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

Band assignment is an important function in multi-band heterogeneous networks. Most of the existing works have considered the rate of user equipment (UE) as a key criterion for the band assignment. However, the power consumption at the mmWave band is significantly higher than the Sub-6 GHz band, which is particularly significant because the UE battery power is limited. In this context, we design a novel long short term memory (LSTM) aided energy efficient band assignment system for a moving UE. Corresponding to the realistic scenario, we apply a timeseries split based approach to train and test the model. The proposed policy is validated on the publicly available ‘DeepMIMO’ dataset. Research findings shows that the RMSE of predicted rate using timeseries split approach is much less than the conventional approach. Moreover, with proposed scheme, the median energy efficiency is 56.30% higher as compared to the case when energy usage is not considered in the bandswitching decision, while the median rate with our proposed scheme reduces only by 13.81%.

Small cells (SCs) have proven their marvelous capability, especially dealing with high density of user equipment (UE) in the configuration of Internet of Things (IoT). It is widely accepted that the SCs concept is one of the prospective solutions for 5G networks, specifically targeting IoT, to attain the high demand in the future smart city. SC deployment has attracted the attention of multiple research efforts, due to its importance and potential towards enhancing future networking for IoT. However, there is still a lack of works providing SC allocation with comprehensive optimization modeling, which provides essential infrastructural platform to SC functionalities and services (e.g. offloading). The analysis of the number and positions of SCs, towards the simultaneous optimization of both energy efficiency and data rates, is a highly required research direction. SC allocation facilitates the sustainability and reliability, to support exponentially increasing number of users, as well as yielding feasibility of achieving high traffic demand and low latency performance, in addition to longer sustainability based on enhanced energy efficiency. In this paper, a smart small cell allocation scheme is proposed for IoT in smart city. Integer programming multi-objective optimization problem is formulated, and a new algorithm, based on the fusion of Branch-and-Bound (BnB) and Non-Dominated Sorting Genetic Algorithm II (NSGA-II), is developed. Energy efficiency optimization and data rate maximization are formulated, as mutual objectives to fulfill the key demands of IoT in smart city, based on the estimation of users' behaviors. Simulations are conducted, whose results show that the proposed Smart-SC allocation outperforms the different considered benchmarks, resulting in higher offered data rates, while achieving better energy efficiency.

Mobile communication is facing new challenges to the soaring traffic demand of numerous user devices; thus, the notion of the small cell has been proposed and realized in recent years. However, licensed spectrum has been occupied by various underlying access technologies, so the deployment of small cells needs a sophisticated planning algorithm. In this article, we provide an overview of reconfigurable radio and small cell technologies, then introduce the tentative network architecture for 5G. Two planning approaches (i.e., genetic-based and graphbased) are proposed that accommodate cognitive radio technology to improve user throughput by eliminating communication interference. Since cognitive radio networking provides frequency allocation with cognition cycle for better spectral efficiency, we tackle the deployment of ultradense small cells and consider the coordination of unlicensed spectrum at the same time. Results show that the proposed algorithms with spectrum cognition improve network performance in terms of throughput and signal-to-interference- plus-noise ratio. Specifically, the genetic- based algorithm increases 232 percent in throughput and 150 percent in signal-to-interference- plus-noise ratio compared to the graphbased algorithm. Finally, we conclude this article by discussing potential challenges and opportunities.

This paper presents a QoS handover scheme (QHS) with priorities for mobile communications on LTE small-cell networks. In a high-dense deployment of small cells, a mobile UE (User Equipment) may handover very frequently. In the proposed QHS, handover priority of a UE can be determined by its traffic type and required data rate. Specifically, QHS gives a UE with higher QoS requirement a higher priority to handover. Additionally, when QHS reveals that the target eNB (Enhanced Node Base-station) cannot bear the data rate of a higher-priority UE to handover, the QoS of lower-priority UEs is sacrificed by delaying or rejecting their handover. To validate the proposed QHS, we implement the associated modules on a Linux-based small cell platform. Traffic in the experiment consists of various types, such as video conferencing, video on demand, FTP, Web browsing, etc. Performance of the proposed QHS in terms of the occurrence of handover and average handover delay is evaluated. The experimental results have demonstrated that the proposed QHS can substantially improve the handover efficiency of multimedia traffic, as it is compared to a traditional scheme.

Big things come in small packages; a particularly apt description of small cell deployment in cellular networks. Small cells have a big role to play in orchestrating a cellular network that can overcome the explosive mobile traffic upsurge at little cost to the network operator. However, if left unchecked, a large-scale small cell deployment can substantially increase the network energy consumption with strong ecological and economic implications. In this article, we introduce energy-efficient SLEEP mode algorithms for small cell base stations in a bid to reduce cellular networks' power consumption. The designed algorithms allow the hardware components in the BS to be astutely switched off in idle conditions, such that the energy consumption is modulated over the variations in traffic load. Three different strategies for algorithm control are discussed, relying on small cell driven, core network driven, and user equipment driven approaches. Based on a mixed voice and data traffic model, the algorithms present energy saving opportunities of approximately 10-60 percent in the network with respect to no SLEEP mode activation in small cells, coupled with additional capacity incentives.

Inbound handover (HO) or hand-in is accomplished when the user equipment (UE) performs HO from macrocell (MC) to a small cell (SC) [1] [2]. When the UE connects to a SC with a time of stay (ToS) less than a predefined time threshold, this will result in frequent unnecessary HOs and also increase service interruption which in turn will degrade the end user quality of service (QoS). In this paper, we propose an inbound HO method for the purpose of throughput enhancement and load balancing in SC heterogeneous networks (HetNets). The impact of interference from both MC and SC tiers is considered so that the UE is offloaded from congested MC and forced to perform the HO to the SC tier that supplies a sufficient data rate by selecting a proper SC target, which has the highest signal to interference plus noise ratio (SINR), from a reduced neighbour cell list (NCL). The proposed method uses a modified A3 HO triggering condition taking into account the interference and cell load. Results show that our proposed method can perform inbound HO while keeping the throughput to the maximum level. Moreover, the proposed method has significantly minimized the unnecessary inbound HOs and radio link failures compared to the competitive methods. With different network load factors, the proposed method can significantly give a good performance which yields higher throughput for the user and the network as well.

Stochastic geometry analysis of coverage probability in energy efficient dense heterogeneous network with sleep control mechanism

The effect of LH on the intracellular free Ca2+ concentration ([Ca2+]i) was investigated in highly purified small and large bovine luteal cell populations. Luteal cells were obtained from midcycle corpora lutea dispersed with collagenase and separated by flow cytometry into large and small cells. Resting levels of Ca2+ were higher (P less than 0.05) in the large than small cells [314 +/- 25 nM (n = 5) vs. 186 +/- 13 nM (mean +/- SE; n = 13) for large and small cells, respectively]. LH rapidly increased [Ca2+]i in both small and large cells loaded with the fluorescent Ca2+ probe fura-2. In the small cells, [Ca2+]i was immediately increased 2- to 6-fold (from 176 +/- 8 to 468 +/- 8 nM; n = 5) after adding LH. The LH induced [Ca2+]i rise occurred in two phases: an initial peak due to intracellular Ca2+ mobilization and a secondary rise due to Ca2+ influx from extracellular sources. Preincubation of the small cells with EGTA reduced the initial phase and abolished the secondary rise in [Ca2+]. Both forskolin and 8-bromo-cAMP increased [Ca2+]i in the small cells. In contrast, only a single phase of [Ca2+]i rise was observed in LH-treated large cells, and the response was 1.5- to 2-fold greater than the resting Ca2+ levels [314 +/- 25 vs. 435 +/- 60 nM (n = 4), for resting vs. LH-treated values, respectively]. The addition of both LH and prostaglandin F2 alpha (PGF2 alpha) to the large cells resulted in increases in [Ca2+]i that were greater than those induced by each hormone separately (2.0-fold for LH and 2.7-fold for PGF2 alpha vs. 7- to 9-fold in the presence of both hormones). These findings demonstrate that LH induces rapid increases in intracellular [Ca2+]i that differ in magnitude and profile between the small and large bovine luteal cells. Furthermore, LH and PGF2 alpha interacted to promote increases in [Ca2+]i in the large cells, that were higher than the sum of [Ca2+]i induced by each hormone separately.

Small cell enhancement has been considered as a promising way to cope with the rapid growth of need in mobile data traffic. However, it also leads to severe inter-cell interference, which means that some interference mitigation scheme is indispensable. Among lots of interference mitigation scheme, small cell on/off adaptation is thought to be an effective one. In this paper, small cells are modeled as a 2-D Poisson point process (PPP) based on stochastic geometry. And then the coverage probability of the small cell network can be derived as a tractable close-form expression. In addition, a Monte Carlo simulation is performed to verify the accuracy of the stochastic geometry model. Subsequently, the numerical results shows that small cell on/off adaptation can improve the receiving signal to interference plus noise ratio (SINR) of small cell downlink transmission by 4-6 dB. Meanwhile, the average ergodic transmission rate and power efficiency are both enhanced due to the improvement of the wireless environment.

This communication presents a dual-band aperture-shared high gain antenna for millimeter-wave (mm-wave) multi-beam and sub-6 GHz applications by integrating transmitarray into Fresnel zone plate (FZP) lens. The transmistarray consists of two sets of unit cells (UCs), which can provide high transmission magnitude and [ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$-\pi $ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula> ] phase tuning at the mm-wave frequency band. Meanwhile, they show distinct transmission features at the sub-6 GHz band (one set of UC allows the electromagnetic (EM) wave to pass while the other prohibits the EM wave from passing). Then, by properly arranging the two kinds of UCs into the transparent and opaque region of the FZP lens respectively, the sub-6 GHz FZP lens and the mm-waveband transmitarray are integrated into the same aperture seamlessly. A waveguide-integrated patch antenna is adopted as the feed. The patch antenna operates at the sub-6 GHz band and three open waveguide antennas are used for the mm-wave multi-beam radiation. The proposed antenna achieves high gain at both bands with a reused radiating aperture. Mm-wave multi-beam radiation is obtained without an extra feeding network. For demonstration purposes, the central frequencies of the sub-6 GHz and the mm-wave bands are selected at 6 and 27 GHz, respectively. An antenna prototype is fabricated and experimentally verified.

Ultra dense network of small cells (SCs) was introduced to support high data rate services and increase network capacity. Owing to user equipment (UE) mobility and limited coverage of SCs, the load across a SC network recurrently becomes unbalanced. Such unbalanced loads result in performance degradation of network in terms of throughput, inefficient utilization of network resources and link failure. This paper proposes and evaluates a novel load balancing methodology based on UE-SC association, which incorporated two main factors:(i)load of SCs in UE’s neighborhood (ii)the received Signal to Interference and Noise Ratio (SINR)/Channel Quality Indicator (CQI) and Quality of Service (QoS) requirements of user. The proposed algorithm ensures that the standard deviation of load in SCs in the neighborhood of a given UE remains minimum when the UE is associated to a potential SC. Consequently, achieving load balancing among SCs proactively while maintaining high SINR/CQI levels for UE, with each UE-SC pairing. System-level simulations show that the proposed algorithm provides a more balanced load across network, which is quantified by a smaller standard deviation of load across the SCs and higher network throughput when compared to other load balancing algorithms.

Storaci-Mobile phone communication has become heart of the Global economic development over past decade. As the number of users (human as well as devices) grow exponentially with each year, there is an immense need to increase capacity and throughput with minimum possible upgradation in vast existing network. The 4G-LTE cellular network capacity can be increased by massive deployment of small cells and leveraging very high frequency bands in conjunction with a Macro cell. The presence and usage of small (Phantom) cells are dynamically controlled by a Macro cell. The connection between user equipment (UE) and small cell nodes is achieved by using control and user (C/U) planes splitted at radio link. It can achieve high capacity enhancement by massive deployment of small cells. NS-3 simulations were carried out and results shows capacity enhancement and throughput.

As one of the key technique to realize the large network capacity in the fifth generation mobile communication networks (5G), ultra-dense networks (UDNs) is centralized deployment of small cell stations (SCSs) which is caused interference problem and complex network structure, hinder the application of existing radio resource management (RRM) and interference management (IM) scheme on UDNs directly. Clustered RRM and IM provides a feasibility mechanism to solve this problem. However, how to properly form SCS cluster has not been well studied. We believe that small cells clustering is an effective method to simplify the topology of ultra-dense network. The trend of clustering approach is lower complexity and user-centric. In this paper, we propose a user-centric adaptive small-cell clustering scheme based on improved K-means algorithm. Simulation results show that the proposed scheme can dynamic adjust the size and number of small cell clusters according to user's signal to interference plus noise ratio (SINR), and reduce the computational complexity in the clustering process effectively.

The second part of the study of beamforming issues, based on positioning in ultra-dense millimeter wave radio access networks, is devoted to the formalization and software implementation of a complex simulation model of the functioning of a set of directional radio links. Each directional radio link between a base station (gNodeB – gNB), equipped with an antenna array, and a user equipment (UE), operating in omnidirectional mode, is formed according to the location of the UE, known at the gNB. The set of gNB→UE directional radio links, simultaneously operating in a common frequency range, is studied as a set of traffic beams, that implement space division multiple access (SDMA). Spatial multiplexing is implemented through three-dimensional beamforming at the gNB and makes it possible to compensate for propagation losses and high levels of interference. In the first part of the study, it was shown that the problem of practical implementation of SDMA in ultra-dense radio access networks is a significant (tens of dB) spread in the signal to interference plus noise ratio (SINR), depending on the arrangement of two devices. The purpose of this study is to establish the dependence of SINR on 1) the beamwidth of the gNB sector in the direction of the user equipment in the radio link of the signal of interest (SOI); 2) uncertainty of the UE location; 3) interference from radio links of signal not of interest (SNOI): a) within its sector, b) other sectors of its cell and c) other cells in the network. The simulation model developed and implemented in software in this work for the first time made it possible to establish the interdependence of the UE positioning error factors and the required width of the traffic beam for its service. In particular, it was found, that as the positioning error decreases from 10 to 1 m, the required beam width in the horizontal and vertical planes narrows to 3 °, which makes it possible to increase the SINR to 25 dB. A simultaneous transmission multiplexing study showed that for 64 spatially multiplexed UEs, as the cell size increases from 20 to 300 m, the SINR increases by approximately 30 dB, subject to a beamwidth constraint of 3°. Unlike similar studies, in this model, the contribution from interference from simultaneously operating traffic beams within its sector, other sectors of its cell and other cells in the network is shown separately for the first time, which allows to differentiate the origin of interference and use scientifically based beamwidth control for their compensation.

Small cells are low power nodes, which have lower transmit power than the macro eNodeB. They are regarded as one of the important solutions in long term evolution advanced (LTE-A) to deal with the dramatically increased mobile data traffic. Small cells deployments in LTE-A release 12 with 4 small cells in a cluster suffer from stronger inter-cell interference than heterogeneous network (HetNet) in the previous release of LTE-A, where one small cell exists in a cluster. We investigate the joint least squares channel estimation (JLSCE) over demodulation reference signals (DMRS) spreading in time and frequency resources in LTE-A systems. Furthermore, different receiver structures using least square channel estimation (LSCE) and JLSCE are investigated in small cell deployments with the presence of strong inter-cell interference. Our results show the linear minimum mean square error (LMMSE)-interference rejection combining (IRC) with LSCE is the most efficient receiver structure compared to the enhanced (e)LMMSE-IRC with JLSCE, interference cancellation (IC) with eLMMSE-IRC and maximum ratio combining (MRC) receiver structures for signal detection in small cell deployments.