Search Results (91)

In 5G networks and beyond, managing handovers (HOs) becomes complex because of frequent user transitions through small coverage areas. The abundance of small cells (SCs) also complicates HO decisions, potentially leading to inefficient resource utilization. To optimize this process, we propose an intelligent algorithm based on a method that utilizes a fuzzy logic controller (FLC), leveraging prior expertise to dynamically adjust the time-to-trigger (TTT), and handover margin (HOM) in a 5G ultra-dense SC heterogeneous network (HetNet). FLC refines TTT based on the user’s velocity to improve the response to movement. Simultaneously, it adapts HOM by considering inputs such as the reference signal received power (RSRP), user equipment (UE) speed, and cell load. The proposed approach enhances HO decisions, thereby improving the overall system performance. Evaluation using metrics such as handover rate (HOR), handover failure (HOF), radio link failure (RLF), and handover ping-pong (HOPP) demonstrate the superiority of the proposed algorithm over existing approaches. Full article

Traditional heterogeneous networks (HetNets) are constrained by their hardware design and configuration. These HetNets have a limited ability to adapt to variations in network dynamics. Software-defined radio technology has the potential to address this adaptability issue. In this paper, we introduce a software-defined radio (SDR)-based long-term evolution licensed assisted access (LTE-LAA) architecture for next-generation communication networks. We show that with proper design and tuning of the proposed architecture, high-level adaptability in HetNets becomes feasible with a higher throughput and lower power consumption. Firstly, maximizing the throughput and minimizing power consumption are formulated as a constrained optimization problem. Then, the obtained solution, alongside a heuristic solution, is compared against the solutions to existing approaches, showing our proposed strategy is drastically superior in terms of both power efficiency and system throughput. This study is then concluded by employing artificial intelligence techniques in multi-objective optimization, namely random forest regression, particle swarm, and genetic algorithms, to balance out the trade-offs between maximizing the throughput and power efficiency and minimizing energy consumption. These investigations demonstrate the potential of employing the proposed LTE-LAA architecture in addressing the requirements of next-generation HetNets in terms of power, throughput, and green scalability. Full article

This research endeavors to advance energy efficiency (EE) within heterogeneous networks (HetNets) through a comprehensive approach. Initially, we establish a foundational framework by implementing a two-tier network architecture based on Poisson process distribution from stochastic geometry. Through this deployment, we develop a tailored EE model, meticulously analyzing the implications of random base station and user distributions on energy efficiency. We formulate joint base station and user densities that are optimized for EE while adhering to stringent quality-of-service (QoS) requirements. Subsequently, we introduce a novel dynamically distributed opportunistic sleep strategy (D-DOSS) to optimize EE. This strategy strategically clusters base stations throughout the network and dynamically adjusts their sleep patterns based on real-time traffic load thresholds. Employing Monte Carlo simulations with MATLAB, we rigorously evaluate the efficacy of the D-DOSS approach, quantifying improvements in critical QoS parameters, such as coverage probability, energy utilization efficiency (EUE), success probability, and data throughput. In conclusion, our research represents a significant step toward optimizing EE in HetNets, simultaneously addressing network architecture optimization and proposing an innovative sleep management strategy, offering practical solutions to maximize energy efficiency in future wireless networks. Full article

In 5G heterogeneous networks (HetNets), small-cell base stations (SBSs) are deployed in the coverage of macro base stations (MBSs) to improve the system performance. However, some macro user equipments (MUEs) have strong interference from neighboring SBSs and thus the performance of MBSs decreases. Thus, in this paper, we propose a novel intelligent dynamic power control (DPC) with cell range expansion (CRE) to improve the downlink performance of both small-cell user equipments (SUEs) and CRE user equipments (CUEs) in 5G HetNets. That is, in the proposed DPC scheme, each MUE first collects the received signal strength indicator (RSSI) measurements from neighboring SBSs and sends them to the serving MBS. Then, the MBS finds MUEs with strong interference from neighboring SBSs based on a given target threshold of CRE and offloads a fraction of MUEs from MBSs to SBSs. In addition, SBSs divide their SUEs and CUEs into two groups, i.e., inner and outer groups, to assign different subchannels and dynamically allocate the appropriate transmission power to increase the performance of both SUEs and CUEs. Through simulation results, it is shown that the proposed DPC scheme outperforms others in terms of the capacity and outage probability of SUEs and CUEs. Full article

Recently, hyperdense small cells have been proposed to meet the challenge of the tremendous increment in cellular data service requirements. To reduce the deployment cost, as well as operated cost, these small cells are usually connected to limited backhauls, in which case the backhaul capacity may become a bottleneck in busy hours. In this paper, we propose an optimal scheme for the small cells to utilize the macrocell links as its wireless backhaul. Based on stochastic geometry, the analytical expressions of network capacity with in-band and out-band wireless backhaul are derived and validated using simulation results. The optimized results show that our proposed scheme can significantly improve the network performance in scenarios with a high traffic load. Full article

The application of drones, also known as unmanned aerial vehicles deployed as unmanned aerial base stations (UABSs), has received extensive interest for public safety communications (PSC) to fill the coverage gaps and establish ubiquitous connectivity. In this article, we design a PSC LTE-Advanced air–ground-based HetNet (AG-HetNet) that is a scenario representation of a geographical area during and after a disaster. As part of the AG-HetNet infrastructure, we have UABSs and ground user equipment (GUE) flocking together in clusters at safe places or evacuation shelters. AG-HetNet uses cell range expansion (CRE), intercell interference coordination (ICIC), and 3D beamforming techniques to ensure ubiquitous connectivity. Through system-level simulations and using a brute-force technique, we evaluate the performance of the AG-HetNet in terms of fifth-percentile spectral efficiency (5pSE) and coverage probability. We compare system-wide 5pSE and coverage probability when UABSs are deployed on a hexagonal grid and for different clustering distributions of GUEs. The results show that reduced power subframes (FeICIC) defined in 3GPP Release-11 can provide practical gains in 5pSE and coverage probability than the 3GPP Release-10 with almost blank subframes (eICIC). Full article

In order to tackle the explosive growth of data traffic and the number of terminals, 5G heterogeneous network (HetNet) has become an important evolution direction of 5G networking architecture. Densely deployed micro base stations (gNBs) in 5G HetNets will dramatically increase the handover frequency of user equipment (UE), resulting in more handover failures, and seriously reducing the user experience of mobile UE. Aiming at tackling this problem, this paper proposes a beam enhancement handover scheme with an adaptive threshold. Firstly, different beamforming gains are configured for the mobile UE in the overlapping area of two gNBs to improve the signal strength received by the UE at the edge of gNB coverage. Secondly, for mobile UE with different speeds, adaptive handover decision parameters are configured, and reference signal receiving strength (RSRP) as well as reference signal receiving quality (RSRQ) are used for joint handover decisions to achieve reliable handover. The simulation results verify that the proposed scheme can effectively improve the signal strength of the edge area, and the adaptive joint handover decision algorithm based on UE speed can also effectively improve the handover success probability. Full article

The sixth-generation (6G) wireless cellular network integrates several wireless bands and modes with the objectives of improving quality of service (QoS) and increasing network connectivity. The 6G environment includes asymmetrical heterogeneous networks (HetNets) with the intention of making effective use of the available frequencies. However, selecting a suitable gNB and a communication channel that works for users in the network is an enormous challenge in 6G HetNets. This paper investigates a joint user association (UA) and channel allocation (CA) problem in two-tier HetNets by considering the downlink scenario to improve QoS. Our study presents an innovative scheme for user association and channel allocation, wherein the user can be connected to either the macro base station (MBS) or a possible small base station (SBS) in a direct or relay-assisted link. Furthermore, the proposed scheme identifies the optimal channel to be allocated to each user so that the overall network QoS can be maximized. A symmetric matching game-based user association is proposed to find the optimal association for users. Moreover, a modified auction game is applied to allocate the optimal channel by considering the quota of each gNB. Regarding connection probability, throughput, energy efficiency (EE), and spectrum efficiency (SE), the simulation results show that the proposed approach performs well over the state-of-the-art techniques. Full article

Natural disasters, including earthquakes, floods, landslides, tsunamis, wildfires, and hurricanes, have become more common in recent years due to rapid climate change. For Post-Disaster Management (PDM), authorities deploy various types of user equipment (UE) for the search and rescue operation, for example, search and rescue robots, drones, medical robots, smartphones, etc., via the Internet of Robotic Things (IoRT) supported by cellular 4G/LTE/5G and beyond or other wireless technologies. For uninterrupted communication services, movable and deployable resource units (MDRUs) have been utilized where the base stations are damaged due to the disaster. In addition, power optimization of the networks by satisfying the quality of service (QoS) of each UE is a crucial challenge because of the electricity crisis after the disaster. In order to optimize the energy efficiency, UE throughput, and serving cell (SC) throughput by considering the stationary as well as movable UE without knowing the environmental priori knowledge in MDRUs aided two-tier heterogeneous networks (HetsNets) of IoRT, the optimization problem has been formulated based on emitting power allocation and user association combinedly in this article. This optimization problem is nonconvex and NP-hard where parameterized (discrete: user association and continuous: power allocation) action space is deployed. The new model-free hybrid action space-based algorithm called multi-pass deep Q network (MP-DQN) is developed to optimize this complex problem. Simulations results demonstrate that the proposed MP-DQN outperforms the parameterized deep Q network (P-DQN) approach, which is well known for solving parameterized action space, DQN, as well as traditional algorithms in terms of reward, average energy efficiency, UE throughput, and SC throughput for motionless as well as moveable UE. Full article

Neurodegenerative diseases (NDs) are a group of complex disorders characterized by the progressive degeneration and dysfunction of neurons in the central nervous system. NDs encompass many conditions, including Alzheimer’s disease and Parkinson’s disease. Alzheimer’s disease (AD) is a complex disease affecting almost forty million people worldwide. AD is characterized by a progressive decline of cognitive functions related to the loss of connections between nerve cells caused by the prevalence of extracellular $A\beta$ plaques and intracellular neurofibrillary tangles plaques. Parkinson’s disease (PD) is a neurodegenerative disorder that primarily affects the movement of an individual. The exact cause of Parkinson’s disease is not fully understood, but it is believed to involve a combination of genetic and environmental factors. Some cases of PD are linked to mutations in the LRRK2, PARKIN and other genes, which are associated with familial forms of the disease. Different research studies have applied the Protein Protein Interaction (PPI) networks to understand different aspects of disease progression. For instance, Caenorhabditis elegans is widely used as a model organism for the study of AD due to roughly 38% of its genes having a human ortholog. This study’s goal consists of comparing PPI network of C. elegans and human by applying computational techniques, widely used for the analysis of PPI networks between species, such as Local Network Alignment (LNA). For this aim, we used L-HetNetAligner algorithm to build a local alignment among two PPI networks, i.e., C. elegans and human PPI networks associated with AD and PD built-in silicon. The results show that L-HetNetAligner can find local alignments representing functionally related subregions. In conclusion, since local alignment enables the extraction of functionally related modules, the method can be used to study complex disease progression. Full article

Massive multiple-input and multiple-output (MIMO) networks with higher throughput rates, where a base station (BS) with a large-scale antenna array serves multiple users, have been widely employed in next-generation wireless communication test systems. Massive MIMO-enabled dense heterogeneous networks (HetNets) have also emerged as a promising architecture to increase the system spectrum efficiency and improve the system reliability. Massive MIMO-enabled HetNets have been successfully exploited in sustainable Internet of Thing networks (IoTs). In order to facilitate the testing and performance estimation of IoTs communication systems, this paper studies the achievable rate performance of massive MIMO and HetNets. Differing from the existing literature, we first consider an interference power model for massive MIMO-enabled HetNets. We next obtain an expression for the signal-to-interference-plus-noise ratio (SINR) by introducing an interference power. Furthermore, we derive a new closed-form lower bound expression for the achievable rate. The proposed closedform expression shows that the achievable rate is an explicit expression of the number of transmit antennas. In simulation results, the impact of the number of transmit antennas on the achievable rate performance is investigated. Full article

With the development of the next generation of mobile networks, new research challenges have emerged, and new technologies have been proposed to address them. On the other hand, reconfigurable intelligent surface (RIS) technology is being investigated for partially controlling wireless channels. RIS is a promising technology for improving signal quality by controlling the scattering of electromagnetic waves in a nearly passive manner. Heterogeneous networks (HetNets) are another promising technology that is designed to meet the capacity requirements of the network. RIS technology can be used to improve system performance in the context of HetNets. This study investigates the applications of reconfigurable intelligent surfaces (RISs) in heterogeneous downlink networks (HetNets). Due to the network densification, the small cell base station (SBS) interferes with the macrocell users (MUEs). In this paper, we utilise RIS to mitigate cross-tier interference in a HetNet via directional beamforming by adjusting the phase shift of the RIS. We consider RIS-assisted heterogeneous networks consisting of multiple SBS nodes and MUEs that utilise both direct paths and reflected paths. Therefore, the aim of this study is to maximise the sum rate of all MUEs by jointly optimising the transmit beamforming of the macrocell base station (MBS) and the phase shift of the RIS. An efficient RIS reflecting coefficient-based optimisation (RCO) is proposed based on a successive convex approximation approach. Simulation results are provided to show the effectiveness of the proposed scheme in terms of its sum rate in comparison with the scheme HetNet without RIS and the scheme HetNet with RIS but with random phase shifts. Full article

Fifth-generation (5G) networks offer high-speed data transmission with low latency, increased base station volume, improved quality of service (QoS), and massive multiple-input–multiple-output (M-MIMO) channels compared to 4G long-term evolution (LTE) networks. However, the COVID-19 pandemic has disrupted the achievement of mobility and handover (HO) in 5G networks due to significant changes in intelligent devices and high-definition (HD) multimedia applications. Consequently, the current cellular network faces challenges in propagating high-capacity data with improved speed, QoS, latency, and efficient HO and mobility management. This comprehensive survey paper specifically focuses on HO and mobility management issues within 5G heterogeneous networks (HetNets). The paper thoroughly examines the existing literature and investigates key performance indicators (KPIs) and solutions for HO and mobility-related challenges while considering applied standards. Additionally, it evaluates the performance of current models in addressing HO and mobility management issues, taking into account factors such as energy efficiency, reliability, latency, and scalability. Finally, this paper identifies significant challenges associated with HO and mobility management in existing research models and provides detailed evaluations of their solutions along with recommendations for future research. Full article

An optimal method for resource allocation based on contract theory is proposed to improve energy utilization. In heterogeneous networks (HetNets), distributed heterogeneous network architectures are designed to balance different computing capacities, and MEC server gains are designed based on the amount of allocated computing tasks. An optimal function based on contract theory is developed to optimize the revenue gain of MEC servers while considering constraints such as service caching, computation offloading, and the number of resources allocated. As the objective function is a complex problem, it is solved utilizing equivalent transformations and variations of the reduced constraints. A greedy algorithm is applied to solve the optimal function. A comparative experiment on resource allocation is conducted, and energy utilization parameters are calculated to compare the effectiveness of the proposed algorithm and the main algorithm. The results show that the proposed incentive mechanism has a significant advantage in improving the utility of the MEC server. Full article

With the rapid growth of data traffic and mobile devices, it is imperative to provide reliable and stable services during mobility. Heterogeneous Networks (HetNets) and dense networks have been identified as potential solutions to address the upcoming capacity crunch, but they also pose significant challenges related to handover optimization. This paper presents a comprehensive review of recent handover decision algorithms in HetNets, categorizing them based on their decision techniques and summarizing their input parameters, techniques, and performance evaluations. Our study highlights the technical challenges and opportunities related to handovers in HetNets and dense cellular networks and provides key findings from recent studies. The significance of this survey is to provide a comprehensive overview of handover decision algorithms in HetNets and dense cellular networks, which can aid in the development of more advanced handover optimization approaches. Full article