• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2454-2467
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• 2015

Increasing traffic and bandwidth requirements bring challenges to the next generation wireless networks (5G). As one of the main technology in 5G networks, Ultra-Dense Network (UDN) can be used to improve network coverage. In this paper, a radio over fiber based model is proposed to solve the load balancing problem in ultra-dense network. Stochastic differential game is introduced for the load balancing algorithm, and optimal load allocated to each access point (RAP) are formulated as Nash Equilibrium. It is proved that the optimal load can be achieved and the stochastic differential game based scheme is applicable and acceptable. Numerical results are given to prove the effectiveness of the optimal algorithm.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.58-67
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• 2020

In this paper, we propose a data-driven-based beam selection scheme for massive multiple-input and multiple-output (MIMO) systems in ultra-dense networks (UDN), which is capable of addressing the problem of high computational cost of conventional coordinated beamforming approaches. We consider highly dense small-cell scenarios with more small cells than mobile stations, in the millimetre-wave band. The analog beam selection for hybrid beamforming is a key issue in realizing millimetre-wave UDN MIMO systems. To reduce the computation complexity for the analog beam selection, in this paper, two deep neural network models are used. The channel samples, channel gains, and radio frequency beamforming vectors between the access points and mobile stations are collected at the central/cloud unit that is connected to all the small-cell access points, and are used to train the networks. The proposed machine-learning-based scheme provides an approach for the effective implementation of massive MIMO system in UDN environment.

• ETRI Journal
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• v.40 no.2
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• pp.227-236
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• 2018

Ultra-dense small cell networks (UD-SCNs) have been identified as a promising scheme for next-generation wireless networks capable of meeting the ever-increasing demand for higher transmission rates and better quality of service. However, UD-SCNs will inevitably suffer from severe interference among the small cell base stations, which will lower their spectral efficiency. In this paper, we propose a software-defined networking (SDN)-based hierarchical agglomerative clustering (SDN-HAC) framework, which leverages SDN to centrally control all sub-channels in the network, and decides on cluster merging using a similarity criterion based on a suitability function. We evaluate the proposed algorithm through simulation. The obtained results show that the proposed algorithm performs well and improves system payoff by 18.19% and 436.34% when compared with the traditional network architecture algorithms and non-cooperative scenarios, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4108-4122
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• 2016

To address challenges of an unprecedented growth in mobile data traffic, the ultra-dense network deployment is a cost efficient solution to off-load the traffic over other small cells. However, the real traffic is often much lower than the peak-hour traffic and certain small cells are superfluous, which will not only introduce extra energy consumption, but also impose extra interference onto the radio environment. In this paper, an elastic energy efficient cell management scheme is proposed based on flow scheduling among multi-layer ultra-dense cells by a SDN controller. A significant power saving was achieved by a cell-level energy manager. The scheme is elastic for energy saving, adaptive to the dynamic traffic distribution in the office or campus environment. In the end, the performance is evaluated and demonstrated. The results show substantial improvements over the conventional method in terms of the number of active BSs, the handover times, and the switches of BSs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2680-2696
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• 2018

The collaborative content caching system is an effective solution developed in recent years to reduce transmission delay and network traffic. In order to decrease the service end-to-end transmission delay for future 5G ultra-dense networks (UDN), this paper proposes a novel service migration method that can guarantee the continuity of service and simultaneously reduce the traffic flow in the network. In this paper, we propose a service migration optimization model that minimizes the cumulative transmission delay within the constraints of quality of service (QoS) guarantee and network condition. Subsequently, we propose an improved firefly algorithm to solve this optimization problem. Simulation results show that compared to traditional collaborative content caching schemes, the proposed algorithm can significantly decrease transmission delay and network traffic flow.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.494-513
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• 2019

A multi-channel access problem based on hypergraph model in ultra-dense small cell networks is studied in this paper. Due to the hyper-dense deployment of samll cells and the low-powered equipment, cumulative interference becomes an important problem besides the direct interference. The traditional binary interference model cannot capture the complicated interference relationship. In order to overcome this shortcoming, we use the hypergraph model to describe the cumulative interference relation among small cells. We formulate the multi-channel access problem based on hypergraph as two local altruistic games. The first game aims at minimizing the protocol MAC layer interference, which requires less information exchange and can converge faster. The second game aims at minimizing the physical layer interference. It needs more information interaction and converges slower, obtaining better performance. The two modeled games are both proved to be exact potential games, which admit at least one pure Nash Equilibrium (NE). To provide information exchange and reduce convergecne time, a cloud-based centralized-distributed algorithm is designed. Simulation results show that the proposed hypergraph models are both superior to the existing binary models and show the pros and cons of the two methods in different aspects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5400-5418
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• 2016

Femtocells are envisioned as a key solution to embrace the ever-increasing high data rate and thus are extensively deployed. However, the dense and random deployments of femtocell access points (FAPs) induce severe intercell inference that in turn may degrade the performance of spectral efficiency. Hence, unrestrained proliferation of FAPs may not acquire a net throughput gain. Besides, given that numerous FAPs deployed in ultra-dense networks (UDNs) lead to significant energy consumption, the amount of FAPs deployed is worthy of more considerations. Nevertheless, little existing works present an analytical result regarding the optimal FAP density for a given User Equipment (UE) density. This paper explores the realistic scenario of randomly distributed FAPs in UDN and derives the coverage probability via Stochastic Geometry. From the analytical results, coverage probability is strictly increasing as the FAP-to-UE ratio increases, yet the growing rate of coverage probability decreases as the ratio grows. Therefore, we can consider a specific FAP-to-UE ratio as the point where further increasing the ratio is not cost-effective with regards to the requirements of communication systems. To reach the optimal FAP density, we can deploy FAPs in line with peak traffic and randomly switch off FAPs to keep the optimal ratio during off-peak hours. Furthermore, considering the unbalanced nature of traffic demands in the temporal and spatial domain, dynamically and carefully choosing the locations of active FAPs would provide advantages over randomization. Besides, with a huge FAP density in UDN, we have more potential choices for the locations of active FAPs and this adds to the demand for a strategic sleeping policy.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.25-31
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• 2022

In ultra dense networks (UDNs), macro user equipments (MUEs) have significant interference from small-cell access points (SAPs) since a number of SAPs are deployed in the coverage of macro base stations of 5G mobile communication systems. In this paper, we propose a dynamic channel assignment scheme to increase the performance of MUEs for the uplink of UDNs even though the number of SAPs is increased. The target of the proposed dynamic channel assignment scheme is that the signal-to-interference and noise ratio (SINR) of MUEs is above a given SINR threshold assigning different subchannels to SUEs from those of MUEs. Simulation results show that the proposed dynamic channel assignment scheme outperforms others in terms of the mean MUE capacity even though the mean SUE capacity is decreased a little lower.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.343-364
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• 2021

In the 5G era, the communication networks tend to be ultra-densified, which will improve the accuracy of indoor positioning and further improve the quality of positioning service. In this study, we propose an indoor three-dimensional (3D) dynamic reconstruction fingerprint matching algorithm (DSR-FP) in a 5G ultra-dense network. The first step of the algorithm is to construct a local fingerprint matrix having low-rank characteristics using partial fingerprint data, and then reconstruct the local matrix as a complete fingerprint library using the FPCA reconstruction algorithm. In the second step of the algorithm, a dynamic base station matching strategy is used to screen out the best quality service base stations and multiple sub-optimal service base stations. Then, the fingerprints of the other base station numbers are eliminated from the fingerprint database to simplify the fingerprint database. Finally, the 3D estimated coordinates of the point to be located are obtained through the K-nearest neighbor matching algorithm. The analysis of the simulation results demonstrates that the average relative error between the reconstructed fingerprint database by the DSR-FP algorithm and the original fingerprint database is 1.21%, indicating that the accuracy of the reconstruction fingerprint database is high, and the influence of the location error can be ignored. The positioning error of the DSR-FP algorithm is less than 0.31 m. Furthermore, at the same signal-to-noise ratio, the positioning error of the DSR-FP algorithm is lesser than that of the traditional fingerprint matching algorithm, while its positioning accuracy is higher.

• Journal of Communications and Networks
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• v.9 no.4
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• pp.482-489
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• 2007

In this paper, two frequency domain signal processing techniques for pulse shape modulation(PSM) ultra wideband(UWB) systems are presented. Firstly, orthogonal detection of UWB PSM Hermite pulses in frequency domain is addressed. It is important because time domain detection by correlation-based receivers is severely degraded by many sources of distortion. Pulse-shape, the information conveying signal characteristic, is deformed by AWGN and shape-destructive addition of multiple paths from the propagation channel. Additionally, because of the short nature of UWB pulses, timing mismatches and synchronism degrade the performance of PSM UWB communication systems. In this paper, frequency domain orthogonality of the Hermite pulses is exploited to propose an alternative detection method, which makes possible efficient detection of PSM in dense multipath channel environments. Secondly, a ranging method employing the Cepstrum algorithm is proposed. This method is partly processed in the frequency domain and can be implemented without additional hardware complexity in the terminal.