Ultra-dense Deployment Of Small Cells Research Articles

Dynamic Repositioning of Aerial Base Stations for Enhanced User Experience in 5G and Beyond.

The ultra-dense deployment (UDD) of small cells in 5G and beyond to enhance capacity and data rate is promising, but since user densities continually change, the static deployment of small cells can lead to wastes of capital, the underutilization of resources, and user dissatisfaction. This work proposes the use of Aerial Base Stations (ABSs) wherein small cells are mounted on Unmanned Aerial Vehicles (UAVs), which can be deployed to a set of candidate locations. Furthermore, based on the current user densities, this work studies the optimal placement of the ABSs, at a subset of potential candidate positions, to maximize the total received power and signal-to-interference ratio. The problems of the optimal placement for increasing received power and signal-to-interference ratio are formulated, and optimal placement solutions are designed. The proposed solutions compute the optimal candidate locations for the ABSs based on the current user densities. When the user densities change significantly, the proposed solutions can be re-executed to re-compute the optimal candidate locations for the ABSs, and hence the ABSs can be moved to their new candidate locations. Simulation results show that a 22% or more increase in the total received power can be achieved through the optimal placement of the Aerial BSs and that more than 60% users have more than 80% chance to have their individual received power increased.

Fiber-terahertz-fiber bridge system in the 355-GHz band using a simple optical frequency comb and a photonics-enabled receiver.

This Letter demonstrates a high-speed fiber-terahertz-fiber system in the 355-GHz band using stable optical frequency comb generation and a photonics-enabled receiver. At the transmitter, a single dual-drive Mach-Zehnder modulator is employed to generate a frequency comb by driving the modulator under an optimal condition. At the antenna site, a photonics-enabled receiver consisting of an optical local oscillator signal generator, a frequency doubler, and an electronic mixer is used to downconvert the terahertz-wave signal to the microwave band. Simple intensity modulation and a direct detection method are used for transmitting the downconverted signal to the receiver over the second fiber link. To demonstrate the proof of concept, we transmitted a 16-quadrature amplitude modulation (QAM) orthogonal frequency-division multiplexing signal over a system consisting of two radio-over-fiber links and a 4 m wireless link in the 355-GHz band and achieved a line rate of 60 Gb/s. We also successfully transmitted a 16-QAM subcarrier multiplexing single-carrier signal over the system and achieved a capacity of 50 Gb/s. The proposed system can facilitate the deployment of ultra-dense small cells in high-frequency bands in beyond-5G networks.

Fifth-generation new radio millimeter-wave radio signal transmission over a seamless fiber-terahertz mobile fronthaul system for an ultra-dense small cell network.

This Letter demonstrates the transmission of fifth-generation new radio (5G NR) millimeter-wave signals over a seamless fiber-terahertz-wave mobile fronthaul system in the 350 GHz band for an ultra-dense small cell network. The system utilizes a simple optical heterodyne method at the transmitter and direct detection at the receiver. As a proof-of-concept demonstration, we successfully transmitted 256- and 64-quadrature amplitude modulation 5G-NR-compliant signals at 24.2 and 38 GHz over a seamless fiber-terahertz system in the 350 GHz band. The proposed system can provide a simple solution to facilitate the deployment of ultra-dense small cells in high-frequency bands in 5G networks and beyond.

High-speed fiber-wireless-fiber system in the 100-GHz band using a photonics-enabled receiver and optical phase modulator.

This Letter describes a high-speed yet simple fiber-wireless-fiber system in the 100-GHz band using a photonics-enabled receiver and optical phase modulator. At the antenna site, a millimeter-wave signal is down-converted to the microwave band using an electronic mixer with a local oscillator signal generated remotely using photonic technology. The down-converted signal is converted to an optical signal using an optical phase modulator. At the receiver, a simple direct detection of the phase-modulated signal is performed using optical filtering technology. To demonstrate the proof-of-concept, we successfully transmitted a 64-quadrature amplitude modulation orthogonal frequency-division multiplexing signal with a record line rate of 80 Gb/s (net data rate of 55 Gb/s) over a system consisting of two radio-over-fiber links and a 5 m wireless link in the 100-GHz band. The proposed system with simple antenna sites and optical transceivers can facilitate the deployment of ultra-dense small cells in high-frequency bands in beyond-5G networks.

Millimeter-wave radio-over-fiber system using optical phase modulation and photonic downconversion for uplink fronthaul transmission.

This Letter proposes a high-performance radio-over-fiber (RoF) system for high-speed and high-fidelity analog waveform transmission of radio signals in the millimeter-wave band in the uplink direction. At the antenna site, the system utilizes a newly fabricated low half-wave voltage broadband phase modulator to convert a millimeter-wave radio signal into an optical signal. At the receiver, by using photonic downconversion and optical filtering technology, a simple direct detection and downconversion of the signal to the microwave band can be achieved simultaneously. As a demonstration of proof of concept, we successfully transmitted a 1024-quadrature amplitude modulation (QAM) narrowband orthogonal frequency-division multiplexing signal at 38 GHz and a 60 Gb/s 64-QAM single-carrier signal at 26.5 GHz over a 20 km RoF system. The system is promising for facilitating the deployment of ultra-dense small cells in high-frequency bands in 5G and beyond networks.

Energy-Efficient Resource Allocation for Ultra-Dense Licensed and Unlicensed Dual-Access Small Cell Networks

In this study, an energy-efficient self-organized framework for sub-channel allocation and power allocation is presented for ultra-dense small cell networks, which can operate in both licensed and unlicensed bands. In order to protect legacy WiFi devices (operating in unlicensed bands), we consider the Long-Term Evolution (LTE) operation in unlicensed bands based on Carrier Sense Adaptive Transmission (CSAT), in which 'ON' and 'OFF' duty cycle approach is utilized. On the other hand, there are severe interference management problems among small cells (operating in licensed and unlicensed bands) and between macro cells and small cells (operating in licensed bands) due to co-channel and ultra-dense deployment of small cells. This article proposes a self-organized optimization framework for the allocation of sub-channels and power levels by exploiting a non-cooperative game with the objective to maximize the energy efficiency of dual-access small cells without creating harmful impact on coexisting network entities including macro cell users, small cell users, and legacy WiFi devices. Simulation results show that the proposed scheme outperforms (6 and 11 percent) and (8 and 18 percent) the round-robin and the spectrum-efficient schemes, respectively, for two different small cell scenarios. In addition, it is shown that for less channel state information (CSI) estimation errors ς = 0.02, the maximum performance degradation of the proposed scheme is reasonably small (5.5 percent) as compared to the perfect CSI.

Deployment of Clustered‐Based Small Cells in Interference‐Limited Dense Scenarios: Analysis, Design, and Trade‐Offs

Network densification is one of the most promising solutions to address the high data rate demands in 5G and beyond (B5G) wireless networks while ensuring an overall adequate quality of service. In this scenario, most users experience significant interference levels from neighbouring mobile stations (MSs) and access points (APs) making the use of advanced interference management techniques mandatory. Clustered interference alignment (IA) has been widely proposed to manage the interference in densely deployed scenarios with a large number of users. Nonetheless, the setups considered in previous works are still far from the densification levels envisaged for 5G/B5G networks that are considered in this paper. Moreover, prior designs of clustered‐IA systems relied on oversimplified channel models and/or enforced single‐stream transmission. In this paper, we explore an ultradense deployment of small cells (SCs) to provide coverage in 5G/B5G wireless networks. A novel cluster design based on a size‐restricted k‐means algorithm to divide the SCs into different clusters is proposed taking into account path loss and shadowing effects, thus providing a more realistic solution than those available in the current literature. Unlike previous works, this clustering method can also cater for spatial multiplexing scenarios. Also, several design parameters such as the number of transmit antennas, multiplexed data streams, and deployed APs are analyzed in order to identify trade‐offs between performance and complexity. The relationship between density of network elements per area unit and performance is investigated, thus allowing to illustrate that there is an optimal coverage area value over which the network resources should be distributed. Moreover, it is shown that the spectral‐efficiency degradation due to the intercluster interference in ultradense networks (UDNs) points to the need of designing an interference management algorithm that accounts for both intracluster and intercluster interferences. Simulation results provide key insights for the deployment of small cells in interference‐limited dense scenarios.

On Maximizing Energy and Spectral Efficiencies Using Small Cells in 5G and Beyond Networks.

Addressing high capacity at low power as a key design goal envisages achieving high spectral efficiency (SE) and energy efficiency (EE) for the next-generation mobile networks. Because most data are generated in indoor environments, an ultra-dense deployment of small cells (SCs), particularly within multistory buildings in urban areas, is revealed as an effective technique to improve SE and EE by numerous studies. In this paper, we present a framework exploiting the four most interconnected-domain, including, power, time, frequency, and space, in the perspectives of SE and EE. Unlike existing literature, the framework takes advantage of higher degrees of freedom to maximize SE and EE using in-building SCs for 5G and beyond mobile networks. We derive average capacity, SE, and EE metrics, along with defining the condition for optimality of SE and EE and developing an algorithm for the framework. An extensive system-level evaluation is performed to show the impact of each domain on SE and EE. It is shown that employing multiband enabled SC base stations (SBSs) to increase operating spectrum in frequency-domain, reusing spectrum to SBSs more than once per building in spatial-domain, switching on and off each in-building SBS based on traffic availability to reduce SBS power consumption in power-domain, and using eICIC to avoid co-channel interference due to sharing spectrum with SBSs in time-domain can achieve massive SE and EE. Finally, we show that the proposed framework can satisfy SE, EE, as well as user experience data rate requirements for 5G and beyond mobile networks.

Velocity-Aware Handover Self-Optimization Management for Next Generation Networks

The fifth generation (5G) network is an upcoming standard for wireless communications that coexists with the current 4G network to increase the throughput. The deployment of ultra-dense small cells (UDSC) over a macro-cell layer yields multi-tier networks, which are known as heterogeneous networks (HetNets). HetNets play a key role in the cellular network to provide services to numerous users. However, the number of handovers (HOs) and radio link failure (RLF) greatly increase due to the increase in the UDSC in the network. Therefore, mobility management becomes a very important function in a self-organizing network to improve the system performance. In this paper, we propose a velocity-based self-optimization algorithm to adjust the HO control parameters in 4G/5G networks. The proposed algorithm utilizes the user’s received power and speed to adjust the HO margin and the time to trigger during the user’s mobility in the network. Simulation results demonstrate that the proposed algorithm achieves a remarkable reduction in the rate of ping-pong HOs and RLF compared with other existing algorithms, thereby outperforming such algorithms by an average of more than 70% for all HO performance metrics.

Combination of Ultra-Dense Networks and Other 5G Enabling Technologies: A Survey

Recently, to address the astonishing capacity requirement of 5G, researchers are investigating the possibility of combining different technologies with ultra-dense networks (UDNs). However, the ultra-dense deployment of small cells in the coverage area of conventional macrocells known as UDNs introduces new technical challenges such as severe interference, unfairness in radio resource sharing, unnecessary handover, a significant increase in energy consumption, and degraded quality-of-service (QoS). To overcome these challenges and achieve the performance requirements in 5G, there is a need to combine UDNs with other 5G enabling technologies and then, design intelligent management techniques for better performance of the overall networks. Hence, in this paper, we present a comprehensive survey on different generations of wireless networks, 5G new radio (NR) standards, 5G enabling technologies and the importance of combining UDNs with other 5G technologies. Also, we present an extensive overview of the recent advances and research challenges in intelligent management techniques and backhaul solutions in the last five years for the combination of UDNs and other enabling technologies that offers the visions of 5G. We summarise the mathematical tools widely exploited in solving these problems and the performance metrics used to evaluate the intelligent management algorithms. Moreover, we classify various intelligent management algorithms according to the adopted enabling technologies, benefits, challenges addressed, mathematical tools and performance metrics used. Finally, we summarise the open research challenges, provide design guidelines and potential research directions for the development of intelligent management techniques and backhaul solutions for the combination of UDNs and other 5G technologies.

Spatio-Temporal Analysis for SINR Coverage in Small Cell Networks

While the growth of mobile applications brings enjoyment to daily life, it also imposes more complicated traffic situations on wireless networks. A complete understanding of the impact from the traffic profile is thus essential for network operators to deploy next generation small cell networks. In this paper, based on stochastic geometry and queuing theory, we develop a mathematical framework that captures the interplay between the spatial location of small access points, which determines the magnitude of mutual interference, and their temporal traffic dynamic. We derive a tractable expression for the SINR distribution, and verify its accuracy via simulations. Based on our analysis, we find that: 1) under the same configuration, when traffic condition changes from light to heavy, the corresponding SINR requirement can differ by more than 10 dB for the network to maintain coverage; 2) the SINR coverage probability varies largely with traffic fluctuation in the sub-medium load regime, whereas in a scenario with a very light traffic load, the SINR outage probability increases linearly with the packet arrival rate; and 3) spatial densification can boost the cell-edge rate almost linearly in the dense regime, and thus confirms the appeal for ultra-dense deployment of small cells in the next generation wireless network.

GRA‐based handover for dense small cells heterogeneous networks

Ultra-dense small cell (SC) deployment in the future 5G network makes the architecture of the network as heterogeneous networks (HetNets). This is a good solution to boost the capacity of the network and extend its coverage. However, the dense SCs deployment has brought new challenges to the network including interference, frequent unnecessary handovers, and handover failures. Therefore, user equipment will suffer from a degraded quality of service. In this paper, the authors propose a grey rational analysis-based handover (GRA-HO) method in dense SCs HetNet. The proposed method combines the analytical hierarchy process technique to obtain the weight of the handover metrics and the GRA method to rank the available cells for the best handover target. The performance of the proposed method is evaluated and compared with the traditional multiple attribute decision-making methods including simple additive weighting and VIKOR methods. Results show that the GRA-HO method has outperformed the existing methods in terms of reducing the number of frequent handovers and link failures, in addition to enhancing energy efficiency.

Analytical Modeling for Mobility Signalling in Ultradense HetNets

Multiband and multitier network densification is being considered the most promising solution to overcome the capacity-crunch problem of cellular networks. In this direction, small cells are being deployed within the macro cell (MC) coverage, to off-load some of the users associated with the MCs. This deployment scenario raises several problems. Among others, signalling overhead and mobility management will become critical considerations. Frequent handovers (HOs) in ultradense small cell (SC) deployments could lead to a dramatic increase in signalling overhead. This suggests a paradigm shift toward a signalling conscious cellular architecture with smart mobility management. To this end, the control/data separation architecture (CDSA) with dual connectivity is being considered for the future radio access. Considering the CDSA as the radio access network architecture, we quantify the reduction in HO signalling w.r.t. the conventional approach. We develop analytical models which compare the signalling generated during various HO scenarios in the CDSA and conventionally deployed networks. New parameters are introduced, which can with optimum value significantly reduce the HO signalling load. The derived model includes HO success and HO failure scenarios along with specific derivations for continuous and noncontinuous mobility users. Numerical results show promising CDSA gains in terms of saving in HO signalling overhead.

User Driven Multiclass Cell Association in 5G HetNets for Mobile & IoT Devices

Fifth generation (5G) needs to support plenty of applications and services with a wide variety of quality of service requirements. The deployment of ultra-dense small cells’ networks as a part of the heterogeneous networks architecture is one of the key technologies to achieve this. In such a dense architecture, associating devices with the network is challenging. The traditional cell association algorithms use signal-to-interference-plus-noise ratio metric. However, this is not appropriate for 5G, especially with the reduction in the cells size and the growing number of the user equipment (UE) and the Internet-of-Things (IoT) devices. In this paper, we propose a distributed multiclass user-driven cell association algorithm based on the multi armed bandit game (CA-MAB) to connect devices with different requirements to the network. Here, we focus on two classes of devices: UE devices and low-power IoT devices. The proposed algorithm is evaluated in static and mobile environments, where the convergence and equilibrium are achieved. Our performance results are validated against the central cell association method that is complex and requires a huge amount of information exchange. The results show that CA-MAB throughput and energy efficiency are within 10% of the centralized solution. These values increase by less than 5% in the case of mobility. However, they reduce with more network densification.

Frequent-Handover Mitigation in Ultra-Dense Heterogeneous Networks

In a heterogeneous network (HetNet) with ultra-dense small-cell deployment, fast-moving users may experience frequent handovers between small cells owing to the small coverage areas of those cells. Moreover, due to shadowing and channel fading, static or slow-moving users can also experience frequent handovers, called ping-pongs. Such redundant handovers are unacceptable, and can cause packet losses or packet delays leading to a poor user experience. To solve these unwanted handover problems, we propose a frequent handover mitigation algorithm for ultra-dense HetNets. Based on mobility behavior, the proposed algorithm categorizes frequent handover-experience users as either fast-moving or ping-pong users. Fast-moving users are then handed over to the macro layer, and ping-pong users are managed by adjustment of handover parameters. However, if ping-pongs cannot be avoided through handover-parameter adjustment, ping-pong users are handed over to the macro layer as well. Simulation results show that the proposed algorithm can reduce 79.56% of the overall handovers, and increase network throughput by 10.82%.

Performance of Small Cell Networks Under Multislope Bounded Pathloss Model: From Sparse to Ultradense Deployment

Network densification is proved to be the most efficient method to expand network capacity over the past few decades. Nevertheless, can network densification always boost network performance? To shed light on this, we explore the pros and cons of network densification in $k$ -dimension downlink small cell networks by analyzing transmission success probability (SP) and network spatial throughput (ST). Remarkably, different from long-distance propagation in sparse networks, short-distance propagation of distinctive features dominates as well under dense deployment of small cells. On this account, we apply a multislope bounded pathloss model (MBPM) to characterize signal attenuation within long and short propagation distance. Under MBPM, it is surprisingly found that network densification would enhance SP and ST only when small cell base station density $\lambda \left(\mathrm{SBS}/\mathrm{m}^{k}\right)$ is smaller than some critical densities. Beyond the critical densities, both SP and ST are proved to exponentially diminish with $\lambda$ and even approach zero when $\lambda$ is sufficiently large. In other words, ultradense deployment of small cells indeed deteriorates network performance. Besides, the numerically derived critical densities are helpful for the practical deployment of small cell networks.

QoS-based distributed flow management in software defined ultra-dense networks

Ultra-dense small cell deployment is a promising solution to meet the 1000 × throughput improvement desired in next-generation wireless networks. This deployment results in a correspondingly high number of small cells, also increasing the complexity of the architecture. The Software-Defined Networking (SDN) can be used as a solution to ease the management of Ultra-Dense data plane with distributed controllers. However, in a distributed architecture, the load must be balanced among the controllers and an outage in any controller should not damage the management of the network. In order to recover from an outage by considering load distributions, we propose a distributed flow management model in Software-Defined Ultra-Dense Networks based on the queuing theory. In this approach, we model the distributed controllers with different Markovian queuing systems by considering the flow characteristics and outage. Thus, the proposed flow separation module divides the incoming flows of controllers according to the characteristics of mice and elephant during modeling. Correspondingly, incoming mice and elephant flows are modeled by using M/M/1 and MX/M/1 systems with additional M/M/c queue until the detection of the outage. The M/M/c queues are used for outage detection thanks to Erlang-C parameter. On the other hand, the M/M/1 and MX/M/1 systems are used to load estimations of mice and elephant flows. Therefore, the mice and elephant flows of the outage controllers are transferred to the compensatory controllers by considering the estimated load distributions. Thence, the M/M/c queues of the compensatory controllers are converted to the M/MY/1 system to satisfy the massive flow traffic with bulk service. With this method, we are able to decrease the waiting times of mice and elephant flows during the outage by 15% and 11% respectively compared to the conventional distributed controller implementation. Moreover, the packet losses of the controllers during the outage are decreased by 32% compared to the conventional implementation.

Multi-Criteria Handover Using Modified Weighted TOPSIS Methods for Heterogeneous Networks

Ultra-dense small cell deployment in future 5G networks is a promising solution to the ever increasing demand of capacity and coverage. However, this deployment can lead to severe interference and high number of handovers, which in turn cause increased signaling overhead. In order to ensure service continuity for mobile users, minimize the number of unnecessary handovers and reduce the signaling overhead in heterogeneous networks, it is important to model adequately the handover decision problem. In this paper, we model the handover decision based on the multiple attribute decision making method, namely Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The base stations are considered as alternatives, and the handover metrics are considered as attributes to selecting the proper base station for handover. In this paper, we propose two modified TOPSIS methods for the purpose of handover management in the heterogeneous network. The first method incorporates the entropy weighting technique for handover metrics weighting. The second proposed method uses a standard deviation weighting technique to score the importance of each handover metric. Simulation results reveal that the proposed methods outperformed the existing methods by reducing the number of frequent handovers and radio link failures, in addition to enhancing the achieved mean user throughput.

Efficient and Reliable Multicast Using Device-to-Device Communication and Network Coding for a 5G Network

How to achieve efficient reliable multicast with 100 percent reliability is an important issue of emerging 5G network. In the 5G network, besides the macro BSs, ultra-dense low-power BSs (e.g., micro, pico, and femto eNBs) are deployed throughout the macrocell to form ultradense small cells, which reduces the number of associated multicast receivers per BS and consequenly reduces the number of retransmissions per packet (i.e., traffic load) at each BS. However, this gain is greatly limited by the nodes with bad channel quality. Adopting D2D-communication- based retransmission can effectively reduce the retransmissions at the BSs. There are some challenging issues to be addressed, like the selection of appropriate D2D links, extremely reducing D2D retransmissions, and the design of an efficient acknowledgment mechanism. In this article, considering the ultra-dense small cell deployment in a 5G network, we propose an efficient reliable multicast scheme that jointly utilizes D2D communication and network coding to achieve 100 percent reliability. In addition to discussing research issues that deserve further study, we present numerical results to illustrate the performance gains achieved by applying the proposed scheme in terms of traffic load reduction at the BSs.

Planning of Ultra-Dense Wireless Networks

Fifth generation (5G) wireless networks adopt the deployment of ultra-dense small cells for efficient slicing of radio resources. This conceptual change in network structure aims to meet the rapid increase in mobile data traffic and connected devices. However, limited free spectrum and dynamic assignment of resources are main concerns when considering the cognitive small cells solution. Therefore, there is a need to map traffic patterns with the number of cognitive small cells to provide an optimized network architecture operating with adequate spectrum resources. This article investigates the case when network densification exceeds the radio resource capacity, causing a large scale overlapping in cell coverage area and used channels. Taking into consideration cognitive network performance characteristics, we identify two spectrum coexistence frameworks, Space Filling and Time Filling, to improve spectrum utilization and scalability for moderately large networks. Simulations show that there is a turning point when network performance starts to decline as the number of cognitive small cells exceeds the shared resources in a site area, subject to a certain load profile. This optimization of network structure, based on spectrum transmission opportunities, brings about a new topic for operators and research communities considering small cells operating in the unlicensed band.