Load Balancing Optimization in LTE/LTE-A Cellular Networks: A Review
---
paper_title: Adaptive Neuro-Fuzzy Inference System for Dynamic Load Balancing in 3GPP LTE

paper_content:

ANFIS is applicable in modeling of key parameters when investigating the performance and functionality of wireless networks. The need to save both capital and operational expenditure in the management of wireless networks cannot be over-emphasized. Automation of network operations is a veritable means of achieving the necessary reduction in CAPEX and OPEX. To this end, next generations networks such WiMAX and 3GPP LTE and LTE-Advanced provide support for self-optimization, self-configuration and self-healing to minimize human-to-system interaction and hence reap the attendant benefits of automation. One of the most important optimization tasks is load balancing as it affects network operation right from planning through the lifespan of the network. Several methods for load balancing have been proposed. While some of them have a very buoyant theoretical basis, they are not practically implementable at the current state of technology. Furthermore, most of the techniques proposed employ iterative algorithm, which in itself is not computationally efficient. This paper proposes the use of soft computing, precisely adaptive neuro-fuzzy inference system for dynamic QoS-aware load balancing in 3GPP LTE. Three key performance indicators (i.e. number of satisfied user, virtual load and fairness distribution index) are used to adjust hysteresis task of load balancing.
---

Title: Load Balancing Optimization in LTE/LTE-A Cellular Networks: A Review

Section 1: Introduction
Description 1: Introduce the increasing demand for bandwidth and the resulting load imbalance in cellular networks, and the role of load balancing techniques.

Section 2: Overview of LTE/LTE -Advanced
Description 2: Provide background information on LTE and LTE-A technologies, including their architecture, features, and components.

Section 3: Load Balancing Mechanism
Description 3: Discuss various load balancing techniques, emphasizing active mode and idle mode load balancing in LTE/LTE-A networks.

Section 4: Active Mode Load Balancing
Description 4: Explain the active mode load balancing process and its advantages in managing user traffic and radio conditions for load balancing.

Section 5: Idle Mode Load Balancing
Description 5: Describe the challenges and mechanisms of achieving idle mode load balancing, including the adjustment of cell reselection parameters.

Section 6: Handover in LTE-Advanced
Description 6: Detail the importance of handovers in load balancing schemes, including intra-LTE and inter-RAT handovers.

Section 7: Classical and Advanced Load Balancing Approaches
Description 7: Review existing load balancing methods, such as dynamic channel assignment, coverage area-based techniques, and advanced approaches like game-theoretic and adaptive neuro-fuzzy methods.

Section 8: Conclusion
Description 8: Summarize the importance of load balancing in cellular networks and the need for self-optimizing mechanisms for future generation networks.