Ultra-dense Network Deployments Research Articles

CEAR: A cooperation based energy aware reward scheme for next generation green cognitive radio networks

Cognitive Radio (CR) networks are envisioned as a key empowering technology of the fifth-generation (5G) wireless communication networks, which solves the major issues of 5G, like high-speed data transmission, seamless connectivity, and increased demand for mobile data. Another significant characteristic of the 5G network is green communications, as energy consumption from the communication field is predicted to rise remarkably by the year 2030. In this work, we are concerned about energy-related issues and propose a cooperation-based energy-aware reward scheme (CEAR) for next-generation green CR networks. The proposed CEAR scheme is based on the antenna and temporal diversity of the primary users (PUs). For providing the service to the PUs, the users of another network called cognitive users (CUs) work as a cooperative relay node, and, in return, they get more spectrum access opportunities as a reward from the primary network. The CUs with delay-tolerant data packets take a cooperative decision by recognizing the availability and traffic load of PUs, channel state information, and data transmission requirements. We utilize the optimal stopping protocol for solving the decision-making problem and use the backward induction method to obtain the optimal cooperative solution. The simulation results reveal notable enhancements in energy efficiency (EE) of CUs compared with other cooperative schemes. The proposed CEAR scheme is more energy-efficient for ultra-dense network deployment because results show that the CU’s EE, spectral efficiency (SE), and throughput improved with the increase of PUs.

Secure 5G Positioning With Truth Discovery, Attack Detection, and Tracing

The fifth-generation (5G) cellular network is expected to provide submeter positioning accuracy without draining the battery of user equipment (UE). As a solution, ultradense network (UDN) deployment and network-based positioning were proposed. However, the openness of UDN and the vulnerability of network devices [e.g., access nodes (ANs)] make it easy for attackers to poison such a positioning system. However, no existing work explores how to overcome this issue. This article concentrates on jamming and collusion attacks in the network-based positioning system. Specifically, we design a novel scheme that contains three functional modules to erase the influence of these attacks. A truth discovery module applies a clustering-based method aiming to generate the most approximate position value and find out suspicious signals. Based on neural network models, we further develop an attack detection module and an attack tracing module to perceive attacked UE and locate malicious or attacked ANs. Through simulation, we conduct extensive experiments to illustrate the effectiveness of our scheme. The result shows high detection and tracing accuracy with very simple neural network models, which also implies the potential of our proposed scheme in practical deployment.

A lightweight cell switching and traffic offloading scheme for energy optimization in ultra-dense heterogeneous networks

One of the major capacity boosters for 5G networks is the deployment of ultra-dense heterogeneous networks (UDHNs). However, this deployment results in a tremendous increase in the energy consumption of the network due to the large number of base stations (BSs) involved. In addition to enhanced capacity, 5G networks must also be energy efficient for it to be economically viable and environmentally friendly. Dynamic cell switching is a very common way of reducing the total energy consumption of the network, but most of the proposed methods are computationally demanding, which makes them unsuitable for application in ultra-dense network deployment with massive number of BSs. To tackle this problem, we propose a lightweight cell switching scheme also known as Threshold-based Hybrid cEll swItching Scheme (THESIS) for energy optimization in UDHNs. The developed approach combines the benefits of clustering and exhaustive search (ES) algorithm to produce a solution whose optimality is close to that of the ES (which is guaranteed to be optimal), but is computationally more efficient than ES and as such can be applied for cell switching in real networks even when their dimension is large. The performance evaluation shows that THESIS significantly reduces the energy consumption of the UDHN and can reduce the complexity of finding a near-optimal solution from exponential to polynomial complexity.

Practical Optimization and Game Theory for 6G Ultra-Dense Networks: Overview and Research Challenges

Ultra-dense networks (UDNs) have been employed to solve the pressing problems in relation to the increasing demand for higher coverage and capacity of the fifth generation (5G) wireless networks. The deployment of UDNs in a very large scale has been envisioned to break the fundamental deadlocks of beyond 5G or the sixth generation (6G) networks and deliver many more orders of magnitude gains that today’s technologies achieve. However, the mathematical tool to optimize the system performance under the stringent radio resource constraints is widely recognized to be a formidable challenge. System-level performance optimization of current UDNs are usually conducted by relying on numerical simulations, which are often time-consuming and have become extremely difficult in the context of 6G with extremely high density. As such, there is an urgent need for developing a realistic mathematical model for optimizing the 6G UDNs. In this paper, we introduce challenges as well as issues that have to be thoroughly considered while deploying UDNs in realistic environment. We revisit efficient mathematical techniques including game theory and real-time optimization in the context of optimizing UDNs performance. In addition, emerging technologies which are suitable to apply in UDNs are also discussed. Some of them have already been used in UDNs with high efficiency while the others which are still under investigation are expected to boost the performance of UDNs to achieve the requirements of 6G. Importantly, for the first time, we introduce the joint optimal approach between realtime optimization and game theory (ROG) which is an effective tool to solve the optimization problems of large-scale UDNs with low complexity. Then, we describe two approaches for using ROG in UDNs. Finally, some case study of ROG are given to illustrate how to apply ROG for solving the problems of different applications in UDNs.

Coordinated 3D spectrum utilization for B5G indoor HetNets: A collaborated crowdsensing approach

The 5G and beyond (B5G) networks are expected to provide significantly increased capacity for diverse services with limited spectrum resources. However, new aspects of B5G networks particularly the ultra-dense network deployment and the heterogeneous network structure, make spectrum resources highly distributed in three-dimension (3D), which brings unprecedented challenges for highly efficient spectrum utilization, especially in an indoor environment. To tackle the challenges on dynamic spectrum utilization and improving the volume capacity of indoor 3D networks, a collaborated crowdsensing approach is proposed for the coordinated 3D spectrum utilization through integrating the crowdsensing, data analytics, and software defined network (SDN) techniques. The integration of sensing, learning, and intelligent control provides critical capabilities for timely observing 3D radio resources and enabling the coordinated radio resource utilization among co-existing indoor heterogeneous networks (HetNets). Case study confirms the superiority of the proposed coordinating method on achieved volume capacity.

Ultra-Dense Networks: A Holistic Analysis of Multi-Piece Path Loss, Antenna Heights, Finite Users and BS Idle Modes

We discover a new capacity scaling law in ultra-dense networks under practical system assumptions, such as a general multi-piece path loss model, a non-zero base station to user equipment antenna height difference, and a finite user equipment density. The intuition and implication of this new capacity scaling law are completely different from those found in the year 2011. That law indicated that the increase of the interference power caused by a denser network would be exactly compensated by the increase of the signal power due to the reduced distance between transmitters and receivers, and thus, network capacity should grow linearly with network densification. However, we find that both the signal and interference powers become bounded in practical ultra-dense networks, which leads to a constant capacity scaling law. Moreover, our new discovery on the constant capacity scaling law indicates three network optimization problems respectively for base station deployment, user equipment scheduling and base station coordination. These three optimization problems are justified and solved in this paper, shedding new light on the deployment and optimization of ultra-dense networks.

SDN-Based Routing for Backhauling in Ultra-Dense Networks

Ultra-Dense Network (UDN) deployment is considered a key element to achieve the requested capacity in future fifth-generation (5G) mobile networks. Backhaul networks in UDNs are formed by heterogeneous links with multi-hop connections and must handle massive traffic. Backhauling in future 5G networks may represent the capacity bottleneck. Therefore, there is the need for efficient and flexible routing schemes able to handle the dynamism of the traffic load in capacity-limited networks. Toward this goal, the emerging Software-Defined Network (SDN) paradigm provides an efficient solution, transferring the routing operation from the data plane switches to a central controller, thus achieving more flexibility, efficiency, and faster convergence time in comparison to conventional networks. This paper proposes and investigates an SDN-approach for an efficient routing in a capacity-limited backhaul network that carries data and control traffic of a heterogeneous UDN. The routing algorithm is centralized in the SDN controller and two different types of traffic flow are considered: data and control plane coordination traffic. The goal is to reduce or even to avoid the amount of traffic that the backhaul network is not able to support, distributing in a fair way the eventual lack of bandwidth among different access points. Simulation results show that with the considered approach the performance significantly improves, especially when there is an excess of traffic load in the network. Moreover, thanks to the SDN-based design, the network can reconfigure the traffic routing depending on the changing conditions.

A Context-aware Radio Access Technology selection mechanism in 5G mobile network for smart city applications

The Fifth Generation (5G) mobile network will revolutionize the way of communication by supporting new innovative applications that require low latency and high data rates in smart city environments. In order to meet these applications' requirements, Ultra-Dense Network (UDN) is considered as one of the promising technological enablers in 5G. 5G UDN deployments are envisaged to be heterogeneous and dense, mainly through the provisioning of small cells such as picocells and femtocells, from different Radio Access Technologies (RATs). Nevertheless, various studies have reported that the densification is not always beneficial to the network performance. As the network density increases, this will pose further requirements and complexity of determining which RAT a user should connect with at a given time. Hence, an efficient RAT selection mechanism to choose the best Radio Access Technology among multiple available ones is a must. This paper proposes a new Context-aware Radio Access Technology (CRAT) selection mechanism that examines the context of the user and the networks in choosing the appropriate RAT to serve. A simplified conceptual model of the Context-aware RAT selection is introduced. Then, a mathematical model of CRAT considering the user and network context is derived, adopting Analytical Hierarchical Process (AHP) for weighting the importance of the selection criteria and TOPSIS for ranking the available RATs. The proposed CRAT was implemented and validated in NS3 simulation environment. The performance of the proposed mechanism was tested using two different scenarios within a smart city environment, called a shopping mall and urban city scenarios. The obtained results showed that CRAT outperforms the conventional approach namely A2A4 of RAT selection in terms of the number of handovers, average network delay, throughput, and packet delivery ratio.

On the Performance of AoA–Based Localization in 5G Ultra–Dense Networks

Cellular systems are undergoing a transformation toward the fifth generation (5G). Envisioned applications in 5G include intelligent transport system (ITS), autonomous vehicles, and robots as a part of future roads, factories, and society. These applications rely to a great extent on accurate and timely location information of connected devices. This paper proposes a practical scheme for acquiring precise and timely position information by means of a user–centric ultra–dense network (UDN) architecture based on an edge cloud. The considered solution consists of estimating and tracking the azimuth angle–of–arrival (AoA) of the line–of–sight (LoS)–path between a device and multiple transmission–reception points (TRPs), each having a uniform linear antenna array (ULA). AoA estimates from multiple TRPs are fused into position estimates at the edge cloud to obtain timely position information. The extensive measurements have been carried out using a proof–of–concept software–defined–radio (SDR) testbed in order to experimentally assess the achievable positioning accuracy of the proposed architecture. A realistic UDN deployment scenario has been considered in which TRPs consist of antenna arrays mounted on lamp posts. Our results show that practical UDNs can provide sub–meter positioning accuracy of mobile users by employing ULAs with at least four antennas per TRP and by taking into account the non–idealities of the ULAs' phase and magnitude response.

A Hierarchical SDN Architecture for Ultra-Dense Millimeter-Wave Cellular Networks

To cope with the tremendous growth in mobile data traffic, ultra-dense networks (UDNs) will be deployed in the future cellular network. Meanwhile, the enormous amount of available spectrum in millimeter-wave (mmWave) bands can be also exploited to increase the wireless link capacity. In accordance with these trends, this article introduces a novel hierarchical software-defined networking (SDN) architecture to facilitate the deployment of UDNs with both microwave base stations and mmWave access points. Aimed at reducing the cost of computational complexity and signaling overhead, the novel SDN architecture employs a semi-distributed design approach by configuring two levels of controllers: the centralized superior SDN controller and the localized subordinate SDN controller. Some practical challenges posed by the characteristics of mmWave transmissions, such as high propagation loss, channel blockage, and directional beamforming, are also discussed. To deal with such challenges, we then propose several important network operations for the hierarchical SDN, including dynamic subordinate SDN management, mobility management, and user-centric design. We finally provide simulation results to demonstrate the performance advantages of our proposals.

A Multi-element Microstrip Antenna for LTE Bands, Wi-Fi and WiMAX Application in Femtocell Network

Interference management is the key point in the deployment of ultra-dense networks. Several techniques in physical and data-link layers have been discussed and proposed to provide lower power and better network capacity, while minimizing the cost and complexity of FemtoCell deployment. The applicability of an antenna with microstrip technology that employs multiple elements is developed here for coverage enhancement of FemtoCell network. The antenna proposed in this research has a size of 35 x 35 x 1.58 mm 3 , it is printed on a commercially available FR4 dielectric substrate and designed for the frequency band from 1.9 GHz to 3.5 GHz. The different results obtained of the studied antenna in the FemtoCell scenario are discussed.

A Multi-element Microstrip Antenna for LTE Bands, Wi-Fi and WiMAX Application in Femtocell Network

Interference management is the key point in the deployment of ultra-dense networks. Several techniques in physical and data-link layers have been discussed and proposed to provide lower power and better network capacity, while minimizing the cost and complexity of FemtoCell deployment. The applicability of an antenna with microstrip technology that employs multiple elements is developed here for coverage enhancement of FemtoCell network. The antenna proposed in this research has a size of 35 x 35 x 1.58 mm 3 , it is printed on a commercially available FR4 dielectric substrate and designed for the frequency band from 1.9 GHz to 3.5 GHz. The different results obtained of the studied antenna in the FemtoCell scenario are discussed.

Impact of Interference Between Neighbouring 5G Micro Operators

Local small cell deployments will become an important part of the future 5G networks, in particular in the higher frequency bands. In order to speed up the wide-spread deployment of such ultra-dense networks, new business and spectrum authorization models are needed. The recently proposed concept of micro operators with local spectrum micro licensing has gained significant interest in research, industry and regulation to complement the traditional models based on networks deployed and operated by the mobile network operators. While assessing the applicability of the proposed micro operator concept, one important aspect is to evaluate the impact of the inter-operator interference on the performance of the victim network when deployed in the same or adjacent channel. To support such interference evaluations between micro operators, this paper proposes a deployment scenario including two neighbouring buildings, propagation models for connections both within a building and between the buildings, and a criteria for the required minimum separation distance based on the observed throughput loss. Finally, system simulations are performed to evaluate the impact of the key deployment aspects on the required minimum separation distance between the micro operators in the 3.5 GHz band. The obtained results indicate that the required minimum separation distances are highly scenario-specific, which needs to be considered in the overall local spectrum micro licensing model development and the setup of appropriate rules to coordinate the interference.

Possible Security Attack Modeling in Ultradense Networks Using High-Speed Handover Management

The next generation of mobile communication has progressed toward the deployment of small cells to meet the growing demands of increased capacity and QoS as compared to the conventional method, where all the computations were performed by the base station (BS)'s only. To reduce burden at the BS side, small cells deployment has been stressed upon, thus resulting in the formation of ultradense networks (UDN) having high concentration of small cells (e.g., picocell, femtocell, hotspots) and as a counter effect of which distance between two small cells is reduced to a greater extent. With such a close association of cells in UDN, the probability of frequent handovers also increases abruptly. As a result, the chances for attacker to spoof the bandwidth also increases many folds. In this paper, we have analyzed SNR, signal-to-interference-plus-noise ratio, and channel quality information channel parameters, such that the position of moving users at which handover is initiated in picocell deployment of UDN can be traced out successfully or region where the probability of attackers presence is high. Through this paper, we have tried to introduce the attacking scenario for the high mobility conditions in UDN.

Mobility Management in Ultra-Dense Networks: Handover Skipping Techniques

Ultra-dense network deployment is a key technology for potentially achieving the capacity target of next-generation wireless communication systems. However, such a deployment results in cell proliferation and cell size decrement, leading to an increased number of handovers and limited sojourn time within a cell, which severely degrade the user’s quality of service (QoS). In this paper, we propose two intelligent handover skipping techniques to overcome the high handover rates. The first technique considers a user associated with a single base station (BS) and the decision to skip a handover is based on the upcoming cell’s topology; we consider three criteria: 1) the area of the cell; 2) the trajectory distance within the cell; and 3) the distance of the BS from the cell edge. The second technique exploits BS cooperation and enables a dynamic handover skipping scheme, where the skipping decision is taken based on the BSs of three consecutive cells in the user’s trajectory. This technique achieves a balance between BS cooperation and single BS transmission and manages to maintain a good QoS during the skipping phase. We show that the proposed techniques reduce both the handover rate and handover cost and outperform the conventional techniques for moderate to high-velocity values.

Research on Downlink Precoding for Interference Cancellation in Massive MIMO Heterogeneous UDN

In order to solve the data surge brought by largescale increasing of mobile de-vices, Massive MIMO ultra dense networking can greatly improve the system spectral efficiency and energy efficiency. It plays an important role in coping with the exponential growth of the business, but also brought big problems and challenges. For heterogeneous ultra dense networks, both macro and femto users are facing with both the cross-layer interference and co-layer in-terference. The precoding technology studied in this paper resolves the cross-layer interference and co-layer interference for macro users and femto users, and lays a theoretical foundation for the deployment of heterogeneous and ultra dense networks.

Multipath multihop mmWave backhaul in ultra-dense small-cell network

Ultra-Dense Network (UDN) is considered to be the key enabler for realizing capacity goals set by 5G. The major concern in UDN deployment is the backhaul network, which should be scalable, cost-effective, and have sufficient capacity to support massive small cell traffic. Otherwise, the backhaul can become the bottleneck of the network. In this paper, we propose a wireless backhaul solution for UDN deployment by considering MultiPath-MultiHop (MPMH) backhaul architecture in mmWave frequency band. In addition, we propose a distributed routing scheme to forward the backhaul traffic over the multihop network. Backhaul capacity and line-of-sight probability of the proposed backhaul architecture for various picocell densities were compared with direct, multiple-association, and multihop backhaul schemes under interference limited scenarios in outdoor and indoor small cell deployments. The simulation results indicate that the MPMH mmWave backhaul is the most cost-effective and scalable solution for UDN deployment.

Performance Limits of Network Densification

Network densification is a promising cellular deployment technique that leverages spatial reuse to enhance coverage and throughput. Recent work has identified that at some point ultra-densification will no longer be able to deliver significant throughput gains. In this paper, we provide a unified treatment of the performance limits of network densification. We develop a general framework, which incorporates multi-slope pathloss and the entire space of shadowing and small scale fading distributions, under strongest cell association in a Poisson field of interferers. First, our results show that there are three scaling regimes for the downlink signal-to-interference-plus-noise ratio (SINR), coverage probability, and average per-user rate. Specifically, depending on the near-field pathloss and the fading distribution, the user performance of 5G ultra dense networks (UDNs) would either monotonically increase, saturate, or decay with increasing network density. Second, we show that network performance in terms of coverage density and area spectral efficiency can scale with the network density better than the user performance does. Furthermore, we provide ordering results for both coverage and average rate as a means to qualitatively compare different transmission techniques that may exhibit the same performance scaling. Our results, which are verified by simulations, provide succinct insights and valuable design guidelines for the deployment of 5G UDNs.

User Bandwidth Demand Centric Soft-Association Control in Wi-Fi Networks

To address the challenge of unprecedented growth in mobile data traffic, ultra-dense network deployment is a cost efficient solution to offload the traffic over some small cells. The overlapped coverage areas of small cells create more than one candidate access points for one mobile user. Signal strength based user association in IEEE 802.11 results in a significantly unbalanced load distribution among access points. However, the effective bandwidth demand of each user actually differs vastly due to their different preferences for mobile applications. In this paper, we formulate a set of non-linear integer programming models for joint user association control and user demand guarantee problem. In this model, we are trying to maximize the system capacity and guarantee the effective bandwidth demand for each user by soft-association control with a software defined network controller. With the fact of NP-hard complexity of non-linear integer programming solver, we propose a Kernighan Lin Algorithm based graph-partitioning method for a large-scale network. Finally, we evaluated the performance of the proposed algorithm for the edge users with heterogeneous bandwidth demands and mobility scenarios. Simulation results show that the proposed adaptive soft-association control can achieve a better performance than the other two and improves the individual quality of user experience with a little price on system throughput.

A Planning and Optimization Framework for Ultra Dense Cellular Deployments

To accommodate the ever-expanding wireless data traffic volumes, mobile network operators are complementing their macrocellular networks by deploying low-power base stations (or small cells) to offload traffic from congested macrocells and to reuse spectrum. To that end, Ultra Dense Network (UDN) deployments provide means to aggressively reuse spectrum, thus providing significant enhancements in terms of system capacity. However, these deployments entail several challenges, including the increased complexity in network planning and optimization. In this paper, we propose a versatile optimization framework for planning UDN deployments. The planning and optimization framework is underpinned by metrics that consider scalability in terms of number of users, cost of densification, and fairness. The proposed methodology is evaluated using a real-world UDN planning case. The numerical results expose a number of interesting insights, including the impact of different bandwidth allocation strategies and spatial service demand distribution on the performance of various network topologies. Specifically, we provide a performance comparison of the optimized UDN topologies versus random (unplanned), regular grid, and heuristically derived UDN topologies. This comparison further underlines the need for flexible network planning and optimization frameworks as different operator performance metrics of interest may require different radio access networks configurations.