Energy-Efficient Power Allocation in Multitier 5G Networks Using Enhanced Online Learning

Abstract

The multi-tier heterogeneous structure of 5G with dense small cells deployment, relays, and device-to-device (D2D) communications operating in an underlay fashion is envisioned as a potential solution to satisfy the future demand for cellular services. However, efficient power allocation among dense secondary transmitters that maintains quality of service (QoS) for macro (primary) cell users and secondary cell users is a critical challenge for operating such radio. In this paper, we focus on the power allocation problem in the multi-tier 5G network structure using a non-cooperative methodology with energy efficiency consideration. Therefore, we propose a distributive intuition-based online learning scheme for power allocation in the downlink of the 5G systems, where each transmitter surmises other transmitters power allocation strategies without information exchange. The proposed learning model exploits a brief state representation to account for the problem of dimensionality in online learning and expedite the convergence. The convergence of the proposed scheme is proved and numerical results demonstrate its capability to achieve fast convergence with QoS guarantee and significant improvement in system energy efficiency.

Robust Multi-Objective Optimization for EE-SE Tradeoff in D2D Communications Underlaying Heterogeneous Networks

“…Besides, the work in [22] investigates the resource allocation problem to maximize the system secure capacity for D2D communications underlaying HetNets where each subcarrier can be allocated to at most one user of the same type. On the contrary, the authors in [23] focus on the power allocation problem in multi-tier HetNets by employing a non-cooperative scheme to optimize the individual EE of each small cell BS and each D2D pair.…”

Energy Efficient Traffic Offloading in Multi-Tier Heterogeneous 5G Networks Using Intuitive Online Reinforcement Learning

“…Machine learning is a powerful tool that penetrated the communication and networking field recently [24] [25] [26] [27]. It is envisioned as potential solution for efficient traffic offloading in heterogeneous cellular networks.…”

Semi‐distributed dynamic inter‐cell interference coordination scheme for interference avoidance in heterogeneous networks

“…Severe interference during downlinking causes degradation in quality of service (QoS) for cell‐edge users and negatively affects overall system capacity. Most previous studies on interference in FC networks have focused on distributed power control methods , various radio resource allocation schemes , cognitive radio resource management strategies using game theory , and beamforming techniques . However, these methods incur substantial signaling overhead and various levels of computational complexity.…”