Fronthaul (FH) bandwidth in cloud radio access network (C-RAN) can be significantly reduced with an appropriate functional split by offloading more signal processing functionalities to the remote radio unit (RRU). However, this not only reduces the acclaimed centralization benefits but also increases the complexity of the RRU. Considering the practical aspects such as power consumption, cost, size and weight, it is often desirable to make RRUs as simple, yet efficient, as possible. In this paper, we analyze the complexity of the RRU with 5G New Radio (NR) considering functional split 7.2 as recently standardized split by the xRAN Forum. C-RAN with 5G NR allows to support a wide range of scenarios and use-case specific requirements. In addition, we compare suitability in terms of efficiency and flexibility of the RRU being implemented using either field programmable gate array (FPGA) or general purpose processor (GPP), e.g., x86 considering their computational requirements. Based on the complexity analysis, we calculate the required number of the FPGA or GPP to support the complexity of the RRU. We show that FPGA is more feasible option compared to x86 in terms of power consumption, particularly for rooftop-mounted RRU.

The increased carrier bandwidth and the number of antenna elements expected in 5G networks require a redesign of the traditional IP-based backhaul and CPRI-based fronthaul interfaces used in 4G networks. We envision future mobile networks to encompass these legacy interfaces together with novel 5G RAN functional splits. In this scenario, a consistent transport network architecture able to jointly support backhaul and 4G/5G fronthaul interfaces is of paramount importance. In this article we present 5G-XHaul, a novel transport network architecture featuring wireless and optical technologies and a multi-technology software defined control plane, which is able to jointly support backhaul and fronthaul services. We have deployed and validated the 5G-XHaul architecture in a city-wide testbed in Bristol.

One of the aims of beyond 5G (B5G) wireless communication networks is to increase the data rates, while keeping lower latency and high energy efficiency. To achieve this, massive multiple-input-multiple-output (mMIMO) systems combined with two dimensional (2D) active antenna array (AAA) design are expected to play a key role. The main objective of this paper is to design a 2D-AAA with beamforming both in azimuth and elevation directions in order to improve the spectral efficiency and energy efficiency. Furthermore, we evaluate the impact of the designed 2D-AAA on the signal-to-interference-plus-noise ratio (SINR) performance by considering the 3D channel model given by 3GPP in the Urban Micro scenarios (UMi). For the design of 2D-AAA we consider 64 cross polarized antenna elements that are arranged as an 8-by-8 array, in which, at each column are stacked together pairwise to form sub-arrays. Therefore, transmit/receive (T/R) module, control circuitry and other RF processing unit are dedicated at a sub-array basis, and, due to this fewer components are required. Therefore, the cost of the 2D-AAA design is reduced. However, with the sub-arrays, the performance is degraded in terms of the side lobe level (SLL) when steering the main beam in other directions. In this contribution, we demonstrated that by proper designing of the 2D-AAA with optimal sub-array amplitude and phase tapering, it is possible to reduce the SLL. Moreover, due to the reduction of the SLL, an increase in spectral efficiency and SINR performance can be obtained.

Cloud-radio access network (C-RAN) has been an attractive solution in the recent years for the future generation mobile networks due to its promising benefits. However, the transport link between the remote radio unit (RRU) and the baseband unit (BBU), known as fronthaul (FH), imposes stringent requirements in terms of data rate, latency, jitter, and synchronization. In the conventional C-RAN, the FH capacity scales linearly with the number of the transmitting antennas, which has posed severe demands on the FH capacity, especially due to emerging 5G technologies such as massive MIMO. However, this can be relaxed by performing precoding at the RRUs instead of centrally at BBU, leading to FH traffic which depends on the number of currently served users. This paper adapts queueing model and spatial traffic model to exploit randomness of the user traffic to achieve statistical multiplexing gain. Through this, we showed that the required FH capacity can be reduced significantly, depending on traffic demand and its statistical properties. Furthermore, we analyzed the impacts of pilots on capacity-constrained FH.

Cloud radio access networks (C-RANs) are a promising concept for the architecture of 5th generation mobile networks. In C-RANs, signal processing is not performed at the access points as in common mobile networks, but is instead centralized in large, cloud-based data centers. This approach promises many benefits, including smaller-footprint base stations, simplified network management, maintenance and upgrades, economies of scale and a more efficient implementation of cooperative processing techniques. However, such a centralized architecture comes at the heavy price of an extensive, so-called fronthaul network, which has to exchange the raw, unprocessed radio signals between the remote access points and the central processing unit. This requires the fronthaul network to fulfill challenging requirements in terms of data rate, latency, and synchronization. Currently, these fronthaul networks are designed, deployed, and operated separately from the radio access network, meaning that there is little cooperation and information exchange between the fronthaul and radio access network. To mitigate this, this thesis proposes a joint design of the radio access and fronthaul links, by considering the impact that they have on one another, and by exchanging more side-information to form a joint radio access/fronthaul link. A first step towards such a joint design is the re-design of the so-called functional split, which refers to the amount of processing performed at the remote access points versus that performed at the central unit. While the current approaches are two extreme cases of either full centralization or decentralization, an intermediate option can reduce the strict fronthaul requirements, while maintaining several of the benefits of centralization. Furthermore, the access and fronthaul links can cooperate on the level of the physical interface by exchanging information about signal statistics and their respective channel qualities. With this, a joint minimum mean square error receiver is designed in this thesis, aiming to improve the performance of the joint radio access and fronthaul link. This receiver is especially beneficial when

Despite the promising benefits of the cloud-radio access network (C-RAN), the fronthaul (FH) imposes stringent requirements in terms of data rate, latency, jitter and synchronisation. In the classical C-RAN, the FH capacity scales linearly with the number of the transmitting antennas, which has posed severe demands on the FH capacity, especially due to emerging 5G technologies such as massive MIMO. However, this can be relaxed by performing precoding at the remote radio units (RRUs) instead of centrally, leading to FH traffic which depends on the number of currently served users. This paper adapts queueing theory and spatial traffic models to derive statistical multiplexing gain enabled by varying number of user streams. Through this, we showed that the required FH capacity can be reduced dramatically, depending on traffic demand and its statistical properties.

This article presents a converged 5G network infrastructure and an overarching architecture to jointly support operational network and end-user services, proposed by the EU 5G PPP project 5G-XHaul. The 5G-XHaul infrastructure adopts a common fronthaul/backhaul network solution, deploying a wealth of wireless technologies and a hybrid active/passive optical transport, supporting flexible fronthaul split options. This infrastructure is evaluated through a novel modeling. Numerical results indicate significant energy savings at the expense of increased end-user service delay.

In this paper, we provide a quantitative evaluation of the dimensioning and deployment aspects of the 5G-XHaul transport architecture in a representative European city. In particular, we select an example Dense Urban City scenario based on the city of Barcelona, and illustrate how the 5G-XHaul architecture can be deployed in that environment. Building on the case of Barcelona, we discuss physical deployment aspects, such as the best locations to deploy small cells, how many compute facilities should be scattered throughout the city, or where the control plane functions should be deployed. In addition, we provide a quantitative evaluation of the 5G-XHaul deployment in Barcelona, including the bandwidth required at the different segments of the architecture, i.e. the wireless segment, the WDMPON access network, and the TSON metro network. We also evaluate control plane aspects, such as the number of 5G-XHaul SDN controllers required for a city like Barcelona. Keywords—5G Transport Network, Network capacity planning; deployment; topology.

In cloud-based radio access networks, remote radio units and central baseband units are connected by fronthaul links, which are commonly assumed to be error-free. However, especially for wireless millimeter wave fronthaul links, this might be challenging to achieve, as they face a more unreliable environment than the conventionally used fiber links. In this paper, we hence aim to mitigate the impact of imperfect fronthaul links. For this, we propose the concept of joint radio access and fronthaul reception, which considers to recover the transmitted messages correctly at the centralized baseband unit, rather than to ensure a nearly perfect fronthaul transmission in between. Based on the Bayesian minimum mean square error criterion, we develop a joint access and fronthaul estimation scheme that can be utilized for various signals transported over the fronthaul, including in-phase/quadrature phase (I/Q) samples, soft-bits, synchronization, and reference signals. In addition, we develop an approximated variant of the scheme to reduced complexity, and an iterative extension to further improve the performance. We demonstrate that our scheme can operate under less reliable fronthaul than conventional approaches by numerical simulation for different signals, and show that our method can be implemented in a parallel architecture to achieve a reasonable computational complexity.

In this paper, we provide a quantitative evaluation of the deployment aspects and dimensioning of the 5G transport architecture in a representative European city. In particular, we select an example dense urban city scenario based on the city of Barcelona, and illustrate how the transport network architecture defined by the 5G-XHaul project can be deployed in that environment. Building on the case of Barcelona, we discuss physical deployment aspects, such as the locations to deploy small cells, how many compute facilities should be scattered throughout the city, or where the control plane functions should be deployed. In addition, we provide a quantitative evaluation of the 5G-XHaul deployment in Barcelona, including the bandwidth required at the different segments of the architecture, i.e. the wireless segment, the WDM-PON access network, and the TSON metro network. We also evaluate control plane aspects, such as the number of 5G-XHaul SDN controllers required for a city like Barcelona.

To meet the requirements of 5G mobile networks, several radio access technologies, such as millimeter wave communications and massive MIMO, are being proposed. In addition, cloud radio access network (C-RAN) architectures are considered instrumental to fully exploit the capabilities of future 5G RANs. However, RAN centralization imposes stringent requirements on the transport network, which today are addressed with purpose-specific and expensive fronthaul links. As the demands on future access networks rise, so will the challenges in the fronthaul and backhaul segments. It is hence of fundamental importance to consider the design of transport networks alongside the definition of future access technologies to avoid the transport becoming a bottleneck. Therefore, we analyze in this work the impact that future RAN technologies will have on the transport network and on the design of the next generation fronthaul interface. To understand the especially important impact of varying user traffic, we utilize measurements from a real-world 4G network and, taking target 5G performance figures into account, extrapolate its statistics to a 5G scenario. With this, we derive both per-cell and aggregated data rate requirements for 5G transport networks. In addition, we show that the effect of statistical multiplexing is an important factor to reduce transport network capacity requirements and costs. Based on our investigations, we provide guidelines for the development of the 5G transport network architecture.

We propose an optical-wireless 5G infrastructure offering converged fronthauling/backhauling functions to support both operational and end-user cloud services. A layered architectural structure required to efficiently support these services is shown. The data plane performance of the proposed infrastructure is evaluated in terms of energy consumption and service delay through a novel modelling framework. Our modelling results show that the proposed architecture can offer significant energy savings but there is a clear trade-off between overall energy consumption and service delay.

The common European Information and Communications Technology sector vision for 5G is that it should leverage on the strengths of both optical and wireless technologies. In the 5G context, a wide spectra of radio access technologies—such as millimetre wave transmission, massive multiple‐input multiple‐output and new waveforms—demand for high capacity, highly flexible and convergent transport networks. As the requirements imposed on future 5G networks rise, so do the challenges in the transport network. Hence, 5G‐XHaul proposes a converged optical and wireless transport network solution with a unified control plane based on software defined networking. This solution is able to support the flexible backhaul and fronthaul—X‐Haul—options required to tackle the future challenges imposed by 5G radio access technologies. 5G‐XHaul studies the trade‐offs involving fully or partially converged backhaul and fronthaul functions, with the aim of maximising the associated sharing benefits, improving efficiency in resource utilisation and providing measurable benefits in terms of overall cost, scalability and sustainability. Copyright © 2016 John Wiley & Sons, Ltd.

This paper provides an overview of joint radio access network (RAN) and backhaul (BH) optimization methods in dense small cell networks, assuming a heterogeneous backhaul and centralization by Cloud RAN. The main focus is on the design of novel MAC (medium access control) and RRM (radio resource management) schemes for constrained, non-ideal backhaul which can influence the RAN performance. In this context, we provide some key technology approaches which incorporate the RAN/BH awareness at the cloud and exploit the benefits of Cloud-RAN by dynamically adapting to BH constraints.

Cloud-based radio access networks, which utilize a centralized baseband unit, require additional fronthaul links as compared to conventional networks. While fiber is commonly used for these fronthaul links, millimeter wave technology offers a cost-effective alternative on the “last mile” of the network. However, millimeter wave technology has to deal with the increased attenuation of outdoor wireless channels, which poses additional challenges on the design of such links. In this work, we combine an optimized quantizer with an improved detection scheme to increase the performance of the uplink in networks utilizing millimeter wave fronthaul technology.

Cloud radio access networks promise considerable benefits compared to decentralized network architectures, but they also put challenging requirements on the fronthaul and backhaul network. Flexible centralization can relax these requirements by adaptively assigning different parts of the processing chain to either the centralized base-band processors or the base stations based on the load situation, user scenario, and availability of fronthaul links. In this article, we provide a comprehensive overview of different functional split options and analyze their specific requirements. We compare these requirements to available fronthaul technologies, and discuss the convergence of fronthaul and backhaul technologies. By evaluating the aggregated fronthaul traffic, we show the benefits of flexible centralization and give guidelines on how to set up the fronthaul network to avoid over-or under-dimensioning.