# Interference Challenges and Management in B5G Network Design: A Comprehensive Review
## 4 Interference in B5G Networks
### Device-to-Device (D2D)
#### 4.2.5 Related Work in D2D
In [105], the authors proposed a decentralized interference management method to improve the overall signal-to-interference-plus-noise ratio (SINR) of the network system while reducing the complex computational load on MBS. The proposed Interference Management (IM) divides the interference into cross-cluster interference and intra-cluster interference and treats them separately. The performance analysis of the spectral clustering technique was compared with benchmark clustering techniques such as Kernel means (K-means) and Kernel Principal Component Analysis (KPCA) clustering. It was found that the proposed technique extremely reduced the average cross-cluster interference. Moreover, the proposed dynamic resource allocation scheme reduces the inter-cluster interference which results in maximizing the overall SINR of the network. However, when the RBs were reused among the D2D Uses set, the proposed system suffers from severe interference. In [106], a novel RA for downlink communications underlying MIMO-NOMA cellular network was proposed for maximization of SE while guaranteeing the QoS of both CUEs and D2D pairs and providing interference protection for CUEs and receivers device user equipment (RDUE). To enhance network SE, an optimum power allocation approach depending on particle swarm optimization (PSO) was proposed for both CUEs and DUEs, while preserving CUEs from intra-cluster interference induced by TDUE and ensuring QoS for CUEs and D2D Pairs. Simulation results stated that the proposed RA algorithm provides massive spectrum and energy efficiency as compared to traditional D2D communications that use MIMO-OMA cellular networks. Yet, when the CUEs and D2D pairing numbers were increased with a decrease in the number of clusters, the SE significantly decreased for the proposed model. In [107], the decentralized algorithm based on the auction approach was proposed to solve the RA issue in multi-tier HetNet and to realize maximum SE and total data rate without causing prominent cross-tier and co-tier interference to the macro user equipments (MUEs) and underlay user equipments (DUEs and SUEs), respectively. Furthermore, the Rayleigh fading, shadow fading, and path losses concerning distance were considered. The simulation results stated that the proposed approach has better performance than the optimum centralized RA algorithm. Moreover, the proposed approach achieved close to 80% of the maximum data rate with less overhead and complexity. Nonetheless, the selfish and bad-behaving transmitters that have large impacts on the data rate of the proposed approach were not taken into consideration. Hybrid strategies  
In [108], the suboptimal DDT-DMU user grouping and RA scenarios were proposed for both DMGs and CMUs to optimize the total network's sum rate while preserving the SINR of the CMUs and DMUs. The DMGs in the underlying cellular network are constructed depending on SIC decoding to decrease intra-user interference. The proposed scenario was compared with the existing joint user clustering and power allocation (JUCPA) and joint spectrum and power allocation (JSPA) scenarios. Numerical results stated that the proposed scenario achieves a better sum rate than the existing NOMA and OFDMA scenarios. However, increasing the number of DMGs in the cell resulted in a decrease in the chance of identifying the optimal RB because of increased co-channel interference. Hence, the time taken for the algorithm implementation increased due to the increase in the cross and co-channel interference via each RB, leading to a decrease in the DMGs sum-rate because of increased co-channel interference. Furthermore, increasing the number of CMUsin the cell reduced the DMG sum-rate because it captures a large portion of the frequency resources required to acquire the minimum data rate. In [109], the authors investigated the joint resource and power allocation issue for cooperative D2D users (CDUs) which multiplex Cus in downlink cooperative D2D heterogeneous networks (CDHN).