BBU Pool Research Articles

Front Cover Image, Volume 4, Number 5, May 2022

This cover image shows a downlink F-RAN architecture. In terms of information transmission, F-APs in the network are connected to the BBU pool through fronthaul links with limited capacity. In terms of energy consumption, F-APs include solar panels and energy storage batteries, and are connected to the smart grid. The BBU pool contains all content files that may be requested by UEs. As a fog access node with caching capability, F-APs can cache files with high popularity at the edge of the network. https://doi.org/10.1002/eng2.12497

Artificial Bee Colonies Solution for Load Sharing in a Cloud RAN

The integration of the cloud in the access network architecture, through the Cloud RAN, allows to increase the network capacity thanks to the virtualization of the base station and the sharing of cloud resources. The great innovation of this concept is the BBU Pool present in the architecture. It is the pool that allows the term "centralized" to be used. The processing that is carried out there is critical for the operation of the entire network.  Indeed, in a cloud based environment such as the C-RAN, it is important that the resources are used optimally. This is where load-balancing comes in, which is defined as a technique used to evenly distribute workloads across multiple servers or other computing resources to optimize network performance, reliability and capacity. This paper proposes a load balancing algorithm in the BBU pool of a C-RAN. It is based on the artificial bee colony metaheuristic (ABC algorithm) and on the Load Balanced Min-Min Algorithm (LBMM). All this is done to improve network performance by guaranteeing high availability of centralized and shared resources. Its effectiveness in terms of performance and execution time against Round Robin and MIN MIN algorithms is studied and the results are appreciable.

Is Cloud RAN a Feasible Option for Industrial Communication Network?

Cloud RAN (C-RAN) is a promising paradigm for the next generation radio access network infrastructure, which offers centralised and coordinated base-band signal processing in a cloud-based BBU pool. This requires extremely low latency responses to achieve real-time signal processing. In this paper, we analysed the challenges to introduce cloud native model for signal processing in C-RAN. We studied the difficulties of achieving real-time processing in a cloud infrastructure by addressing its latency-constraint. To evaluate the performance of such a system, we mainly investigated a massive MIMO pilot scheduling process in a C-RAN infrastructure under a factory automation scenario. We considered the stochastic delays incurred by the cloud execution environment as the main constraint that has has impact on the scheduling performance. We use simulations to provide insights on the feasibility of C-RAN deployment for industrial communication, which has stringent criteria to meet Industry 4.0 standards under this constraint. Our experiment results show that, concerning a pilot scheduling problem, the CRAN system is capable of meeting the industrial criteria when the fronthaul and the cloud execution environment has introduced latency in the order of milliseconds.

Flexible functional split for cost-efficient C-RAN

In this paper, we propose flexible functional split schemes for a multi-tier C-RAN architecture based on the concept of virtual remote radio heads (V-RRHs), aiming at optimizing the resource utilization while reducing the overall cost of BBU pool. A V-RRH consists of a digital unit (DU) that hosts a few baseband (BB) processing functionalities and a radio unit (RU) with RF functionality. Specifically, three types of V-RRHs differing in the number of BB processing function slices are considered in three functional split options. We aim at finding the optimal functional split option for each task and thus allocate the appropriate function slice block (FSB) of BBU pool for it. The issue of optimally allocating FSBs to tasks is normalized as a zero–one (0–1) packing problem which is NP-complete. To solve the 0–1 packing problem, we divide it into three stages and solve them by a pure integer non-linear programming (PINLP) model. Numerical results show that the proposed flexible functional split strategies comprehensively outperform the existing C-RAN and D-RAN schemes in terms of the overall cost.

A View Synthesis-Based 360° VR Caching System Over MEC-Enabled C-RAN

With the development of virtual reality (VR) technology, the future of VR systems is evolving from single-user wired connections to multi-user wireless connections. However, wireless online rendering and transmission incur extra processing and transmission latency, as well as higher bandwidth requirements. To meet the requirements of wireless VR applications and enhance the quality of the VR user experience, this paper designs a view synthesis-based 360° VR caching system over Cloud Radio Access Network (C-RAN), where both mobile edge computing (MEC) and hierarchical caching are supported. In the system, an MEC-Cache Server is deployed in the pooled Base band Units (BBU pool) and used for view synthesis and caching. In addition, the remote radio heads (RRHs) can also cache some video contents. If the requested content of a specific view is cached in the BBU pool or RRHs, or can be synthesized with the aid of the cached adjacent views, it is unnecessary to request the content from the remote VR video source server. Therefore, the transmission latency and backhaul traffic load for VR services can be decreased. We formulate a hierarchical collaborative caching problem aiming to minimize the transmission latency, which is proved NP-hard. To address the impractical expenses of the offline optimal method, an online MaxMinDistance caching algorithm with low complexity is proposed. Numerical simulation results demonstrate that the proposed caching strategy provides significantly improved cache hit rate, backhaul traffic load, transmission latency, and Quality of Experience (QoE) performances relative to conventional caching strategies.

Optimising the multiplexing gain in Cloud RAN using the minimum spanning tree algorithm

The cloud radio access network (Cloud-RAN) has been proposed as a cost efficient way of serving the increasing mobile traffic. The basic idea, supporting the cost efficiency, is the statistical multiplexing gain. Such a gain can be achieved when reusing the same processing power, realising BBU functions, for different, spatially distributed cells. Cells served by a single BBU pool need to be close to each other to support the mobility (handovers) and improve coordination. This article proposes the clustering algorithm, based on the minimum spanning tree (MSP). The algorithm allocates the geographically distributed sites onto a predefined set of BBU pools, keeping the clusters compact while achieving high multiplexing gain. We created, using the described algorithm, the BBU pools based on data traffic statistics from commercial network. We compared the multiplexing gain achieved with the maximum multiplexing gain achievable having given the daily profiles of analysed sites.

Nuoxus: A proactive caching model to manage multimedia content distribution on fog radio access networks

One of the most recently proposed 5G architectures, Fog Radio Access Network or F-RAN, has the same cloud computing-based approach of C-RANs while giving additional storage and processing power to the edge nodes so that they can address network activities. The main problem of F-RANs is the intense data traffic in the fronthaul, which is the centralized physical channel used to connect the antennas (F-APs) to the BBU pool. To minimize this bottleneck, we propose the Nuoxus model, whose objective is to cache multimedia content in the edge of the network. By taking advantage of the hierarchical structure of F-RANs, Nuoxus content replacement policy analyses the similarity of requests amongst the children nodes to define the relevance of storing a requested content in cache. It also uses this process to proactively suggest to nodes located lower in the network hierarchy the caching of relevant content. The state-of-the-art analysis reveals Nuoxus as the first model to explore the nodes' request history to perform proactive caching without relying on external and centralized components. Furthermore, the developed proof-of-concept shows significant gains when compared to other caching strategies.

Power-Aware Optimized RRH to BBU Allocation in C-RAN

Wireless networks have faced increasing demand to cope with the exponential growth of data. Conventional architectures have hindered the evolution of network scalability. However, the introduction of cloud technology has brought tremendous flexible and scalable on demand resources. Thus, cloud radio access networks (C-RANs) have been introduced as a new trend in wireless technologies. Despite the novel advancements that C-RAN offers, remote radio head (RRH)-to-base band unit (BBU) resource allocation can cause significant downgrade in efficiency, particularly the allocation of computational resources in the BBU pool to densely deployed small cells. This causes an increase in power consumption and wasted resources. Consequently, an efficient resource allocation method is vital for achieving efficient resource consumption. In this paper, the optimal allocation of computational resources between RRHs and BBUs is modeled. This is dependent on having an optimal physical resource allocation for users to determine the required computational resources. For this purpose, an optimization problem that models the assignment of resources at these two levels is formulated. A decomposition model is adopted to solve the problem by formulating two binary integer programming subproblems; one for each level. Furthermore, two low complexity heuristic algorithms are developed to solve each subproblem. Results show that the computational resource requirements and the power consumption of BBUs and the physical machines decrease as the channel quality worsens. Moreover, the developed heuristic solution achieves a close to optimal performance while having a lower complexity. Finally, both models achieve high resource utilization, cementing the efficiency of the proposed solutions.

FBMC in Next-Generation Mobile Fronthaul Networks With Centralized Pre-Equalization

In this letter, we proposed a centralized pre-equalization mechanism in a fiber-wireless integrated mobile fronthaul system to compensate the channel degradation among multiple component carriers (CCs) with reduced complexity and cost at user terminals. Orthogonal frequency division multiplexing and filter-bank multicarrier (FBMC) with and without frequency-domain pre-equalization are compared in a 50-GHz radio-over-fiber testbed. In comparison, FBMC with the proposed pre-equalization performs better because asynchronous up-link CCs can be quasi-seamlessly aggregated without interference, which enables baseband-unit (BBU) pool to precisely estimate the channel quality and perform pre-equalization for multiple bands with high spectral efficiency. Bidirectional transmission experiments are conducted with two independent asynchronous user terminals controlled by one BBU pool. An error vector magnitude of <6% is obtained with 1.1-GHz 5-CC carrier aggregation over 25-km standard single-mode fiber and 1.2-m wireless channel.

Cross layer optimization for cloud-based radio over optical fiber networks

Abstract To adapt the 5G communication, the cloud radio access network is a paradigm introduced by operators which aggregates all base stations computational resources into a cloud BBU pool. The interaction between RRH and BBU or resource schedule among BBUs in cloud have become more frequent and complex with the development of system scale and user requirement. It can promote the networking demand among RRHs and BBUs, and force to form elastic optical fiber switching and networking. In such network, multiple stratum resources of radio, optical and BBU processing unit have interweaved with each other. In this paper, we propose a novel multiple stratum optimization (MSO) architecture for cloud-based radio over optical fiber networks (C-RoFN) with software defined networking. Additionally, a global evaluation strategy (GES) is introduced in the proposed architecture. MSO can enhance the responsiveness to end-to-end user demands and globally optimize radio frequency, optical spectrum and BBU processing resources effectively to maximize radio coverage. The feasibility and efficiency of the proposed architecture with GES strategy are experimentally verified on OpenFlow-enabled testbed in terms of resource occupation and path provisioning latency.

Baseband unit cloud interconnection enabled by flexible grid optical networks with software defined elasticity

The evolution toward 5G mobile networks is characterized by supporting higher data rate, excellent end-to-end performance and ubiquitous user-coverage with lower latency, power consumption, and cost. To support this, the RANs are evolving in two important aspects. One aspect is “cloudification,” which is to pool baseband units to be centralized for statistical multiplexing gain. The other aspect is to use advanced optical technologies for digital and analog signal transmission in a cloud-based RAN. In this article, we focus on BBU cloud interconnection with optical layer technologies. Flexible grid optical networks with the enabling technologies are introduced to provide elastic, transparent, and virtualized optical paths between the BBU pools. To improve the elasticity and intelligence of C-RAN, we propose a software defined centralized control plane to coordinate heterogeneous resources from three domains: the BBU domain, radio domain, and optical domain. We report an experimental demonstration of elastic lightpath provision for cloud radio-over-flexible grid optical networks in a software-defined-networking-based testbed.

A new C-RAN architecture based on RF signal soft-switching

Coordinated multi-point (CoMP) is known to be one of the key technologies for long-term evolution (LTE)-advanced systems. CoMP technology can improve system capacity and the quality of wireless communication services for users in LTE networks. However, in practice, the actual performance of CoMP technology is limited by the switching capacity of the backhaul network among distributed base stations as well as its latencies. In this paper, we propose a new cloud radio access network architecture based on RF signal soft-switching to solve this problem. Furthermore, we introduce a narrow-band parallel processing technique on a common public radio interface in downlink and uplink to reduce the volume of data as well as the latencies in the transmission process among base band units and remote radio units. By combining theoretical analysis with computer simulations, we show that the technique is valid both for downlink and uplink, i.e., it does not degrade the performance of downlink and uplink propagation between BBU pool and user equipments. Moreover, the computational time of the narrow-band parallel processing technique is less than that of the standard technique.