5G Ultradense Networks With Nonuniform Distributed Users

Ye, Junliang; Ge, Xiaohu; Mao, Guoqiang; Zhong, Yi

doi:10.1109/tvt.2017.2771481

Cited by 28 publications

(6 citation statements)

References 38 publications

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“…In mmWave networks, since mmWave signals are transmitted with narrow beamwidths, therefore, the effects of multipath fading is not that severe as the delay spread of the channel is small. It is also clearly outlined in [2,5] that the small-scale fading can be ignored in the analysis carried out for the mmWave network. For an analytical tractability, in this work the Nakagami fading model is considered.…”

Section: A Received Signal Power Model 1) Mmwave Networkmentioning

confidence: 99%

“…The key enablers for 5G networks at the physical layer include heterogeneous cellular networks (HetNets) with massive multiple-input multiple-output (MIMO) technology and millimeter wave (mmWave) communication at 10 to 300 GHz radio frequency bands with bandwidths as high as 2 GHz [2]- [4]. The HetNets create a layer of overlay deployment of small cells of low-powered base stations (BS), variable communication ranges, and operating frequencies on the existing sub-6 GHz macro cells thus providing enhanced coverage and throughput to the end users by bringing network closer to them [5].…”

Section: Introductionmentioning

confidence: 99%

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Secrecy Spectrum and Energy Efficiency Analysis in Massive MIMO-Enabled Multi-Tier Hybrid HetNets

Umer

Hassan

Pervaiz

et al. 2020

IEEE Trans. on Green Commun. Netw.

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Massive multiple antenna systems in conjunction with millimeter (mmWave) communication have gained tremendous attention in the recent years owing to their high speed data delivery. However, security in these networks has been overlooked; thereby necessitating a comprehensive study. This paper analyzes the physical layer security performance of the downlink of a massive multiple-input multiple-output (MIMO)-based hybrid heterogeneous network (HetNet) where both mmWave and sub-6 GHz small cells coexist. Specifically, a tractable approach using stochastic geometry is proposed to analyze the secrecy outage probability, secrecy energy efficiency (SEE) and secrecy spectrum efficiency (SSE) of the hybrid HetNets. Our study further characterizes the impact of large antenna arrays, directional beamforming gains, transmit power, and cell density on the above mentioned secrecy performance measures. The results show that at low transmit power operation, the secrecy performance enhances for higher small cell density. It has also been observed that the higher directivity gains at mmWave cells lead to a drop in secrecy performance of the network; thus a tradeoff exists between better coverage or secrecy.This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TGCN.2019.2956433, IEEE Transactions on Green Communications and Networking complex solution for the protection of confidential information in complex wireless networks [8]. Particularly, PLS in massive MIMO-enabled hybrid HetNets with mmWave small cells is important since the aforementioned networks present the most common deployment scenario for the future 5G communication networks. This paper analyses the PLS in massive MIMO-enabled hybrid HetNets by digging into unique advantageous properties of massive MIMO and mmWave channel.

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Section: A Received Signal Power Model 1) Mmwave Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Secrecy Spectrum and Energy Efficiency Analysis in Massive MIMO-Enabled Multi-Tier Hybrid HetNets

Umer

Hassan

Pervaiz

et al. 2020

IEEE Trans. on Green Commun. Netw.

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“…In [21], the authors accounted for the backhaul limitation to address the user's outage probability with homogeneous small cells, providing insights over the enhanced SCDP when adjusting the access nodes' density given a fixed content caching placement strategy. Most recently, in [22], queuing theory was employed to model the movement of UEs to distinct hot-spots and evaluate the throughput and EE performance. Though spatially dependent UE density was considered, homogeneous deployment of SBS was assumed within the same hot-spot.…”

Section: A Literature Reviewmentioning

confidence: 99%

Ultra Dense Edge Caching Networks With Arbitrary User Spatial Density

Gruppi

Wong

Bocus

et al. 2020

IEEE Trans. Wireless Commun.

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Cache-enabled small cells can be an effective solution to deliver contents to mobile users with much lower power and latency. While the trend for getting smaller and denser cells is clear, interference will soon become unmanageable and an obstacle when the number of content requests is massive. Moreover, content request is seldom a spatially homogeneous process due to physical impediments (e.g., buidings) and social activities, which makes resource allocation for content delivery more challenging. In this paper, we consider an ultra-dense network (UDN) in which content requests are served by cacheenabled access nodes which can either be active for delivering contents to users, or inactive to reduce interference and network energy consumption. Our aim is to devise an approach that can locally adapt the caching node density and content caching probabilities to accommodate any arbitrary user density and content request for maximizing the network's successful content delivery probability (SCDP). With a non-homogeneous spatial distribution for user equipments (UEs), we find that user-load, a parameter at the access node, plays a major role in the overall optimization. Simulation results illustrate that the proposed method can obtain superior performance against the considered benchmarks, with up to 150-160% increase, and our optimized solutions effectively adapt to the spatial-dependent user density.

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“…ALGORITHM FOR PREDICTING USER DATA THROUGHPUT SC on/off process has the various effects on the network because the traffics of turned off cells are handed over to neighboring cells. Although several SCs are turned off in order to improve NEE, the UEs in turned off cell may be connected to a SC that shows a lower RSRP than original cell and UEs in neighboring cell have to share the radio resource with handover UEs [9]. Therefore, the SC on/off process is carried out after sufficient consideration.…”

Section: System Modelmentioning

confidence: 99%

UE throughput guaranteed small cell on/off algorithm with machine learning

2020

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Ultra-dense network (UDN) has been considered a promising solution to improve the signal quality of cell edge UEs and enhance the serving coverage. However, a large number of small cells causes severe inter-cell interference and high energy consumption, and efficient small cell management is an important issue. In this paper, a UE throughput guaranteed small cell on/off algorithm in UDN environment is proposed to solve the problem of UE throughput reduction due to small cell off process. The proposed small cell on/off algorithm with machine learning is executed by the following processes: First, the network attributes that affect UE throughput are analyzed. Second, the correlation between UE throughput and network attributes is evaluated through multiple linear regression analysis. Third, through understanding the correlation between UE throughput and network attributes, we determine the proper criteria for small cell on/off process. Simulation results show that the proposed small cell on/off algorithm can improve the total network energy efficiency as well as efficiently ensure sufficient UE throughput. Compare to the conventional algorithm, the proposed algorithm shows more than 75% improvements of average network energy efficiency. whole network.

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5G Ultradense Networks With Nonuniform Distributed Users

Cited by 28 publications

References 38 publications

Secrecy Spectrum and Energy Efficiency Analysis in Massive MIMO-Enabled Multi-Tier Hybrid HetNets

Secrecy Spectrum and Energy Efficiency Analysis in Massive MIMO-Enabled Multi-Tier Hybrid HetNets

Ultra Dense Edge Caching Networks With Arbitrary User Spatial Density

UE throughput guaranteed small cell on/off algorithm with machine learning

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