Cloud Radio Access Network (C-RAN) is a novel mobile network architecture which can address a number of challenges the operators face while trying to support growing end-user's needs. The main idea behind C-RAN is to pool the Baseband Units (BBUs) from multiple base stations into centralized BBU Pool for statistical multiplexing gain, while shifting the burden to the high-speed wireline transmission of In-phase and Quadrature (IQ) data. C-RAN enables energy efficient network operation and possible cost savings on baseband resources. Furthermore, it improves network capacity by performing load balancing and cooperative processing of signals originating from several base stations. This paper surveys the state-of-the-art literature on C-RAN. It can serve as a starting point for anyone willing to understand C-RAN architecture and advance the research on C-RAN.

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Cloud RAN for Mobile Networks—A Technology Overview

A wireless communication method in a system in which subscriber stations are each operable for communication with a base station is provided. The base station is capable of performing simultaneous communications with a plurality of the subscriber stations simultaneously by exchange of packets each conforming with a layered protocol of said system. The packets include a first portion for defining physical layer (PHY) parameters and a second portion for defining media access layer (MAC) parameters. Furthermore, communications between the subscriber stations and the base station are performed wholly or partly through at least one relay station. In this system, the method includes, in the relay station, receiving a plurality of packets from the subscriber stations, detecting the second portion of each of the packets, combining the detected second portions to form a second portion of at least one new packet, and transmitting the new packet to the base station.

Wireless communication systems

The exponential increase in mobile data traffic is considered to be a critical driver towards the new era, or 5G, of mobile wireless networks. 5G will require a paradigm shift that includes very high carrier frequency spectra with massive bandwidths, extreme base station densities, and unprecedented numbers of antennas to support the enormous increase in the volume of traffic. This paper discusses several design choices, features, and technical challenges that illustrate potential research topics and challenges for the future generation of mobile networks. This article does not provide a final solution but highlights the most promising lines of research from the recent literature in common directions for the 5G project. The potential physical layer technologies that are considered for future wireless communications include spatial multiplexing using massive multi-user multiple-input multiple-output (MIMO) techniques with millimetre-waves (mm-waves) in small cell geometries. These technologies are discussed in detail along with the areas for future research.

Evolution towards fifth generation (5G) wireless networks: Current trends and challenges in the deployment of millimetre wave, massive MIMO, and small cells

Mobile data traffic grew by 74% in 2015 and it is expected to grow eight-fold by 2020. Future wireless networks will need to deploy massive number of small cells to cope with this increasing demand. Dense deployment of small cells will require advanced interference mitigation techniques to improve spectral efficiency and enhance much needed capacity. Coordinated multi-point (CoMP) is a key feature for mitigating inter-cell interference, improve throughput and cell edge performance. However, cooperation will need to be limited to few cells only due to additional overhead required by CoMP due to channel state information (CSI) exchange, scheduling complexity, and additional backhaul limitation. Hence, small CoMP clusters will need to be formed in the network. This paper surveys the state-of-the-art on one of the key challenges of CoMP implementation: CoMP clustering. As a starting point, we present the need for CoMP, the clustering challenge for 5G wireless networks and provide a brief essential background about CoMP and the enabling network architectures. We then provide the key framework for CoMP clustering and introduce self organization as an important concept for effective CoMP clustering to maximize CoMP gains. Next, we present two novel taxonomies on existing CoMP clustering solutions, based on self organization and aimed objective function. Strengths and weaknesses of the available clustering solutions in the literature are critically discussed. We then discuss future research areas and potential approaches for CoMP clustering. We present a future outlook on the utilization of big data in cellular context to support proactive CoMP clustering based on prediction modeling. Finally, we conclude this paper with a summary of lessons learned in this field. This paper aims to be a key guide for anyone who wants to research on CoMP clustering for future wireless networks.

Coordinated Multi-Point Clustering Schemes: A Survey

Coordinated multi-point (CoMP) has been selected as a key technology feature of LTE-Advanced, as it enables the exploitation of inter-cell interference in order to significantly increase spectral efficiency, especially at the cell-edge. While first field trials on CoMP schemes have delivered the proof-of-concept and shown that a moderate extent of theoretically predicated CoMP gains can indeed be achieved in practical systems, the implementation of these schemes has revealed many practical challenges. One central question is, for example, how small cooperation clusters can be extracted from large cellular systems, such that major portions of potential CoMP gains can be obtained at minimum signaling overhead. This paper deals with static clustering concepts, and shows that both in a hexagonal cell layout and under a realistic deployment and signal propagation scenario, static clustering concepts can perform close to optimal UE-specific clustering, while being easy to use and requiring negligible signaling overhead.

Static Clustering for Cooperative Multi-Point (CoMP) in Mobile Communications

Mobile data traffic has been increasing at a rapid pace over the past few years due to the rise of both smartphones and tablets. Small cell deployments are one of the most effective ways to increase system capacity by improving the spatial reuse of radio resources for the explosive increase in traffic loads. However, it leads to be a large cost impact for operators. Centralized RAN (C-RAN) has been proposed, which has the potential ability to reduce network costs due to reductions in civil work and/or electricity costs at local base station sites by centralizing baseband units to the center side. Moreover, C-RAN can be expected to further reduce network costs using baseband unit (BBU) pooling functions in which the centralized BBU resources can be dynamically allocated to remote radio heads (RRHs) depending on traffic load. This paper proposes semi-static and adaptive BBU-RRH switching schemes for C-RAN and evaluates their effectiveness through simulations. Under conditions of 100 RRHs, here, a RRH is comparable to a cell, and traffic distribution with a typical traffic profile in office (business) area, we confirmed that the number of BBUs can be reduced by 26% and 47% for semi-static and adaptive schemes, respectively, compared with conventional cell deployment.

BBU-RRH switching schemes for centralized RAN

Mobile data traffic has been increasing at a rapid pace over the past few years due to the rise of both smartphones and tablets To accommodate such a huge traffic volume in cellular systems, it is imperative to reduce cell size to increase system capacity To reduce cell size, the main issue confronting mobile network operators is system cost to provide coverage areas with small cells Therefore, we propose a suitable RAN architecture for deploying small cells First, a base band is physically separated into one baseband unit (BBU) and remote radio heads (RRHs) The BBUs are centralized in some locations One BBU can connect to one or more RRHs Such a network architecture, which we call Colony-RAN due to its ability to flexibly change cell layout, can dynamically change the connections of BBUs and RRHs in respect to traffic demand As a result, because traffic distribution is non-uniform, Colony-RAN can drastically reduce the number of BBUs due to the statistical multiplexing effect As a rough estimation based on the population of the Tokyo metropolitan area, we confirmed that the number of BBUs can be reduced by 75% with the co-located BBU and RRHs compared with conventional cellular systems Another characteristic of Colony-RAN is its ability to reduce inter-cell interference and increase link quality by accommodating several RRHs in the same BBU taking user mobility and/or user distributions into consideration

Colony-RAN architecture for future cellular network

Heterogeneous Network (HetNet) in 3GPP is a technique to increase network capacity. In order to further increase network capacity, Cell Range Expansion (CRE) and Time Domain Multiplexing Inter-Cell Interference Coordination (TDM-ICIC) have been discussed for LTE-Advanced. Since the　parameter values for CRE and TDM-ICIC have a huge effect on network capacity expansion, in this paper, a cell-planning model for the downlink in HetNet with CRE and TDM-ICIC is presented in order to find the minimum number of installed pico BSs under the constraint of covering all user data traffic. The constraint condition is formulated by using an overload indicator for the cases of between normal subframes and muted subframes, because different interference sources are considered for these subframes by adopting TDM-ICIC. The appropriate parameter values of not only CRE and TDM-ICIC but also the location, transmission power, and antenna tilt for each pico BS are determined. Cell planning is conducted for traffic distribution generated by reference to realistic traffic distribution by a greedy algorithm based on the proposed cell-planning model. The result shows that the solution algorithm finds a good approximate solution which covers all data traffic by installing one pico BS with CRE bias value = 8 dB and setting the muted subframe ratio = 0.2.

A Cell-Planning Model for HetNet with CRE and TDM-ICIC in LTE-Advanced

In conventional cellular systems, transmission rate degrades at cell-edge because of inter-cell interference and pathloss. This problem is called “cell-edge problem”. To solve this problem, Coordinated Multi-Point (CoMP) technique has been proposed recently. CoMP can convert inter-cell interference signals from neighbor base stations (BSs) to desired signals. However, CoMP requires accurate synchronization among cooperative BSs as well as Channel State Information (CSI) between target user and all cooperative BSs. For practical realization of CoMP, new BS architecture in which a BS unit is connected to multiple Remote Radio Heads (RRHs) located apart through optical fiber has been proposed. Even using this architecture, however, CoMP can only be realized within the predefined connected RRHs (CoMP cluster). Therefore, cluster-edge users cannot experience throughput improvement by means of CoMP. This paper proposes a novel BS architecture called shared RRH network, in which each RRH is additionally connected to multiple BS units. As flexible clustering is made possible by this architecture, semi-dynamic clustering using geometrically overlapped cluster patterns allocated with orthogonal resources can be achieved which alleviates the cluster-edge problem. Simulation with parameters based on the 3GPP is setup for performance evaluation of the proposed system. Numerical results show that semi-dynamic CoMP using shared RRHs can significantly improve the system performance both at cell-inner and cell-edge compared with the conventional RRH systems, which confirms the effectiveness of the proposed network.

Shared Remote Radio Head architecture to realize semi-dynamic clustering in CoMP cellular networks

In modern cellular systems, high-rate communication is performed using MIMO transmission by a Single Base Station (BS). This method is able to improve the transmission rate when the user is at the cell-inner. However the rate severely degrades when the user is located at cell-edge. Base Station Cooperation (BSC) MIMO is solve the cell-edge problem. BSC MIMO can improve capacity at the cell-edge than FFR or TAA cancellation, however, it has minimal impact on cell-inner users and increases complexity of the network. In this paper, Fractional Base Station Cooperation Cellular Network (FBSC-CN) is proposed in which a combination of Single BS MIMO and BSC Multiuser (MU) MIMO is performed in order to achieve gains both at the cell-inner and cell-edge with limited complexity. Furthermore, by cooperating with each BS autonomously and distributedly, cooperative BSs are able to select the most suitable transmission schemes to the users accordingly.

Shoji Kaneko

Papers

BBU-RRH switching schemes for centralized RAN

Colony-RAN architecture for future cellular network

A Cell-Planning Model for HetNet with CRE and TDM-ICIC in LTE-Advanced

Shared Remote Radio Head architecture to realize semi-dynamic clustering in CoMP cellular networks

Fractional Base Station Cooperation Cellular Network