• Journal of Communications and Networks
• /
• v.18 no.2
• /
• pp.135-149
• /
• 2016

Cloud radio access network (C-RAN) refers to the virtualization of base station functionalities by means of cloud computing. This results in a novel cellular architecture in which low-cost wireless access points, known as radio units or remote radio heads, are centrally managed by a reconfigurable centralized "cloud", or central, unit. C-RAN allows operators to reduce the capital and operating expenses needed to deploy and maintain dense heterogeneous networks. This critical advantage, along with spectral efficiency, statistical multiplexing and load balancing gains, make C-RAN well positioned to be one of the key technologies in the development of 5G systems. In this paper, a succinct overview is presented regarding the state of the art on the research on C-RAN with emphasis on fronthaul compression, baseband processing, medium access control, resource allocation, system-level considerations and standardization efforts.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.3
• /
• pp.1174-1192
• /
• 2021

With the assistance of non-orthogonal multiple access (NOMA), the spectrum efficiency and the number of users in cloud radio access network (CRAN) can be greatly improved. In this paper, the system performance of NOMA-assisted CRAN is investigated. Specially, the outage probability (OP) and ergodic sum rate (ESR), are derived for performance evaluation of the system, respectively. Based on this, by minimizing the OP of the system, a suboptimal power allocation (PA) scheme with closed-form PA coefficients is proposed. Numerical simulations validate the accuracy of the theoretical results, where the derived OP has more accuracy than the existing one. Moreover, the developed PA scheme has superior performance over the conventional fixed PA scheme but has smaller performance loss than the optimal PA scheme using the exhaustive search method.

• The Journal of Korean Institute of Information Technology
• /
• v.17 no.2
• /
• pp.71-77
• /
• 2019

With 5G standards proceeding in earnest and increasing demand for services of indoor localization, research on indoor location recognition is being studied in various industrial fields, and research based on fingerprint recognition technology using Wireless Local Area Network (WLAN) is representative. In this paper, we propose an indoor positioning system based on fingerprinting technique that uses Cloud Radio Access Network (C-RAN) architecture and Channel State Information (CSI). In order to improve the performance in indoor positioning, we combined existing fingerprinting method and K nearest neighbor (KNN) technology which is one of the machine running technique. The performance improvements of the proposed indoor positioning system was verified by comparative experiments with the existing localization technique in a indoor localizztion testbed.

• Journal of Communications and Networks
• /
• v.15 no.4
• /
• pp.398-406
• /
• 2013

In this paper, we investigate two types of in-phase and quadrature-phase (IQ) data transfer methods for cloud multiple-input multiple-output (MIMO) network operation. They are termed "after-precoding" and "before-precoding". We formulate a cloud massive MIMO operation problem that aims at selecting the best IQ data transfer method and transmission strategy (beamforming technique, the number of concurrently receiving users, the number of used antennas for transmission) to maximize the ergodic sum-rate under a limited capacity of the digital unit-radio unit link. Based on our proposed solution, the optimal numbers of users and antennas are simultaneously chosen. Numerical results confirm that the sum-rate gain is greater when adaptive "after/before-precoding" method is available than when only conventional "after-precoding" IQ-data transfer is available.

• Journal of Broadcast Engineering
• /
• v.19 no.1
• /
• pp.14-23
• /
• 2014

This paper proposed controlling methods for SDN(Software Defined Network) based multiple radio access technology as the solutions of following two issues which were mainly occurred by explosive increasing of video traffic. The first one is a requirement for traffic off-loading caused by 3rd-party video service providers from the mobile network operator's viewpoint. The other one is a provision of high-speed video contents transmission services with low price. Furthermore, the performance evaluation was also conducted on the real test-bed which is composed of OpenStack cloud and SDN technology such as OpenFlow and Open vSwitch. A virtual machine running on the OpenStack provide a video service and the terminal which is able to use multiple radio access technology supports two 2.4GHz WLANs(Wireless Local Area Network) and three 5GHz WLANs, concurrently. Finally, we can get 820Mbps of the maximum transmission speed by using that five WLAN links for the single service at the same time.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.8
• /
• pp.3821-3841
• /
• 2019

Cloud radio access networks (C-RANs) have been regarded in recent times as a promising concept in future 5G technologies where all DSP processors are moved into a central base band unit (BBU) pool in the cloud, and distributed remote radio heads (RRHs) compress and forward received radio signals from mobile users to the BBUs through radio links. In such dynamic environment, automatic decision-making approaches, such as artificial intelligence based deep reinforcement learning (DRL), become imperative in designing new solutions. In this paper, we propose a generic framework of autonomous cell activation and customized physical resource allocation schemes for energy consumption and QoS optimization in wireless networks. We formulate the problem as fractional power control with bandwidth adaptation and full power control and bandwidth allocation models and set up a Q-learning model to satisfy the QoS requirements of users and to achieve low energy consumption with the minimum number of active RRHs under varying traffic demand and network densities. Extensive simulations are conducted to show the effectiveness of our proposed solution compared to existing schemes.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38A no.1
• /
• pp.68-78
• /
• 2013

In this paper, we propose an early spectrum sensing(ESS) as an advance preparation for radio-access trial, which enables multi-mode terminals to access the most appropriate radio-access system in a cloud-conceptual base station system where multiple radio access technologies(RATs) coexist. Prior to a random access to one of RATs, a multi-mode terminal conducts a spectrum sensing over entire frequency bands of whole RATs, then select the RAT with the lowest sensing power, that is likely to have the most available spectrum. Thus, an access failure caused by that the selected RAT has no available radio spectrum could be avoidable in advance. In computer simulation, we consider as various RATs as possible. First, circuit and packet systems are taken into consideration. In addition, the packet systems are classified according to the feasibility of carrier aggregation(CA). In case of terminal, three modes are considered with circuit-only, packet-only, and multi-mode. Subsequently, packet traffic is classified into real-time and non-real-time traffic with three different tolerable delay levels. The simulation includes a call process starting with a call generation and ending up with a resource allocation reflecting individual user's QoS requirements and evaluates the proposed scheme in terms of the successful access probability, system access time, system balancing factor and packet loss probability.

• Information and Communications Magazine
• /
• v.30 no.9
• /
• pp.78-84
• /
• 2013

최근 4세대 이동통신은 기술/경제적인 이유로 클라우드 기지국 (또는 C-RAN: Cloud Radio Access Network) 구조를 택하는 추세이다. C-RAN은 기존 일체형 기지국에서의 MAC/PHY 기능을 담당하는 BBU(Base Band Unit)와 RF신호 송수신 만을 담당하는 RRH(Remote Radio Head)로 분리된 기지국 구조를 가지며, RRH의 무선 송수신 신호는 중앙의 BBU에 집중되어 처리된다. 본고에서는 BBU와 RRH로 분리되어 설치/운용되는 C-RAN의 구조와 기지국 가상화 개념을 소개하며, 향후 이동통신시스템에서의 기술동향과 관련하여 C-RAN에서 발생할 수 있는 이슈들을 살펴본다.

• Information and Communications Magazine
• /
• v.33 no.1
• /
• pp.49-53
• /
• 2015

본고에서는 4G/5G/WiFi 무선 통신의 C-RAN(Centralized/Cloud Radio Access Network)을 지원하는 xhaul망에서의 이더넷 응용 기술에 대해 분석한다. xhaul에서의 요구사항을 고찰하고, 이를 충족시키기 위한 이더넷 응용으로서 RoE(Radio over Ethernet)을 중심으로 한 기술 분석과 함께, 그 외 프론트홀 전송 기술을 알아봄으로써, xhaul에서의 이더넷의 응용과 더불어 기타 차세대 무선 망 기술과 함께 유무선 융합 전송 기술에 대한 방향을 타진해 보도록 한다.

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