Traffic-aware user association technique for dynamic on/off switching of small cells

2015 ◽  
Author(s):  
Shady O. Elbassiouny ◽  
Ahmed Elhamy ◽  
Ahmed S. Ibrahim
Keyword(s):  
Small Cells ◽  
User Association

scholarly journals Transmit and Receive Antenna Selection Based Resource Allocation for Self-Backhaul 5G Massive MIMO HetNets

2021 ◽  
Author(s):  
Farah Akif ◽  
Aqdas Malik ◽  
Ijaz Qureshi ◽  
Ayesha Abassi
Keyword(s):  
Network Performance ◽  
Service Providers ◽  
Antenna Selection ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Base Stations ◽  
Small Cells ◽  
User Association ◽  
Transmit Antenna Selection ◽  
Coverage Area

With the advancement in wireless communication technology, the ease of accessibility and increasing coverage area is a major challenge for service providers. Network densification through Small cell Base Stations (SBS) integration in Heterogeneous Networks (HetNets) promises to improve network performance for cell edge users. Since providing wired backhaul for small cells is not cost effective or practical, the third-Generation Partnership Project (3GPP) has developed architecture for self-backhaul known as Integrated Access and Backhaul (IAB) for Fifth Generation (5G). This allows for Main Base Station (MBS) resources to be shared between SBS and MBS users. However, fair and efficient division of MBS resources remains a problem to be addressed. We develop a novel transmit antenna selection/partitioning technique for taking advantage of IAB 5G standard for Massive Multiple Input Multiple Output (MIMO) HetNets. Transmit antenna resources are divided among access for MBS users and for providing wireless backhaul for SBS. We develop A Genetic Algorithm (GA) based Transmit Antenna Selection (TAS) scheme and compare with random selection, eigenvalue-based selection and bandwidth portioning. Our analysis show that GA based TAS has the ability to converge to an optimum antenna subset providing better rate coverage. Furthermore, we also signify the performance of TAS based partitioning over bandwidth partitioning and also show user association can also be controlled using number of antennas reserved for access or backhaul.

scholarly journals Cross-Entropy Method for Content Placement and User Association in Cache-Enabled Coordinated Ultra-Dense Networks

Entropy ◽  
2019 ◽  
Vol 21 (6) ◽  
pp. 576 ◽  
Author(s):  
Jia Yu ◽  
Ye Wang ◽  
Shushi Gu ◽  
Qinyu Zhang ◽  
Siyun Chen ◽  
...  
Keyword(s):  
Mobile Communications ◽  
Network Throughput ◽  
Cross Entropy ◽  
Traffic Load ◽  
Small Cells ◽  
User Association ◽  
Cell Edge ◽  
Dense Networks ◽  
Cross Entropy Method ◽  
Content Placement

Due to the high splitting-gain of dense small cells, Ultra-Dense Network (UDN) is regarded as a promising networking technology to achieve high data rate and low latency in 5G mobile communications. In UDNs, each User Equipment (UE) may receive signals from multiple Base Stations (BSs), which impose severe interference in the networks and in turn motivates the possibility of using Coordinated Multi-Point (CoMP) transmissions to further enhance network capacity. In CoMP-based Ultra-Dense Networks, a great challenge is to tradeoff between the gain of network throughput and the worsening backhaul latency. Caching popular files on BSs has been identified as a promising method to reduce the backhaul traffic load. In this paper, we investigated content placement strategies and user association algorithms for the proactive caching ultra dense networks. The problem has been formulated to maximize network throughput of cell edge UEs under the consideration of backhaul load, which is a constrained non-convex combinatorial optimization problem. To decrease the complexity, the problem is decomposed into two suboptimal problems. We first solved the content placement algorithm based on the cross-entropy (CE) method to minimize the backhaul load of the network. Then, a user association algorithm based on the CE method was employed to pursue larger network throughput of cell edge UEs. Simulation were conducted to validate the performance of the proposed cross-entropy based schemes in terms of network throughput and backhaul load. The simulation results show that the proposed cross-entropy based content placement scheme significantly outperform the conventional random and Most Popular Content placement schemes, with with 50% and 20% backhaul load decrease respectively. Furthermore, the proposed cross-entropy based user association scheme can achieve 30% and 23% throughput gain, compared with the conventional N-best, No-CoMP, and Threshold based user association schemes.

scholarly journals QoS controlled capacity offload optimization in heterogeneous networks

2020 ◽  
Vol 9 (6) ◽  
pp. 2667-2680
Author(s):  
Siva Priya Thiagarajah ◽  
Mohamad Yusoff Alias ◽  
Wooi-Nee Tan
Keyword(s):  
Load Balancing ◽  
High Efficiency ◽  
Low Complexity ◽  
Network Capacity ◽  
Small Cells ◽  
User Association ◽  
Allocation Mechanism ◽  
Grid Topology ◽  
Efficient Resource ◽  
User Data

An efficient resource allocation mechanism in the physical layer of wireless networks ensures that resources such as bandwidth and power are used with high efficiency in spite of low delay and high edge user data rate. Microcells in the network are typically set with bias settings to artificially increase the Signal-to-Interference-Plus-Noise Ratio, thus encouraging users to offload to the microcell. However, the artificial bias settings are tedious and often suboptimal. This work presents a low complexity algorithm for maximization of network capacity with load balancing in a heterogeneous network without the need for bias setting. The small cells were deployed in a grid topology at a selected distance from macrocell to enhance network capacity through coverage overlap.  User association and minimum user throughput were incorporated as constraints to enable closer simulation to real word Quality of Service requirements. The results showed that the proposed algorithm was able to maintain less than 10% user drop rate. The proposed algorithm can increase user confidence as well as maintain load balancing, maintain the scalability, and reduce power consumption of the wireless network.

scholarly journals Scalable Spectrum Allocation and User Association in Networks With Many Small Cells

2017 ◽  
Vol 65 (7) ◽  
pp. 2931-2942 ◽  
Author(s):  
Binnan Zhuang ◽  
Dongning Guo ◽  
Ermin Wei ◽  
Michael L. Honig
Keyword(s):  
Spectrum Allocation ◽  
Small Cells ◽  
User Association

Comparison of Choriocarcinoma and Normal Placenta

1971 ◽  
Vol 29 ◽  
pp. 324-325
Author(s):  
John C. Garancis ◽  
Roland A. Pattillo ◽  
Robert O. Hussa ◽  
Jon V. Straumfjord
Keyword(s):  
Cell Lines ◽  
Small Cells ◽  
Tissue Cultures ◽  
Glycogen Depletion ◽  
Cell Surfaces ◽  
Intercellular Spaces ◽  
Concomitant Increase ◽  
Gestational Choriocarcinoma ◽  
Cytoplasmic Glycogen ◽  
Normal Placenta

Two different cell lines (Be-Wo and Jar) of human gestational choriocarcinoma have been maintained in continuous tissue culture for a period of four and two years respectively without losing the ability to elaborate human chorionic gonadotropin (HCG). Tissue cultures, as revealed by electron microscopy, consisted of small cells with single nuclei. In some instances cell surfaces were provided with microvilli but more often the intercellular spaces were narrow and bridged by desmosomes. However, syncytium was not formed. Endoplasmic reticulum (ER) was poorly developed in both cell lines, except in some Be-Wo cells it was prominent. Golgi complex, lysosomes and numerous free ribosomes, as well as excessive cytoplasmic glycogen, were present in all cells (Fig. 1). Glycogen depletion and concomitant increase of ER were observed in many cells following a single dose of 10 ugm/ml of adrenalin added to medium (Fig. 2).

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