# AI Optimization-Based Heterogeneous Approach for Green Next-Generation Communication Systems
## 2 Related Work and Problem Statement  
### Related Work  
Recently, considerable attention has been directed toward HetNets in the realm of research due to their adaptability to the variability in traffic patterns for improving network energy efficiency [14; 15], with a wealth of research offering various techniques to enhance their performance. For instance, the authors of [16; 17; 18] conducted extensive research on optimizing the HetNet backhauling architecture, focusing on minimizing power consumption through the introduction of diverse backhaul solutions. In a similar vein, the authors of [19] delved into utilization of the millimeter-wave spectrum in both backhaul and access networks. Their thorough analysis covered a range of frequency bands, including 73 GHz,  
Figure 1: Carrier aggregation in LTE-LAA. 60 GHz, 38 GHz, and 28 GHz, all aimed at enhancing the small cell capacity. Meanwhile, [PERSON] et al., as explored in [20], assessed the feasibility of millimeter-wave technology for both backhaul and access infrastructures, with a particular emphasis on the V and E bands. In a different approach, the authors of [21] introduced an innovative HetNet backhaul infrastructure which harnessed millimeter-wave and orthogonal frequency division multiple access (OFDMA-PON) in conjunction with software-defined radio, facilitating flexible and cost-effective coverage solutions. In terms of SDR, ref. [22] presented a comprehensive overview of the SDR concept, elucidating the challenges and potential benefits associated with its adoption in cellular networks. Meanwhile, ref. [23] proposed an SDR-based networking architecture called SoftAir, designed to optimize the allocation of licensed spectrum resources through various traffic-engineering solutions. In a distinct approach, ref. [5] developed a centralized control plane for cellular networks based on SDR technology. Their SoftRAN approach treated all base stations within a specific coverage area as components of a unified virtual BS under a single central controller, aiming to enhance network management efficiency and profitability. Furthermore, ref. [24] introduced a user-associating scheme which incorporates SDR technology to adapt and distribute the associating algorithm according to traffic load, with the primary objective of reducing overall power consumption and relieving backhaul network burdens. Finally, ref. [25] proposed a mobility-based user-associating scheme suitable for cooperative communication scenarios. The HetNet concept is highly sensitive to user-cell association rules due to significant disparities in BSs' coverage areas. Incommensurate cell coverage areas lead to unequal traffic loads in the case of a maximum signal-to-interference-and-noise ratio (SINR) cell association, presuming that the mobile user distribution is relatively uniform. The load difference in a macro cell-only network is limited because the size of almost all cells' coverage areas is the same. However, the opposite is true in HetNets. This leads to a higher level of complexity with regard to the user association problem in HetNets. Recent studies on user association can be categorized into two groups:  
* Group (1) uses techniques based on borrowing channels from underutilized BSs, such as hybrid channel assignment (HCA) in [26], load balancing with selective borrowing (LBSB), and channel borrowing without locking (CBWL) [27]. * Group (2) uses techniques based on transferring traffic to underutilized BSs, such as hierarchical macrocell overlay system cell zooming [28; 29] and biasing methods [30]. The subject of traffic load balancing within HetNets has garnered substantial attention in recent research endeavors. Various algorithms have emerged with the aim of achieving effective traffic load distribution in HetNets, thereby optimizing network resources. For instance, in [31], the authors approached the challenge of load balancing as an optimization problem, focused on maximizing efficiency.