the power allocation problem among the interfering user stations is considered by guaranteeing their Quality of Service (QoS) requirements. To solve the non-convex optimization problem, some of the algorithms like Sequential quadratic programming (SQP), Log-space sequential quadratic programming (LSQP), Interior point Trust Region (IPTR) are discussed. The performance comparison is done with these algorithms to analyse the effect on sum rate, individual rates and computational complexity in small cell network scenarios. The results show that the LSQP technique has improved sum and user rate performance compared to SQP and trust region-based methods.