Ultra-dense Small Cell Networks Research Articles

Radio propagation and wireless coverage of LSAA-based 5G millimeter-wave mobile communication systems

Millimeter-wave (mmWave) communications will be used in fifth-generation (5G) mobile communication systems, but they experience severe path loss and have high sensitivity to physical objects, leading to smaller cell radii and complicated network architectures. A coverage extension scheme using large-scale antenna arrays (LSAAs) has been suggested and theoretically proven to be cost-efficient in combination with ultradense small cell networks. To analyze and optimize the LSAA-based network deployments, a comprehensive survey of recent advances in statistical mmWave channel modeling is first presented in terms of channel parameter estimation, large-scale path loss models, and small-scale cluster models. Next, the measurement and modeling results at two 5G candidate mmWave bands (e.g., 28 GHz and 39 GHz) are reviewed and compared in several outdoor scenarios of interest, where the propagation characteristics make crucial contributions to wireless network designs. Finally, the coverage behaviors of systems employing a large number of antenna arrays are discussed, as well as some implications on future mmWave cellular network designs.

Multi-Location-Aware Joint Optimization of Content Caching and Delivery for Backhaul-Constrained UDN.

Mobile edge caching is regarded as a promising way to reduce the backhaul load of the base stations (BSs). However, the capacity of BSs’ cache tends to be small, while mobile users’ content preferences are diverse. Furthermore, both the locations of users and user-BS association are uncertain in wireless networks. All of these pose great challenges on the content caching and content delivery. This paper studies the joint optimization of the content placement and content delivery schemes in the cache-enabled ultra-dense small-cell network (UDN) with constrained-backhaul link. Considering the differences in decision time-scales, the content placement and content delivery are investigated separately, but their interplay is taken into consideration. Firstly, a content placement problem is formulated, where the uncertainty of user-BS association is considered. Specifically, different from the existing works, the specific multi-location request pattern is considered that users tend to send content requests from more than one but limited locations during one day. Secondly, a user-BS association and wireless resources allocation problem is formulated, with the objective of maximizing users’ data rates under the backhaul bandwidth constraint. Due to the non-convex nature of these two problems, the problem transformation and variables relaxation are adopted, which convert the original problems into more tractable forms. Then, based on the convex optimization methods, a content placement algorithm, and a cache-aware user association and resources allocation algorithm are proposed, respectively. Finally, simulation results are given, which validate that the proposed algorithms have obvious performance advantages in terms of the network utility, the hit ratio of the cache, and the quality of service guarantee, and are suitable for the cache-enabled UDN with constrained-backhaul link.

Coverage Analysis for Multi-Request Association Model (MRAM) in a Caching Ultra-Dense Network

This paper examines the impact of multiple requests based user association model on the performance of ultra-dense small cell network. We consider a cache-enabled small cell network where popular files are cached in different small cells according to the spatial popularity of files. Unlike traditional models, where a user sends requests to a single nearby small cell, we propose a multi-request based user association model (MRAM). In this model, a user selects multiple small cells in its vicinity, referred to as neighbors, for sending file requests. This subset of neighbors search the requested file simultaneously, in order to provide it to the user at the small cell level. This results in an improved coverage probability, which increases the cache hit ratio, eventually alleviating the backhaul congestion. We further exploit coverage probability by considering different coverage patterns and derive closed-form expressions based on these coverage scenarios. We concretely demonstrate that the performance of such a multi-request model is improved with user's movement in different regions. Gains obtained from MRAM are quantified in terms of coverage probability through numerical simulations as well as network simulations.

Hypergraph Game Theoretic Solutions for Load Aware Dynamic Access of Ultra-dense Small Cell Networks

A multi-channel access problem based on hypergraph model in ultra-dense small cell networks is studied in this paper. Due to the hyper-dense deployment of samll cells and the low-powered equipment, cumulative interference becomes an important problem besides the direct interference. The traditional binary interference model cannot capture the complicated interference relationship. In order to overcome this shortcoming, we use the hypergraph model to describe the cumulative interference relation among small cells. We formulate the multi-channel access problem based on hypergraph as two local altruistic games. The first game aims at minimizing the protocol MAC layer interference, which requires less information exchange and can converge faster. The second game aims at minimizing the physical layer interference. It needs more information interaction and converges slower, obtaining better performance. The two modeled games are both proved to be exact potential games, which admit at least one pure Nash Equilibrium (NE). To provide information exchange and reduce convergecne time, a cloud-based centralized-distributed algorithm is designed. Simulation results show that the proposed hypergraph models are both superior to the existing binary models and show the pros and cons of the two methods in different aspects.

Machine Learning Aided Context-Aware Self-Healing Management for Ultra Dense Networks With QoS Provisions

The self-organizing network is envisioned as a key technology to future wireless networks, especially for densely deployed small cell scenarios. Self-healing (SH) is an essential functionality to allow the networks to automatically detect and compensate for cell outages, which typically occur when unexpected network failures arise. In this paper, reaping the benefits of machine learning, we propose a novel SH framework in ultra dense small cell networks for meeting the demands of low-cost and fast network operation, quality of service (QoS), and energy efficiency. The proposed SH scheme comprises small cell outage detection (SCOD) and small cell outage compensation (SCOC) to enable self-healing in ultra dense small cell networks. Based on the context information of the partial key performance indicator (KPI) statistics, we propose a novel SCOD algorithm to detect the outage by applying support vector data description (SVDD) approach. The SCOD algorithm detects a small cell outage efficiently considering two situations: KPIs available situation and non-KPIs available situation. Furthermore, in order to compensate the small cell outage, SCOC is formulated as a network utility maximization problem to optimally compensate for the outaged zone in small cell network. A distributed compensation algorithm with low computational complexity is developed to balance the load of small cell networks, considering the QoS provision for users. Simulation results demonstrate that the proposed SH scheme can detect the small cell outage efficiently and can achieve an optimized QoS performance when compensating for the detected small cell outage.

Location-Aware Self-Optimization for Interference Management in Ultra-Dense Small Cell Networks

To disperse traffic explosion in hotspot areas, the operators have been overlaying their formerly deployed legacy networks with small cells in a denser manner. In this letter, a location-aware self-optimization scheme is proposed, which improves per-user throughput by adjusting downlink transmission power offset based on the effective provision of positioning. The simulation results confirm that, without relying on discovery signals, the proposed scheme provides higher average SINR per user equipment than the small cell on/off control scheme with the discovery signal in 3GPP-LTE Standards, and the localized capacity is also improved.

Joint Interference Management in Ultra-Dense Small-Cell Networks: A Multi-Domain Coordination Perspective

Extensive deployment of heterogeneous small cells in cellular networks results in ultra-dense small-cell networks (USNs). The USNs have been established as one of the vital networking architectures in the 5G to expand system capacity and augment network coverage. However, intensive deployment of cells results in a complex interference problem. In this paper, we propose a distributed multi-domain interference management scheme among cooperative small cells. The proposed scheme mitigates the interference while optimizing the overall network utility. In addition, we jointly investigate OFDMA scheduling, TDMA scheduling, interference alignment (IA), and power control. We model small cells’ coordination behavior as an overlapping coalition formation game. In this game, each base station can make an autonomous decision and participate in more than one coalition to perform IA and suppress intra-coalition interference. To achieve this goal, we propose a distributed joint interference management (JIM) algorithm. The proposed algorithm allows each small-cell base station to self-organize and interact into a stable overlapping coalition structure and reduce interference gradually from multi-domain, thus achieving an optimal tradeoff between costs and benefits. Compared with existing approaches, the proposed JIM algorithm provides appreciable performance improvement in terms of total throughput, which is demonstrated by simulation results.

Limitation of SDMA in Ultra-Dense Small Cell Networks

Benefitting from multi-user gain brought by multi-antenna techniques, space division multiple access (SDMA) is capable of significantly enhancing spatial throughput (ST) in wireless networks. Nevertheless, we show in this letter that, even when SDMA is applied, ST would diminish to be zero in ultra-dense networks (UDN), where small cell base stations are fully densified. More importantly, we compare the performance of SDMA, single-user beamforming (SU-BF) (one user is served in each cell) and full SDMA (the number of served users equals the number of equipped antennas). Surprisingly, it is shown that SU-BF achieves the highest ST and critical density, beyond which ST starts to degrade, in UDN. The results in this letter could shed light on the fundamental limitation of SDMA in UDN.

Energy Efficient Backhauling for 5G Small Cell Networks

While the concept of ultra-dense small cell networks (SCNs) has brought a number of significant opportunities for the telecommunication industry, it has also introduced a major challenge for researchers, who must develop techniques to reduce the sharp increase in power consumption that will be required to backhaul traffic from SCNs to the core network. In this research, we investigate the green backhauling challenge for a fifth generation (5G) wireless communication network that uses both the passive optical network (PON) and millimeter wave (mmWave) backhauling to support its diverse groups of customers and applications. Our approach is based on the fact that the energy efficiency figures for the PON and the mmWave technologies are different under a given load condition. The PON technology is more energy efficient under heavy load conditions, whereas the mmWave technology offers better energy efficiency under low load conditions. As such, in response to varying traffic loads during various hours of the day, a fixed backhauling strategy is insufficient to guarantee the minimum power consumption and the required data rates. We formulate an optimization problem that considers the estimated hourly traffic load and determines the most energy efficient backhauling strategy for various hours of the day. Considering the complexity of the optimization problem, we also propose an energy efficient heuristic solution to solve this problem. Simulation results indicate that the proposed solution provides up to 32 percent more energy savings than the existing solution.

Load Balancing for 5G Ultra-Dense Networks Using Device-to-Device Communications

Load balancing is an effective approach to address the spatial–temporal fluctuation problem of mobile data traffic for cellular networks. The existing schemes that focus on channel borrowing from neighboring cells cannot be directly applied to the future 5G wireless networks, because the neighboring cells will reuse the same spectrum band in 5G systems. In this paper, we consider an orthogonal frequency division multiple access ultra-dense small cell network, where device-to-device (D2D) communication is advocated to facilitate load balancing without extra spectrum. Specifically, the data traffic can be effectively offloaded from a congested small cell to other underutilized small cells by D2D communications. The problem is naturally formulated as a joint resource allocation and D2D routing problem that maximizes the system sum-rate. To efficiently solve the problem, we decouple the problem into a resource allocation subproblem and a D2D routing subproblem. The two subproblems are solved iteratively as a monotonic optimization problem and a complementary geometric programming problem, respectively. Simulation results show that the data sum-rate in the neighboring small cells increases 20% on average by offloading the data traffic in the congested small cell to the neighboring small cell base stations.

Radio resource coordination and scheduling scheme in ultra-dense cloud-based small cell networks

In a 5G ultra-dense network, dynamic network topology and traffic patterns lead to excessive system overhead and complex radio resource conflicts. The cloud radio access network and the fog computing have the advantages of high computation capabilities and low transmission delays. Therefore, by taking full advantage of these two characteristics, this study proposes a novel radio resource coordination and scheduling scheme in an ultra-dense cloud-based small cell network. Interference among small cells (or remote radio heads) can be avoided by implementing centralized cooperative processing in the base band unit pool in advance. Resource sharing in coordination and transfer depend on fog computing to relieve the overloaded cloud processing platform and reduce transmission delays, thereby maximizing resource utilization and minimizing system overhead when the network topology and number of users change dynamically. The simulation shows that the proposed scheme can increase the system throughput by 20% compared with the clustering-based algorithm; it can also increase system throughput by 33% compared with the graph coloring algorithm, decrease the signaling overhead by about 50%, and improve network’s quality of service.

On the Fundamental Characteristics of Ultra-Dense Small Cell Networks

In order to cope with the forecasted 1000 increase in wireless capacity demands by 2030, network operators will aggressively densify their network infrastructure to reuse the spectrum as much as possible. However, it is important to realize that these new ultra-dense small cell networks are fundamentally different from the traditional macrocell or sparse small cell networks, and thus UDNs cannot be deployed and operated in the same way as in the last 25 years. In this article, we systematically investigate and visualize the performance impacts of several fundamental characteristics of UDNs that mobile operators should consider when deploying UDNs. Moreover, we also provide new deployment and management guidelines to address the main challenges brought by UDNs in the future.

UNII-MAC protocol: Design and evaluation for 5G ultra-dense small cell networks operating in 5 GHz unlicensed spectrum

Ultra-densification and efficient spectrum utilization are key features for the next 5G wireless networks to address the well-known challenges of high capacity demands and mobile data traffic explosion. In this article, a physical layer and a medium access control (MAC) sublayer are presented for small cells to operate in the 5 GHz unlicensed national information infrastructure (UNII) band. The physical layer is based on filter bank multi-carrier modulation able to achieve better spectral efficiency and access flexibility. The MAC protocol is based on beacon-enabled superframe consisting of scheduled and contention access schemes. The proposed UNII-MAC design relies on a listen-before-talk procedure in order to comply with ETSI regulations and to fairly coexist with neighboring systems sharing the same band. The performance of the UNII-MAC is then evaluated in dense indoor/outdoor deployment scenarios under various parameters and traffic patterns. Moreover, the coexistence between UNII-MAC and WiFi systems is reported. Based on the obtained results, we provide recommendations for 5G small cell deployment in dense environments.

SDN-Based Hierarchical Agglomerative Clustering Algorithm for Interference Mitigation in Ultra-Dense Small Cell Networks

Ultra-dense small cell networks (UD-SCNs) have been identified as a promising scheme for next-generation wireless networks capable of meeting the ever-increasing demand for higher transmission rates and better quality of service. However, UD-SCNs will inevitably suffer from severe interference among the small cell base stations, which will lower their spectral efficiency. In this paper, we propose a software-defined networking (SDN)-based hierarchical agglomerative clustering (SDN-HAC) framework, which leverages SDN to centrally control all sub-channels in the network, and decides on cluster merging using a similarity criterion based on a suitability function. We evaluate the proposed algorithm through simulation. The obtained results show that the proposed algorithm performs well and improves system payoff by 18.19% and 436.34% when compared with the traditional network architecture algorithms and non-cooperative scenarios, respectively.

Resource Split Full Duplex to Mitigate Inter-Cell Interference in Ultra-Dense Small Cell Networks

When a full duplex (FD) system is used in a multi-cell environment, the simultaneous transmission and reception cause an increase in inter-cell interference compared with half duplex (HD) systems. This problem is more severe in ultra-dense small cell network (UDN) environments where small cells are extremely dense. Therefore, the performance gain of FD transmission over traditional HD transmission is significantly degraded by this increase in inter-cell interference. To overcome the performance loss, we consider a new FD operation that can avoid the increased inter-cell interference caused by FD use. The basic idea involves separating the small cell base stations into two groups and using half of the communication resources in a manner similar to HD systems. We compare the performance of conventional HD and FD with the proposed scheme in terms of network throughput. Network throughput physically refers to the total throughput per unit area of the network. The simulation results consider indoor and outdoor scenarios and show that our proposed scheme outperforms conventional FD and conventional HD.

Theoretical Analysis of Interference Effect From Idle Cells in Ultra-Dense Small Cell Networks

One of the key characteristics in ultra-dense small cell networks (UDNs) is the advent of idle cells which have no associated user equipment (UE). Indeed, idle cells always transmit the cell-specific reference signal (CRS), while they do not transmit data signals. In this paper, we focus on providing a theoretical analysis on the effect of idle cells in terms of the aggregate interference and signal-to-interference ratio (SIR). First, we investigate how idle cells affect the CRS interference (i.e., aggregate interference at the CRS) and data interference (i.e., aggregate interference at the data signals). Specifically, we derive the statistical distribution for the ratio of CRS interference to data interference. Second, by using the Kolmogorov–Smirnov statistic, we qualitatively measure the amount of SIR mismatch between CRS SIR and data SIR caused by idle cells in the UDN. In the numerical results, we show that CRS interference becomes larger than data interference with cell densification. We also illustrate that the SIR mismatch between CRS SIR and data SIR becomes severe, as base station (BS)-to-UE density ratio increases (i.e., idle BS ratio increases). Moreover, we can confirm that the SIR mismatch in indoor environment is weaker than outdoor owing to the multiple penetration losses such as outer walls and inner walls.

User Oriented Resource Management With Virtualization: A Hierarchical Game Approach

The explosive advancements in mobile Internet and Internet of Things challenge the network capacity and architecture. The ossification of wireless networks hinders the further evolution toward the fifth generation of mobile communication systems. Ultra-dense small cell networks are considered as a feasible way to meet high-capacity demands. Meanwhile, ultra-dense small cell network virtualization also exploits an insightful perspective for the evolution because of its superiority, such as diversity, flexibility, low cost, and scalability. In this paper, we specify the necessity of resource management in virtualized ultra-dense small cell networks through a mapping and management architecture and consider the problem of user-oriented virtual resource management. Then, we model the virtual resource management problem as a hierarchical game and obtain the closed-form solutions for spectrum, power, and price, respectively. Furthermore, we propose a customer-first (CF) algorithm that characterizes the user-oriented service of virtualization, and analyze its convergence. Simulation results present the effectiveness of the proposed CF algorithm.

Distributed Interference-Aware Power Control in Ultra-Dense Small Cell Networks: A Robust Mean Field Game

In ultra-dense small cell networks, interference mitigation is very important due to severe interference. Interference dynamics caused by time-varying environment should be aware and characterized when an interference-aware power control policy is designed to mitigate interference. Meanwhile, interference perception should not be naturally assumed to have complete information with certainty. Generally, it is known that a generic player will react to all the players actions and states in a power control game, which involves huge interference-related information exchange with dynamics and uncertainties. Therefore, to reduce requirements of complete information, we formulate a robust power control mean field game taking the uncertainties of both state dynamics and cost functions into consideration. To achieve the robust power control, we regard the power control problem as a game with players whose individual states are combined by a disturbance term and a Brownian motion. We derive the robust Fokker–Planck–Kolmogorov and Hamilton–Jacobi–Bellman equations, and based on which we propose the robust interference-aware power control algorithm. Simulation results demonstrate the improved performance and the robustness of the proposed algorithm.

Data-Driven Deployment and Cooperative Self-Organization in Ultra-Dense Small Cell Networks

Ultra-dense small-cell network is widely acknowledged as a key enabler for high capacity wireless networks. Some of the key challenges that ultra-dense networks face are profitable deployment distribution under complex traffic loads and efficient radio resource management (RRM) in excessive interference environments. Poor small-cell deployment locations can lead to excessive interference without clear profit margins and inefficient resource utilization. As such, data-driven small-cell deployment and self-organizing RRM of small-cell clusters are regarded as the two main technologies that can improve ultra-dense small-cell services. This paper first reviews the latest research in data-driven small-cell deployment using structured and unstructured social media data. A combination of irregular clustering techniques is used to identify hotspots, and natural language processing algorithms are used to identify blackspots. This paper then reviews recent advances in self-organization of small-cell RRM and analyzes how data can improve self-organization performance. Moreover, the idea of cooperative self-organization is introduced to further promote the self-organization capability. Finally, two ultra-dense small-cell RRM case studies are presented to demonstrate the performance which improves of cooperative self-organization.

Performance Analysis of Dense Small Cell Networks With Practical Antenna Heights Under Rician Fading

In this paper, we examine the combined impacts of distance-dependent Rician fading channel model and the absolute difference between the heights of base station (BS) and user equipment (UE) antennas on the coverage probability and the area spectral efficiency in an interference-limited ultra-dense (UD) small cell network (SCN). Exploiting distance dependent models for both path loss and multi-path fading, we show that in interference-limited UD-SCNs, Rician fading with variant Rician $K$ factor aggravates the performance loss caused by the difference between the heights of the BS and UE antennas in comparison to Rayleigh fading. In particular, we demonstrate that due to presence of the specular line-of-sight component in the Rician fading, both the coverage probability and the area spectral efficiency experience a steeper decline towards zero as the BS density increases. Our performance analysis has a prominent impact on the deployment of UD-SCNs in the 5th-generation of mobile networks, as it indicates that the right modeling of multi-path fading makes a significant difference when assessing the performance of UD-SCNs with non-identical UE-BS antenna heights.