Deployment Of Small Cells Research Articles

Joint congestion control and resource allocation for energy-efficient transmission in 5G heterogeneous networks

The deployment of small cells with carrier aggregation (CA) is a significant feature of fifth generation (5G) mobile communication systems which could be characterized by the multi-dimensional heterogeneity on their diversified requirements upon different resources. Taking the heterogeneity into account, we consider here a joint optimization problem wherein multiple kinds of resources are concurrently allocated to optimize the system throughput utility while enhancing the network energy efficiency (EE) and maintaining the system stability. Especially, for the high-dimensional non-deterministic polynomial (NP)-hard allocation problem embedded, we conduct a mathematical programming model involving nonlinear integer constraints to seek the long-term stable utility on throughput and introduce an iterative optimal modulation and coding scheme-based (optimal MCS-based) heuristic algorithm as an effective solver. In addition, as data traffic and channel condition will be time-varying in the real world, an admission control based on the Lyapunov technique that requires no prior knowledge on channel information is proposed to reduce the system overhead. Finally, not only the performance bound is derived in theory, but also the numerical experiments are conduced to reveal its characteristics with respect to the system parameter V and the EE requirement.

Joint Communication and Computing Resource Allocation in 5G Cloud Radio Access Networks

Cloud-radio access network (C-RAN) is regarded as a promising solution to manage heterogeneity and scalability of future wireless networks. The centralized cooperative resource allocation and interference cancellation methods in C-RAN significantly reduce the interference levels to provide high data rates. However, the centralized solution is not scalable due to the dense deployment of small cells with fractional frequency reuse, causing severe inter-tier and inter-cell interference turning the resource allocation and user association into a more challenging problem. In this paper, we investigate joint communication and computing resource allocation along with user association, and baseband unit (BBU) and remote radio head (RRH) mapping in C-RANs. We initially establish a queueing model in C-RAN, followed by formulation of two optimization problems for communication [e.g., resource blocks (RBs) and power] and computing [e.g., virtual machines (VMs)] resources allocation with the aim to minimize mean response time. User association along with the RB allocation, interference, and queueing stability constraints are considered in the communication resource optimization problem. The computing resource optimization problem considers BBU-RRH mapping and VM allocation for small cells, constrained to BBU server capacity and queueing stability. To solve the communication and computing resource optimization problem, we propose a joint resource allocation solution that considers a double-sided auction based distributed resource allocation (DS-ADRA) method, where small cell base stations and users jointly participate using the concept of auction theory. The proposed method is evaluated via simulations by considering the effect of bandwidth utilization percentage, signal-to-interference ratio threshold value and the number of users. The results show that the proposed method can be successfully implemented for 5G C-RANs.

Collaborative Resource Management for Negotiable Multi-Operator Small Cell Networks.

The ubiquitous coverage/connectivity requirement of wireless cellular networks has shifted mobile network operators’ (MNOs) interest toward dense deployment of small cells with coverage areas that are much smaller as compared to macrocell base stations (MBSs). Multi-operator small cells could provide virtualization of network resources (infrastructure and spectrum) and enable its efficient utilization, i.e., uninterrupted coverage and connectivity to subscribers, and an opportunity to avoid under-utilization of the network resources. However, a MNO with exclusive ownership to network resources would have little incentive to utilize its precious resources to serve users of other MNOs, since MNOs differentiate among others based on their ownership of the licensed spectrum. Thus, considering network resources scarcity and under-utilization, this paper proposes a mechanism for multi-operator small cells collaboration through negotiation that establishes a mutual agreement acceptable to all involved parties, i.e., a win–win situation for the collaborating MNOs. It enables subscribers of a MNO to utilize other MNOs’ network resources, and allows MNOs to offer small cells “as a service” to users with ubiquitous access to wireless coverage/connectivity, maximize the use of an existing network resources by serving additional users from a market share, and enhance per-user data rate. We validated and evaluated the proposed mechanism through simulations considering various performance metrics.

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.

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.

Millimeter-Wave Multi-Beam Waveguide Lens Antenna

A millimeter-wave multi-beam antenna operating dual-band with a 1 GHz bandwidth each, around the 28 and 31 GHz frequencies, is presented. The antenna is designed on the principle of transformation of the cylindrical wavefront to planar to enhance the gain. A metal ridge lens is used for the wavefront transformation by a phase extraction and compensation method. The dual-band operation of the antenna aids in transmitting and receiving at two independent frequencies. An advantage to this is the significant reduction of the number of RF chains due to the use of the shared aperture over the lens. The antenna has been validated for casting the beam in three primary target directions of - 60°, 0°, and 60°, however, other beam directions can be suitably designed. The spatial footprint of the antenna is 170 mm × 150 mm and has a gain varying between 14 and 15 dBi at each of the three ports centered around 28 and 31 GHz. The theoretical simulated results are in good agreement with the measurements. The antenna could potentially be used in 5G small cell deployments of a millimeter-wave local multipoint distribution system (LMDS).

A Survey on Recent Trends and Open Issues in Energy Efficiency of 5G.

The rapidly increasing interest from various verticals for the upcoming 5th generation (5G) networks expect the network to support higher data rates and have an improved quality of service. This demand has been met so far by employing sophisticated transmission techniques including massive Multiple Input Multiple Output (MIMO), millimeter wave (mmWave) bands as well as bringing the computational power closer to the users via advanced baseband processing units at the base stations. Future evolution of the networks has also been assumed to open many new business horizons for the operators and the need of not only a resource efficient but also an energy efficient ecosystem has greatly been felt. The deployment of small cells has been envisioned as a promising answer for handling the massive heterogeneous traffic, but the adverse economic and environmental impacts cannot be neglected. Given that 10% of the world’s energy consumption is due to the Information and Communications Technology (ICT) industry, energy-efficiency has thus become one of the key performance indicators (KPI). Various avenues of optimization, game theory and machine learning have been investigated for enhancing power allocation for downlink and uplink channels, as well as other energy consumption/saving approaches. This paper surveys the recent works that address energy efficiency of the radio access as well as the core of wireless networks, and outlines related challenges and open issues.

Iris: Deep Reinforcement Learning Driven Shared Spectrum Access Architecture for Indoor Neutral-Host Small Cells

We consider indoor mobile access, a vital use case for current and future mobile networks. For this key use case, we outline a vision that combines a neutral-host based shared small-cell infrastructure with a common pool of spectrum for dynamic sharing as a way forward to proliferate indoor small-cell deployments and open up the mobile operator ecosystem. Towards this vision, we focus on the challenges pertaining to managing access to shared spectrum (e.g., 3.5GHz US CBRS spectrum). We propose Iris, a practical shared spectrum access architecture for indoor neutral-host small-cells. At the core of Iris is a deep reinforcement learning based dynamic pricing mechanism that efficiently mediates access to shared spectrum for diverse operators in a way that provides incentives for operators and the neutral-host alike. We then present the Iris system architecture that embeds this dynamic pricing mechanism alongside cloud-RAN and RAN slicing design principles in a practical neutral-host design tailored for the indoor small-cell environment. Using a prototype implementation of the Iris system, we present extensive experimental evaluation results that not only offer insight into the Iris dynamic pricing process and its superiority over alternative approaches but also demonstrate its deployment feasibility.

Spectral Efficiency and Deployment Cost Efficiency Analysis of mmW/UHF-Based Cellular Network

Next-generation heterogeneous cellular network (HCN) expects more and more deployment of the base stations and spectrum to achieve data rate in gigabits per second with seamless connectivity. Recently, small cell deployment has proven its effectiveness for increasing the coverage and area spectral efficiency (ASE) of the cellular network. Although, dense small cell deployment also increases the deployment cost and cross-tier interference of the network. This paper suggests switching-based mixed millimeter wave (mmW)/ultra high frequency (UHF) cellular network as a possible solution to overcome these challenges. In mixed mmW/UHF cellular network (named as MMUCN), mmW is used as the main transmission link, and UHF band is utilized as a backup link. In this paper, a theoretical framework is developed using tools from the stochastic geometry to analyze the outage performance, ASE, and deployment cost efficiency (DCE) of the MMUCN, which comprises existing macro base stations and mmW base stations. Optimal mmW base station densities constraints by the outage are calculated, which maximizes the ASE and DCE. Furthermore, a multiobjective optimization problem is formulated to maximize ASE and DCE simultaneously. Numerical results show that MMUCN outperforms UHF-based two-tier cellular network and efficiently mitigates the cross-tier interference of the system.

Communication-Free Inter-Operator Interference Management in Shared Spectrum Small Cell Networks

Emergence of shared spectrum, such as the 3.5-GHz citizen broadband radio service (CBRS) band in the U.S., promises to broaden the mobile operator ecosystem and lead to proliferation of small cell deployments. We consider the inter-operator interference problem that arises when multiple small cell networks access the shared spectrum. Towards this end, we take a novel communication-free approach that seeks implicit coordination between operators without explicit communication. The key idea is for each operator to sense the spectrum through its mobiles to be able to model the channel vacancy distribution and extrapolate it for the next epoch. We use reproducing kernel Hilbert space kernel embedding of channel vacancy and predict it by vector-valued regression. This predicted value is then relied on by each operator to perform independent but optimal channel assignment to its base stations taking traffic load into account. Via numerical results, we show that our approach, aided by the above channel vacancy forecasting, adapts the spectrum allocation over time as per the traffic demands and more crucially, yields as good as or better performance than a coordination-based approach, even without accounting the overhead of the latter.

Coverage and rate analysis in two‐tier heterogeneous networks under suburban and urban scenarios

AbstractMassive boost in data traffic demand and inconsistent user's behavior have necessitated modern cellular networks to evolve toward heterogeneous architectural framework consisting of macro and small cells to accommodate ever‐increasing user's density. Literature survey reveals that the deployment of additional small cells can encounter the booming coverage, capacity, and QoS constraints by maintaining the overall operational cost of the network. In this paper, at first, a suitable model based on nonhomogeneous Poisson point process (NHPPP) is designed for heterogeneous wireless network (HetNet) consisting of two‐tiers eNodeBs (Macro and Small Cell), where each of the tiers is differentiated in terms of transmitting power, eNodeB density, and supported data rate. Subsequently, analytical expressions are derived for coverage probability (CP) and average rate (AR) to assess the performance of the HetNet. The contribution of the paper further lies in integrating the K‐means clustering algorithm with NHPPP to find the optimal locations of the small cell eNodeBs for extended coverage and rate improvement. The proposed model is investigated under differently dense scenarios like urban and suburban areas in India. It establishes the requisite of an optimal number of small cells along with the traditional infrastructure to maximize the performance in terms of CP and AR. Finally, the proposed integrated model is compared with the traditional homogeneous Poisson point process (HPPP) and NHPPP for coverage and rate analysis. It is observed that the K‐means clustering algorithm in integration with NHPPP overshadows both HPPP and NHPPP in terms of coverage and rate under both urban and suburban deployment scenarios.

A REM-Enabled Diagnostic Framework in Cellular-Based IoT Networks

With the flourishing growth of Internet-of-Things (IoT) applications, cellular-assisted IoT networks are promising to support the ever-increasing wireless traffic demands generated by various kinds of IoT devices. As one of the emerging technologies in the next-generation cellular systems, small cells, or so-called “femtocells” in indoor environments, are expected to be densely deployed for the ubiquitous coverage and capacity enhancement in a cost-effective and energy-efficient way. However, unplanned femtocell deployment and complex interior layouts of buildings may lead to severe coverage and capacity problems and even possible negative impacts on the dense deployment. In this paper, we aim at developing a data-driven indoor diagnostic framework for fault detection in cellular-assisted IoT networks. The framework utilizes machine learning techniques to analyze crowd-sourced measurements uploaded from diverse end devices. Then, some well-trained prediction models are used to construct a global view of a radio environment, namely, radio environment map (REM), for diagnosis and management purposes. Moreover, REMs enable operators to detect existing coverage and capacity problems at any interested location. To verify the feasibility of indoor diagnoses, we collect a real trace data from an indoor testbed and then conduct a series of experiments to evaluate the performance of the machine-learning algorithms in terms of the accuracy, the time complexity, and the sensitivity to data volumes. The experimental results provide an insightful guideline to the indoor deployment of small cells in cellular-based IoT networks.

Small Cell Deployment Along Roads: Coverage Analysis and Slice-Aware RAT Selection

We characterize a multi-tier wireless network consisting of multi-radio access technology (RAT) small cells, operating in both sub-6GHz and millimeter wave (mm-wave) bands, overlaid on top of traditional macro cells. To realistically characterize the user equipment (UE) performance, we model the position of the small cells along roads. First, we provide tractable, yet realistic models to characterize the mm-wave interference and the effect of vehicular blockages on the mm-wave signals. Then, we introduce an association policy, where an UE selects the serving tier using the powers measured on the sub-6GHz band, and then, using the biased power of the mm-wave band, selects the RAT. Based on this, we derive the signal to interference plus noise ratio (SINR) coverage probabilities of pedestrian UEs. We investigate the effect of the RAT selection bias on the vehicular blockage, SINR coverage, and rate coverage experienced by the UEs. Leveraging the results of our analysis, we propose to use a varied range of RAT selection biases to support the diverse applications of the fifth generation (5G) mobile networks. Accordingly, we provide a slice-aware RAT selection strategy to support three types of services, characterized by different requirements in terms of reliability, coverage, and data rates.

Interference management issues for the future 5G network: a review

The future wireless Fifth Generation (5G) communication network required a higher bandwidth in order to achieve greater data rate. It will be largely characterized by small cell deployments, typically in the range of 200 meters of radius/cell, at most. The implementation of small size networks delivers various advantages such as high data rate and low signal delay. However, it also suffers from various issues such as inter-cell, intra-cell, and inter-user interferences. This paper discusses the issues related to interference management for 5G network from the perspective of Heterogeneous Network and Device-to-Device communication, by using enabling techniques, such as Inter-cell Interference Coordination, Coordinated Multipoint, and Coordinated Scheduling. Furthermore, several pertinent issues have been critically reviewed focusing on their methodologies, advantages and limitations along with the future work. Future directions proposed by the 3rd Generation Partnership Project for interference mitigation has also been outlined. This review will act as a guide for the researchers to comprehend various existing and emerging enabling interference mitigation techniques for further exploration and smooth implementation of 5G wireless network.

Effect on energy efficiency with small cell deployment in heterogeneous cellular networks

Recently, data demand has grown explosively due to tremendous growth in cellular traffic. To meet the user's data requirement, Small cells (SCs) have been overlaid with existing macro cell (MC) leading to heterogeneity to the network. Although SCs enhances system throughput, to find the required number of SCs and energy efficiency of such network is of concern for vendors. Looking at the real‐world scenario of user's distribution in a geographical area, authors consider the SCs (eg, Picocells) deployment as uniform or cluster based (user‐density and k‐means). The work considers uniform deployment of SCs modeled as homogeneous Poisson Point Process (PPP) and user clusters are considered for user‐density‐based and k‐means‐based deployment. The locations for SCs is considered in the cell boundaries and hotspot regions where user density is highly consistent, huge gathering takes place, mobility is seldom and data demand is high such as at railway stations, shopping malls, working farms and organization, etc. The downlink performances in terms of average user throughput, system capacity and network energy efficiency for these three deployments of SC base‐stations in a heterogeneous network are explored. User distributions are modeled by adopting Cox process (also known as doubly stochastic poison process) and cluster process in the heterogeneous network operating area. It is observed that energy efficiency in terms of bps per watt decreases after a certain number of SCs for uniform and k‐means‐based deployment. The results show better performance for user‐density‐based SCs deployment compared to uniform and k‐means one.

An Energy Saving Small Cell Sleeping Mechanism With Cell Range Expansion in Heterogeneous Networks

In recent years, the explosion of wireless data traffic has resulted in a trend of large scale dense deployment of small cells, with which the rising cost of energy has attracted a lot of research interest. In this paper, we present a novel sleeping mechanism for small cells to decrease the energy consumption of heterogeneous networks. Specifically, in the cell-edge area of a macrocell, the small cells will be put into sleep where possible and their service areas will be covered by the range-expanded small cells nearby and the macrocell; in areas close to the macrocell, the user equipments associated with a sleeping small cell will be handed over to the macrocell. Furthermore, we use enhanced inter-cell interference coordination techniques to support the range expanded small cells to avoid QoS degradation. Using a stochastic geometry-based network model, we provide the numerical analysis of the proposed approach, and the results indicate that the proposed sleeping mechanism can significantly reduce the power consumption of the network compared with the existing sleeping methods while guaranteeing the QoS requirement.

Spectral Efficiency Improvement based on Small-cell Deployments Toward 5G Communications Technologies

This paper emphasizes a method for improving spectral efficiency based on small cells (SCs) deployed in an existing macrocell (MC), which ultimately results in overall enhancement of the network capacity and coverage area. In addition, it allows an unlicensed secondary network to deliver messages through opportunistic access to the licensed network spectrum. By deploying SCs, users either inside or outside high residential buildings and/or commercial buildings can acquire signals during communications without interruption. The connectivity in the alliance of the two-tier networks becomes abundant, resulting in spectral efficiency improvement. In this paper, we first recall performance based on the Vandermonde-subspace frequency division multiplexing (VFDM) spectrum-sharing technique for spectrum management under both conventional (single-user) and enhanced scenarios; subsequently, the proposed method is introduced for comparison purposes. The performance of both methods is manifested in simulation results for the achievable rate, which demonstrate that the proposed approach outperforms enhanced VFDM and is a potential candidate in next-generation cellular technology. The motivation for the preference for SC deployment in the proposed approach is due to worthy characteristics (low power, low cost, very light weight, and self-organization). Unlike MCs, which need a considerable budget, they are installed anywhere without a lot of expense, and hence, save the network infrastructure.

Energy Efficient and Delay Aware 5G Multi-Tier Network

Multi-tier heterogeneous Networks (HetNets) with dense deployment of small cells in 5G networks are expected to effectively meet the ever increasing data traffic demands and offer improved coverage in indoor environments. However, HetNets are raising major concerns to mobile network operators such as complex distributed control plane management, handover management issue, increases latency and increased energy expenditures. Sleep mode implementation in multi-tier 5G networks has proven to be a very good approach for reducing energy expenditures. In this paper, a Markov Decision Process (MDP)-based algorithm is proposed to switch between three different power consumption modes of a base station (BS) for improving the energy efficiency and reducing latency in 5G networks. The MDP-based approach intelligently switches between the states of the BS based on the offered traffic while maintaining a prescribed minimum channel rate per user. Simulation results show that the proposed MDP algorithm together with the three-state BSs results in a significant gain in terms of energy efficiency and latency.

Small Cells Integration with the Macro-Cell Under LTE Cellular Networks and Potential Extension for 5G

Heterogeneous Networks (HetNet) requires the deployment of small cell networks that can co-exist with the existing macro-cell. To provide a high Quality of Service (QoS), a massive multiple-input-multiple-output (MIMO) must be equipped with a HetNet of a macro-cell base station to the multiple users. This paper highlights three important aspects of the emerging small cell wireless networks. First, the architectures of small cell networks in LTE wireless network is reviewed, with specific references to the current wireless network standards. Second, the performance evaluation of overlay small cells integrated with the underlay macro-cell is investigated. The third part of this study focuses on the future trends of small cell deployment in 5G and the critical technical preparation needs to be done to allow integration with the existing 4G network. The results show that the proposed integration of 5G small cells into existing macro 4G networks has improved both of the data rate (91.46%) and energy efficiency (98.66%).

Planning While Flying: A Measurement-Aided Dynamic Planning of Drone Small Cells

The deployment of drone small cells has emerged as a promising solution to agile provisioning of Internet backbone access for Internet of Things devices, and many other types of users/devices. In this paper, we consider the problem of deploying a set of drone cells operating on multiple channels in a target area to provide access to the backbone/core network, which is formulated as a combinatorial network utility maximization problem. Since an offline and centralized solution to such a problem is not feasible, a low-complexity and distributed online algorithm is highly desired. Therefore, we propose a measurement-aided dynamic planning (MAD-P) algorithm, where the dispatched drones perform position and channel configurations autonomously on the fly based on the real-time measurement of network throughput to solve the problem in a distributed fashion during flight with minimal centralized control. We prove that the proposed MAD-P algorithm is asymptotically optimal, and investigate how long it takes for the convergence to stationarity under the MAD-P algorithm by giving a mixing time analysis. We also derive an upper bound of the performance gap in presence of measurement errors. Simulation results are provided to validate our analytic results and demonstrate the effectiveness of our algorithm.