Device to Device Hybridization in 5G and Beyond: A Literature Review

Abstract- Device-to-Device (D2D) communication is one of the most promising technologies to enhance user experience in 5G and beyond. Despite the huge benefit anticipated, enabling D2D in cellular network has encounter some challenges, these challenges include peer discovery and synchronization, mode selection and interference management. However, resolving these challenges promises improved service delivery, spectrum efficiency and reduced latency amongst other gains. Attempts to enable D2D in both microwave and millimeter wave network gained some traction in recent years in a bid to enable wider coverage and utilization of the technology. Some of the research attempts, challenges and prosects are discussed in this paper.Keywords- Device-to-Device, Microwave, millimeter wave, Inter-cell Interference

Interference Management with Dynamic Resource Allocation Method on Ultra-Dense Networks in Femto-Macrocellular Network

Ultra-Dense Network (UDN) which is formed from femtocells densely deployed is known as one of key technologies for 5th generation (5G) cellular networks. UDN promises for increased capacity and quality of cellular networks. However, UDN faces more complex interference problems than rarely deployed femtocells, worse on femtocells that are located on cell edge area of macrocell. Therefore, mitigating or reducing effects of interferences is an important issue in UDN. This paper focuses on interference management using dynamic resource allocation for UDN. Types of interference considered in this study are cross-tier (macrocell-to-femtocell) and co-tier (femtocellto-femtocell) interferences for uplink transmission. We consider several scenarios to examine the dynamic resource allocation method for UDN in case of femtocells deployed in the whole area of microcell and in the cell edge area of macrocell. Simulation experiment using MATLAB program has been carried out. The performance parameters that are collected from the simulation are Signal to Interference and Noise Ratio (SINR), throughput, and Bit Error Rate (BER). The obtained simulation results show that system using dynamic resource allocation method outperforms conventional system and the results were consistent for the collected performance parameters. The dynamic resource allocation promises to reduce the effects of interference in UDN.

Interference Suppression in Heterogeneous Massive MIMO Systems with Imperfect CSI

Interference management is of paramount importance in heterogeneous massive mimo networks (HetNet). In this paper, an algorithm has been suggested to suppress the interference in large-MIMO HetNets with imperfect channel state information(CSI). The proposed technique controls both the intra-tier and cross-tier interference of the macrocell as well as the small cells. The intra-tier interference of the macrocell as well as the cross-tier interference have been minimized under maximum transmission power and minimum signal to interference and noise ratio (SINR) constraint. The channel estimation error matrix has also been modeled using the joint sparsity property. The precoding algorithm is thus achieved through the application of semi-definite relaxation and block coordinate descent techniques. The intra-tier interference of the small cells are addressed with the aid of the zero forcing scheme. The proposed method has been validated through various simulations which confirm the superiority of the algorithm over its counterparts.

Relay-Based Clustering Method for Interference Management in Heterogeneous Wireless Cellular Network

Femtocell is one of solutions to improve quality of services and network capacity for users in indoor areas. Radio resources used by femtocells are shared from macrocell network, thus it saves the use of frequency spectrum. However, one of problems in deploying femtocells within coverage area of macrocells is interference due to radio resources sharing between femtocells and macrocells. It creates interferences called as cross-tier (macrocell-femtocell/femtocell-macrocell) and co-tier (macrocell-macrocell/femtocell-femtocell) interferences. This paper proposes a relay-based clustering method to mitigate interference in femtocells located in the whole edge area of macrocell and the cell edge area of sectorized macrocells. Relay nodes are deployed statically (fixed location) in the neighboring macrocell area. Relay node will recruit their members based on the shortest distance. Certain relay node’s members do not need to transmit large amounts of power to enhanced Node B (eNB), such that interference from Macrocell User Equipment (MUE) to Home enhanced Node B (HeNB) can be minimized. Simulation experiments has been carried out and optimistic results for the sectorized macrocells scenario show that Signal-to-Interference-plus-Noise-Ratio (SINR) of femtocells for the conventional system that does not reach the targeted SINR of 20 dB is 87%. Meanwhile, after applying the relay-based clustering method, SINR value of femtocells below or equal to 20 dB reaches 72%. Optimistic results for throughput and Bit Error Rate (BER) show improvement of 15% and 14%, respectively. It has been shown that the relay-based clustering method can provide better performance compared to the conventional system even for femtocells densely deployed.

Deep Reinforcement Learning Based Resource Allocation with Radio Remote Head Grouping and Vehicle Clustering in 5G Vehicular Networks

With increasing data traffic requirements in vehicular networks, vehicle-to-everything (V2X) communication has become imperative in improving road safety to guarantee reliable and low latency services. However, V2X communication is highly affected by interference when changing channel states in a high mobility environment in vehicular networks. For optimal interference management in high mobility environments, it is necessary to apply deep reinforcement learning (DRL) to allocate communication resources. In addition, to improve system capacity and reduce system energy consumption from the traffic overheads of periodic messages, a vehicle clustering technique is required. In this paper, a DRL based resource allocation method is proposed with remote radio head grouping and vehicle clustering to maximize system energy efficiency while considering quality of service and reliability. The proposed algorithm is compared with three existing algorithms in terms of performance through simulations, in each case outperforming the existing algorithms in terms of average signal to interference noise ratio, achievable data rate, and system energy efficiency.

Intelligent Interference Management in UAV-Based HetNets

Unmanned aerial vehicles (UAVs) can play a key role in meeting certain demands of cellular networks. UAVs can be used not only as user equipment (UE) in cellular networks but also as mobile base stations (BSs) wherein they can either augment conventional BSs by adapting their position to serve the changing traffic and connectivity demands or temporarily replace BSs that are damaged due to natural disasters. The flexibility of UAVs allows them to provide coverage to UEs in hot-spots, at cell-edges, in coverage holes, or regions with scarce cellular infrastructure. In this work, we study how UAV locations and other cellular parameters may be optimized in such scenarios to maximize the spectral efficiency (SE) of the network. We compare the performance of machine learning (ML) techniques with conventional optimization approaches. We found that, on an average, a double deep Q learning approach can achieve 93.46% of the optimal median SE and 95.83% of the optimal mean SE. A simple greedy approach, which tunes the parameters of each BS and UAV independently, performed very well in all the cases that we tested. These computationally efficient approaches can be utilized to enhance the network performance in existing cellular networks.

Interference Management for the Coexistence of DTTV and LTE Systems within the Proposed Digital Dividend Band in Nigeria

This paper seeks to present the Interference Management for the Coexistence of DTTV and LTE Systems within the proposed digital dividend band in Nigeria. The study focused on LTE Down-link (DL) signal from the nearest cell site interfering with the Digital Terrestrial Television (DTTV) fixed outdoor receiving antenna in Port Harcourt, Nigeria. The qualitative signal analysis of the DTTV systems is essential as DTTV system cannot start to operate in the newly formed frequency band without the evaluation of the possible harmful influence of the coexisting systems. This research work investigated the Compatibility of the two systems and the Probability of interference of Channel 17 (490MHz) and Channel 51 (693MHz) when DTTV and LTE systems coexist within the proposed Digital Dividend band. A test-bed approach method was adopted for the generation of the required simulation data. Star Time transmitting Station in Port Harcourt and Smile LTE 4G Communication LTE Base Station (eNBs) Network also in Port Harcourt were adopted as the Victim Link Transmitter (VLT) and Interfering Link Transmitter (ILT) respectively. Data was obtained, analyzed, and evaluated. It was observed from the simulation result that the probability of interference is a function of the separation distance between ILT and VLR. The Compatibility analysis result shows that the resulting C/I is above the protection criteria (19dB), that is there’s a minimal rate of interference. Hence, the interference issue can be managed when the two systems coexist in700MHz band. It was also established that DTTV channel 51 suffers more interference when compared with DTTV channel 17 for the same separation distance. The study recommended the minimum protection distance approach (Interference Avoidance method) as the interference management techniques when DTTV and LTE systems coexist in the proposed digital dividend (700MHz) band in Nigeria.