Heterogeneous Cellular Networks Research Articles

Energy-Efficient 5G Heterogeneous Cloud Radio Access Networks (RRH to BBU) Using a Hybrid OGASCDASA-SAGMDEBROA Scheduling Algorithm

In fifth-generation (5G) networks, the deployment of heterogeneous networks (HetNets) with macrocells layered over tiny cells is considered to be a practical solution to handle the growing demand for mobile traffic. Even though the deployment of a significant count of small cell base stations (BSs) results in a notable rise in energy consumption. In this manuscript, Energy-Efficient (EE) 5G Heterogeneous Cloud Radio Access Networks (RRH to BBU), using Hybrid online green algorithm-based sleep scheduling and cost-efficient deadline-aware Scheduling Algorithm (OGASCDASA), are proposed. Here, the energy efficiency optimization issue is in the downlink of two-tier Heterogeneous Cloud Radio Access Networks (H-CRAN) by lowering micro and pico cells. Hybrid OGASCDASA is proposed for reducing remote radio side energy use when maintaining coverage and Quality of service (QoS) of H-CRAN. At the cloud side Baseband Units (BBU), hybrid Simulated Annealing with the Gaussian Mutation and Distortion Equalization algorithm with Battle Royale optimization is proposed to reduce the energy consumption of BBU by decreasing the count of BBU servers. The proposed EE-HCRAN-Hybrid OGASCDASA-SAGMDEBROA method attains 20.48%, 27.34%, and 32.24% higher throughput and 28.30%, 17.30%, and 32.94% lower delay compared to the existing models, such as heterogeneous computational resource allocation for NOMA (HCRA-NOMA-GMECS), energy-efficient hierarchical resource sharing in uplink-downlink decoupled NOMA heterogeneous networks (EE-HRA-NOMA-HetNet), energy-aware hierarchical resource management with backhaul traffic optimization in heterogeneous cellular networks (EA-HRM-BTO-HCN), respectively.

Power-Aware User Association and Renewable Energy Configuration for the Optimized On-Grid Energy in Hybrid-Energy Heterogeneous Cellular Networks

Power-Aware User Association and Renewable Energy Configuration for the Optimized On-Grid Energy in Hybrid-Energy Heterogeneous Cellular Networks

A Base Station Sleeping Strategy in Heterogeneous Cellular Networks Based on User Traffic Prediction

A Base Station Sleeping Strategy in Heterogeneous Cellular Networks Based on User Traffic Prediction

A joint resource optimization allocation algorithm for NOMA‐D2D communication

AbstractThe AIoT, with its artificial intelligence capabilities, can further enhance Device‐to‐Device (D2D) communication. Based on Non‐Orthogonal Multiple Access (NOMA), D2D technology can effectively alleviate wireless spectrum resource pressure and improve the capacity of heterogeneous cellular networks. However, it also introduces significant system interference issues. In this paper, a resource allocation algorithm is proposed for the NOMA‐D2D heterogeneous cellular network, based on a multi‐agent deep reinforcement learning framework. Firstly, the algorithm allocates appropriate channels to D2D clusters. Then, the power allocation factors and D2D transmit power are jointly optimized to suppress the interference and improve the system performance. Simulation results show that both the channel allocation efficiency and the power control performance of the system can be significantly improved.

Energy-efficient joint resource allocation for heterogeneous cellular networks with wireless backhauls

The extensive utilization of wireless services, coupled with the exponential surge in data traffic, has triggered substantial energy consumption. Thereby, growing attentions have been paid to energy-efficient heterogeneous cellular networks (HCNs). In this paper, we concentrate on the joint resource allocation issue under the framework of the non-orthogonal multiple access (NOMA) assisted HCNs with wireless backhauls. To furthermore improve the total system energy efficiency (EE) while ensuring the quality of service (QoS), we formulate the optimization problem as a hybrid joint resource allocation (HJRA) of integer programming and continuous optimization under the cross-tier interference threshold and minimum data rate constraint. The non-convex nature of the optimization problem arises from the fractional objective function and non-convex constraints, making it intractable to efficiently get an exact solution. In this regard, a quantum-inspired political optimizer (QPO) algorithm is devised to find the optimal solution for the HJRA issue, which realizes synchronous allocation of backhaul bandwidth, sub-channels, and power. Simulation results confirm the superiority of the QPO regarding the total system EE over other strategies.

Nonlinear wireless energy harvesting based uplink transmission in K-tier heterogeneous networks over Nakagami-m fading channels

With the widespread application of various battery-powered devices, it is very challenging to sustainably meet the tremendous wireless transmission requirements over limited spectrum. We propose a wireless energy harvesting (EH) based uplink transmission scheme for the K-tier heterogeneous cellular network (HCN) with all the channels undergoing Nakagami-m fading. The locations of base stations (BSs) in each tier, mobile users (MUs), and power beacons (PBs) are properly modeled as independent homogeneous Poisson point processes. Each MU can be associated with a BS in any tier that provides the maximum averaged received signal power. MUs can harvest wireless energy from all the PBs in a nonlinear fashion, and then transmit data to the associated BS by using the harvested energy. We properly model the energy statuses of MUs by defining a series of unequally spaced energy levels according to the probability distribution of EH amount. Through properly modeling the aggregate interference, we analyze the outage probability and the area throughput of the multi-tier HCN. Numerical results show that our proposed scheme can greatly outperform the benchmark scheme in terms of outage probability and area throughput. The impacts of key parameters are revealed through extensive simulations, which can guide the network deployment.

Application of quantum computing based on heterogeneous cellular network algorithm in college student entrepreneurship management

Application of quantum computing based on heterogeneous cellular network algorithm in college student entrepreneurship management

Research on interference coordination techniques in heterogeneous cellular networks

Research on interference coordination techniques in heterogeneous cellular networks

Energy-Spectral-Efficient Heterogeneous Cellular Networks: Joint Optimization of Cross-Tier Inter-BS Cooperation and BS Deployment

Energy-Spectral-Efficient Heterogeneous Cellular Networks: Joint Optimization of Cross-Tier Inter-BS Cooperation and BS Deployment

Outage Probability Analysis for D2D-Enabled Heterogeneous Cellular Networks with Exclusion Zone: A Stochastic Geometry Approach

Outage Probability Analysis for D2D-Enabled Heterogeneous Cellular Networks with Exclusion Zone: A Stochastic Geometry Approach

On Impact of HPA Nonlinearity in NOMA Enabled Heterogeneous Cellular Network

On Impact of HPA Nonlinearity in NOMA Enabled Heterogeneous Cellular Network

Two-Timescale Dynamic Resource Management in Smart-Grid Powered Heterogeneous Cellular Networks

Two-Timescale Dynamic Resource Management in Smart-Grid Powered Heterogeneous Cellular Networks

Mathematical modeling method based on heterogeneous cellular network algorithm and computer multi-dimensional space

Due to the rapid development of services such as computer multi-dimensional space, traditional cellular networks are quantified and diversified, and it is difficult to meet the future connection needs of green network users. The heterogeneous cellular network algorithm places multiple microcells and relay nodes under the macrocell. This multi-layer network architecture can not only shorten the data transmission link, but also reduce the energy consumption of base stations and terminals. In addition, through spectrum space reuse Capability and spectrum efficiency improve the efficiency of the system, but this also increases the number of base stations and network construction costs, and significantly increases energy consumption and operating costs of operators' electricity expenditures. In addition, in order to achieve parallel transmission of data, placing multiple millimeter wave input and output antenna systems in heterogeneous network microcells can meet the high-speed data needs of indoor users, but the antenna array requires many RF links to drive, which increases the hardware implementation. Complexity, cost and energy consumption. According to the above-mentioned problems, a reconfigurable modular robot is established based on the multi-dimensional computer space. It is composed of modules with the same interface and can be assembled into different configurations according to different tasks. Compared with the original robot, the reconfigurable modular robot is more adaptable to the work and environment, and flexible. Then the basic and core technologies such as kinematics, type synthesis, scale synthesis, error and control of the reconfigurable modular robot are mathematically modeled, so as to effectively apply and promote the reconfigurable modular robot in practice, and make it has theoretical and practical value.

Resource Allocation for RIS-Assisted Device-to-Device Communications in Heterogeneous Cellular Networks

In recent years, with the explosive growth of data traffic, communication base stations (BSs) need to serve more and more users. Offloading traffic from BSs has become an efficient way to reduce the burden on BSs. Device-to-Device (D2D) communications have emerged to improve spectrum utilization by reusing the frequency spectrum of the cellular frequency band. In the general environment, Heterogeneous Cellular Networks (HCNs) including millimeter wave (mm-wave) have appeared. Since the D2D link allows to share of spectrum resources with the cellular user, it will bring potential interference to the cellular user. Fortunately, an emerging technology called Reconfigurable Intelligent Surface (RIS) can mitigate the severe interference caused by D2D links by shaping the incident beam and improving the multipath phase shift. In this paper, we study the resource allocation scheme to maximize the system sum rate, in the RIS-assisted single-cell heterogeneous D2D communication scenario. To solve the Block Coordinate Descent (BCD) problem, the problem of maximizing the sum rate is decomposed into three sub-problems. The resource allocation sub-problem is solved by a coalitional game method based on the game theory. The power allocation problem of the coalition converts the concave function into a convex optimization by mathematical transformation. The problem is solved by the gradient descent method. The local search method is adopted to find the optimum for the phase conversion problem. Then iterate until the difference of sum rate is less than the threshold. The simulation results show that the designed algorithm is superior to other benchmark schemes in the literature.

Power allocation and antenna selection for heterogeneous cellular networks

Power allocation and antenna selection for heterogeneous cellular networks

Network political education optimization based on heterogeneous cellular networks and deep learning

Network political education optimization based on heterogeneous cellular networks and deep learning

Performance Analysis of UL-DL Decoupled Access in Two-Tier Cellular Heterogeneous Networks

With the advent of the 5th generation mobile communication technology (5G) era, cellular networks are evolving towards highly heterogeneous and ultra-dense network structures, posing challenges for achieving high communication rates. Existing coupled access methods can no longer meet user demands. As a promising solution to this issue, decoupled uplink-downlink access has gained significant attention. This paper investigates the performance of decoupled uplink-downlink access in a two-tier cellular network model. We obtain the analytical expressions of association probabilities, distance distribution, and spectral efficiency of base stations (BSs) when femto-cell BSs are selected for uplink access and macro-cell BSs are selected for downlink access by a user device. Our findings provide insights into the selection of access patterns and decoupled methods for better efficiency and quality of service. Furthermore, our model and approach can guide the design and deployment of next-generation networks to enhance performance.

Research on dynamic time warping algorithm and intelligent financial management system based on heterogeneous cellular network

Research on dynamic time warping algorithm and intelligent financial management system based on heterogeneous cellular network

Packet-Level Throughput Analysis and Energy Efficiency Optimization for UAV-Assisted IAB Heterogeneous Cellular Networks

In this paper, we investigate the packet-level throughput and energy efficiency of millimeter-wave unmanned aerial vehicle (UAV)-assisted integrated access and backhaul (IAB) heterogeneous cellular networks with spatiotemporal traffic. Specifically, we develop a theoretical framework to analyze the mean packet throughput and energy efficiency of the network based on stochastic geometry and queueing theory, whereby the spatial randomness of network deployment and the temporal randomness of network traffic can be appropriately characterized. Different from the traditional network performance metrics emphasizing transmission and resource consumption, the packet-level performance helps to better understand the impact of not only packet transmission but also packet waiting time in a multihop network. Simulation results demonstrate that the assistance of IAB-based UAVs can efficiently relieve the load of terrestrial macro- and small-cell networks, and the appropriate network deployment parameters play pivotal roles in improving both the packet-level throughput and energy efficiency performance. By jointly optimizing the key network parameters, the packet energy efficiency can be significantly improved while ensuring the required mean packet throughput of the network.

Interference mitigation in intentional jammers aided non-uniform heterogeneous cellular networks.

Coverage and capacity are optimized in fifth generation (5G) networks by small base station (SBS) distribution in the coverage realm of macro base station (MBS). However, system performance is significantly reduced by inter-cell interference (ICI) because of the orthogonal frequency division multiple access assumption. In addition to ICI, this work considers intentional jammers' interference (IJI) due to the presence of jammers. These Jammers try to inject undesirable energies into the legitimate communication band, which significantly degrade uplink (UL) signal-to-interference ratio (SIR). To reduce ICI and IJI, in this work, we employ SBS muting, where the SBSs near MBS are switched off. To further mitigate ICI and IJI, we use one of the effective interference management schemes a.k.a reverse frequency allocation (RFA). We presume that due to mitigation in ICI and IJI, the UL coverage performance of the proposed network model can be further improved.