Dense Small Cell Research Articles

Hybrid inter-cell interference management for ultra-dense heterogeneous network in 5G

The Ultra-dense Heterogeneous Network (HetNet), which consists of macro-cells and pico-cells, has been recognized as a key technique to improve network performance. However, the increasing number of pico-cells also causes severe interference including inter-cell interference and intra-cell interference. Therefore, interference management has become an important issue in ultra-dense HetNets, and the traditional enhanced inter-cell interference coordination (eICIC) scheme is no longer fit for the high density of small cells. In this paper, a hybrid interference management method based on dynamic eICIC and coordinated multi-point transmission (CoMP) is proposed. Firstly, a virtual cell is established based on the characteristics of ultra dense HetNets. Then, a novel joint dynamic eICIC scheme combined with multi-user beamforming is deployed to eliminate the inter-cell interference, and improve the throughput of virtual cell significantly without sharp decrease of throughput of macro-cell. Furthermore, a virtual cell based joint transmission scheme is deployed with a power control algorithm, which can obviously increase the spectrum efficiency of virtual cell edge. Simulation results verify that the proposed scheme can achieve better spectrum efficiency both at macro-cell and virtual cell edges, and the network throughput is also improved.

Cooperation-enabled energy efficient base station management for dense small cell networks

Dense small cell networks are deployed for future wireless communication to meet the ever-increasing mobile traffic demand. However, network densification will significantly increase the energy budget and lead to energy inefficiency due to the constant operation of network hardware. In this paper, we consider cooperation-enabled dynamic base station (BS) management for downlink dense small cell networks. By introducing two traffic-aware sleep modes, i.e., deep sleep mode and opportunistic sleep mode which are operating in different time and energy consumption scales, the network hardwares are turned to be the resources that can be occupied and released dynamically. Small cell BSs (SBSs) with zero or low load are completely switched off and reside in deep sleep mode during a predefined time interval. At each time slot, SBS dynamically turn some antennas and associated physical components into opportunistic sleep mode according to the short term traffic distribution, and the users are jointly served by the remaining antennas via cooperative transmission. The corresponding sleep mode decision making are presented respectively to find the optimal number of SBS and antennas that should be switched off. Numerical results are then presented to illustrate the superior performance in terms of energy efficiency gain. In summary, the proposed cooperation-aided sleep strategies for dense small cell networks take both traffic features and optimal cooperative transmission into account, and can achieve great energy saving while maintaining required quality of service.

Changes in small intestinal chromogranin A-immunoreactive cell densities in patients with irritable bowel syndrome after receiving dietary guidance.

Chromogranin A (CgA) is a common marker for enteroendocrine cells in the gut, and CgA-immunoreactive cell densities are abnormal in patients with irritable bowel syndrome (IBS). The majority of patients with IBS report that their symptoms develop after consuming certain foodstuffs. In the present study, we investigated the effects of dietary guidance on the total enteroendocrine cell densities in the small intestine, as detected by CgA. A total of 14 patients with IBS underwent a gastroscopy with duodenal biopsies and 11 of them also underwent a colonoscopy, with biopsy samples obtained from the ileum. Fourteen control subjects were also included. Each patient received 3 sessions of dietary guidance. Gastroscopies and colonoscopies were performed on both the controls and patients with IBS (at baseline and at 3–9 months after receiving guidance). Biopsy samples obtained from the duodenum and ileum were immunostained for CgA using the avidin-biotin complex (ABC) method and were quantified using computerized image analysis. The density of CgA-immunoreactive cells in the duodenum (mean ± SEM values) in the control subjects was 235.9±31.9 cells/mm2; in the patients with IBS, the density was 36.9±9.8 and 103.7±16.9 cells/mm2 before and after they received dietary guidance, respectively (P=0.007). The density of CgA-immunoreactive cells in the ileum in the control subjects was 47.4±8.3 cells/mm2; in the patients with IBS, the density was 48.4±8.1 and 17.9±4.4 cells/mm2, before and after they received dietary guidance, respectively (P=0.0006). These data indicate that changes in CgA-immunoreactive cell densities in patients with IBS after receiving dietary guidance may reflect a change in the densities of the small intestinal enteroendocrine cells, which may contribute to an improvement in the IBS symptoms.

Performance Impact of LoS and NLoS Transmissions in Dense Cellular Networks

In this paper, we introduce a sophisticated path loss model incorporating both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions to study their impact on the performance of dense small cell networks (SCNs). Analytical results are obtained for the coverage probability and the area spectral efficiency (ASE), assuming both a general path loss model and a special case with a linear LoS probability function. The performance impact of LoS and NLoS transmissions in dense SCNs in terms of the coverage probability and the ASE is significant, both quantitatively and qualitatively, compared with the previous work that does not differentiate LoS and NLoS transmissions. Our analysis demonstrates that the network coverage probability first increases with the increase of the base station (BS) density, and then decreases as the SCN becomes denser. This decrease further makes the ASE suffer from a slow growth or even a decrease with network densification. The ASE will grow almost linearly as the BS density goes ultra dense. For practical regime of the BS density, the performance results derived from our analysis are distinctively different from previous results, and thus shed new insights on the design and deployment of future dense SCNs.

Green cell planning and deployment for small cell networks in smart cities

In smart cities, cellular network plays a crucial role to support wireless access for numerous devices anywhere and anytime. The future 5G network aims to build the infrastructure from mobile internet to connected world. Small Cell is one of the most promising technologies of 5G to provide more connections and high data rate. In order to make the best use of small cell technology, smart cell planning should be implemented to guarantee connectivity and performance for all end nodes. It is particularly a challenging task to deploy dense small cells in the presence of dynamic traffic demands and severe co-channel interference. In this paper, we model various traffic patterns using stochastic geometry approach and propose an energy-efficient scheme to deploy and plan small cells according to the prevailing traffic pattern. The simulation results indicate that our scheme can meet dynamic traffic demands with optimized deployment of small cells and enhance the energy efficiency of the system without compromising on quality-of-service (QoS) requirements. In addition, our scheme can achieve very close performance compared with the leading optimization solver CPLEX and find solutions in much less computational times than CPLEX.

Downlink Power Control in Self-Organizing Dense Small Cells Underlaying Macrocells: A Mean Field Game

A novel distributed power control paradigm is proposed for dense small cell networks co-existing with a traditional macrocellular network. The power control problem is first modeled as a stochastic game and the existence of the Nash Equilibrium is proven. Then, we extend the formulated stochastic game to a mean field game (MFG) considering a highly dense network. An MFG is a special type of differential game which is ideal for modeling the interactions among a large number of entities. We analyze the performance of two different cost functions for the mean field game formulation. Both of these cost functions are designed using stochastic geometry analysis in such a way that the cost functions are valid for the MFG setting. A finite difference algorithm is then developed based on the Lax-Friedrichs scheme and Lagrange relaxation to solve the corresponding MFG. Each small cell base station can independently execute the proposed algorithm offline, i.e., prior to data transmission. The output of the algorithm shows how each small cell base station should adjust its transmit power in order to minimize the cost over a predefined period of time. Moreover, sufficient conditions for the uniqueness of the mean field equilibrium for a generic cost function are also given. The effectiveness of the proposed algorithm is demonstrated via numerical results.

A Tractable Approach to Uplink Spectral Efficiency of Two-Tier Massive MIMO Cellular HetNets

This letter investigates the uplink spectral efficiency (SE) of a two-tier cellular network, where massive multiple-input multiple-output macro base stations are overlaid with dense small cells. Macro user equipments (MUEs) and small cells with single user equipment uniformly scattered are modeled as two independent homogeneous Poisson point processes. By applying stochastic geometry, we analyze the multiuser uplink SE at a macro base station that employs a zero-forcing detector and we obtain a novel lower bound as well as its approximation. According to the simple and near-exact analytical expression, we observe that the ideal way to improve the SE is by increasing the MUE density and the base station antennas synchronously rather than increasing them individually. Furthermore, a large value of path loss exponent has a positive effect on the SE due to the reduced aggregated interference.

Sojourn Time-Based Velocity Estimation in Small Cell Poisson Networks

Due to the increasing density of small cells, mobility management in heterogeneous networks has become a challenging task. One key challenge facing the development of advanced mobility management techniques is the accurate estimation of the users' velocity. One simple way to estimate a user's velocity is via the use of sojourn time samples. In this letter, the Cramer-Rao lower bound (CRLB) for the sojourn time-based velocity estimation is analyzed. Stochastic geometry is used for the spatial modeling of small cells, and the CRLB is derived using the tools from estimation theory. An asymptotically unbiased velocity estimator is also derived. Our analysis shows that the sojourn time-based velocity estimation exhibit a lower CRLB compared to the CRLB of classical velocity estimation using handover count.

Joint Power Coordination for Spectral-and-Energy Efficiency in Heterogeneous Small Cell Networks: A Bargaining Game-Theoretic Perspective

Extensive deployment of small cells in heterogenous cellular networks introduces both challenges and opportunities. Challenges come with the reuse of the limited frequency resource for improving spectral efficiency, which always introduces serious mutual inter- and intracell interference between or among small cells and macrocells. The opportunities refer to more potential chances of inter- and intratier cooperations among small cells and macrocells. Energy efficiency will be a critical performance requirement for future green communications, especially when small cells are densely deployed to enhance the quality of user's experience. We exploit the potential cooperation diversities to combat the interference and energy management challenges. To capture the complicated interference interaction and also the possible coordination behavior among small cells and macrocells, this paper proposes a novel bargaining cooperative game (BCG) framework for energy efficient and interference-aware power coordination in a dense small cell network. In particular, a new adjustable utility function is employed in the BCG framework to jointly address both the spectral efficiency and energy efficiency issues. Using the BCG framework, we then derive the closed-form power coordination solutions and further propose a joint interference-aware power coordination scheme (Joint) with the considerations of both interference mitigation and energy saving. Moreover, a simplified algorithm (Simplified) is presented to combat the heavy signaling overhead, which is one of the significant challenges in the scenario of extensive deployment of small cells. Finally, numerical results are provided to illustrate the effectiveness of the proposed Joint and Simplified schemes.

Cache-enabled Software Defined Heterogeneous Networks for Green and Flexible 5G Networks

The network densification of small cells (SCs) is a promising way to cope with the explosive growth of future traffic demands in 5G networks. However, the overall power consumption and the backhaul limitation of the network have become the key factors affecting the network performance and users’ quality-of-experience, which have great importance in 5G wireless networks. Due to the complexity of 5G networks and the variety of user behaviors, the combination of software-defined networks and content delivery strategy could be a more efficient way to manage such networks. In this paper, a cache-enabled wireless heterogeneous network with the control-plane ( $C$ -plane) and user-plane ( $U$ -plane) split is proposed, where the macro cell and SCs with different cache abilities are overlaid and cooperated together in the backhaul scenario. Using an evaluation tool composed of stochastic processes and classical power consumption model, key performance indicators, e.g., the coverage probability, throughput, and energy efficiency (EE), are derived as closed-form expressions or the functions of the signal-to-interference-plus-noise ratio threshold, path loss exponent, transmission power and density of macro and SCs, cache ability, file popularity, and backhaul capacity. Fundamental trade-offs are illustrated between EE and transmission power, EE and SC density, as well as the throughput and density of SCs. Numerical results show that the proposed cache-enabled software-defined networks have much higher throughput and improved EE than current LTE networks, which shows a promising solution for future cellular networks.

United block sequence mapping-based visible light positioning for dense small cell deployment

Visible light positioning (VLP) is an emerging candidate for indoor positioning, which can simultaneously meet the requirements for accuracy, cost, coverage area, and security. However, intercell interference caused by light intensity superposition limits the application of VLP. In this Letter, we propose a united block sequence mapping (UBSM)-based VLP that utilizes superposition to integrate the multidimensional information from dense small cells into 2D information. The experimental result shows that UBSM-based VLP can achieve an accuracy of 1.5 cm with a 0.4 m row spacing and 0.35 m column spacing of LED lights.

A Green and Structure-Controlled Approach to the Generation of Silicone Rubber Foams by Means of Carbon Dioxide

Silicone rubber foams were successfully generated by environmentally friendly blowing agent, supercritical carbon dioxide (scCO2), in this research. Firstly, the effect of the saturation time on the cellular structure was investigated. The diffusion of scCO2 into the rubber matrix would be enhanced thus decreasing the viscosity as increasing the saturation time. It would further promote the cell growth, which has a close connection with the cellular structure. After that, the effect of pre-curing time on cellular morphology of silicone rubber foams was further researched in detail. When increasing pre-curing time in the short time range, cell nucleation would be affected more than cell growth in the foaming process. If continuously increasing pre-curing time, both cell nucleation and growth would be restricted thus resulting in the formation of silicone rubber foams with small cell density and small cell size. This investigation not only provided a green way to produce silicone rubber foams, but also guided us to control cellular morphology via the saturation time and pre-curing time.

Handover Count Based Velocity Estimation and Mobility State Detection in Dense HetNets

In wireless cellular networks with densely deployed base stations, knowing the velocities of mobile devices is key to avoiding call drops and improving the quality of service to the user equipments (UEs). A simple and efficient way to estimate a UE’s velocity is by counting the number of handovers made by the UE during a predefined time window. Indeed, handover-count based mobility state detection has been standardized since long term evolution (LTE) Release-8 specifications. The increasing density of small cells in wireless networks can help in accurate estimation of velocity and mobility state of a UE. In this paper, we model densely deployed small cells using stochastic geometry, and then analyze the statistics of the number of handovers as a function of UE velocity, small-cell density, and handover count measurement time window. Using these statistics, we derive approximations to the Cramer–Rao lower bound (CRLB) for the velocity estimate of a UE. Also, we determine a minimum variance unbiased (MVU) velocity estimator whose variance tightly matches with the CRLB. Using this velocity estimator, we formulate the problem of detecting the mobility state of a UE as low, medium, or high-mobility, as in LTE specifications. Subsequently, we derive the probability of correctly detecting the mobility state of a UE. Finally, we evaluate the accuracy of the velocity estimator under more realistic scenarios such as clustered deployment of small cells, random way point (RWP) mobility model for UEs, and variable UE velocity. Our analysis shows that the accuracy of velocity estimation and mobility state detection increases with increasing small cell density and with increasing handover count measurement time window.

Improving Dense Network Performance through Centralized Scheduling and Interference Coordination

Dense network deployments comprising small cells pose a series of important challenges when it comes to achieving an efficient resource use and curbing intercell interference in the downlink. This paper examines different techniques to treat these problems in a dynamic way, from the network and the receiver sides. As a network coordination scheme, we apply a centralized joint cell association and scheduling mechanism based on dynamic cell switching by which users are not always served by the strongest perceived cell. The method simultaneously results in more balanced loads and increased performance. Interference management at the receiver is achieved through the use of a network-assisted interference cancellation and suppression (NAICS) receiver. In order to further boost the fifth percentile user data rates, the transmission rank at the interferers is selectively reduced by a centralized rank coordination functionality. These mechanisms are evaluated in an LTE-Advanced dense small cell scenario with dynamic traffic. Simulation results illustrate that a combination of the centralized cell association and scheduling scheme and interference cancellation at the receiver can provide fifth percentile data rate gains of up to 80% without a detrimental effect on the median user rates, under the applied assumptions and simulation settings. The gains reach 110% when rank coordination is applied.

Reverse Auction Based Green Offloading Scheme for Small Cell Heterogeneous Networks

The small cell is treated as a promising proposition to provide hot spot capacity and higher data rates. However, even with dense small cell deployment scenario, the heavy traffic load pressure and low energy efficiency in the small cell heterogeneous network (HetNet) still exist. Therefore, how to make the best use of densely deployed small cells under HetNet environments becomes the focus of researches. Offloading provides a feasible solution to promote cooperation between macrocells and small cells for user traffic supporting. In this paper, we propose the reverse auction based Green Offloading (GO) scheme for energy efficiency improvements. The proposed GO scheme employs the reverse auction theory to handle the offloading decision process, aiming at maximizing the system energy efficiency under the constraints of user Quality of Service (QoS) requirements, bandwidth, and transmission power limitations. Moreover, the reverse auction model gives the facility of multicell coordination transmissions with multiple winners situation. The energy efficiency optimization problem with constraints is solved by Dynamic Programming method with Karush-Kuhn-Tucker (KKT) conditions. The Individual Rationality and Truthfulness of the reverse auction model are also proved. By comparing the energy efficiency performances of the proposed GO scheme with current works within the Long Term Evolution-Advanced (LTE-A) system downlink scenario, simulation results show the improvements of the proposed GO scheme.

Hierarchical Resource Allocation Framework for Hyper-Dense Small Cell Networks

This paper considers joint power control and subchannel allocation for co-tier interference mitigation in extremely dense small cell networks, which is formulated as a combinatorial optimization problem. Since it is intractable to obtain the globally optimum assignment policy for existing techniques due to the huge computation and communication overheads in ultra-dense scenario, in this paper, we propose a hierarchical resource allocation framework to achieve a desirable solution. Specifically, the solution is obtained by dividing the original optimization problem into four stages in partially distributed manner. First, we propose a divide-and-conquer strategy by invoking clustering technique to decompose the dense network into smaller disjoint clusters. Then, within each cluster, one of the small cell access points is elected as a cluster head to carry out intra-cluster subchannel allocation with a low-complexity algorithm. To tackle the issue of inter-cluster interference, we further develop a distributed learning-base coordination mechanism. Moreover, a local power adjustment scheme is also presented to improve the system performance. Numerical results verify the efficiency of the proposed hierarchical scheme, and demonstrate that our solution outperforms the state-of-the-art methods, especially for hyper-dense networks.

Ultra-Dense Networks: A Survey

The exponential growth and availability of data in all forms is the main booster to the continuing evolution in the communications industry. The popularization of traffic-intensive applications including high definition video, 3-D visualization, augmented reality, wearable devices, and cloud computing defines a new era of mobile communications. The immense amount of traffic generated by today’s customers requires a paradigm shift in all aspects of mobile networks. Ultradense network (UDN) is one of the leading ideas in this racetrack. In UDNs, the access nodes and/or the number of communication links per unit area are densified. In this paper, we provide a survey-style introduction to dense small cell networks. Moreover, we summarize and compare some of the recent achievements and research findings. We discuss the modeling techniques and the performance metrics widely used to model problems in UDN. Also, we present the enabling technologies for network densification in order to understand the state-of-the-art. We consider many research directions in this survey, namely, user association, interference management, energy efficiency, spectrum sharing, resource management, scheduling, backhauling, propagation modeling, and the economics of UDN deployment. Finally, we discuss the challenges and open problems to the researchers in the field or newcomers who aim to conduct research in this interesting and active area of research.

Research and development of indoor positioning

5G sets an ambitious goal of increasing the capacity per area of current 4G network by 1000 fold. Due to the high splitting gain of dense small cells, ultra dense network (UDN) is widely considered as a key component in achieving this goal. In this paper, we outline the main challenges that come with dense cell deployment, including interference, mobility, power consumption and backhaul. Technologies designed to tackle these challenges in long term evolution system (LTE) and their deficiencies in UDN context are also analyzed. To combat these challenges more efficiently, a series of technologies are introduced along with some of our initial research results. Moreover, the trends of user-centric and peer-to-peer design in UDN are also elaborated.

Cooperative Sleep and Power Allocation for Energy Saving in Dense Small Cell Networks

Energy consumption has become a crucial issue due to the large-scale deployment of small base stations (SBSs) in dense small cell networks (DSCNs). In this paper, a joint optimization problem involving sleep mode in subframes and power allocation to minimize the DSCN energy consumption while guaranteeing users’ rate requirements is formulated as a mixed integer nonlinear programming. To address this problem, we propose a cooperative sleep and power allocation approach by decomposing it into two subproblems. First, we derive the optimum number of active subframes for each SBS and present a centralized heuristic coalition formation algorithm to manage SBSs to form coalitions. In such a case, SBSs can transmit data in active subframes and sleep in others. We then obtain the SBSs’ optimum transmit power in the active subframes relying on a distributed price-based power allocation algorithm. Systemlevel simulation results show that our proposed cooperative scheme can yield significant performance gains in terms of energy saving compared with the maximum power allocation and the non-cooperative power allocation (NCPA) approaches. In addition, the effects of target rates on coalition size and energy consumption are also analyzed.

Small Cell In-Band Wireless Backhaul in Massive MIMO Systems: A Cooperation of Next-Generation Techniques

Massive multiple-inputmultiple-output (MIMO) systems, dense small-cells (SCs), and full duplex are three candidate techniques for next-generation communication systems. The cooperation of next-generation techniques could offer more benefits, e.g., SC in-band wireless backhaul in massive MIMO systems. In this paper, three strategies of SC in-band wireless backhaul in massive MIMO systems are introduced and compared, i.e., complete time-division duplex (CTDD), zero-division duplex (ZDD), and ZDD with interference rejection (ZDD-IR). Simulation results demonstrate that SC in-band wireless backhaul has the potential to improve the throughput for massive MIMO systems. Specifically, among the three strategies, CTDD is the simplest one and could achieve decent throughput improvement. Depending on conditions, with the self-interference cancellation capability at SCs, ZDD could achieve better throughput than CTDD, even with residual self-interference. Moreover, ZDD-IR requires the additional interference rejection process at the BS compared to ZDD, but it could generally achieve better throughput than CTDD and ZDD.